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{{Short description|Intelligence of machines}}
{{Redirect|AI|other uses|AI (disambiguation)|and|Artificial intelligence (disambiguation)}}
{{Use dmy dates|date=July 2023}}{{Pp|small=yes}}
{{Artificial intelligence}}
'''Artificial intelligence''' ('''AI''') refers to the capability of [[computer|computational systems]] to perform tasks typically associated with [[human intelligence]], such as learning, reasoning, problem-solving, perception, and decision-making. It is a [[field of research]] in [[computer science]] that develops and studies methods and [[software]] that enable machines to [[machine perception|perceive their environment]] and use [[machine learning|learning]] and [[intelligence]] to take actions that maximize their chances of achieving defined goals.{{Sfnp|Russell|Norvig|2021|pp=1–4}} Such machines may be called AIs.
High-profile [[applications of AI]] include advanced [[web search engine]]s (e.g., [[Google Search]]); [[recommendation systems]] (used by [[YouTube]], [[Amazon (company)|Amazon]], and [[Netflix]]); [[virtual assistant]]s (e.g., [[Google Assistant]], [[Siri]], and [[Amazon Alexa|Alexa]]); [[autonomous vehicles]] (e.g., [[Waymo]]); [[Generative artificial intelligence|generative]] and [[Computational creativity|creative]] tools (e.g., [[ChatGPT]] and [[AI art]]); and [[Superintelligence|superhuman]] play and analysis in [[strategy game]]s (e.g., [[chess]] and [[Go (game)|Go]]). However, many AI applications are not perceived as AI: "A lot of cutting edge AI has filtered into general applications, often without being called AI because once something becomes useful enough and common enough it's [[AI effect|not labeled AI anymore]]."[[http://www.cnn.com/2006/TECH/science/07/24/ai.bostrom/ AI set to exceed human brain power] {{Webarchive|url=https://web.archive.org/web/20080219001624/http://www.cnn.com/2006/TECH/science/07/24/ai.bostrom/|date=2008-02-19}} CNN.com (July 26, 2006)][{{Cite journal |last1=Kaplan |first1=Andreas |last2=Haenlein |first2=Michael |date=2019 |title=Siri, Siri, in my hand: Who's the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence |journal=Business Horizons |volume=62 |pages=15–25 |doi=10.1016/j.bushor.2018.08.004 |issn=0007-6813 |s2cid=158433736}}]
Various subfields of AI research are centered around particular goals and the use of particular tools. The traditional goals of AI research include learning, [[automated reasoning|reasoning]], [[knowledge representation]], [[Automated planning and scheduling|planning]], [[natural language processing]], [[Machine perception|perception]], and support for [[robotics]].{{Efn|name="Problems of AI"}} [[Artificial general intelligence|General intelligence]]—the ability to complete any task performed by a human on an at least equal level—is among the field's long-term goals.[{{Harvtxt|Russell|Norvig|2021|loc=§1.2}}.]
Artificial intelligence was founded as an academic discipline in 1956,[Problem-solving, puzzle solving, game playing, and deduction: {{Harvtxt|Russell|Norvig|2021|loc=chpt. 3–5}}, {{Harvtxt|Russell|Norvig|2021|loc=chpt. 6}} ([[constraint satisfaction]]), {{Harvtxt|Poole|Mackworth|Goebel|1998|loc=chpt. 2, 3, 7, 9}}, {{Harvtxt|Luger|Stubblefield|2004|loc=chpt. 3, 4, 6, 8}}, {{Harvtxt|Nilsson|1998|loc=chpt. 7–12}}] By the late 1980s and 1990s, methods were developed for dealing with [[uncertainty|uncertain]] or incomplete information, employing concepts from [[probability]] and [[economics]].[Uncertain reasoning: {{Harvtxt|Russell|Norvig|2021|loc=chpt. 12–18}}, {{Harvtxt|Poole|Mackworth|Goebel|1998|pp=345–395}}, {{Harvtxt|Luger|Stubblefield|2004|pp=333–381}}, {{Harvtxt|Nilsson|1998|loc=chpt. 7–12}}]
Many of these algorithms are insufficient for solving large reasoning problems because they experience a "combinatorial explosion": They become exponentially slower as the problems grow.[[[Intractably|Intractability and efficiency]] and the [[combinatorial explosion]]: {{Harvtxt|Russell|Norvig|2021|p=21}}] Even humans rarely use the step-by-step deduction that early AI research could model. They solve most of their problems using fast, intuitive judgments.[Psychological evidence of the prevalence of sub-symbolic reasoning and knowledge: {{Harvtxt|Kahneman|2011}}, {{Harvtxt|Dreyfus|Dreyfus|1986}}, {{Harvtxt|Wason|Shapiro|1966}}, {{Harvtxt|Kahneman|Slovic|Tversky|1982}}] Accurate and efficient reasoning is an unsolved problem.
=== Knowledge representation ===
[[File:General Formal Ontology.svg|thumb|upright=1.2|An ontology represents knowledge as a set of concepts within a domain and the relationships between those concepts.]]
[[Knowledge representation]] and [[knowledge engineering]][[[Knowledge representation]] and [[knowledge engineering]]: {{Harvtxt|Russell|Norvig|2021|loc=chpt. 10}}, {{Harvtxt|Poole|Mackworth|Goebel|1998|pp=23–46, 69–81, 169–233, 235–277, 281–298, 319–345}}, {{Harvtxt|Luger|Stubblefield|2004|pp=227–243}}, {{Harvtxt|Nilsson|1998|loc=chpt. 17.1–17.4, 18}}] allow AI programs to answer questions intelligently and make deductions about real-world facts. Formal knowledge representations are used in content-based indexing and retrieval,{{Sfnp|Smoliar|Zhang|1994}} scene interpretation,{{Sfnp|Neumann|Möller|2008}} clinical decision support,{{Sfnp|Kuperman|Reichley|Bailey|2006}} knowledge discovery (mining "interesting" and actionable inferences from large [[database]]s),{{Sfnp|McGarry|2005}} and other areas.{{Sfnp|Bertini|Del Bimbo|Torniai|2006}}
A [[knowledge base]] is a body of knowledge represented in a form that can be used by a program. An [[ontology (information science)|ontology]] is the set of objects, relations, concepts, and properties used by a particular domain of knowledge.{{Sfnp|Russell|Norvig|2021|pp=272}} Knowledge bases need to represent things such as objects, properties, categories, and relations between objects;[Representing categories and relations: [[Semantic network]]s, [[description logic]]s, [[Inheritance (object-oriented programming)|inheritance]] (including [[Frame (artificial intelligence)|frames]], and [[Scripts (artificial intelligence)|scripts]]): {{Harvtxt|Russell|Norvig|2021|loc=§10.2 & 10.5}}, {{Harvtxt|Poole|Mackworth|Goebel|1998|pp=174–177}}, {{Harvtxt|Luger|Stubblefield|2004|pp=248–258}}, {{Harvtxt|Nilsson|1998|loc=chpt. 18.3}}] situations, events, states, and time;[Representing events and time:[[Situation calculus]], [[event calculus]], [[fluent calculus]] (including solving the [[frame problem]]): {{Harvtxt|Russell|Norvig|2021|loc=§10.3}}, {{Harvtxt|Poole|Mackworth|Goebel|1998|pp=281–298}}, {{Harvtxt|Nilsson|1998|loc=chpt. 18.2}}] causes and effects;[[[Causality#Causal calculus|Causal calculus]]: {{Harvtxt|Poole|Mackworth|Goebel|1998|pp=335–337}}] knowledge about knowledge (what we know about what other people know);[Representing knowledge about knowledge: Belief calculus, [[modal logic]]s: {{Harvtxt|Russell|Norvig|2021|loc=§10.4}}, {{Harvtxt|Poole|Mackworth|Goebel|1998|pp=275–277}}] [[default reasoning]] (things that humans assume are true until they are told differently and will remain true even when other facts are changing);[[[Default reasoning]], [[Frame problem]], [[default logic]], [[non-monotonic logic]]s, [[circumscription (logic)|circumscription]], [[closed world assumption]], [[abductive reasoning|abduction]]: {{Harvtxt|Russell|Norvig|2021|loc=§10.6}}, {{Harvtxt|Poole|Mackworth|Goebel|1998|pp=248–256, 323–335}}, {{Harvtxt|Luger|Stubblefield|2004|pp=335–363}}, {{Harvtxt|Nilsson|1998|loc=~18.3.3}}
(Poole ''et al.'' places abduction under "default reasoning". Luger ''et al.'' places this under "uncertain reasoning").] and many other aspects and domains of knowledge.
Among the most difficult problems in knowledge representation are the breadth of commonsense knowledge (the set of atomic facts that the average person knows is enormous);[Breadth of commonsense knowledge: {{Harvtxt|Lenat|Guha|1989|loc=Introduction}}, {{Harvtxt|Crevier|1993|pp=113–114}}, {{Harvtxt|Moravec|1988|p=13}}, {{Harvtxt|Russell|Norvig|2021|pp=241, 385, 982}} ([[qualification problem]])] and the sub-symbolic form of most commonsense knowledge (much of what people know is not represented as "facts" or "statements" that they could express verbally).[[[Automated planning]]: {{Harvtxt|Russell|Norvig|2021|loc=chpt. 11}}.] In [[automated decision-making]], the agent has preferences—there are some situations it would prefer to be in, and some situations it is trying to avoid. The decision-making agent assigns a number to each situation (called the "[[utility]]") that measures how much the agent prefers it. For each possible action, it can calculate the "[[expected utility]]": the [[utility]] of all possible outcomes of the action, weighted by the probability that the outcome will occur. It can then choose the action with the maximum expected utility.[[[Automated decision making]], [[Decision theory]]: {{Harvtxt|Russell|Norvig|2021|loc=chpt. 16–18}}.]
In [[Automated planning and scheduling#classical planning|classical planning]], the agent knows exactly what the effect of any action will be.[[[Automated planning and scheduling#classical planning|Classical planning]]: {{Harvtxt|Russell|Norvig|2021|loc=Section 11.2}}.] In most real-world problems, however, the agent may not be certain about the situation they are in (it is "unknown" or "unobservable") and it may not know for certain what will happen after each possible action (it is not "deterministic"). It must choose an action by making a probabilistic guess and then reassess the situation to see if the action worked.[Sensorless or "conformant" planning, contingent planning, replanning (a.k.a online planning): {{Harvtxt|Russell|Norvig|2021|loc=Section 11.5}}.]
In some problems, the agent's preferences may be uncertain, especially if there are other agents or humans involved. These can be learned (e.g., with [[inverse reinforcement learning]]), or the agent can seek information to improve its preferences.[Uncertain preferences: {{Harvtxt|Russell|Norvig|2021|loc=Section 16.7}}
[[Inverse reinforcement learning]]: {{Harvtxt|Russell|Norvig|2021|loc=Section 22.6}}] [[Information value theory]] can be used to weigh the value of exploratory or experimental actions.[[[Information value theory]]: {{Harvtxt|Russell|Norvig|2021|loc=Section 16.6}}.] The space of possible future actions and situations is typically [[intractably]] large, so the agents must take actions and evaluate situations while being uncertain of what the outcome will be.
A [[Markov decision process]] has a [[Finite-state machine|transition model]] that describes the probability that a particular action will change the state in a particular way and a [[reward function]] that supplies the utility of each state and the cost of each action. A [[Reinforcement learning#Policy|policy]] associates a decision with each possible state. The policy could be calculated (e.g., by [[policy iteration|iteration]]), be [[heuristic]], or it can be learned.[[[Markov decision process]]: {{Harvtxt|Russell|Norvig|2021|loc=chpt. 17}}.]
[[Game theory]] describes the rational behavior of multiple interacting agents and is used in AI programs that make decisions that involve other agents.[[[Game theory]] and multi-agent decision theory: {{Harvtxt|Russell|Norvig|2021|loc=chpt. 18}}.]
=== Learning ===
[[Machine learning]] is the study of programs that can improve their performance on a given task automatically.[[[machine learning|Learning]]: {{Harvtxt|Russell|Norvig|2021|loc=chpt. 19–22}}, {{Harvtxt|Poole|Mackworth|Goebel|1998|pp=397–438}}, {{Harvtxt|Luger|Stubblefield|2004|pp=385–542}}, {{Harvtxt|Nilsson|1998|loc=chpt. 3.3, 10.3, 17.5, 20}}] It has been a part of AI from the beginning.{{Efn
|[[Alan Turing]] discussed the centrality of learning as early as 1950, in his classic paper "[[Computing Machinery and Intelligence]]".{{Sfnp|Turing|1950}} In 1956, at the original Dartmouth AI summer conference, [[Ray Solomonoff]] wrote a report on unsupervised probabilistic machine learning: "An Inductive Inference Machine".{{Sfnp|Solomonoff|1956}}
}}
[[File:Supervised and unsupervised learning.png|right|upright=1.4|frameless]]
There are several kinds of machine learning. [[Unsupervised learning]] analyzes a stream of data and finds patterns and makes predictions without any other guidance.[[[Unsupervised learning]]: {{Harvtxt|Russell|Norvig|2021|pp=653}} (definition), {{Harvtxt|Russell|Norvig|2021|pp=738–740}} ([[cluster analysis]]), {{Harvtxt|Russell|Norvig|2021|pp=846–860}} ([[word embedding]])] [[Supervised learning]] requires labeling the training data with the expected answers, and comes in two main varieties: [[statistical classification|classification]] (where the program must learn to predict what category the input belongs in) and [[Regression analysis|regression]] (where the program must deduce a numeric function based on numeric input).[[[Supervised learning]]: {{Harvtxt|Russell|Norvig|2021|loc=§19.2}} (Definition), {{Harvtxt|Russell|Norvig|2021|loc=Chpt. 19–20}} (Techniques)]
In [[reinforcement learning]], the agent is rewarded for good responses and punished for bad ones. The agent learns to choose responses that are classified as "good".[[[Reinforcement learning]]: {{Harvtxt|Russell|Norvig|2021|loc=chpt. 22}}, {{Harvtxt|Luger|Stubblefield|2004|pp=442–449}}] [[Transfer learning]] is when the knowledge gained from one problem is applied to a new problem.[[[Transfer learning]]: {{Harvtxt|Russell|Norvig|2021|pp=281}}, {{Harvtxt|The Economist|2016}}] [[Deep learning]] is a type of machine learning that runs inputs through biologically inspired [[artificial neural networks]] for all of these types of learning.[{{Cite web |title=Artificial Intelligence (AI): What Is AI and How Does It Work? {{!}} Built In |url=https://builtin.com/artificial-intelligence |access-date=2023-10-30 |website=builtin.com}}]
[[Computational learning theory]] can assess learners by [[computational complexity]], by [[sample complexity]] (how much data is required), or by other notions of [[optimization]].[[[Computational learning theory]]: {{Harvtxt|Russell|Norvig|2021|pp=672–674}}, {{Harvtxt|Jordan|Mitchell|2015}}]
{{Clear}}
=== Natural language processing ===
[[Natural language processing]] (NLP)[[[Natural language processing]] (NLP): {{Harvtxt|Russell|Norvig|2021|loc=chpt. 23–24}}, {{Harvtxt|Poole|Mackworth|Goebel|1998|pp=91–104}}, {{Harvtxt|Luger|Stubblefield|2004|pp=591–632}}] allows programs to read, write and communicate in human languages such as [[English (language)|English]]. Specific problems include [[speech recognition]], [[speech synthesis]], [[machine translation]], [[information extraction]], [[information retrieval]] and [[question answering]].[Subproblems of [[Natural language processing|NLP]]: {{Harvtxt|Russell|Norvig|2021|pp=849–850}}]
Early work, based on [[Noam Chomsky]]'s [[generative grammar]] and [[semantic network]]s, had difficulty with [[word-sense disambiguation]]{{Efn|See {{Section link|AI winter|Machine translation and the ALPAC report of 1966
}}}} unless restricted to small domains called "[[blocks world|micro-worlds]]" (due to the common sense knowledge problem[Modern statistical and deep learning approaches to [[Natural language processing|NLP]]: {{Harvtxt|Russell|Norvig|2021|loc=chpt. 24}}, {{Harvtxt|Cambria|White|2014}}] In 2019, [[generative pre-trained transformer]] (or "GPT") language models began to generate coherent text,{{Sfnp|Vincent|2019}}{{Sfnp|Russell|Norvig|2021|pp=875–878}} and by 2023, these models were able to get human-level scores on the [[bar exam]], [[SAT]] test, [[GRE]] test, and many other real-world applications.{{Sfnp|Bushwick|2023}}
=== Perception ===
[[Machine perception]] is the ability to use input from sensors (such as cameras, microphones, wireless signals, active [[lidar]], sonar, radar, and [[tactile sensor]]s) to deduce aspects of the world. [[Computer vision]] is the ability to analyze visual input.[[[Computer vision]]: {{Harvtxt|Russell|Norvig|2021|loc=chpt. 25}}, {{Harvtxt|Nilsson|1998|loc=chpt. 6}}]
The field includes [[speech recognition]],{{Sfnp|Russell|Norvig|2021|pp=849–850}} [[image classification]],{{Sfnp|Russell|Norvig|2021|pp=895–899}} [[facial recognition system|facial recognition]], [[object recognition]],{{Sfnp|Russell|Norvig|2021|pp=899–901}}[[motion capture|object tracking]],{{Sfnp|Challa|Moreland|Mušicki|Evans|2011}} and [[robotic perception]].{{Sfnp|Russell|Norvig|2021|pp=931–938}}
=== Social intelligence ===
[[File:Kismet-IMG 6007-gradient.jpg|thumb|[[Kismet (robot)|Kismet]], a robot head which was made in the 1990s; it is a machine that can recognize and simulate emotions.{{Sfnp|MIT AIL|2014}}]]
[[Affective computing]] is a field that comprises systems that recognize, interpret, process, or simulate human [[Affect (psychology)|feeling, emotion, and mood]].[[[Affective computing]]: {{Harvtxt|Thro|1993}}, {{Harvtxt|Edelson|1991}}, {{Harvtxt|Tao|Tan|2005}}, {{Harvtxt|Scassellati|2002}}] For example, some [[virtual assistant]]s are programmed to speak conversationally or even to banter humorously; it makes them appear more sensitive to the emotional dynamics of human interaction, or to otherwise facilitate [[human–computer interaction]].
However, this tends to give naïve users an unrealistic conception of the intelligence of existing computer agents.{{Sfnp|Waddell|2018}} Moderate successes related to affective computing include textual [[sentiment analysis]] and, more recently, [[multimodal sentiment analysis]], wherein AI classifies the effects displayed by a videotaped subject.{{Sfnp|Poria|Cambria|Bajpai |Hussain|2017}}
=== General intelligence ===
A machine with [[artificial general intelligence]] should be able to solve a wide variety of problems with breadth and versatility similar to [[human intelligence]].[
[[Artificial general intelligence]]: {{Harvtxt|Russell|Norvig|2021|pp=32–33, 1020–1021}}]
Proposal for the modern version: {{Harvtxt|Pennachin|Goertzel|2007}}
Warnings of overspecialization in AI from leading researchers: {{Harvtxt|Nilsson|1995}}, {{Harvtxt|McCarthy|2007}}, {{Harvtxt|Beal|Winston|2009}}
== Techniques ==
AI research uses a wide variety of techniques to accomplish the goals above.{{Efn|name="Tools of AI"|This list of tools is based on the topics covered by the major AI textbooks, including: {{Harvtxt|Russell|Norvig|2021}}, {{Harvtxt|Luger|Stubblefield|2004}}, {{Harvtxt|Poole|Mackworth|Goebel|1998}} and {{Harvtxt|Nilsson|1998}}}}
=== Search and optimization ===
AI can solve many problems by intelligently searching through many possible solutions.[[[Search algorithm]]s: {{Harvtxt|Russell|Norvig|2021|loc=chpts. 3–5}}, {{Harvtxt|Poole|Mackworth|Goebel|1998|pp=113–163}}, {{Harvtxt|Luger|Stubblefield|2004|pp=79–164, 193–219}}, {{Harvtxt|Nilsson|1998|loc=chpts. 7–12}}] There are two very different kinds of search used in AI: [[state space search]] and [[Local search (optimization)|local search]].
==== State space search ====
[[State space search]] searches through a tree of possible states to try to find a goal state.[[[State space search]]: {{Harvtxt|Russell|Norvig|2021|loc=chpt. 3}}] For example, [[Automated planning and scheduling|planning]] algorithms search through trees of goals and subgoals, attempting to find a path to a target goal, a process called [[means-ends analysis]].{{Sfnp|Russell|Norvig|2021|loc=sect. 11.2}}
[[Brute force search|Simple exhaustive searches]][[[Uninformed search]]es ([[breadth first search]], [[depth-first search]] and general [[state space search]]): {{Harvtxt|Russell|Norvig|2021|loc=sect. 3.4}}, {{Harvtxt|Poole|Mackworth|Goebel|1998|pp=113–132}}, {{Harvtxt|Luger|Stubblefield|2004|pp=79–121}}, {{Harvtxt|Nilsson|1998|loc=chpt. 8}}] are rarely sufficient for most real-world problems: the [[Search algorithm|search space]] (the number of places to search) quickly grows to [[Astronomically large|astronomical numbers]]. The result is a search that is [[Computation time|too slow]] or never completes.[[[Heuristic]] or informed searches (e.g., greedy [[Best-first search|best first]] and [[A* search algorithm|A*]]): {{Harvtxt|Russell|Norvig|2021|loc=sect. 3.5}}, {{Harvtxt|Poole|Mackworth|Goebel|1998|pp=132–147}}, {{Harvtxt|Poole|Mackworth|2017|loc=sect. 3.6}}, {{Harvtxt|Luger|Stubblefield|2004|pp=133–150}}]
[[Adversarial search]] is used for [[game AI|game-playing]] programs, such as chess or Go. It searches through a [[Game tree|tree]] of possible moves and countermoves, looking for a winning position.[[[Adversarial search]]: {{Harvtxt|Russell|Norvig|2021|loc=chpt. 5}}]
==== Local search ====
[[File:Gradient descent.gif|class=skin-invert-image|thumb|Illustration of [[gradient descent]] for 3 different starting points; two parameters (represented by the plan coordinates) are adjusted in order to minimize the [[loss function]] (the height)]] [[Local search (optimization)|Local search]] uses [[mathematical optimization]] to find a solution to a problem. It begins with some form of guess and refines it incrementally.[[[Local search (optimization)|Local]] or "[[optimization]]" search: {{Harvtxt|Russell|Norvig|2021|loc=chpt. 4}}]
[[Gradient descent]] is a type of local search that optimizes a set of numerical parameters by incrementally adjusting them to minimize a [[loss function]]. Variants of gradient descent are commonly used to train [[Artificial neural network|neural networks]],[{{Cite web |last=Singh Chauhan |first=Nagesh |date=December 18, 2020 |title=Optimization Algorithms in Neural Networks |url=https://www.kdnuggets.com/optimization-algorithms-in-neural-networks |access-date=2024-01-13 |website=KDnuggets}}] through the [[backpropagation]] algorithm.
Another type of local search is [[evolutionary computation]], which aims to iteratively improve a set of candidate solutions by "mutating" and "recombining" them, [[Artificial selection|selecting]] only the fittest to survive each generation.[[[Evolutionary computation]]: {{Harvtxt|Russell|Norvig|2021|loc=sect. 4.1.2}}]
Distributed search processes can coordinate via [[swarm intelligence]] algorithms. Two popular swarm algorithms used in search are [[particle swarm optimization]] (inspired by bird [[flocking]]) and [[ant colony optimization]] (inspired by [[ant trail]]s).{{Sfnp|Merkle|Middendorf|2013}}
=== Logic ===
Formal [[logic]] is used for [[automatic reasoning|reasoning]] and [[knowledge representation]].[[[Logic]]: {{Harvtxt|Russell|Norvig|2021|loc=chpts. 6–9}}, {{Harvtxt|Luger|Stubblefield|2004|pp=35–77}}, {{Harvtxt|Nilsson|1998|loc=chpt. 13–16}}]
Formal logic comes in two main forms: [[propositional logic]] (which operates on statements that are true or false and uses [[logical connective]]s such as "and", "or", "not" and "implies")[[[Propositional logic]]: {{Harvtxt|Russell|Norvig|2021|loc=chpt. 6}}, {{Harvtxt|Luger|Stubblefield|2004|pp=45–50}}, {{Harvtxt|Nilsson|1998|loc=chpt. 13}}] and [[predicate logic]] (which also operates on objects, predicates and relations and uses [[Quantifier (logic)|quantifier]]s such as "''Every'' ''X'' is a ''Y''" and "There are ''some'' ''X''s that are ''Y''s").[[[First-order logic]] and features such as [[Equality (mathematics)|equality]]: {{Harvtxt|Russell|Norvig|2021|loc=chpt. 7}}, {{Harvtxt|Poole|Mackworth|Goebel|1998|pp=268–275}}, {{Harvtxt|Luger|Stubblefield|2004|pp=50–62}}, {{Harvtxt|Nilsson|1998|loc=chpt. 15}}]
[[Deductive reasoning]] in logic is the process of [[logical proof|proving]] a new statement ([[Logical consequence|conclusion]]) from other statements that are given and assumed to be true (the [[premise]]s).[[[Logical inference]]: {{Harvtxt|Russell|Norvig|2021|loc=chpt. 10}}] Proofs can be structured as proof [[tree structure|trees]], in which nodes are labelled by sentences, and children nodes are connected to parent nodes by [[inference rule]]s.
Given a problem and a set of premises, problem-solving reduces to searching for a proof tree whose root node is labelled by a solution of the problem and whose [[leaf nodes]] are labelled by premises or [[axiom]]s. In the case of [[Horn clause]]s, problem-solving search can be performed by reasoning [[Forward chaining|forwards]] from the premises or [[backward chaining|backwards]] from the problem.[logical deduction as search: {{Harvtxt|Russell|Norvig|2021|loc=sects. 9.3, 9.4}}, {{Harvtxt|Poole|Mackworth|Goebel|1998|pp=~46–52}}, {{Harvtxt|Luger|Stubblefield|2004|pp=62–73}}, {{Harvtxt|Nilsson|1998|loc=chpt. 4.2, 7.2}}] In the more general case of the clausal form of [[first-order logic]], [[resolution (logic)|resolution]] is a single, axiom-free rule of inference, in which a problem is solved by proving a contradiction from premises that include the negation of the problem to be solved.[[[Resolution (logic)|Resolution]] and [[unification (computer science)|unification]]: {{Harvtxt|Russell|Norvig|2021|loc= sections 7.5.2, 9.2, 9.5}}]
Inference in both Horn clause logic and first-order logic is [[Undecidable problem|undecidable]], and therefore [[Intractable problem|intractable]]. However, backward reasoning with Horn clauses, which underpins computation in the [[logic programming]] language [[Prolog]], is [[Turing complete]]. Moreover, its efficiency is competitive with computation in other [[symbolic programming]] languages.[{{Cite journal |last1=Warren |first1=D.H. |last2=Pereira |first2=L.M. |last3=Pereira |first3=F. |date=1977 |title=Prolog-the language and its implementation compared with Lisp |journal=[[ACM SIGPLAN Notices]] |volume=12 |issue=8 |pages=109–115 |doi=10.1145/872734.806939}}]
[[Fuzzy logic]] assigns a "degree of truth" between 0 and 1. It can therefore handle propositions that are vague and partially true.[Fuzzy logic: {{Harvtxt|Russell|Norvig|2021|pp=214, 255, 459}}, {{Harvtxt|Scientific American|1999}}]
[[Non-monotonic logic]]s, including logic programming with [[negation as failure]], are designed to handle [[default reasoning]].[Stochastic methods for uncertain reasoning: {{Harvtxt|Russell|Norvig|2021|loc=chpt. 12–18, 20}}, {{Harvtxt|Poole|Mackworth|Goebel|1998|pp=345–395}}, {{Harvtxt|Luger|Stubblefield|2004|pp=165–191, 333–381}}, {{Harvtxt|Nilsson|1998|loc=chpt. 19}}] Precise mathematical tools have been developed that analyze how an agent can make choices and plan, using [[decision theory]], [[decision analysis]],[[[decision theory]] and [[decision analysis]]: {{Harvtxt|Russell|Norvig|2021|loc=chpt. 16–18}}, {{Harvtxt|Poole|Mackworth|Goebel|1998|pp=381–394}}] and [[information value theory]].[[[Information value theory]]: {{Harvtxt|Russell|Norvig|2021|loc=sect. 16.6}}] These tools include models such as [[Markov decision process]]es,[[[Markov decision process]]es and dynamic [[decision network]]s: {{Harvtxt|Russell|Norvig|2021|loc=chpt. 17}}] dynamic [[decision network]]s,[[[Game theory]] and [[mechanism design]]: {{Harvtxt|Russell|Norvig|2021|loc=chpt. 18}}]
[[Bayesian network]]s[[[Bayesian network]]s: {{Harvtxt|Russell|Norvig|2021|loc=sects. 12.5–12.6, 13.4–13.5, 14.3–14.5, 16.5, 20.2–20.3}}, {{Harvtxt|Poole|Mackworth|Goebel|1998|pp=361–381}}, {{Harvtxt|Luger|Stubblefield|2004|pp=~182–190, ≈363–379}}, {{Harvtxt|Nilsson|1998|loc=chpt. 19.3–19.4}}] are a tool that can be used for [[automated reasoning|reasoning]] (using the [[Bayesian inference]] algorithm),{{Efn|
Compared with symbolic logic, formal Bayesian inference is computationally expensive. For inference to be tractable, most observations must be [[conditionally independent]] of one another. [[AdSense]] uses a Bayesian network with over 300 million edges to learn which ads to serve.{{Sfnp|Domingos|2015|loc=chpt. 6}}
}}[[[Bayesian inference]] algorithm: {{Harvtxt|Russell|Norvig|2021|loc=sect. 13.3–13.5}}, {{Harvtxt|Poole|Mackworth|Goebel|1998|pp=361–381}}, {{Harvtxt|Luger|Stubblefield|2004|pp=~363–379}}, {{Harvtxt|Nilsson|1998|loc=chpt. 19.4 & 7}}] [[Machine learning|learning]] (using the [[expectation–maximization algorithm]]),{{Efn|Expectation–maximization, one of the most popular algorithms in machine learning, allows clustering in the presence of unknown [[latent variables]].{{Sfnp|Domingos|2015|p=210}}}}[[[Bayesian learning]] and the [[expectation–maximization algorithm]]: {{Harvtxt|Russell|Norvig|2021|loc=chpt. 20}}, {{Harvtxt|Poole|Mackworth|Goebel|1998|pp=424–433}}, {{Harvtxt|Nilsson|1998|loc=chpt. 20}}, {{Harvtxt|Domingos|2015|p=210}}] [[Automated planning and scheduling|planning]] (using [[decision network]]s)[[[Bayesian decision theory]] and Bayesian [[decision network]]s: {{Harvtxt|Russell|Norvig|2021|loc=sect. 16.5}}] and [[Machine perception|perception]] (using [[dynamic Bayesian network]]s).[Stochastic temporal models: {{Harvtxt|Russell|Norvig|2021|loc=chpt. 14}}
[[Hidden Markov model]]: {{Harvtxt|Russell|Norvig|2021|loc=sect. 14.3}}
[[Kalman filter]]s: {{Harvtxt|Russell|Norvig|2021|loc=sect. 14.4}}
[[Dynamic Bayesian network]]s: {{Harvtxt|Russell|Norvig|2021|loc=sect. 14.5}}]
[[File:EM_Clustering_of_Old_Faithful_data.gif|thumb|upright=1.2|[[Expectation–maximization algorithm|Expectation–maximization]] [[cluster analysis|clustering]] of [[Old Faithful]] eruption data starts from a random guess but then successfully converges on an accurate clustering of the two physically distinct modes of eruption.]]
=== Classifiers and statistical learning methods ===
The simplest AI applications can be divided into two types: classifiers (e.g., "if shiny then diamond"), on one hand, and controllers (e.g., "if diamond then pick up"), on the other hand. [[Classifier (mathematics)|Classifiers]][Statistical learning methods and [[Classifier (mathematics)|classifiers]]: {{Harvtxt|Russell|Norvig|2021|loc=chpt. 20}},] are functions that use [[pattern matching]] to determine the closest match. They can be fine-tuned based on chosen examples using [[supervised learning]]. Each pattern (also called an "[[random variate|observation]]") is labeled with a certain predefined class. All the observations combined with their class labels are known as a [[data set]]. When a new observation is received, that observation is classified based on previous experience.[{{Cite book |last1=Ciaramella |first1=Alberto |author-link=Alberto Ciaramella |title=Introduction to Artificial Intelligence: from data analysis to generative AI |last2=Ciaramella |first2=Marco |date=2024 |publisher=Intellisemantic Editions |isbn=978-8-8947-8760-3}}] The [[decision tree]] is the simplest and most widely used symbolic machine learning algorithm.[[[Alternating decision tree|Decision tree]]s: {{Harvtxt|Russell|Norvig|2021|loc=sect. 19.3}}, {{Harvtxt|Domingos|2015|p=88}}] [[K-nearest neighbor]] algorithm was the most widely used analogical AI until the mid-1990s, and [[Kernel methods]] such as the [[support vector machine]] (SVM) displaced k-nearest neighbor in the 1990s.[[[Nonparametric statistics|Non-parameteric]] learning models such as [[K-nearest neighbor]] and [[support vector machines]]: {{Harvtxt|Russell|Norvig|2021|loc=sect. 19.7}}, {{Harvtxt|Domingos|2015|p=187}} (k-nearest neighbor)
* {{Harvtxt|Domingos|2015|p=88}} (kernel methods)]
The [[naive Bayes classifier]] is reportedly the "most widely used learner"{{Sfnp|Domingos|2015|p=152}} at Google, due in part to its scalability.[[[Naive Bayes classifier]]: {{Harvtxt|Russell|Norvig|2021|loc=sect. 12.6}}, {{Harvtxt|Domingos|2015|p=152}}]
[[Artificial neural network|Neural networks]] are also used as classifiers.[Neural networks: {{Harvtxt|Russell|Norvig|2021|loc=chpt. 21}}, {{Harvtxt|Domingos|2015|loc=Chapter 4}}]
Learning algorithms for neural networks use [[local search (optimization)|local search]] to choose the weights that will get the right output for each input during training. The most common training technique is the [[backpropagation]] algorithm.[Gradient calculation in computational graphs, [[backpropagation]], [[automatic differentiation]]: {{Harvtxt|Russell|Norvig|2021|loc=sect. 21.2}}, {{Harvtxt|Luger|Stubblefield|2004|pp=467–474}}, {{Harvtxt|Nilsson|1998|loc=chpt. 3.3}}] Neural networks learn to model complex relationships between inputs and outputs and [[Pattern recognition|find patterns]] in data. In theory, a neural network can learn any function.[[[Universal approximation theorem]]: {{Harvtxt|Russell|Norvig|2021|p=752}}
The theorem: {{Harvtxt|Cybenko|1988}}, {{Harvtxt|Hornik|Stinchcombe|White|1989}}]
In [[feedforward neural network]]s the signal passes in only one direction.[[[Feedforward neural network]]s: {{Harvtxt|Russell|Norvig|2021|loc=sect. 21.1}}] [[Recurrent neural network]]s feed the output signal back into the input, which allows short-term memories of previous input events. [[Long short term memory]] is the most successful network architecture for recurrent networks.[[[Recurrent neural network]]s: {{Harvtxt|Russell|Norvig|2021|loc=sect. 21.6}}] [[Perceptron]]s[[[Perceptron]]s: {{Harvtxt|Russell|Norvig|2021|pp=21, 22, 683, 22}}] use only a single layer of neurons; deep learning[[[Convolutional neural networks]]: {{Harvtxt|Russell|Norvig|2021|loc=sect. 21.3}}]
{{Clear}}
=== Deep learning ===
[[File:AI hierarchy.svg|thumb|upright]]
[[Deep learning]][[[Deep learning]]: {{Harvtxt|Russell|Norvig|2021|loc=chpt. 21}}, {{Harvtxt|Goodfellow|Bengio|Courville|2016}}, {{Harvtxt|Hinton ''et al.''|2016}}, {{Harvtxt|Schmidhuber|2015}}] uses several layers of neurons between the network's inputs and outputs. The multiple layers can progressively extract higher-level features from the raw input. For example, in [[image processing]], lower layers may identify edges, while higher layers may identify the concepts relevant to a human such as digits, letters, or faces.{{Sfnp|Deng|Yu|2014|pp=199–200}}
Deep learning has profoundly improved the performance of programs in many important subfields of artificial intelligence, including [[computer vision]], [[speech recognition]], [[natural language processing]], [[image classification]],{{Sfnp|Ciresan|Meier|Schmidhuber|2012}} and others. The reason that deep learning performs so well in so many applications is not known as of 2021.{{Sfnp|Russell|Norvig|2021|p=750}} The sudden success of deep learning in 2012–2015 did not occur because of some new discovery or theoretical breakthrough (deep neural networks and backpropagation had been described by many people, as far back as the 1950s){{Efn|
Some form of deep neural networks (without a specific learning algorithm) were described by:
[[Warren S. McCulloch]] and [[Walter Pitts]] (1943){{Sfnp|Russell|Norvig|2021|p=17}}
[[Alan Turing]] (1948);{{Sfnp|Russell|Norvig|2021|p=785}}
[[Karl Steinbuch]] and [[Roger David Joseph]] (1961).{{Sfnp|Schmidhuber|2022|loc=sect. 5}}
Deep or recurrent networks that learned (or used gradient descent) were developed by:
[[Frank Rosenblatt]](1957);{{Sfnp|Russell|Norvig|2021|p=785}}
[[Oliver Selfridge]] (1959);{{Sfnp|Schmidhuber|2022|loc=sect. 5}}
[[Alexey Ivakhnenko]] and [[Valentin Lapa]] (1965);{{Sfnp|Schmidhuber|2022|loc=sect. 6}}
[[Kaoru Nakano]] (1971);{{Sfnp|Schmidhuber|2022|loc=sect. 7}}
[[Shun-Ichi Amari]] (1972);{{Sfnp|Schmidhuber|2022|loc=sect. 7}}
[[John Joseph Hopfield]] (1982).{{Sfnp|Schmidhuber|2022|loc=sect. 7}}
Precursors to backpropagation were developed by:
[[Henry J. Kelley]] (1960);{{Sfnp|Russell|Norvig|2021|p=785}}
[[Arthur E. Bryson]] (1962);{{Sfnp|Russell|Norvig|2021|p=785}}
[[Stuart Dreyfus]] (1962);{{Sfnp|Russell|Norvig|2021|p=785}}
[[Arthur E. Bryson]] and [[Yu-Chi Ho]] (1969);{{Sfnp|Russell|Norvig|2021|p=785}}
Backpropagation was independently developed by:
[[Seppo Linnainmaa]] (1970);{{Sfnp|Schmidhuber|2022|loc=sect. 8}}
[[Paul Werbos]] (1974).{{Sfnp|Russell|Norvig|2021|p=785}}
}} but because of two factors: the incredible increase in computer power (including the hundred-fold increase in speed by switching to [[GPU]]s) and the availability of vast amounts of training data, especially the giant [[List of datasets for machine-learning research|curated datasets]] used for benchmark testing, such as [[ImageNet]].{{Efn|[[Geoffrey Hinton]] said, of his work on neural networks in the 1990s, "our labeled datasets were thousands of times too small. [And] our computers were millions of times too slow."[Quoted in {{Harvtxt|Christian|2020|p=22}}]}}
===GPT===
[[Generative pre-trained transformer]]s (GPT) are [[large language model]]s (LLMs) that generate text based on the semantic relationships between words in sentences. Text-based GPT models are pretrained on a large [[corpus of text]] that can be from the Internet. The pretraining consists of predicting the next [[Lexical analysis|token]] (a token being usually a word, subword, or punctuation). Throughout this pretraining, GPT models accumulate knowledge about the world and can then generate human-like text by repeatedly predicting the next token. Typically, a subsequent training phase makes the model more truthful, useful, and harmless, usually with a technique called [[reinforcement learning from human feedback]] (RLHF). Current GPT models are prone to generating falsehoods called "[[Hallucination (artificial intelligence)|hallucinations]]", although this can be reduced with RLHF and quality data. They are used in [[chatbot]]s, which allow people to ask a question or request a task in simple text.{{Sfnp|Smith|2023}}[{{Cite web |date=9 November 2023 |title=Explained: Generative AI |url=https://news.mit.edu/2023/explained-generative-ai-1109}}]
Current models and services include [[Gemini (chatbot)|Gemini]] (formerly Bard), [[ChatGPT]], [[Grok (chatbot)|Grok]], [[Anthropic#Claude|Claude]], [[Microsoft Copilot|Copilot]], and [[LLaMA]].[{{Cite web |title=AI Writing and Content Creation Tools |url=https://mitsloanedtech.mit.edu/ai/tools/writing |access-date=25 December 2023 |publisher=MIT Sloan Teaching & Learning Technologies |archive-date=25 December 2023 |archive-url=https://web.archive.org/web/20231225232503/https://mitsloanedtech.mit.edu/ai/tools/writing/ |url-status=live }}] [[Multimodal learning|Multimodal]] GPT models can process different types of data ([[Modality (human–computer interaction)|modalities]]) such as images, videos, sound, and text.{{Sfnp|Marmouyet|2023}}
===Hardware and software===
{{Main|Programming languages for artificial intelligence|Hardware for artificial intelligence}}
In the late 2010s, [[graphics processing unit]]s (GPUs) that were increasingly designed with AI-specific enhancements and used with specialized [[TensorFlow]] software had replaced previously used [[central processing unit]] (CPUs) as the dominant means for large-scale (commercial and academic) [[machine learning]] models' training.{{Sfnp|Kobielus|2019}} Specialized [[programming language]]s such as [[Prolog]] were used in early AI research,[{{Cite web |last=Thomason |first=James |date=2024-05-21 |title=Mojo Rising: The resurgence of AI-first programming languages |url=https://venturebeat.com/ai/mojo-rising-the-resurgence-of-ai-first-programming-languages |access-date=2024-05-26 |website=VentureBeat |archive-date=27 June 2024 |archive-url=https://web.archive.org/web/20240627143853/https://venturebeat.com/ai/mojo-rising-the-resurgence-of-ai-first-programming-languages/ |url-status=live }}] but [[general-purpose programming language]]s like [[Python (programming language)|Python]] have become predominant.[{{Cite news |last=Wodecki |first=Ben |date=May 5, 2023 |title=7 AI Programming Languages You Need to Know |url=https://aibusiness.com/verticals/7-ai-programming-languages-you-need-to-know |work=AI Business |access-date=5 October 2024 |archive-date=25 July 2024 |archive-url=https://web.archive.org/web/20240725164443/https://aibusiness.com/verticals/7-ai-programming-languages-you-need-to-know |url-status=live }}]
The transistor density in [[integrated circuit]]s has been observed to roughly double every 18 months—a trend known as [[Moore's law]], named after the [[Intel]] co-founder [[Gordon Moore]], who first identified it. Improvements in [[GPUs]] have been even faster,[{{Cite web |last=Plumb |first=Taryn |date=2024-09-18 |title=Why Jensen Huang and Marc Benioff see 'gigantic' opportunity for agentic AI |url=https://venturebeat.com/ai/why-jensen-huang-and-marc-benioff-see-gigantic-opportunity-for-agentic-ai/ |access-date=2024-10-04 |website=VentureBeat |language=en-US |archive-date=5 October 2024 |archive-url=https://web.archive.org/web/20241005165649/https://venturebeat.com/ai/why-jensen-huang-and-marc-benioff-see-gigantic-opportunity-for-agentic-ai/ |url-status=live }}] a trend sometimes called [[Huang's law]],[{{Cite news |last=Mims |first=Christopher |date=2020-09-19 |title=Huang's Law Is the New Moore's Law, and Explains Why Nvidia Wants Arm |url=https://www.wsj.com/articles/huangs-law-is-the-new-moores-law-and-explains-why-nvidia-wants-arm-11600488001 |access-date=2025-01-19 |work=Wall Street Journal |language=en-US |issn=0099-9660 |archive-date=2 October 2023 |archive-url=https://web.archive.org/web/20231002080608/https://www.wsj.com/articles/huangs-law-is-the-new-moores-law-and-explains-why-nvidia-wants-arm-11600488001 |url-status=live }}] named after [[Nvidia]] co-founder and CEO [[Jensen Huang]].
== Applications ==
{{Main|Applications of artificial intelligence}}AI and machine learning technology is used in most of the essential applications of the 2020s, including: [[search engines]] (such as [[Google Search]]), [[Targeted advertising|targeting online advertisements]], [[recommendation systems]] (offered by [[Netflix]], [[YouTube]] or [[Amazon (company)|Amazon]]), driving [[internet traffic]], [[Marketing and artificial intelligence|targeted advertising]] ([[AdSense]], [[Facebook]]), [[virtual assistant]]s (such as [[Siri]] or [[Amazon Alexa|Alexa]]), [[autonomous vehicles]] (including [[Unmanned aerial vehicle|drones]], [[Advanced driver-assistance system|ADAS]] and [[self-driving cars]]), [[automatic language translation]] ([[Microsoft Translator]], [[Google Translate]]), [[Facial recognition system|facial recognition]] ([[Apple Computer|Apple]]'s [[Face ID]] or [[Microsoft]]'s [[DeepFace]] and [[Google]]'s [[FaceNet]]) and [[image labeling]] (used by [[Facebook]], Apple's [[iPhoto]] and [[TikTok]]). The deployment of AI may be overseen by a [[Chief automation officer]] (CAO).
===Health and medicine===
{{Main|Artificial intelligence in healthcare}}
The application of AI in [[medicine]] and [[medical research]] has the potential to increase patient care and quality of life.[{{Cite journal |last1=Davenport |first1=T |last2=Kalakota |first2=R |date=June 2019 |title=The potential for artificial intelligence in healthcare |journal=Future Healthc J. |volume=6 |issue=2 |pages=94–98 |doi=10.7861/futurehosp.6-2-94 |pmc=6616181 |pmid=31363513}}] Through the lens of the [[Hippocratic Oath]], medical professionals are ethically compelled to use AI, if applications can more accurately diagnose and treat patients.[{{Cite journal |last1=Lyakhova |first1=U.A. |last2=Lyakhov |first2=P.A. |date=2024 |title=Systematic review of approaches to detection and classification of skin cancer using artificial intelligence: Development and prospects |url=https://linkinghub.elsevier.com/retrieve/pii/S0010482524008278 |journal=Computers in Biology and Medicine |language=en |volume=178 |pages=108742 |doi=10.1016/j.compbiomed.2024.108742 |pmid=38875908 |archive-date=3 December 2024 |access-date=10 October 2024 |archive-url=https://web.archive.org/web/20241203172502/https://linkinghub.elsevier.com/retrieve/pii/S0010482524008278 |url-status=live }}][{{Cite journal |last1=Alqudaihi |first1=Kawther S. |last2=Aslam |first2=Nida |last3=Khan |first3=Irfan Ullah |last4=Almuhaideb |first4=Abdullah M. |last5=Alsunaidi |first5=Shikah J. |last6=Ibrahim |first6=Nehad M. Abdel Rahman |last7=Alhaidari |first7=Fahd A. |last8=Shaikh |first8=Fatema S. |last9=Alsenbel |first9=Yasmine M. |last10=Alalharith |first10=Dima M. |last11=Alharthi |first11=Hajar M. |last12=Alghamdi |first12=Wejdan M. |last13=Alshahrani |first13=Mohammed S. |date=2021 |title=Cough Sound Detection and Diagnosis Using Artificial Intelligence Techniques: Challenges and Opportunities |journal=IEEE Access |volume=9 |pages=102327–102344 |doi=10.1109/ACCESS.2021.3097559 |issn=2169-3536 |pmc=8545201 |pmid=34786317|bibcode=2021IEEEA...9j2327A }}]
For medical research, AI is an important tool for processing and integrating [[big data]]. This is particularly important for [[organoid]] and [[tissue engineering]] development which use [[microscopy]] imaging as a key technique in fabrication.[{{Cite journal |last1=Bax |first1=Monique |last2=Thorpe |first2=Jordan |last3=Romanov |first3=Valentin |date=December 2023 |title=The future of personalized cardiovascular medicine demands 3D and 4D printing, stem cells, and artificial intelligence |journal=Frontiers in Sensors |volume=4 |doi=10.3389/fsens.2023.1294721 |issn=2673-5067 |doi-access=free}}] It has been suggested that AI can overcome discrepancies in funding allocated to different fields of research.[{{Cite journal |last=Dankwa-Mullan |first=Irene |date=2024 |title=Health Equity and Ethical Considerations in Using Artificial Intelligence in Public Health and Medicine |url=https://www.cdc.gov/pcd/issues/2024/24_0245.htm |journal=Preventing Chronic Disease |language=en-us |volume=21 |pages=E64 |doi=10.5888/pcd21.240245 |pmid=39173183 |issn=1545-1151|pmc=11364282 }}] New AI tools can deepen the understanding of biomedically relevant pathways. For example, [[AlphaFold 2]] (2021) demonstrated the ability to approximate, in hours rather than months, the 3D [[Protein structure|structure of a protein]].[{{Cite journal |last1=Jumper |first1=J |last2=Evans |first2=R |last3=Pritzel |first3=A |date=2021 |title=Highly accurate protein structure prediction with AlphaFold |journal=Nature |volume=596 |issue=7873 |pages=583–589 |bibcode=2021Natur.596..583J |doi=10.1038/s41586-021-03819-2 |pmc=8371605 |pmid=34265844}}] In 2023, it was reported that AI-guided drug discovery helped find a class of antibiotics capable of killing two different types of drug-resistant bacteria.[{{Cite web |date=2023-12-20 |title=AI discovers new class of antibiotics to kill drug-resistant bacteria |url=https://www.newscientist.com/article/2409706-ai-discovers-new-class-of-antibiotics-to-kill-drug-resistant-bacteria/ |access-date=5 October 2024 |archive-date=16 September 2024 |archive-url=https://web.archive.org/web/20240916014421/https://www.newscientist.com/article/2409706-ai-discovers-new-class-of-antibiotics-to-kill-drug-resistant-bacteria/ |url-status=live }}] In 2024, researchers used machine learning to accelerate the search for [[Parkinson's disease]] drug treatments. Their aim was to identify compounds that block the clumping, or aggregation, of [[alpha-synuclein]] (the protein that characterises Parkinson's disease). They were able to speed up the initial screening process ten-fold and reduce the cost by a thousand-fold.[{{Cite web |date=2024-04-17 |title=AI speeds up drug design for Parkinson's ten-fold |url=https://www.cam.ac.uk/research/news/ai-speeds-up-drug-design-for-parkinsons-ten-fold |publisher=Cambridge University |access-date=5 October 2024 |archive-date=5 October 2024 |archive-url=https://web.archive.org/web/20241005165755/https://www.cam.ac.uk/research/news/ai-speeds-up-drug-design-for-parkinsons-ten-fold |url-status=live }}][{{Cite journal |last1=Horne |first1=Robert I. |last2=Andrzejewska |first2=Ewa A. |last3=Alam |first3=Parvez |last4=Brotzakis |first4=Z. Faidon |last5=Srivastava |first5=Ankit |last6=Aubert |first6=Alice |last7=Nowinska |first7=Magdalena |last8=Gregory |first8=Rebecca C. |last9=Staats |first9=Roxine |last10=Possenti |first10=Andrea |last11=Chia |first11=Sean |last12=Sormanni |first12=Pietro |last13=Ghetti |first13=Bernardino |last14=Caughey |first14=Byron |last15=Knowles |first15=Tuomas P. J. |last16=Vendruscolo |first16=Michele |date=2024-04-17 |title=Discovery of potent inhibitors of α-synuclein aggregation using structure-based iterative learning |journal=Nature Chemical Biology |publisher=Nature |volume=20 |issue=5 |pages=634–645 |doi=10.1038/s41589-024-01580-x |pmc=11062903 |pmid=38632492}}]
=== Games ===
{{Main|Game artificial intelligence}}
[[Game AI|Game playing]] programs have been used since the 1950s to demonstrate and test AI's most advanced techniques.[{{Cite magazine |last1=Grant |first1=Eugene F. |last2=Lardner |first2=Rex |date=1952-07-25 |title=The Talk of the Town – It |url=https://www.newyorker.com/magazine/1952/08/02/it |access-date=2024-01-28 |magazine=The New Yorker |issn=0028-792X |archive-date=16 February 2020 |archive-url=https://web.archive.org/web/20200216034025/https://www.newyorker.com/magazine/1952/08/02/it |url-status=live }}] [[IBM Deep Blue|Deep Blue]] became the first computer chess-playing system to beat a reigning world chess champion, [[Garry Kasparov]], on 11 May 1997.[{{Cite web |last=Anderson |first=Mark Robert |date=2017-05-11 |title=Twenty years on from Deep Blue vs Kasparov: how a chess match started the big data revolution |url=http://theconversation.com/twenty-years-on-from-deep-blue-vs-kasparov-how-a-chess-match-started-the-big-data-revolution-76882 |access-date=2024-01-28 |website=The Conversation |archive-date=17 September 2024 |archive-url=https://web.archive.org/web/20240917000827/https://theconversation.com/twenty-years-on-from-deep-blue-vs-kasparov-how-a-chess-match-started-the-big-data-revolution-76882 |url-status=live }}] In 2011, in a ''[[Jeopardy!]]'' [[quiz show]] exhibition match, [[IBM]]'s [[question answering system]], [[Watson (artificial intelligence software)|Watson]], defeated the two greatest ''Jeopardy!'' champions, [[Brad Rutter]] and [[Ken Jennings]], by a significant margin.[{{Cite news |last=Markoff |first=John |date=2011-02-16 |title=Computer Wins on 'Jeopardy!': Trivial, It's Not |url=https://www.nytimes.com/2011/02/17/science/17jeopardy-watson.html |url-access=subscription |access-date=2024-01-28 |work=The New York Times |issn=0362-4331 |archive-date=22 October 2014 |archive-url=https://web.archive.org/web/20141022023202/http://www.nytimes.com/2011/02/17/science/17jeopardy-watson.html |url-status=live }}] In March 2016, [[AlphaGo]] won 4 out of 5 games of [[Go (game)|Go]] in a match with Go champion [[Lee Sedol]], becoming the first [[computer Go]]-playing system to beat a professional Go player without [[Go handicaps|handicaps]]. Then, in 2017, it [[AlphaGo versus Ke Jie|defeated Ke Jie]], who was the best Go player in the world.[{{Cite web |last=Byford |first=Sam |date=2017-05-27 |title=AlphaGo retires from competitive Go after defeating world number one 3–0 |url=https://www.theverge.com/2017/5/27/15704088/alphago-ke-jie-game-3-result-retires-future |access-date=2024-01-28 |website=The Verge |archive-date=7 June 2017 |archive-url=https://web.archive.org/web/20170607184301/https://www.theverge.com/2017/5/27/15704088/alphago-ke-jie-game-3-result-retires-future |url-status=live }}] Other programs handle [[Imperfect information|imperfect-information]] games, such as the [[poker]]-playing program [[Pluribus (poker bot)|Pluribus]].[{{Cite journal |last1=Brown |first1=Noam |last2=Sandholm |first2=Tuomas |date=2019-08-30 |title=Superhuman AI for multiplayer poker |url=https://www.science.org/doi/10.1126/science.aay2400 |journal=Science |volume=365 |issue=6456 |pages=885–890 |bibcode=2019Sci...365..885B |doi=10.1126/science.aay2400 |issn=0036-8075 |pmid=31296650}}] [[DeepMind]] developed increasingly generalistic [[reinforcement learning]] models, such as with [[MuZero]], which could be trained to play chess, Go, or [[Atari]] games.[{{Cite web |date=2020-12-23 |title=MuZero: Mastering Go, chess, shogi and Atari without rules |url=https://deepmind.google/discover/blog/muzero-mastering-go-chess-shogi-and-atari-without-rules |access-date=2024-01-28 |website=Google DeepMind}}] In 2019, DeepMind's AlphaStar achieved grandmaster level in [[StarCraft II]], a particularly challenging real-time strategy game that involves incomplete knowledge of what happens on the map.[{{Cite news |last=Sample |first=Ian |date=2019-10-30 |title=AI becomes grandmaster in 'fiendishly complex' StarCraft II |url=https://www.theguardian.com/technology/2019/oct/30/ai-becomes-grandmaster-in-fiendishly-complex-starcraft-ii |access-date=2024-01-28 |work=The Guardian |issn=0261-3077 |archive-date=29 December 2020 |archive-url=https://web.archive.org/web/20201229185547/https://www.theguardian.com/technology/2019/oct/30/ai-becomes-grandmaster-in-fiendishly-complex-starcraft-ii |url-status=live }}] In 2021, an AI agent competed in a PlayStation [[Gran Turismo (series)|Gran Turismo]] competition, winning against four of the world's best Gran Turismo drivers using deep reinforcement learning.[{{Cite journal |last1=Wurman |first1=P. R. |last2=Barrett |first2=S. |last3=Kawamoto |first3=K. |date=2022 |title=Outracing champion Gran Turismo drivers with deep reinforcement learning |journal=Nature |volume=602 |issue=7896 |pages=223–228 |bibcode=2022Natur.602..223W |doi=10.1038/s41586-021-04357-7 |pmid=35140384|url=https://www.researchsquare.com/article/rs-795954/latest.pdf }}] In 2024, Google DeepMind introduced SIMA, a type of AI capable of autonomously playing nine previously unseen [[open-world]] video games by observing screen output, as well as executing short, specific tasks in response to natural language instructions.[{{Cite web |last=Wilkins |first=Alex |date=13 March 2024 |title=Google AI learns to play open-world video games by watching them |url=https://www.newscientist.com/article/2422101-google-ai-learns-to-play-open-world-video-games-by-watching-them |access-date=2024-07-21 |website=New Scientist |archive-date=26 July 2024 |archive-url=https://web.archive.org/web/20240726182946/https://www.newscientist.com/article/2422101-google-ai-learns-to-play-open-world-video-games-by-watching-them/ |url-status=live }}]
=== Mathematics ===
Large language models, such as [[GPT-4]], [[Gemini (chatbot)|Gemini]], [[Claude (language model)|Claude]], [[Llama (language model)|LLaMa]] or [[Mistral AI|Mistral]], are increasingly used in mathematics. These probabilistic models are versatile, but can also produce wrong answers in the form of [[Hallucination (artificial intelligence)|hallucinations]]. They sometimes need a large database of mathematical problems to learn from, but also methods such as [[Supervised learning|supervised]] [[Fine-tuning (deep learning)|fine-tuning]][{{Cite journal |date=2024 |title=ReFT: Representation Finetuning for Language Models |journal=NeurIPS |arxiv=2404.03592 |last1=Wu |first1=Zhengxuan |last2=Arora |first2=Aryaman |last3=Wang |first3=Zheng |last4=Geiger |first4=Atticus |last5=Jurafsky |first5=Dan |last6=Manning |first6=Christopher D. |last7=Potts |first7=Christopher }}] or trained [[Statistical classification|classifiers]] with human-annotated data to improve answers for new problems and learn from corrections.[{{Cite web |date=2023-05-31 |title=Improving mathematical reasoning with process supervision |url=https://openai.com/index/improving-mathematical-reasoning-with-process-supervision/ |access-date=2025-01-26 |website=OpenAI |language=en-US}}] A February 2024 study showed that the performance of some language models for reasoning capabilities in solving math problems not included in their training data was low, even for problems with only minor deviations from trained data.[{{Cite arXiv |eprint=2402.19450 |class=cs.AI |first=Saurabh |last=Srivastava |title=Functional Benchmarks for Robust Evaluation of Reasoning Performance, and the Reasoning Gap |date=2024-02-29}}] One technique to improve their performance involves training the models to produce correct [[Automated reasoning|reasoning]] steps, rather than just the correct result.[{{cite arXiv |eprint=2305.20050v1 |class=cs.LG |first1=Hunter |last1=Lightman |first2=Vineet |last2=Kosaraju |title=Let's Verify Step by Step |date=2023 |last3=Burda |first3=Yura |last4=Edwards |first4=Harri |last5=Baker |first5=Bowen |last6=Lee |first6=Teddy |last7=Leike |first7=Jan |last8=Schulman |first8=John |last9=Sutskever |first9=Ilya |last10=Cobbe |first10=Karl}}] The [[Alibaba Group]] developed a version of its ''[[Qwen]]'' models called ''Qwen2-Math'', that achieved state-of-the-art performance on several mathematical benchmarks, including 84% accuracy on the MATH dataset of competition mathematics problems.[{{cite web |last1=Franzen |first1=Carl |title=Alibaba claims no. 1 spot in AI math models with Qwen2-Math |url=https://venturebeat.com/ai/alibaba-claims-no-1-spot-in-ai-math-models-with-qwen2-math/ |website=VentureBeat |date=2024-08-08|access-date=2025-02-16}}] In January 2025, Microsoft proposed the technique ''rStar-Math'' that leverages [[Monte Carlo tree search]] and step-by-step reasoning, enabling a relatively small language model like ''Qwen-7B'' to solve 53% of the [[American Invitational Mathematics Examination|AIME]] 2024 and 90% of the MATH benchmark problems.[{{Cite web |last=Franzen |first=Carl |date=2025-01-09 |title=Microsoft's new rStar-Math technique upgrades small models to outperform OpenAI's o1-preview at math problems |url=https://venturebeat.com/ai/microsofts-new-rstar-math-technique-upgrades-small-models-to-outperform-openais-o1-preview-at-math-problems/ |access-date=2025-01-26 |website=VentureBeat |language=en-US}}]
Alternatively, dedicated models for mathematical problem solving with higher precision for the outcome including proof of theorems have been developed such as ''AlphaTensor'', ''[[AlphaGeometry]]'' and ''AlphaProof'' all from [[Google DeepMind]],[{{Cite web |last=Roberts |first=Siobhan |date=July 25, 2024 |title=AI achieves silver-medal standard solving International Mathematical Olympiad problems |url=https://www.nytimes.com/2024/07/25/science/ai-math-alphaproof-deepmind.html |access-date=2024-08-07 |website=[[The New York Times]] |archive-date=26 September 2024 |archive-url=https://web.archive.org/web/20240926131402/https://www.nytimes.com/2024/07/25/science/ai-math-alphaproof-deepmind.html |url-status=live }}] ''Llemma'' from [[EleutherAI]][{{Cite web |last1=Azerbayev |first1=Zhangir |last2=Schoelkopf |first2=Hailey |last3=Paster |first3=Keiran |last4=Santos |first4=Marco Dos |last5=McAleer' |first5=Stephen |last6=Jiang |first6=Albert Q. |last7=Deng |first7=Jia |last8=Biderman |first8=Stella |last9=Welleck |first9=Sean |date=2023-10-16 |title=Llemma: An Open Language Model For Mathematics |url=https://blog.eleuther.ai/llemma/ |access-date=2025-01-26 |website=EleutherAI Blog |language=en}}] or ''Julius''.[{{Cite web |title=Julius AI |url=https://julius.ai/home/ai-math |access-date= |website=julius.ai |language=en}}]
When natural language is used to describe mathematical problems, converters can transform such prompts into a formal language such as [[Lean (proof assistant)|Lean]] to define mathematical tasks.
Some models have been developed to solve challenging problems and reach good results in benchmark tests, others to serve as educational tools in mathematics.[{{Cite web |last=McFarland |first=Alex |date=2024-07-12 |title=8 Best AI for Math Tools (January 2025) |url=https://www.unite.ai/best-ai-for-math-tools/ |access-date=2025-01-26 |website=Unite.AI |language=en-US}}]
[[Topological deep learning]] integrates various [[topology|topological]] approaches.
=== Finance ===
Finance is one of the fastest growing sectors where applied AI tools are being deployed: from retail online banking to investment advice and insurance, where automated "robot advisers" have been in use for some years.[Matthew Finio & Amanda Downie: IBM Think 2024 Primer, "What is Artificial Intelligence (AI) in Finance?" 8 Dec. 2023]
According to Nicolas Firzli, director of the [[World Pensions & Investments Forum]], it may be too early to see the emergence of highly innovative AI-informed financial products and services. He argues that "the deployment of AI tools will simply further automatise things: destroying tens of thousands of jobs in banking, financial planning, and pension advice in the process, but I'm not sure it will unleash a new wave of [e.g., sophisticated] pension innovation."[M. Nicolas, J. Firzli: Pensions Age / European Pensions magazine, "Artificial Intelligence: Ask the Industry", May–June 2024. https://videovoice.org/ai-in-finance-innovation-entrepreneurship-vs-over-regulation-with-the-eus-artificial-intelligence-act-wont-work-as-intended/ {{Webarchive|url=https://web.archive.org/web/20240911125502/https://videovoice.org/ai-in-finance-innovation-entrepreneurship-vs-over-regulation-with-the-eus-artificial-intelligence-act-wont-work-as-intended/ |date=11 September 2024}}.]
=== Military ===
{{main|Military applications of artificial intelligence}}
Various countries are deploying AI military applications.[{{Cite book|last=Congressional Research Service|url=https://fas.org/sgp/crs/natsec/R45178.pdf|title=Artificial Intelligence and National Security|publisher=Congressional Research Service|year=2019|location=Washington, DC|archive-date=8 May 2020|access-date=25 February 2024|archive-url=https://web.archive.org/web/20200508062631/https://fas.org/sgp/crs/natsec/R45178.pdf|url-status=live}}[[Template:PD-notice|PD-notice]]] The main applications enhance [[command and control]], communications, sensors, integration and interoperability.[{{cite report |type=Preprint |last1=Slyusar |first1=Vadym |title=Artificial intelligence as the basis of future control networks |date=2019 |doi=10.13140/RG.2.2.30247.50087 }}] Research is targeting intelligence collection and analysis, logistics, cyber operations, information operations, and semiautonomous and [[Vehicular automation|autonomous vehicles]].[{{Cite web |last=Iraqi |first=Amjad |date=2024-04-03 |title='Lavender': The AI machine directing Israel's bombing spree in Gaza |url=https://www.972mag.com/lavender-ai-israeli-army-gaza/ |access-date=2024-04-06 |website=+972 Magazine |language=en-US |archive-date=10 October 2024 |archive-url=https://web.archive.org/web/20241010022042/https://www.972mag.com/lavender-ai-israeli-army-gaza/ |url-status=live }}][{{Cite news |last1=Davies |first1=Harry |last2=McKernan |first2=Bethan |last3=Sabbagh |first3=Dan |date=2023-12-01 |title='The Gospel': how Israel uses AI to select bombing targets in Gaza |language=en-GB |work=The Guardian |url=https://www.theguardian.com/world/2023/dec/01/the-gospel-how-israel-uses-ai-to-select-bombing-targets |access-date=2023-12-04 |archive-date=6 December 2023 |archive-url=https://web.archive.org/web/20231206213901/https://www.theguardian.com/world/2023/dec/01/the-gospel-how-israel-uses-ai-to-select-bombing-targets |url-status=live }}][{{Cite news|last=Marti|first=J Werner|title=Drohnen haben den Krieg in der Ukraine revolutioniert, doch sie sind empfindlich auf Störsender – deshalb sollen sie jetzt autonom operieren|url=https://www.nzz.ch/international/die-ukraine-setzt-auf-drohnen-die-autonom-navigieren-und-toeten-koennen-ld.1838731|date=10 August 2024|access-date=10 August 2024|newspaper=Neue Zürcher Zeitung|language=German|archive-date=10 August 2024|archive-url=https://web.archive.org/web/20240810054043/https://www.nzz.ch/international/die-ukraine-setzt-auf-drohnen-die-autonom-navigieren-und-toeten-koennen-ld.1838731|url-status=live}}]
=== Generative AI ===
[[File:Vincent van Gogh in watercolour.png|thumb|[[Vincent van Gogh]] in watercolour created by generative AI software]]{{Excerpt|Generative artificial intelligence|only=paragraphs|paragraphs=1-3}}
===Agents===
Artificial intelligent (AI) agents are software entities designed to perceive their environment, make decisions, and take actions autonomously to achieve specific goals. These agents can interact with users, their environment, or other agents. AI agents are used in various applications, including [[virtual assistant]]s, [[chatbots]], [[autonomous vehicles]], [[Video game console|game-playing systems]], and [[industrial robotics]]. AI agents operate within the constraints of their programming, available computational resources, and hardware limitations. This means they are restricted to performing tasks within their defined scope and have finite memory and processing capabilities. In real-world applications, AI agents often face time constraints for decision-making and action execution. Many AI agents incorporate learning algorithms, enabling them to improve their performance over time through experience or training. Using machine learning, AI agents can adapt to new situations and optimise their behaviour for their designated tasks.[{{Cite book |last1=Poole |first1=David |url=https://doi.org/10.1017/9781009258227 |title=Artificial Intelligence, Foundations of Computational Agents |last2=Mackworth |first2=Alan |date=2023 |publisher=Cambridge University Press |isbn=978-1-0092-5819-7 |edition=3rd |doi=10.1017/9781009258227 |access-date=5 October 2024 |archive-date=5 October 2024 |archive-url=https://web.archive.org/web/20241005165650/https://www.cambridge.org/highereducation/books/artificial-intelligence/C113F6CE284AB00F5489EBA5A59B93B7#overview |url-status=live }}][{{Cite book |last1=Russell |first1=Stuart |title=[[Artificial Intelligence: A Modern Approach]] |last2=Norvig |first2=Peter |publisher=Pearson |date=2020 |isbn=978-0-1346-1099-3 |edition=4th}}][{{Cite web |date=2024-07-24 |title=Why agents are the next frontier of generative AI |url=https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/why-agents-are-the-next-frontier-of-generative-ai |access-date=2024-08-10 |website=McKinsey Digital |archive-date=3 October 2024 |archive-url=https://web.archive.org/web/20241003212335/https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/why-agents-are-the-next-frontier-of-generative-ai |url-status=live }}]
=== Sexuality ===
Applications of AI in this domain include AI-enabled menstruation and fertility trackers that analyze user data to offer prediction,[{{Cite journal |last1=Figueiredo |first1=Mayara Costa |last2=Ankrah |first2=Elizabeth |last3=Powell |first3=Jacquelyn E. |last4=Epstein |first4=Daniel A. |last5=Chen |first5=Yunan |date=2024-01-12 |title=Powered by AI: Examining How AI Descriptions Influence Perceptions of Fertility Tracking Applications |url=https://dl.acm.org/doi/10.1145/3631414 |journal=Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. |volume=7 |issue=4 |pages=154:1–154:24 |doi=10.1145/3631414}}] AI-integrated sex toys (e.g., [[teledildonics]]),[{{Cite journal |last1=Power |first1=Jennifer |last2=Pym |first2=Tinonee |last3=James |first3=Alexandra |last4=Waling |first4=Andrea |date=2024-07-05 |title=Smart Sex Toys: A Narrative Review of Recent Research on Cultural, Health and Safety Considerations |journal=Current Sexual Health Reports |language=en |volume=16 |issue=3 |pages=199–215 |doi=10.1007/s11930-024-00392-3 |issn=1548-3592 |doi-access=free}}] AI-generated sexual education content,[{{Cite journal |last1=Marcantonio |first1=Tiffany L. |last2=Avery |first2=Gracie |last3=Thrash |first3=Anna |last4=Leone |first4=Ruschelle M. |date=2024-09-10 |title=Large Language Models in an App: Conducting a Qualitative Synthetic Data Analysis of How Snapchat's "My AI" Responds to Questions About Sexual Consent, Sexual Refusals, Sexual Assault, and Sexting |url=https://www.tandfonline.com/doi/full/10.1080/00224499.2024.2396457 |url-status=live |journal=The Journal of Sex Research |language=en |pages=1–15 |doi=10.1080/00224499.2024.2396457 |pmid=39254628 |pmc=11891083 |pmc-embargo-date=March 10, 2026 |issn=0022-4499 |archive-url=https://web.archive.org/web/20241209185843/https://www.tandfonline.com/doi/full/10.1080/00224499.2024.2396457 |archive-date=9 December 2024 |access-date=9 December 2024}}] and AI agents that simulate sexual and romantic partners (e.g., [[Replika]]).[{{Cite journal |last1=Hanson |first1=Kenneth R. |last2=Bolthouse |first2=Hannah |date=2024 |title="Replika Removing Erotic Role-Play Is Like Grand Theft Auto Removing Guns or Cars": Reddit Discourse on Artificial Intelligence Chatbots and Sexual Technologies |journal=Socius: Sociological Research for a Dynamic World |language=en |volume=10 |doi=10.1177/23780231241259627 |issn=2378-0231 |doi-access=free}}] AI is also used for the production of non-consensual [[deepfake pornography]], raising significant ethical and legal concerns.[{{Cite journal |last=Mania |first=Karolina |date=2024-01-01 |title=Legal Protection of Revenge and Deepfake Porn Victims in the European Union: Findings From a Comparative Legal Study |url=https://journals.sagepub.com/doi/abs/10.1177/15248380221143772?journalCode=tvaa |journal=Trauma, Violence, & Abuse |language=en |volume=25 |issue=1 |pages=117–129 |doi=10.1177/15248380221143772 |pmid=36565267 |issn=1524-8380}}]
AI technologies have also been used to attempt to identify [[online gender-based violence]] and online [[sexual grooming]] of minors.[{{Cite journal |last1=Singh |first1=Suyesha |last2=Nambiar |first2=Vaishnavi |date=2024 |title=Role of Artificial Intelligence in the Prevention of Online Child Sexual Abuse: A Systematic Review of Literature |url=https://www.tandfonline.com/doi/full/10.1080/19361610.2024.2331885 |url-status=live |journal=Journal of Applied Security Research |language=en |volume=19 |issue=4 |pages=586–627 |doi=10.1080/19361610.2024.2331885 |issn=1936-1610 |archive-url=https://web.archive.org/web/20241209171923/https://www.tandfonline.com/doi/full/10.1080/19361610.2024.2331885 |archive-date=9 December 2024 |access-date=9 December 2024}}][{{Cite journal |last1=Razi |first1=Afsaneh |last2=Kim |first2=Seunghyun |last3=Alsoubai |first3=Ashwaq |last4=Stringhini |first4=Gianluca |last5=Solorio |first5=Thamar |last6=De Choudhury |first6=Munmun|author6-link=Munmun De Choudhury |last7=Wisniewski |first7=Pamela J. |date=2021-10-13 |title=A Human-Centered Systematic Literature Review of the Computational Approaches for Online Sexual Risk Detection |url=https://dl.acm.org/doi/10.1145/3479609 |url-status=live |journal=Proceedings of the ACM on Human-Computer Interaction |language=en |volume=5 |issue=CSCW2 |pages=1–38 |doi=10.1145/3479609 |issn=2573-0142 |archive-url=https://web.archive.org/web/20241209171735/https://dl.acm.org/doi/10.1145/3479609 |archive-date=9 December 2024 |access-date=9 December 2024}}]
===Other industry-specific tasks===
There are also thousands of successful AI applications used to solve specific problems for specific industries or institutions. In a 2017 survey, one in five companies reported having incorporated "AI" in some offerings or processes.[{{Cite journal |last1=Ransbotham |first1=Sam |last2=Kiron |first2=David |last3=Gerbert |first3=Philipp |last4=Reeves |first4=Martin |date=2017-09-06 |title=Reshaping Business With Artificial Intelligence |url=https://sloanreview.mit.edu/projects/reshaping-business-with-artificial-intelligence |url-status=live |journal=MIT Sloan Management Review |archive-url=https://web.archive.org/web/20240213070751/https://sloanreview.mit.edu/projects/reshaping-business-with-artificial-intelligence |archive-date=Feb 13, 2024}}] A few examples are [[energy storage]], medical diagnosis, military logistics, applications that predict the result of judicial decisions, [[foreign policy]], or supply chain management.
AI applications for evacuation and [[disaster]] management are growing. AI has been used to investigate if and how people evacuated in large scale and small scale evacuations using historical data from GPS, videos or social media. Further, AI can provide real time information on the real time evacuation conditions.[{{Citation |last1=Sun |first1=Yuran |title=8 – AI for large-scale evacuation modeling: promises and challenges |date=2024-01-01 |work=Interpretable Machine Learning for the Analysis, Design, Assessment, and Informed Decision Making for Civil Infrastructure |pages=185–204 |editor-last=Naser |editor-first=M. Z. |url=https://www.sciencedirect.com/science/article/pii/B9780128240731000149 |access-date=2024-06-28 |series=Woodhead Publishing Series in Civil and Structural Engineering |publisher=Woodhead Publishing |isbn=978-0-1282-4073-1 |last2=Zhao |first2=Xilei |last3=Lovreglio |first3=Ruggiero |last4=Kuligowski |first4=Erica |archive-date=19 May 2024 |archive-url=https://web.archive.org/web/20240519121547/https://www.sciencedirect.com/science/article/abs/pii/B9780128240731000149 |url-status=live }}.][{{Cite journal |last1=Gomaa |first1=Islam |last2=Adelzadeh |first2=Masoud |last3=Gwynne |first3=Steven |last4=Spencer |first4=Bruce |last5=Ko |first5=Yoon |last6=Bénichou |first6=Noureddine |last7=Ma |first7=Chunyun |last8=Elsagan |first8=Nour |last9=Duong |first9=Dana |last10=Zalok |first10=Ehab |last11=Kinateder |first11=Max |date=2021-11-01 |title=A Framework for Intelligent Fire Detection and Evacuation System |url=https://doi.org/10.1007/s10694-021-01157-3 |journal=Fire Technology |volume=57 |issue=6 |pages=3179–3185 |doi=10.1007/s10694-021-01157-3 |issn=1572-8099 |access-date=5 October 2024 |archive-date=5 October 2024 |archive-url=https://web.archive.org/web/20241005165650/https://link.springer.com/article/10.1007/s10694-021-01157-3 |url-status=live }}][{{Cite journal |last1=Zhao |first1=Xilei |last2=Lovreglio |first2=Ruggiero |last3=Nilsson |first3=Daniel |date=2020-05-01 |title=Modelling and interpreting pre-evacuation decision-making using machine learning |url=https://www.sciencedirect.com/science/article/pii/S0926580519313184 |journal=Automation in Construction |volume=113 |pages=103140 |doi=10.1016/j.autcon.2020.103140 |issn=0926-5805 |access-date=5 October 2024 |archive-date=19 May 2024 |archive-url=https://web.archive.org/web/20240519121548/https://www.sciencedirect.com/science/article/abs/pii/S0926580519313184 |url-status=live |hdl=10179/17315 |hdl-access=free }}]
In agriculture, AI has helped farmers identify areas that need irrigation, fertilization, pesticide treatments or increasing yield. Agronomists use AI to conduct research and development. AI has been used to predict the ripening time for crops such as tomatoes, monitor soil moisture, operate agricultural robots, conduct [[predictive analytics]], classify livestock pig call emotions, automate greenhouses, detect diseases and pests, and save water.
Artificial intelligence is used in astronomy to analyze increasing amounts of available data and applications, mainly for "classification, regression, clustering, forecasting, generation, discovery, and the development of new scientific insights." For example, it is used for discovering exoplanets, forecasting solar activity, and distinguishing between signals and instrumental effects in gravitational wave astronomy. Additionally, it could be used for activities in space, such as space exploration, including the analysis of data from space missions, real-time science decisions of spacecraft, space debris avoidance, and more autonomous operation.
During the [[2024 Indian general election|2024 Indian elections]], US$50 million was spent on authorized AI-generated content, notably by creating [[deepfake]]s of allied (including sometimes deceased) politicians to better engage with voters, and by translating speeches to various local languages.[{{Cite web |date=2024-06-12 |title=India's latest election embraced AI technology. Here are some ways it was used constructively |url=https://www.pbs.org/newshour/world/indias-latest-election-embraced-ai-technology-here-are-some-ways-it-was-used-constructively |access-date=2024-10-28 |website=PBS News |language=en-us |archive-date=17 September 2024 |archive-url=https://web.archive.org/web/20240917194950/https://www.pbs.org/newshour/world/indias-latest-election-embraced-ai-technology-here-are-some-ways-it-was-used-constructively |url-status=live }}]
==Ethics==
{{Main|Ethics of artificial intelligence}}
AI has potential benefits and potential risks.[{{Cite web |title=Ethics of Artificial Intelligence and Robotics |url=https://plato.stanford.edu/archives/fall2023/entries/ethics-ai/ |website=Stanford Encyclopedia of Philosophy Archive |date=30 April 2020 |last1=Müller |first1=Vincent C. |access-date=5 October 2024 |archive-date=5 October 2024 |archive-url=https://web.archive.org/web/20241005165650/https://plato.stanford.edu/archives/fall2023/entries/ethics-ai/ |url-status=live }}] AI may be able to advance science and find solutions for serious problems: [[Demis Hassabis]] of [[DeepMind]] hopes to "solve intelligence, and then use that to solve everything else".{{Sfnp|Simonite|2016}} However, as the use of AI has become widespread, several unintended consequences and risks have been identified.{{Sfnp|Russell|Norvig|2021|p=987}} In-production systems can sometimes not factor ethics and bias into their AI training processes, especially when the AI algorithms are inherently unexplainable in deep learning.{{Sfnp|Laskowski|2023}}
=== Risks and harm ===
==== Privacy and copyright ====
{{Further|Information privacy|Artificial intelligence and copyright}}
Machine learning algorithms require large amounts of data. The techniques used to acquire this data have raised concerns about [[privacy]], [[surveillance]] and [[copyright]].
AI-powered devices and services, such as virtual assistants and IoT products, continuously collect personal information, raising concerns about intrusive data gathering and unauthorized access by third parties. The loss of privacy is further exacerbated by AI's ability to process and combine vast amounts of data, potentially leading to a surveillance society where individual activities are constantly monitored and analyzed without adequate safeguards or transparency.
Sensitive user data collected may include online activity records, geolocation data, video, or audio.{{Sfnp|GAO|2022}} For example, in order to build [[speech recognition]] algorithms, [[Amazon (company)|Amazon]] has recorded millions of private conversations and allowed [[temporary worker]]s to listen to and transcribe some of them.{{Sfnp|Valinsky|2019}} Opinions about this widespread surveillance range from those who see it as a [[necessary evil]] to those for whom it is clearly [[unethical]] and a violation of the [[right to privacy]].{{Sfnp|Russell|Norvig|2021|p=991}}
AI developers argue that this is the only way to deliver valuable applications and have developed several techniques that attempt to preserve privacy while still obtaining the data, such as [[data aggregation]], [[de-identification]] and [[differential privacy]].{{Sfnp|Russell|Norvig|2021|pp=991–992}} Since 2016, some privacy experts, such as [[Cynthia Dwork]], have begun to view privacy in terms of [[fairness (machine learning)|fairness]]. [[Brian Christian]] wrote that experts have pivoted "from the question of 'what they know' to the question of 'what they're doing with it'."{{Sfnp|Christian|2020|p=63}}
Generative AI is often trained on unlicensed copyrighted works, including in domains such as images or computer code; the output is then used under the rationale of "[[fair use]]". Experts disagree about how well and under what circumstances this rationale will hold up in courts of law; relevant factors may include "the purpose and character of the use of the copyrighted work" and "the effect upon the potential market for the copyrighted work".{{Sfnp|Vincent|2022}}[{{Cite web |last=Kopel |first=Matthew |title=Copyright Services: Fair Use |url=https://guides.library.cornell.edu/copyright/fair-use |access-date=2024-04-26 |website=Cornell University Library |archive-date=26 September 2024 |archive-url=https://web.archive.org/web/20240926194057/https://guides.library.cornell.edu/copyright/fair-use |url-status=live }}] Website owners who do not wish to have their content scraped can indicate it in a "[[robots.txt]]" file.[{{Cite magazine |last=Burgess |first=Matt |title=How to Stop Your Data From Being Used to Train AI |url=https://www.wired.com/story/how-to-stop-your-data-from-being-used-to-train-ai |access-date=2024-04-26 |magazine=Wired |issn=1059-1028 |archive-date=3 October 2024 |archive-url=https://web.archive.org/web/20241003180100/https://www.wired.com/story/how-to-stop-your-data-from-being-used-to-train-ai/ |url-status=live }}] In 2023, leading authors (including [[John Grisham]] and [[Jonathan Franzen]]) sued AI companies for using their work to train generative AI.{{Sfnp|Reisner|2023}}{{Sfnp|Alter|Harris|2023}} Another discussed approach is to envision a separate ''[[sui generis]]'' system of protection for creations generated by AI to ensure fair attribution and compensation for human authors.[{{Cite web |title=Getting the Innovation Ecosystem Ready for AI. An IP policy toolkit |url=https://www.wipo.int/edocs/pubdocs/en/wipo-pub-2003-en-getting-the-innovation-ecosystem-ready-for-ai.pdf |website=[[WIPO]]}}]
====Dominance by tech giants====
The commercial AI scene is dominated by [[Big Tech]] companies such as [[Alphabet Inc.]], [[Amazon (company)|Amazon]], [[Apple Inc.]], [[Meta Platforms]], and [[Microsoft]].[{{Cite web |last=Hammond |first=George |date=27 December 2023 |title=Big Tech is spending more than VC firms on AI startups |url=https://arstechnica.com/ai/2023/12/big-tech-is-spending-more-than-vc-firms-on-ai-startups |url-status=live |archive-url=https://web.archive.org/web/20240110195706/https://arstechnica.com/ai/2023/12/big-tech-is-spending-more-than-vc-firms-on-ai-startups |archive-date=Jan 10, 2024 |website=Ars Technica}}][{{Cite web |last=Wong |first=Matteo |date=24 October 2023 |title=The Future of AI Is GOMA |url=https://www.theatlantic.com/technology/archive/2023/10/big-ai-silicon-valley-dominance/675752 |url-access=subscription |url-status=live |archive-url=https://web.archive.org/web/20240105020744/https://www.theatlantic.com/technology/archive/2023/10/big-ai-silicon-valley-dominance/675752 |archive-date=Jan 5, 2024 |website=The Atlantic |ref=none}}][{{Cite news |date=Mar 26, 2023 |title=Big tech and the pursuit of AI dominance |url=https://www.economist.com/business/2023/03/26/big-tech-and-the-pursuit-of-ai-dominance |url-access=subscription |url-status=live |archive-url=https://web.archive.org/web/20231229021351/https://www.economist.com/business/2023/03/26/big-tech-and-the-pursuit-of-ai-dominance |archive-date=Dec 29, 2023 |newspaper=The Economist}}] Some of these players already own the vast majority of existing [[cloud computing|cloud infrastructure]] and [[computing]] power from [[data center]]s, allowing them to entrench further in the marketplace.[{{Cite news |last=Fung |first=Brian |date=19 December 2023 |title=Where the battle to dominate AI may be won |url=https://www.cnn.com/2023/12/19/tech/cloud-competition-and-ai/index.html |url-status=live |archive-url=https://web.archive.org/web/20240113053332/https://www.cnn.com/2023/12/19/tech/cloud-competition-and-ai/index.html |archive-date=Jan 13, 2024 |work=CNN Business}}][{{Cite news |last=Metz |first=Cade |date=5 July 2023 |title=In the Age of A.I., Tech's Little Guys Need Big Friends |url=https://www.nytimes.com/2023/07/05/business/artificial-intelligence-power-data-centers.html |work=The New York Times |access-date=5 October 2024 |archive-date=8 July 2024 |archive-url=https://web.archive.org/web/20240708214644/https://www.nytimes.com/2023/07/05/business/artificial-intelligence-power-data-centers.html |url-status=live }}]
====Power needs and environmental impacts====
{{See also|Environmental impacts of artificial intelligence}}
In January 2024, the [[International Energy Agency]] (IEA) released ''Electricity 2024, Analysis and Forecast to 2026'', forecasting electric power use.[{{Cite web |date=2024-01-24 |title=Electricity 2024 – Analysis |url=https://www.iea.org/reports/electricity-2024 |access-date=2024-07-13 |website=IEA}}] This is the first IEA report to make projections for data centers and power consumption for artificial intelligence and cryptocurrency. The report states that power demand for these uses might double by 2026, with additional electric power usage equal to electricity used by the whole Japanese nation.[{{Cite web |last=Calvert |first=Brian |date=28 March 2024 |title=AI already uses as much energy as a small country. It's only the beginning. |url=https://www.vox.com/climate/2024/3/28/24111721/ai-uses-a-lot-of-energy-experts-expect-it-to-double-in-just-a-few-years |website=Vox |location=New York, New York |access-date=5 October 2024 |archive-date=3 July 2024 |archive-url=https://web.archive.org/web/20240703080555/https://www.vox.com/climate/2024/3/28/24111721/ai-uses-a-lot-of-energy-experts-expect-it-to-double-in-just-a-few-years |url-status=live }}]
Prodigious power consumption by AI is responsible for the growth of fossil fuels use, and might delay closings of obsolete, carbon-emitting coal energy facilities. There is a feverish rise in the construction of data centers throughout the US, making large technology firms (e.g., Microsoft, Meta, Google, Amazon) into voracious consumers of electric power. Projected electric consumption is so immense that there is concern that it will be fulfilled no matter the source. A ChatGPT search involves the use of 10 times the electrical energy as a Google search. The large firms are in haste to find power sources – from nuclear energy to geothermal to fusion. The tech firms argue that – in the long view – AI will be eventually kinder to the environment, but they need the energy now. AI makes the power grid more efficient and "intelligent", will assist in the growth of nuclear power, and track overall carbon emissions, according to technology firms.[{{Cite news |last1=Halper |first1=Evan |last2=O'Donovan |first2=Caroline |date=21 June 2024 |title=AI is exhausting the power grid. Tech firms are seeking a miracle solution. |url=https://www.washingtonpost.com/business/2024/06/21/artificial-intelligence-nuclear-fusion-climate/?utm_campaign=wp_post_most&utm_medium=email&utm_source=newsletter&wpisrc=nl_most&carta-url=https%3A%2F%2Fs2.washingtonpost.com%2Fcar-ln-tr%2F3e0d678%2F6675a2d2c2c05472dd9ec0f4%2F596c09009bbc0f20865036e7%2F12%2F52%2F6675a2d2c2c05472dd9ec0f4 |newspaper=Washington Post}}]
A 2024 [[Goldman Sachs]] Research Paper, ''AI Data Centers and the Coming US Power Demand Surge'', found "US power demand (is) likely to experience growth not seen in a generation...." and forecasts that, by 2030, US data centers will consume 8% of US power, as opposed to 3% in 2022, presaging growth for the electrical power generation industry by a variety of means.[{{Cite web |last=Davenport |first=Carly |title=AI Data Centers and the Coming YS Power Demand Surge |url=https://www.goldmansachs.com/intelligence/pages/gs-research/generational-growth-ai-data-centers-and-the-coming-us-power-surge/report.pdf |website=Goldman Sachs |access-date=5 October 2024 |archive-date=26 July 2024 |archive-url=https://web.archive.org/web/20240726080428/https://www.goldmansachs.com/intelligence/pages/gs-research/generational-growth-ai-data-centers-and-the-coming-us-power-surge/report.pdf |url-status=dead }}] Data centers' need for more and more electrical power is such that they might max out the electrical grid. The Big Tech companies counter that AI can be used to maximize the utilization of the grid by all.[{{Cite news |last=Ryan |first=Carol |date=12 April 2024 |title=Energy-Guzzling AI Is Also the Future of Energy Savings |url=https://www.wsj.com/business/energy-oil/ai-data-centers-energy-savings-d602296e |work=Wall Street Journal |publisher=Dow Jones}}]
In 2024, the ''Wall Street Journal'' reported that big AI companies have begun negotiations with the US nuclear power providers to provide electricity to the data centers. In March 2024 Amazon purchased a Pennsylvania nuclear-powered data center for $650 Million (US).[{{Cite news |last=Hiller |first=Jennifer |date=1 July 2024 |title=Tech Industry Wants to Lock Up Nuclear Power for AI |url=https://www.wsj.com/business/energy-oil/tech-industry-wants-to-lock-up-nuclear-power-for-ai-6cb75316?mod=djem10point |work=Wall Street Journal |publisher=Dow Jones |access-date=5 October 2024 |archive-date=5 October 2024 |archive-url=https://web.archive.org/web/20241005165650/https://www.wsj.com/business/energy-oil/tech-industry-wants-to-lock-up-nuclear-power-for-ai-6cb75316?mod=djem10point |url-status=live }}] [[Nvidia]] CEO [[Jen-Hsun Huang]] said nuclear power is a good option for the data centers.[{{Cite news |last1=Kendall |first1=Tyler |date=28 September 2024 |title=Nvidia's Huang Says Nuclear Power an Option to Feed Data Centers |url=https://www.bloomberg.com/news/articles/2024-09-27/nvidia-s-huang-says-nuclear-power-an-option-to-feed-data-centers |newspaper=Bloomberg}}]
In September 2024, [[Microsoft]] announced an agreement with [[Constellation Energy]] to re-open the [[Three Mile Island]] nuclear power plant to provide Microsoft with 100% of all electric power produced by the plant for 20 years. Reopening the plant, which suffered a partial nuclear meltdown of its Unit 2 reactor in 1979, will require Constellation to get through strict regulatory processes which will include extensive safety scrutiny from the US [[Nuclear Regulatory Commission]]. If approved (this will be the first ever US re-commissioning of a nuclear plant), over 835 megawatts of power – enough for 800,000 homes – of energy will be produced. The cost for re-opening and upgrading is estimated at $1.6 billion (US) and is dependent on tax breaks for nuclear power contained in the 2022 US [[Inflation Reduction Act]].[{{Cite news |last=Halper |first=Evan |date=20 September 2024 |title=Microsoft deal would reopen Three Mile Island nuclear plant to power AI |url=https://www.washingtonpost.com/business/2024/09/20/microsoft-three-mile-island-nuclear-constellation |newspaper=Washington Post}}] The US government and the state of Michigan are investing almost $2 billion (US) to reopen the [[Palisades Nuclear Generating Station|Palisades Nuclear]] reactor on Lake Michigan. Closed since 2022, the plant is planned to be reopened in October 2025. The Three Mile Island facility will be renamed the Crane Clean Energy Center after Chris Crane, a nuclear proponent and former CEO of [[Exelon]] who was responsible for Exelon spinoff of Constellation.[{{Cite news |last=Hiller |first=Jennifer |date=20 September 2024 |title=Three Mile Island's Nuclear Plant to Reopen, Help Power Microsoft's AI Centers |url=https://www.wsj.com/business/energy-oil/three-mile-islands-nuclear-plant-to-reopen-help-power-microsofts-ai-centers-aebfb3c8?mod=Searchresults_pos1&page=1 |work=Wall Street Journal |publisher=Dow Jones |access-date=5 October 2024 |archive-date=5 October 2024 |archive-url=https://web.archive.org/web/20241005170152/https://www.wsj.com/business/energy-oil/three-mile-islands-nuclear-plant-to-reopen-help-power-microsofts-ai-centers-aebfb3c8?mod=Searchresults_pos1&page=1 |url-status=live }}]
After the last approval in September 2023, [[Taiwan]] suspended the approval of data centers north of [[Taoyuan, Taiwan|Taoyuan]] with a capacity of more than 5 MW in 2024, due to power supply shortages.[{{Cite news |author=Niva Yadav |date=19 August 2024 |title=Taiwan to stop large data centers in the North, cites insufficient power |url=https://www.datacenterdynamics.com/en/news/taiwan-to-stop-large-data-centers-in-the-north-cites-insufficient-power/ |publisher=DatacenterDynamics |archive-date=8 November 2024 |access-date=7 November 2024 |archive-url=https://web.archive.org/web/20241108213650/https://www.datacenterdynamics.com/en/news/taiwan-to-stop-large-data-centers-in-the-north-cites-insufficient-power/ |url-status=live }}] Taiwan aims to [[Nuclear power phase-out|phase out nuclear power]] by 2025.[{{Cite news |last1=Mochizuki |first1=Takashi |last2=Oda |first2=Shoko |date=18 October 2024 |title=エヌビディア出資の日本企業、原発近くでＡＩデータセンター新設検討 |url=https://www.bloomberg.co.jp/news/articles/2024-10-18/SLHGKKT0AFB400 |newspaper=Bloomberg |language=Japanese |archive-date=8 November 2024 |access-date=7 November 2024 |archive-url=https://web.archive.org/web/20241108213843/https://www.bloomberg.co.jp/news/articles/2024-10-18/SLHGKKT0AFB400 |url-status=live }}] Ubitus CEO Wesley Kuo said nuclear power plants are the most efficient, cheap and stable power for AI.[{{Cite news |author=Naureen S Malik and Will Wade |date=5 November 2024 |title=Nuclear-Hungry AI Campuses Need New Plan to Find Power Fast |url=https://www.bloomberg.com/news/articles/2024-11-04/nuclear-hungry-ai-campuses-need-new-strategy-to-find-power-fast |publisher=Bloomberg}}]
According to the Commission Chairman [[Willie L. Phillips]], it is a burden on the electricity grid as well as a significant cost shifting concern to households and other business sectors.[{{cite web |title=Energy and AI Executive summary |url=https://www.iea.org/reports/energy-and-ai/executive-summary |website=International Energy Agency |access-date=10 April 2025}}]
==== Misinformation ====
{{See also|YouTube#Moderation and offensive content}}
[[YouTube]], [[Facebook]] and others use [[recommender system]]s to guide users to more content. These AI programs were given the goal of [[mathematical optimization|maximizing]] user engagement (that is, the only goal was to keep people watching). The AI learned that users tended to choose [[misinformation]], [[conspiracy theories]], and extreme [[partisan (politics)|partisan]] content, and, to keep them watching, the AI recommended more of it. Users also tended to watch more content on the same subject, so the AI led people into [[filter bubbles]] where they received multiple versions of the same misinformation.{{Sfnp|Nicas|2018}} This convinced many users that the misinformation was true, and ultimately undermined trust in institutions, the media and the government.[{{Cite web |last1=Rainie |first1=Lee |last2=Keeter |first2=Scott |last3=Perrin |first3=Andrew |date=July 22, 2019 |title=Trust and Distrust in America |url=https://www.pewresearch.org/politics/2019/07/22/trust-and-distrust-in-america |url-status=live |archive-url=https://web.archive.org/web/20240222000601/https://www.pewresearch.org/politics/2019/07/22/trust-and-distrust-in-america |archive-date=Feb 22, 2024 |website=Pew Research Center}}] The AI program had correctly learned to maximize its goal, but the result was harmful to society. After the U.S. election in 2016, major technology companies took some steps to mitigate the problem.[{{Cite magazine |last=Kosoff |first=Maya |date=2018-02-08 |title=YouTube Struggles to Contain Its Conspiracy Problem |url=https://www.vanityfair.com/news/2018/02/youtube-conspiracy-problem |access-date=2025-04-10 |magazine=Vanity Fair |language=en-US}}]
In 2022, [[generative AI]] began to create images, audio, video and text that are indistinguishable from real photographs, recordings, films, or human writing. It is possible for bad actors to use this technology to create massive amounts of misinformation or propaganda.{{Sfnp|Williams|2023}} One such potential malicious use is deepfakes for [[computational propaganda]][{{Cite journal |last=Olanipekun |first=Samson Olufemi |date=2025 |title=Computational propaganda and misinformation: AI technologies as tools of media manipulation |url=https://journalwjarr.com/node/366 |journal=World Journal of Advanced Research and Reviews |language=en |volume=25 |issue=1 |pages=911–923 |doi=10.30574/wjarr.2025.25.1.0131 |issn=2581-9615}}]. AI pioneer [[Geoffrey Hinton]] expressed concern about AI enabling "authoritarian leaders to manipulate their electorates" on a large scale, among other risks.{{Sfnp|Taylor|Hern|2023}}
====Algorithmic bias and fairness====
{{Main|Algorithmic bias|Fairness (machine learning)}}
Machine learning applications will be [[algorithmic bias|biased]]{{Efn|In statistics, a [[Bias (statistics)|bias]] is a systematic error or deviation from the correct value. But in the context of [[Fairness (machine learning)|fairness]], it refers to a tendency in favor or against a certain group or individual characteristic, usually in a way that is considered unfair or harmful. A statistically unbiased AI system that produces disparate outcomes for different demographic groups may thus be viewed as biased in the ethical sense.[{{Harvtxt|Berdahl|Baker|Mann|Osoba|2023}}; {{Harvtxt|Goffrey|2008|p=17}}; {{Harvtxt|Rose|2023}}; {{Harvtxt|Russell|Norvig|2021|p=995}}] The field of [[fairness (machine learning)|fairness]] studies how to prevent harms from algorithmic biases.
On June 28, 2015, [[Google Photos]]'s new image labeling feature mistakenly identified Jacky Alcine and a friend as "gorillas" because they were black. The system was trained on a dataset that contained very few images of black people,{{Sfnp|Christian|2020|p=25}} a problem called "sample size disparity".{{Sfnp|Russell|Norvig|2021|p=995}} Google "fixed" this problem by preventing the system from labelling ''anything'' as a "gorilla". Eight years later, in 2023, Google Photos still could not identify a gorilla, and neither could similar products from Apple, Facebook, Microsoft and Amazon.{{Sfnp|Grant|Hill|2023}}
[[COMPAS (software)|COMPAS]] is a commercial program widely used by [[U.S. court]]s to assess the likelihood of a [[defendant]] becoming a [[recidivist]]. In 2016, [[Julia Angwin]] at [[ProPublica]] discovered that COMPAS exhibited racial bias, despite the fact that the program was not told the races of the defendants. Although the error rate for both whites and blacks was calibrated equal at exactly 61%, the errors for each race were different—the system consistently overestimated the chance that a black person would re-offend and would underestimate the chance that a white person would not re-offend.{{Sfnp|Larson|Angwin|2016}} In 2017, several researchers{{Efn|Including [[Jon Kleinberg]] ([[Cornell University]]), Sendhil Mullainathan ([[University of Chicago]]), Cynthia Chouldechova ([[Carnegie Mellon]]) and Sam Corbett-Davis ([[Stanford]]){{Sfnp|Christian|2020|p=67–70}}}} showed that it was mathematically impossible for COMPAS to accommodate all possible measures of fairness when the base rates of re-offense were different for whites and blacks in the data.[{{Harvtxt|Christian|2020|pp=67–70}}; {{Harvtxt|Russell|Norvig|2021|pp=993–994}}]
A program can make biased decisions even if the data does not explicitly mention a problematic feature (such as "race" or "gender"). The feature will correlate with other features (like "address", "shopping history" or "first name"), and the program will make the same decisions based on these features as it would on "race" or "gender".[{{Harvtxt|Russell|Norvig|2021|p=995}}; {{Harvtxt|Lipartito|2011|p=36}}; {{Harvtxt|Goodman|Flaxman|2017|p=6}}; {{Harvtxt|Christian|2020|pp=39–40, 65}}] Moritz Hardt said "the most robust fact in this research area is that fairness through blindness doesn't work."[Quoted in {{Harvtxt|Christian|2020|p=65}}.]
Criticism of COMPAS highlighted that machine learning models are designed to make "predictions" that are only valid if we assume that the future will resemble the past. If they are trained on data that includes the results of racist decisions in the past, machine learning models must predict that racist decisions will be made in the future. If an application then uses these predictions as ''recommendations'', some of these "recommendations" will likely be racist.[{{Harvtxt|Russell|Norvig|2021|p=994}}; {{Harvtxt|Christian|2020|pp=40, 80–81}}] Thus, machine learning is not well suited to help make decisions in areas where there is hope that the future will be ''better'' than the past. It is descriptive rather than prescriptive.{{Efn|Moritz Hardt (a director at the [[Max Planck Institute for Intelligent Systems]]) argues that machine learning "is fundamentally the wrong tool for a lot of domains, where you're trying to design interventions and mechanisms that change the world."[Quoted in {{Harvtxt|Christian|2020|p=80}}]}}
Bias and unfairness may go undetected because the developers are overwhelmingly white and male: among AI engineers, about 4% are black and 20% are women.{{Sfnp|Russell|Norvig|2021|p=995}}
There are various conflicting definitions and mathematical models of fairness. These notions depend on ethical assumptions, and are influenced by beliefs about society. One broad category is [[Distributive justice|distributive fairness]], which focuses on the outcomes, often identifying groups and seeking to compensate for statistical disparities. Representational fairness tries to ensure that AI systems do not reinforce negative [[stereotype]]s or render certain groups invisible. Procedural fairness focuses on the decision process rather than the outcome. The most relevant notions of fairness may depend on the context, notably the type of AI application and the stakeholders. The subjectivity in the notions of bias and fairness makes it difficult for companies to operationalize them. Having access to sensitive attributes such as race or gender is also considered by many AI ethicists to be necessary in order to compensate for biases, but it may conflict with [[anti-discrimination law]]s.[{{Cite web |last=Samuel |first=Sigal |date=2022-04-19 |title=Why it's so damn hard to make AI fair and unbiased |url=https://www.vox.com/future-perfect/22916602/ai-bias-fairness-tradeoffs-artificial-intelligence |access-date=2024-07-24 |website=Vox |archive-date=5 October 2024 |archive-url=https://web.archive.org/web/20241005170153/https://www.vox.com/future-perfect/22916602/ai-bias-fairness-tradeoffs-artificial-intelligence |url-status=live }}]
At its 2022 [[ACM Conference on Fairness, Accountability, and Transparency|Conference on Fairness, Accountability, and Transparency]] (ACM FAccT 2022), the [[Association for Computing Machinery]], in Seoul, South Korea, presented and published findings that recommend that until AI and robotics systems are demonstrated to be free of bias mistakes, they are unsafe, and the use of self-learning neural networks trained on vast, unregulated sources of flawed internet data should be curtailed.{{Dubious|date=July 2024|reason=Depending on what is meant by "free of bias", it may be impossible in practice to demonstrate it. Additionally, the study evaluates the priors (initial assumptions) of the robots, rather than their decision-making in scenarios where there is a correct choice. For example, it may not be sexist to have the prior that most doctors are males (it's actually an accurate statistical prior in the world we currently live in, so the bias may arguably be to not have this prior). If forced to choose which one is the doctor based solely on gender, a rational person seeking to maximize the number of correct answers would choose the man 100% of the time. The real issue arises when such priors lead to significant discrimination.}}{{Sfnp|Dockrill|2022}}
==== Lack of transparency ====
{{See also|Explainable AI|Algorithmic transparency|Right to explanation}}
Many AI systems are so complex that their designers cannot explain how they reach their decisions.{{Sfnp|Sample|2017}} Particularly with [[deep neural networks]], in which there are a large amount of non-[[linear]] relationships between inputs and outputs. But some popular explainability techniques exist.[{{Cite web |date=16 June 2023 |title=Black Box AI |url=https://www.techopedia.com/definition/34940/black-box-ai |access-date=5 October 2024 |archive-date=15 June 2024 |archive-url=https://web.archive.org/web/20240615100800/https://www.techopedia.com/definition/34940/black-box-ai |url-status=live }}]
It is impossible to be certain that a program is operating correctly if no one knows how exactly it works. There have been many cases where a machine learning program passed rigorous tests, but nevertheless learned something different than what the programmers intended. For example, a system that could identify skin diseases better than medical professionals was found to actually have a strong tendency to classify images with a [[ruler]] as "cancerous", because pictures of malignancies typically include a ruler to show the scale.{{Sfnp|Christian|2020|p=110}} Another machine learning system designed to help effectively allocate medical resources was found to classify patients with asthma as being at "low risk" of dying from pneumonia. Having asthma is actually a severe risk factor, but since the patients having asthma would usually get much more medical care, they were relatively unlikely to die according to the training data. The correlation between asthma and low risk of dying from pneumonia was real, but misleading.{{Sfnp|Christian|2020|pp=88–91}}
People who have been harmed by an algorithm's decision have a right to an explanation.[{{Harvtxt|Christian|2020|p=83}}; {{Harvtxt|Russell|Norvig|2021|p=997}}] Doctors, for example, are expected to clearly and completely explain to their colleagues the reasoning behind any decision they make. Early drafts of the European Union's [[General Data Protection Regulation]] in 2016 included an explicit statement that this right exists.{{Efn|When the law was passed in 2018, it still contained a form of this provision.}} Industry experts noted that this is an unsolved problem with no solution in sight. Regulators argued that nevertheless the harm is real: if the problem has no solution, the tools should not be used.{{Sfnp|Christian|2020|p=91}}
[[DARPA]] established the [[Explainable Artificial Intelligence|XAI]] ("Explainable Artificial Intelligence") program in 2014 to try to solve these problems.{{Sfnp|Christian|2020|p=83}}
Several approaches aim to address the transparency problem. SHAP enables to visualise the contribution of each feature to the output.{{Sfnp|Verma|2021}} LIME can locally approximate a model's outputs with a simpler, interpretable model.{{Sfnp|Rothman|2020}} [[Multitask learning]] provides a large number of outputs in addition to the target classification. These other outputs can help developers deduce what the network has learned.{{Sfnp|Christian|2020|pp=105–108}} [[Deconvolution]], [[DeepDream]] and other [[generative AI|generative]] methods can allow developers to see what different layers of a deep network for computer vision have learned, and produce output that can suggest what the network is learning.{{Sfnp|Christian|2020|pp=108–112}} For [[generative pre-trained transformer]]s, [[Anthropic]] developed a technique based on [[dictionary learning]] that associates patterns of neuron activations with human-understandable concepts.[{{Cite web |last=Ropek |first=Lucas |date=2024-05-21 |title=New Anthropic Research Sheds Light on AI's 'Black Box' |url=https://gizmodo.com/new-anthropic-research-sheds-light-on-ais-black-box-1851491333 |access-date=2024-05-23 |website=Gizmodo |archive-date=5 October 2024 |archive-url=https://web.archive.org/web/20241005170309/https://gizmodo.com/new-anthropic-research-sheds-light-on-ais-black-box-1851491333 |url-status=live }}]
==== Bad actors and weaponized AI ====
{{Main|Lethal autonomous weapon|Artificial intelligence arms race|AI safety}}
Artificial intelligence provides a number of tools that are useful to [[bad actor]]s, such as [[authoritarian|authoritarian governments]], [[terrorist]]s, [[criminals]] or [[rogue states]].
A lethal autonomous weapon is a machine that locates, selects and engages human targets without human supervision.{{Efn|This is the [[United Nations]]' definition, and includes things like [[land mines]] as well.{{Sfnp|Russell|Norvig|2021|p=989}}}} Widely available AI tools can be used by bad actors to develop inexpensive autonomous weapons and, if produced at scale, they are potentially [[weapons of mass destruction]].{{Sfnp|Russell|Norvig|2021|pp=987–990}} Even when used in conventional warfare, they currently cannot reliably choose targets and could potentially [[murder|kill an innocent person]].{{Sfnp|Russell|Norvig|2021|pp=987–990}} In 2014, 30 nations (including China) supported a ban on autonomous weapons under the [[United Nations]]' [[Convention on Certain Conventional Weapons]], however the [[United States]] and others disagreed.{{Sfnp|Russell|Norvig|2021|p=988}} By 2015, over fifty countries were reported to be researching battlefield robots.[{{Harvtxt|Robitzski|2018}}; {{Harvtxt|Sainato|2015}}]
AI tools make it easier for [[Authoritarian|authoritarian governments]] to efficiently control their citizens in several ways. [[Facial recognition system|Face]] and [[Speaker recognition|voice recognition]] allow widespread [[surveillance]]. [[Machine learning]], operating this data, can [[classifier (machine learning)|classify]] potential enemies of the state and prevent them from hiding. [[Recommendation systems]] can precisely target [[propaganda]] and [[misinformation]] for maximum effect. [[Deepfakes]] and [[generative AI]] aid in producing misinformation. Advanced AI can make authoritarian [[technocracy|centralized decision making]] more competitive than liberal and decentralized systems such as [[market (economics)|market]]s. It lowers the cost and difficulty of [[digital warfare]] and [[spyware|advanced spyware]].{{Sfnp|Harari|2018}} All these technologies have been available since 2020 or earlier—AI [[facial recognition system]]s are already being used for [[mass surveillance]] in China.[{{Cite news |last1=Buckley |first1=Chris |last2=Mozur |first2=Paul |date=22 May 2019 |title=How China Uses High-Tech Surveillance to Subdue Minorities |url=https://www.nytimes.com/2019/05/22/world/asia/china-surveillance-xinjiang.html |work=The New York Times |access-date=2 July 2019 |archive-date=25 November 2019 |archive-url=https://web.archive.org/web/20191125180459/https://www.nytimes.com/2019/05/22/world/asia/china-surveillance-xinjiang.html |url-status=live }}][{{Cite web |date=3 May 2019 |title=Security lapse exposed a Chinese smart city surveillance system |url=https://techcrunch.com/2019/05/03/china-smart-city-exposed |url-status=live |archive-url=https://web.archive.org/web/20210307203740/https://consent.yahoo.com/v2/collectConsent?sessionId=3_cc-session_c8562b93-9863-4915-8523-6c7b930a3efc |archive-date=7 March 2021 |access-date=14 September 2020}}]
There many other ways that AI is expected to help bad actors, some of which can not be foreseen. For example, machine-learning AI is able to design tens of thousands of toxic molecules in a matter of hours.{{Sfnp|Urbina|Lentzos|Invernizzi|Ekins|2022}}
==== Technological unemployment ====
{{Main|Workplace impact of artificial intelligence|Technological unemployment}}
Economists have frequently highlighted the risks of redundancies from AI, and speculated about unemployment if there is no adequate social policy for full employment.[E. McGaughey, 'Will Robots Automate Your Job Away? Full Employment, Basic Income, and Economic Democracy' (2022), [https://academic.oup.com/ilj/article/51/3/511/6321008 51(3) Industrial Law Journal 511–559]. {{Webarchive|url=https://web.archive.org/web/20230527163045/https://academic.oup.com/ilj/article/51/3/511/6321008|date=27 May 2023}}.]
In the past, technology has tended to increase rather than reduce total employment, but economists acknowledge that "we're in uncharted territory" with AI.[{{Harvtxt|Ford|Colvin|2015}};{{Harvtxt|McGaughey|2022}}] A survey of economists showed disagreement about whether the increasing use of robots and AI will cause a substantial increase in long-term [[unemployment]], but they generally agree that it could be a net benefit if [[productivity]] gains are [[Redistribution of income and wealth|redistributed]].{{Sfnp|IGM Chicago|2017}} Risk estimates vary; for example, in the 2010s, Michael Osborne and [[Carl Benedikt Frey]] estimated 47% of U.S. jobs are at "high risk" of potential automation, while an OECD report classified only 9% of U.S. jobs as "high risk".{{Efn|See table 4; 9% is both the OECD average and the U.S. average.{{Sfnp|Arntz|Gregory|Zierahn|2016|p=33}}}}[{{Harvtxt|Lohr|2017}}; {{Harvtxt|Frey|Osborne|2017}}; {{Harvtxt|Arntz|Gregory|Zierahn|2016|p=33}}] The methodology of speculating about future employment levels has been criticised as lacking evidential foundation, and for implying that technology, rather than social policy, creates unemployment, as opposed to redundancies.[{{Cite web |last=Zhou |first=Viola |date=2023-04-11 |title=AI is already taking video game illustrators' jobs in China |url=https://restofworld.org/2023/ai-image-china-video-game-layoffs |access-date=2023-08-17 |website=Rest of World |archive-date=21 February 2024 |archive-url=https://web.archive.org/web/20240221131748/https://restofworld.org/2023/ai-image-china-video-game-layoffs/ |url-status=live }}][{{Cite web |last=Carter |first=Justin |date=2023-04-11 |title=China's game art industry reportedly decimated by growing AI use |url=https://www.gamedeveloper.com/art/china-s-game-art-industry-reportedly-decimated-ai-art-use |access-date=2023-08-17 |website=Game Developer |archive-date=17 August 2023 |archive-url=https://web.archive.org/web/20230817010519/https://www.gamedeveloper.com/art/china-s-game-art-industry-reportedly-decimated-ai-art-use |url-status=live }}]
Unlike previous waves of automation, many middle-class jobs may be eliminated by artificial intelligence; ''[[The Economist]]'' stated in 2015 that "the worry that AI could do to white-collar jobs what steam power did to blue-collar ones during the Industrial Revolution" is "worth taking seriously".{{Sfnp|Morgenstern|2015}} Jobs at extreme risk range from [[paralegal]]s to fast food cooks, while job demand is likely to increase for care-related professions ranging from personal healthcare to the clergy.[{{Harvtxt|Mahdawi|2017}}; {{Harvtxt|Thompson|2014}}]
From the early days of the development of artificial intelligence, there have been arguments, for example, those put forward by [[Joseph Weizenbaum]], about whether tasks that can be done by computers actually should be done by them, given the difference between computers and humans, and between quantitative calculation and qualitative, value-based judgement.[{{Cite news |last=Tarnoff |first=Ben |date=4 August 2023 |title=Lessons from Eliza |work=[[The Guardian Weekly]] |pages=34–39}}]
==== Existential risk ====
{{Main|Existential risk from artificial intelligence}}
It has been argued AI will become so powerful that humanity may irreversibly lose control of it. This could, as physicist [[Stephen Hawking]] stated, "[[Global catastrophic risk|spell the end of the human race]]".{{Sfnp|Cellan-Jones|2014}} This scenario has been common in science fiction, when a computer or robot suddenly develops a human-like "self-awareness" (or "sentience" or "consciousness") and becomes a malevolent character.{{Efn|Sometimes called a "[[robopocalypse]]"{{Sfn|Russell|Norvig|2021|p=1001}}}} These sci-fi scenarios are misleading in several ways.
First, AI does not require human-like [[sentience]] to be an existential risk. Modern AI programs are given specific goals and use learning and intelligence to achieve them. Philosopher [[Nick Bostrom]] argued that if one gives ''almost any'' goal to a sufficiently powerful AI, it may choose to destroy humanity to achieve it (he used the example of a [[Instrumental convergence#Paperclip maximizer|paperclip factory manager]]).{{Sfnp|Bostrom|2014}} [[Stuart J. Russell|Stuart Russell]] gives the example of household robot that tries to find a way to kill its owner to prevent it from being unplugged, reasoning that "you can't fetch the coffee if you're dead."{{Sfnp|Russell|2019}} In order to be safe for humanity, a [[superintelligence]] would have to be genuinely [[AI alignment|aligned]] with humanity's morality and values so that it is "fundamentally on our side".[{{Harvtxt|Bostrom|2014}}; {{Harvtxt|Müller|Bostrom|2014}}; {{Harvtxt|Bostrom|2015}}.]
Second, [[Yuval Noah Harari]] argues that AI does not require a robot body or physical control to pose an existential risk. The essential parts of civilization are not physical. Things like [[ideologies]], [[law]], [[government]], [[money]] and the [[economy]] are built on [[language]]; they exist because there are stories that billions of people believe. The current prevalence of [[misinformation]] suggests that an AI could use language to convince people to believe anything, even to take actions that are destructive.{{Sfnp|Harari|2023}}
The opinions amongst experts and industry insiders are mixed, with sizable fractions both concerned and unconcerned by risk from eventual superintelligent AI.{{Sfnp|Müller|Bostrom|2014}} Personalities such as [[Stephen Hawking]], [[Bill Gates]], and [[Elon Musk]],[Leaders' concerns about the existential risks of AI around 2015: {{Harvtxt|Rawlinson|2015}}, {{Harvtxt|Holley|2015}}, {{Harvtxt|Gibbs|2014}}, {{Harvtxt|Sainato|2015}}] as well as AI pioneers such as [[Yoshua Bengio]], [[Stuart J. Russell|Stuart Russell]], [[Demis Hassabis]], and [[Sam Altman]], have expressed concerns about existential risk from AI.
In May 2023, [[Geoffrey Hinton]] announced his resignation from Google in order to be able to "freely speak out about the risks of AI" without "considering how this impacts Google".[{{Cite news |date=25 March 2023 |title="Godfather of artificial intelligence" talks impact and potential of new AI |url=https://www.cbsnews.com/video/godfather-of-artificial-intelligence-talks-impact-and-potential-of-new-ai |url-status=live |archive-url=https://web.archive.org/web/20230328225221/https://www.cbsnews.com/video/godfather-of-artificial-intelligence-talks-impact-and-potential-of-new-ai |archive-date=28 March 2023 |access-date=2023-03-28 |work=CBS News}}] He notably mentioned risks of an [[AI takeover]],[{{Cite news |last=Pittis |first=Don |date=May 4, 2023 |title=Canadian artificial intelligence leader Geoffrey Hinton piles on fears of computer takeover |url=https://www.cbc.ca/news/business/ai-doom-column-don-pittis-1.6829302 |work=CBC |access-date=5 October 2024 |archive-date=7 July 2024 |archive-url=https://web.archive.org/web/20240707032135/https://www.cbc.ca/news/business/ai-doom-column-don-pittis-1.6829302 |url-status=live }}] and stressed that in order to avoid the worst outcomes, establishing safety guidelines will require cooperation among those competing in use of AI.[{{Cite web |date=2024-06-14 |title='50–50 chance' that AI outsmarts humanity, Geoffrey Hinton says |url=https://www.bnnbloomberg.ca/50-50-chance-that-ai-outsmarts-humanity-geoffrey-hinton-says-1.2085394 |access-date=2024-07-06 |website=Bloomberg BNN |archive-date=14 June 2024 |archive-url=https://web.archive.org/web/20240614144506/https://www.bnnbloomberg.ca/50-50-chance-that-ai-outsmarts-humanity-geoffrey-hinton-says-1.2085394 |url-status=live }}]
In 2023, many leading AI experts endorsed [[Statement on AI risk of extinction|the joint statement]] that "Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war".{{Sfnp|Valance|2023}}
Some other researchers were more optimistic. AI pioneer [[Jürgen Schmidhuber]] did not sign the joint statement, emphasising that in 95% of all cases, AI research is about making "human lives longer and healthier and easier."[{{Cite news |last=Taylor |first=Josh |date=7 May 2023 |title=Rise of artificial intelligence is inevitable but should not be feared, 'father of AI' says |url=https://www.theguardian.com/technology/2023/may/07/rise-of-artificial-intelligence-is-inevitable-but-should-not-be-feared-father-of-ai-says |access-date=26 May 2023 |work=The Guardian |archive-date=23 October 2023 |archive-url=https://web.archive.org/web/20231023061228/https://www.theguardian.com/technology/2023/may/07/rise-of-artificial-intelligence-is-inevitable-but-should-not-be-feared-father-of-ai-says |url-status=live }}] While the tools that are now being used to improve lives can also be used by bad actors, "they can also be used against the bad actors."[{{Cite news |last=Colton |first=Emma |date=7 May 2023 |title='Father of AI' says tech fears misplaced: 'You cannot stop it' |url=https://www.foxnews.com/tech/father-ai-jurgen-schmidhuber-says-tech-fears-misplaced-cannot-stop |access-date=26 May 2023 |work=Fox News |archive-date=26 May 2023 |archive-url=https://web.archive.org/web/20230526162642/https://www.foxnews.com/tech/father-ai-jurgen-schmidhuber-says-tech-fears-misplaced-cannot-stop |url-status=live }}][{{Cite news |last=Jones |first=Hessie |date=23 May 2023 |title=Juergen Schmidhuber, Renowned 'Father Of Modern AI,' Says His Life's Work Won't Lead To Dystopia |url=https://www.forbes.com/sites/hessiejones/2023/05/23/juergen-schmidhuber-renowned-father-of-modern-ai-says-his-lifes-work-wont-lead-to-dystopia |access-date=26 May 2023 |work=Forbes |archive-date=26 May 2023 |archive-url=https://web.archive.org/web/20230526163102/https://www.forbes.com/sites/hessiejones/2023/05/23/juergen-schmidhuber-renowned-father-of-modern-ai-says-his-lifes-work-wont-lead-to-dystopia/ |url-status=live }}] [[Andrew Ng]] also argued that "it's a mistake to fall for the doomsday hype on AI—and that regulators who do will only benefit vested interests."[{{Cite news |last=McMorrow |first=Ryan |date=19 Dec 2023 |title=Andrew Ng: 'Do we think the world is better off with more or less intelligence?' |url=https://www.ft.com/content/2dc07f9e-d2a9-4d98-b746-b051f9352be3 |access-date=30 Dec 2023 |work=Financial Times |archive-date=25 January 2024 |archive-url=https://web.archive.org/web/20240125014121/https://www.ft.com/content/2dc07f9e-d2a9-4d98-b746-b051f9352be3 |url-status=live }}] [[Yann LeCun]] "scoffs at his peers' dystopian scenarios of supercharged misinformation and even, eventually, human extinction."[{{Cite magazine |last=Levy |first=Steven |date=22 Dec 2023 |title=How Not to Be Stupid About AI, With Yann LeCun |url=https://www.wired.com/story/artificial-intelligence-meta-yann-lecun-interview |access-date=30 Dec 2023 |magazine=Wired |archive-date=28 December 2023 |archive-url=https://web.archive.org/web/20231228152443/https://www.wired.com/story/artificial-intelligence-meta-yann-lecun-interview/ |url-status=live }}] In the early 2010s, experts argued that the risks are too distant in the future to warrant research or that humans will be valuable from the perspective of a superintelligent machine.[Arguments that AI is not an imminent risk: {{Harvtxt|Brooks|2014}}, {{Harvtxt|Geist|2015}}, {{Harvtxt|Madrigal|2015}}, {{Harvtxt|Lee|2014}}] However, after 2016, the study of current and future risks and possible solutions became a serious area of research.{{Sfnp|Christian|2020|pp=67, 73}}
=== Ethical machines and alignment ===
{{Main|Machine ethics|AI safety|Friendly artificial intelligence|Artificial moral agents|Human Compatible}}
Friendly AI are machines that have been designed from the beginning to minimize risks and to make choices that benefit humans. [[Eliezer Yudkowsky]], who coined the term, argues that developing friendly AI should be a higher research priority: it may require a large investment and it must be completed before AI becomes an existential risk.{{Sfnp|Yudkowsky|2008}}
Machines with intelligence have the potential to use their intelligence to make ethical decisions. The field of machine ethics provides machines with ethical principles and procedures for resolving ethical dilemmas.{{Sfnp|Anderson|Anderson|2011}}
The field of machine ethics is also called computational morality,{{Sfnp|Anderson|Anderson|2011}}
and was founded at an [[AAAI]] symposium in 2005.{{Sfnp|AAAI|2014}}
Other approaches include [[Wendell Wallach]]'s "artificial moral agents"{{Sfnp|Wallach|2010}} and [[Stuart J. Russell]]'s [[Human Compatible#Russell's three principles|three principles]] for developing provably beneficial machines.{{Sfnp|Russell|2019|p=173}}
=== Open source ===
Active organizations in the AI open-source community include [[Hugging Face]],[{{Cite web |last1=Stewart |first1=Ashley |last2=Melton |first2=Monica |title=Hugging Face CEO says he's focused on building a 'sustainable model' for the $4.5 billion open-source-AI startup |url=https://www.businessinsider.com/hugging-face-open-source-ai-approach-2023-12 |access-date=2024-04-14 |website=Business Insider |archive-date=25 September 2024 |archive-url=https://web.archive.org/web/20240925013220/https://www.businessinsider.com/hugging-face-open-source-ai-approach-2023-12 |url-status=live }}] [[Google]],[{{Cite web |last=Wiggers |first=Kyle |date=2024-04-09 |title=Google open sources tools to support AI model development |url=https://techcrunch.com/2024/04/09/google-open-sources-tools-to-support-ai-model-development |access-date=2024-04-14 |website=TechCrunch |archive-date=10 September 2024 |archive-url=https://web.archive.org/web/20240910112401/https://techcrunch.com/2024/04/09/google-open-sources-tools-to-support-ai-model-development/ |url-status=live }}] [[EleutherAI]] and [[Meta Platforms|Meta]].[{{Cite web |last=Heaven |first=Will Douglas |date=May 12, 2023 |title=The open-source AI boom is built on Big Tech's handouts. How long will it last? |url=https://www.technologyreview.com/2023/05/12/1072950/open-source-ai-google-openai-eleuther-meta |access-date=2024-04-14 |website=MIT Technology Review}}] Various AI models, such as [[LLaMA|Llama 2]], [[Mistral AI|Mistral]] or [[Stable Diffusion]], have been made open-weight,[{{Cite news |last=Brodsky |first=Sascha |date=December 19, 2023 |title=Mistral AI's New Language Model Aims for Open Source Supremacy |url=https://aibusiness.com/nlp/mistral-ai-s-new-language-model-aims-for-open-source-supremacy |work=AI Business |access-date=5 October 2024 |archive-date=5 September 2024 |archive-url=https://web.archive.org/web/20240905212607/https://aibusiness.com/nlp/mistral-ai-s-new-language-model-aims-for-open-source-supremacy |url-status=live }}][{{Cite web |last=Edwards |first=Benj |date=2024-02-22 |title=Stability announces Stable Diffusion 3, a next-gen AI image generator |url=https://arstechnica.com/information-technology/2024/02/stability-announces-stable-diffusion-3-a-next-gen-ai-image-generator |access-date=2024-04-14 |website=Ars Technica |archive-date=5 October 2024 |archive-url=https://web.archive.org/web/20241005170201/https://arstechnica.com/information-technology/2024/02/stability-announces-stable-diffusion-3-a-next-gen-ai-image-generator/ |url-status=live }}] meaning that their architecture and trained parameters (the "weights") are publicly available. Open-weight models can be freely [[Fine-tuning (deep learning)|fine-tuned]], which allows companies to specialize them with their own data and for their own use-case.[{{Cite news |last=Marshall |first=Matt |date=January 29, 2024 |title=How enterprises are using open source LLMs: 16 examples |url=https://venturebeat.com/ai/how-enterprises-are-using-open-source-llms-16-examples |work=VentureBeat |access-date=5 October 2024 |archive-date=26 September 2024 |archive-url=https://web.archive.org/web/20240926171131/https://venturebeat.com/ai/how-enterprises-are-using-open-source-llms-16-examples/ |url-status=live }}] Open-weight models are useful for research and innovation but can also be misused. Since they can be fine-tuned, any built-in security measure, such as objecting to harmful requests, can be trained away until it becomes ineffective. Some researchers warn that future AI models may develop dangerous capabilities (such as the potential to drastically facilitate [[bioterrorism]]) and that once released on the Internet, they cannot be deleted everywhere if needed. They recommend pre-release audits and cost-benefit analyses.[{{Cite web |last=Piper |first=Kelsey |date=2024-02-02 |title=Should we make our most powerful AI models open source to all? |url=https://www.vox.com/future-perfect/2024/2/2/24058484/open-source-artificial-intelligence-ai-risk-meta-llama-2-chatgpt-openai-deepfake |access-date=2024-04-14 |website=Vox |archive-date=5 October 2024 |archive-url=https://web.archive.org/web/20241005170204/https://www.vox.com/future-perfect/2024/2/2/24058484/open-source-artificial-intelligence-ai-risk-meta-llama-2-chatgpt-openai-deepfake |url-status=live }}]
=== Frameworks ===
Artificial Intelligence projects can be guided by ethical considerations during the design, development, and implementation of an AI system. An AI framework such as the Care and Act Framework, developed by the [[Alan Turing Institute]] and based on the SUM values, outlines four main ethical dimensions, defined as follows:[{{Cite web |author=Alan Turing Institute |date=2019 |title=Understanding artificial intelligence ethics and safety |url=https://www.turing.ac.uk/sites/default/files/2019-06/understanding_artificial_intelligence_ethics_and_safety.pdf |access-date=5 October 2024 |archive-date=11 September 2024 |archive-url=https://web.archive.org/web/20240911131935/https://www.turing.ac.uk/sites/default/files/2019-06/understanding_artificial_intelligence_ethics_and_safety.pdf |url-status=live }}][{{Cite web |author=Alan Turing Institute |date=2023 |title=AI Ethics and Governance in Practice |url=https://www.turing.ac.uk/sites/default/files/2023-12/aieg-ati-ai-ethics-an-intro_1.pdf |access-date=5 October 2024 |archive-date=11 September 2024 |archive-url=https://web.archive.org/web/20240911125504/https://www.turing.ac.uk/sites/default/files/2023-12/aieg-ati-ai-ethics-an-intro_1.pdf |url-status=live }}]
* '''Respect''' the dignity of individual people
* '''Connect''' with other people sincerely, openly, and inclusively
* '''Care''' for the wellbeing of everyone
* '''Protect''' social values, justice, and the public interest
Other developments in ethical frameworks include those decided upon during the [[Asilomar Conference on Beneficial AI|Asilomar Conference]], the Montreal Declaration for Responsible AI, and the IEEE's Ethics of Autonomous Systems initiative, among others;[{{Cite journal |last1=Floridi |first1=Luciano |last2=Cowls |first2=Josh |date=2019-06-23 |title=A Unified Framework of Five Principles for AI in Society |url=https://hdsr.mitpress.mit.edu/pub/l0jsh9d1 |journal=Harvard Data Science Review |volume=1 |issue=1 |doi=10.1162/99608f92.8cd550d1 |s2cid=198775713 |doi-access=free |archive-date=7 August 2019 |access-date=5 December 2023 |archive-url=https://archive.today/20190807202909/https://hdsr.mitpress.mit.edu/pub/l0jsh9d1 |url-status=live }}] however, these principles are not without criticism, especially regards to the people chosen to contribute to these frameworks.[{{Cite journal |last1=Buruk |first1=Banu |last2=Ekmekci |first2=Perihan Elif |last3=Arda |first3=Berna |date=2020-09-01 |title=A critical perspective on guidelines for responsible and trustworthy artificial intelligence |url=https://doi.org/10.1007/s11019-020-09948-1 |journal=Medicine, Health Care and Philosophy |volume=23 |issue=3 |pages=387–399 |doi=10.1007/s11019-020-09948-1 |issn=1572-8633 |pmid=32236794 |s2cid=214766800 |access-date=5 October 2024 |archive-date=5 October 2024 |archive-url=https://web.archive.org/web/20241005170206/https://link.springer.com/article/10.1007/s11019-020-09948-1 |url-status=live }}]
Promotion of the wellbeing of the people and communities that these technologies affect requires consideration of the social and ethical implications at all stages of AI system design, development and implementation, and collaboration between job roles such as data scientists, product managers, data engineers, domain experts, and delivery managers.[{{Cite journal |last1=Kamila |first1=Manoj Kumar |last2=Jasrotia |first2=Sahil Singh |date=2023-01-01 |title=Ethical issues in the development of artificial intelligence: recognizing the risks |url=https://doi.org/10.1108/IJOES-05-2023-0107 |journal=International Journal of Ethics and Systems |pages=45–63 |volume=41 |issue=ahead-of-print |doi=10.1108/IJOES-05-2023-0107 |issn=2514-9369 |s2cid=259614124 |access-date=5 October 2024 |archive-date=5 October 2024 |archive-url=https://web.archive.org/web/20241005170207/https://www.emerald.com/insight/content/doi/10.1108/IJOES-05-2023-0107/full/html |url-status=live }}]
The [[AI Safety Institute (United Kingdom)|UK AI Safety Institute]] released in 2024 a testing toolset called 'Inspect' for AI safety evaluations available under a MIT open-source licence which is freely available on GitHub and can be improved with third-party packages. It can be used to evaluate AI models in a range of areas including core knowledge, ability to reason, and autonomous capabilities.[{{Cite web |date=10 May 2024 |title=AI Safety Institute releases new AI safety evaluations platform |url=https://www.gov.uk/government/news/ai-safety-institute-releases-new-ai-safety-evaluations-platform |access-date=14 May 2024 |publisher=UK Government |archive-date=5 October 2024 |archive-url=https://web.archive.org/web/20241005170207/https://www.gov.uk/government/news/ai-safety-institute-releases-new-ai-safety-evaluations-platform |url-status=live }}]
=== Regulation ===
{{Main|Regulation of artificial intelligence|Regulation of algorithms|AI safety}}
[[File:Vice President Harris at the group photo of the 2023 AI Safety Summit.jpg|upright=1.2|thumb|alt=AI Safety Summit|The first global [[AI Safety Summit]] was held in the United Kingdom in November 2023 with a declaration calling for international cooperation.]]
The regulation of artificial intelligence is the development of public sector policies and laws for promoting and regulating AI; it is therefore related to the broader regulation of algorithms.[Regulation of AI to mitigate risks: {{Harvtxt|Berryhill|Heang|Clogher|McBride|2019}}, {{Harvtxt|Barfield|Pagallo|2018}}, {{Harvtxt|Iphofen|Kritikos|2019}}, {{Harvtxt|Wirtz|Weyerer|Geyer|2018}}, {{Harvtxt|Buiten|2019}}] The regulatory and policy landscape for AI is an emerging issue in jurisdictions globally.{{Sfnp|Law Library of Congress (U.S.). Global Legal Research Directorate|2019}} According to AI Index at [[Stanford]], the annual number of AI-related laws passed in the 127 survey countries jumped from one passed in 2016 to 37 passed in 2022 alone.{{Sfnp|Vincent|2023}}{{Sfnp|Stanford University|2023}} Between 2016 and 2020, more than 30 countries adopted dedicated strategies for AI.{{Sfnp|UNESCO|2021}} Most EU member states had released national AI strategies, as had Canada, China, India, Japan, Mauritius, the Russian Federation, Saudi Arabia, United Arab Emirates, U.S., and Vietnam. Others were in the process of elaborating their own AI strategy, including Bangladesh, Malaysia and Tunisia.{{Sfnp|UNESCO|2021}} The [[Global Partnership on Artificial Intelligence]] was launched in June 2020, stating a need for AI to be developed in accordance with human rights and democratic values, to ensure public confidence and trust in the technology.{{Sfnp|UNESCO|2021}} [[Henry Kissinger]], [[Eric Schmidt]], and [[Daniel Huttenlocher]] published a joint statement in November 2021 calling for a government commission to regulate AI.{{Sfnp|Kissinger|2021}} In 2023, OpenAI leaders published recommendations for the governance of superintelligence, which they believe may happen in less than 10 years.{{Sfnp|Altman|Brockman|Sutskever |2023}} In 2023, the United Nations also launched an advisory body to provide recommendations on AI governance; the body comprises technology company executives, governments officials and academics.[{{Cite web |last=VOA News |date=October 25, 2023 |title=UN Announces Advisory Body on Artificial Intelligence |url=https://www.voanews.com/a/un-announces-advisory-body-on-artificial-intelligence-/7328732.html |access-date=5 October 2024 |archive-date=18 September 2024 |archive-url=https://web.archive.org/web/20240918071530/https://www.voanews.com/a/un-announces-advisory-body-on-artificial-intelligence-/7328732.html |url-status=live }}] In 2024, the [[Council of Europe]] created the first international legally binding treaty on AI, called the "[[Framework Convention on Artificial Intelligence and Human Rights, Democracy and the Rule of Law]]". It was adopted by the European Union, the United States, the United Kingdom, and other signatories.[{{Cite web |date=5 September 2024 |title=Council of Europe opens first ever global treaty on AI for signature |url=https://www.coe.int/en/web/portal/-/council-of-europe-opens-first-ever-global-treaty-on-ai-for-signature |access-date=2024-09-17 |website=Council of Europe |archive-date=17 September 2024 |archive-url=https://web.archive.org/web/20240917001330/https://www.coe.int/en/web/portal/-/council-of-europe-opens-first-ever-global-treaty-on-ai-for-signature |url-status=live }}]
In a 2022 [[Ipsos]] survey, attitudes towards AI varied greatly by country; 78% of Chinese citizens, but only 35% of Americans, agreed that "products and services using AI have more benefits than drawbacks".{{Sfnp|Vincent|2023}} A 2023 [[Reuters]]/Ipsos poll found that 61% of Americans agree, and 22% disagree, that AI poses risks to humanity.{{Sfnp|Edwards|2023}} In a 2023 [[Fox News]] poll, 35% of Americans thought it "very important", and an additional 41% thought it "somewhat important", for the federal government to regulate AI, versus 13% responding "not very important" and 8% responding "not at all important".{{Sfnp|Kasperowicz|2023}}{{Sfnp|Fox News|2023}}
In November 2023, the first global [[AI Safety Summit]] was held in [[Bletchley Park]] in the UK to discuss the near and far term risks of AI and the possibility of mandatory and voluntary regulatory frameworks.[{{Cite news |last=Milmo |first=Dan |date=3 November 2023 |title=Hope or Horror? The great AI debate dividing its pioneers |work=[[The Guardian Weekly]] |pages=10–12}}] 28 countries including the United States, China, and the European Union issued a declaration at the start of the summit, calling for international co-operation to manage the challenges and risks of artificial intelligence.[{{Cite web |date=1 November 2023 |title=The Bletchley Declaration by Countries Attending the AI Safety Summit, 1–2 November 2023 |url=https://www.gov.uk/government/publications/ai-safety-summit-2023-the-bletchley-declaration/the-bletchley-declaration-by-countries-attending-the-ai-safety-summit-1-2-november-2023 |archive-url=https://web.archive.org/web/20231101123904/https://www.gov.uk/government/publications/ai-safety-summit-2023-the-bletchley-declaration/the-bletchley-declaration-by-countries-attending-the-ai-safety-summit-1-2-november-2023 |archive-date=1 November 2023 |access-date=2 November 2023 |website=GOV.UK}}][{{Cite press release |title=Countries agree to safe and responsible development of frontier AI in landmark Bletchley Declaration |url=https://www.gov.uk/government/news/countries-agree-to-safe-and-responsible-development-of-frontier-ai-in-landmark-bletchley-declaration |access-date=1 November 2023 |url-status=live |archive-url=https://web.archive.org/web/20231101115016/https://www.gov.uk/government/news/countries-agree-to-safe-and-responsible-development-of-frontier-ai-in-landmark-bletchley-declaration |archive-date=1 November 2023 |website=GOV.UK}}] In May 2024 at the [[AI Seoul Summit]], 16 global AI tech companies agreed to safety commitments on the development of AI.[{{Cite web |date=21 May 2024 |title=Second global AI summit secures safety commitments from companies |url=https://www.reuters.com/technology/global-ai-summit-seoul-aims-forge-new-regulatory-agreements-2024-05-21 |access-date=23 May 2024 |publisher=Reuters}}][{{Cite web |date=21 May 2024 |title=Frontier AI Safety Commitments, AI Seoul Summit 2024 |url=https://www.gov.uk/government/publications/frontier-ai-safety-commitments-ai-seoul-summit-2024/frontier-ai-safety-commitments-ai-seoul-summit-2024 |archive-url=https://web.archive.org/web/20240523201611/https://www.gov.uk/government/publications/frontier-ai-safety-commitments-ai-seoul-summit-2024/frontier-ai-safety-commitments-ai-seoul-summit-2024 |archive-date=23 May 2024 |access-date=23 May 2024 |publisher=gov.uk}}]
== History ==
{{Main|History of artificial intelligence}}
{{For timeline}}
[[File:2024 AI patents by country - artificial intelligence.svg |thumb |In 2024, AI patents in China and the US numbered more than three-fourths of AI patents worldwide.[ Though China had more AI patents, the US had 35% more patents per AI patent-applicant company than China.][{{cite web |last1=Buntz |first1=Brian |title=Quality vs. quantity: US and China chart different paths in global AI patent race in 2024 / Geographical breakdown of AI patents in 2024 |url=https://www.rdworldonline.com/quality-vs-quantity-us-and-china-chart-different-paths-in-global-ai-patent-race-in-2024/ |publisher=R&D World |archive-url=https://web.archive.org/web/20241209072113/https://www.rdworldonline.com/quality-vs-quantity-us-and-china-chart-different-paths-in-global-ai-patent-race-in-2024/ |archive-date=9 December 2024 |date=3 November 2024 |url-status=live}}]]]
The study of mechanical or "formal" reasoning began with philosophers and mathematicians in antiquity. The study of logic led directly to [[Alan Turing]]'s [[theory of computation]], which suggested that a machine, by shuffling symbols as simple as "0" and "1", could simulate any conceivable form of mathematical reasoning.{{Sfn|Russell|Norvig|2021|p=9}}[{{Cite web |title=Google books ngram |url=https://books.google.com/ngrams/graph?content=electronic+brain&year_start=1930&year_end=2019&corpus=en-2019&smoothing=3 |access-date=5 October 2024 |archive-date=5 October 2024 |archive-url=https://web.archive.org/web/20241005170209/https://books.google.com/ngrams/graph?content=electronic+brain&year_start=1930&year_end=2019&corpus=en-2019&smoothing=3 |url-status=live }}]}} They developed several areas of research that would become part of AI,[AI's immediate precursors: {{Harvtxt|McCorduck|2004|pp=51–107}}, {{Harvtxt|Crevier|1993|pp=27–32}}, {{Harvtxt|Russell|Norvig|2021|pp=8–17}}, {{Harvtxt|Moravec|1988|p=3}}] such as [[Warren McCullouch|McCullouch]] and [[Walter Pitts|Pitts]] design for "artificial neurons" in 1943,{{Sfnp|Russell|Norvig|2021|p=17}} and Turing's influential 1950 paper '[[Computing Machinery and Intelligence]]', which introduced the [[Turing test]] and showed that "machine intelligence" was plausible.[{{Cite book |title=The Essential Turing: the ideas that gave birth to the computer age |date=2004 |publisher=Clarendon Press |isbn=0-1982-5079-7 |editor-last=Copeland |editor-first=J. |location=Oxford, England}}]
The field of AI research was founded at [[Dartmouth workshop|a workshop]] at [[Dartmouth College]] in 1956.{{Efn|
Daniel Crevier wrote, "the conference is generally recognized as the official birthdate of the new science."{{Sfnp|Crevier|1993|pp=47–49}} [[Stuart J. Russell|Russell]] and [[Norvig]] called the conference "the inception of artificial intelligence."{{Sfnp|Russell|Norvig|2021|p=17}}}}[[[Dartmouth workshop]]: {{Harvtxt|Russell|Norvig|2021|p=18}}, {{Harvtxt|McCorduck|2004|pp=111–136}}, {{Harvtxt|NRC|1999|pp=200–201}}]
The proposal: {{Harvtxt|McCarthy|Minsky|Rochester|Shannon|1955}} The attendees became the leaders of AI research in the 1960s.{{Efn|
[[Stuart J. Russell|Russell]] and [[Norvig]] wrote "for the next 20 years the field would be dominated by these people and their students."{{Sfnp|Russell|Norvig|2003|p=17}}
}} They and their students produced programs that the press described as "astonishing":{{Efn|
[[Stuart J. Russell|Russell]] and [[Norvig]] wrote, "it was astonishing whenever a computer did anything kind of smartish".{{Sfnp|Russell|Norvig|2003|p=18}}
}} computers were learning [[checkers]] strategies, solving word problems in algebra, proving [[Theorem|logical theorems]] and speaking English.{{Efn|
The programs described are [[Arthur Samuel (computer scientist)|Arthur Samuel]]'s checkers program for the [[IBM 701]], [[Daniel Bobrow]]'s [[STUDENT]], [[Allen Newell|Newell]] and [[Herbert A. Simon|Simon]]'s [[Logic Theorist]] and [[Terry Winograd]]'s [[SHRDLU]].
}}[Successful programs of the 1960s: {{Harvtxt|McCorduck|2004|pp=243–252}}, {{Harvtxt|Crevier|1993|pp=52–107}}, {{Harvtxt|Moravec|1988|p=9}}, {{Harvtxt|Russell|Norvig|2021|pp=19–21}}] Artificial intelligence laboratories were set up at a number of British and U.S. universities in the latter 1950s and early 1960s.[{{Harvtxt|Simon|1965|p=96}} quoted in {{Harvtxt|Crevier|1993|p=109}}] In 1967 [[Marvin Minsky]] agreed, writing that "within a generation ... the problem of creating 'artificial intelligence' will substantially be solved".[{{Harvtxt|Minsky|1967|p=2}} quoted in {{Harvtxt|Crevier|1993|p=109}}] They had, however, underestimated the difficulty of the problem.{{Efn|[[Stuart J. Russell|Russell]] and [[Norvig]] write: "in almost all cases, these early systems failed on more difficult problems"{{Sfnp|Russell|Norvig|2021|p=21}}}} In 1974, both the U.S. and British governments cut off exploratory research in response to the [[Lighthill report|criticism]] of [[Sir James Lighthill]]{{Sfnp|Lighthill|1973}} and ongoing pressure from the U.S. Congress to [[Mansfield Amendment|fund more productive projects]].{{Sfn|NRC|1999|pp=212–213}} [[Marvin Minsky|Minsky]]'s and [[Papert]]'s book ''[[Perceptron]]s'' was understood as proving that [[artificial neural networks]] would never be useful for solving real-world tasks, thus discrediting the approach altogether.{{Sfnp|Russell|Norvig|2021|p=22}} The "[[AI winter]]", a period when obtaining funding for AI projects was difficult, followed.[First [[AI Winter]], [[Lighthill report]], [[Mansfield Amendment]]: {{Harvtxt|Crevier|1993|pp=115–117}}, {{Harvtxt|Russell|Norvig|2021|pp=21–22}}, {{Harvtxt|NRC|1999|pp=212–213}}, {{Harvtxt|Howe|1994}}, {{Harvtxt|Newquist|1994|pp=189–201}}]
In the early 1980s, AI research was revived by the commercial success of [[expert system]]s,[[[Expert systems]]: {{Harvtxt|Russell|Norvig|2021|pp=23, 292}}, {{Harvtxt|Luger|Stubblefield|2004|pp=227–331}}, {{Harvtxt|Nilsson|1998|loc=chpt. 17.4}}, {{Harvtxt|McCorduck|2004|pp=327–335, 434–435}}, {{Harvtxt|Crevier|1993|pp=145–162, 197–203}}, {{Harvtxt|Newquist|1994|pp=155–183}}] a form of AI program that simulated the knowledge and analytical skills of human experts. By 1985, the market for AI had reached over a billion dollars. At the same time, Japan's [[fifth generation computer]] project inspired the U.S. and British governments to restore funding for [[academic research]].[Funding initiatives in the early 1980s: [[Fifth Generation Project]] (Japan), [[Alvey]] (UK), [[Microelectronics and Computer Technology Corporation]] (US), [[Strategic Computing Initiative]] (US): {{Harvtxt|McCorduck|2004|pp=426–441}}, {{Harvtxt|Crevier|1993|pp=161–162, 197–203, 211, 240}}, {{Harvtxt|Russell|Norvig|2021|p=23}}, {{Harvtxt|NRC|1999|pp=210–211}}, {{Harvtxt|Newquist|1994|pp=235–248}}] However, beginning with the collapse of the [[Lisp Machine]] market in 1987, AI once again fell into disrepute, and a second, longer-lasting winter began.[Second [[AI Winter]]: {{Harvtxt|Russell|Norvig|2021|p=24}}, {{Harvtxt|McCorduck|2004|pp=430–435}}, {{Harvtxt|Crevier|1993|pp=209–210}}, {{Harvtxt|NRC|1999|pp=214–216}}, {{Harvtxt|Newquist|1994|pp=301–318}}]
Up to this point, most of AI's funding had gone to projects that used high-level [[symbolic AI|symbols]] to represent [[mental objects]] like plans, goals, beliefs, and known facts. In the 1980s, some researchers began to doubt that this approach would be able to imitate all the processes of human cognition, especially [[machine perception|perception]], [[robotics]], [[machine learning|learning]] and [[pattern recognition]],{{Sfnp|Russell|Norvig|2021|p=24}} and began to look into "sub-symbolic" approaches.{{Sfnp|Nilsson|1998|p=7}} [[Rodney Brooks]] rejected "representation" in general and focussed directly on engineering machines that move and survive.{{Efn|
[[embodied mind|Embodied]] approaches to AI{{Sfnp|McCorduck|2004|pp=454–462}} were championed by [[Hans Moravec]]{{Sfnp|Moravec|1988}} and [[Rodney Brooks]]{{Sfnp|Brooks|1990}} and went by many names: [[Nouvelle AI]].{{Sfnp|Brooks|1990}} [[Developmental robotics]].[[[Developmental robotics]]: {{Harvtxt|Weng|McClelland|Pentland|Sporns|2001}}, {{Harvtxt|Lungarella|Metta|Pfeifer|Sandini|2003}}, {{Harvtxt|Asada|Hosoda|Kuniyoshi|Ishiguro|2009}}, {{Harvtxt|Oudeyer|2010}}]
}} [[Judea Pearl]], [[Lofti Zadeh]], and others developed methods that handled incomplete and uncertain information by making reasonable guesses rather than precise logic.[{{Harvtxt|Crevier|1993|pp=214–215}}, {{Harvtxt|Russell|Norvig|2021|pp=24, 26}}] In 1990, [[Yann LeCun]] successfully showed that [[convolutional neural networks]] can recognize handwritten digits, the first of many successful applications of neural networks.{{Sfnp|Russell|Norvig|2021|p=26}}
AI gradually restored its reputation in the late 1990s and early 21st century by exploiting formal mathematical methods and by finding specific solutions to specific problems. This "[[narrow AI|narrow]]" and "formal" focus allowed researchers to produce verifiable results and collaborate with other fields (such as [[statistics]], [[economics]] and [[mathematical optimization|mathematics]]).[[[#Neat vs. scruffy|Formal]] and [[#Narrow vs. general AI|narrow]] methods adopted in the 1990s: {{Harvtxt |Russell|Norvig|2021|pp=24–26}}, {{Harvtxt|McCorduck|2004|pp=486–487}}] By 2000, solutions developed by AI researchers were being widely used, although in the 1990s they were rarely described as "artificial intelligence" (a tendency known as the [[AI effect]]).[AI widely used in the late 1990s: {{Harvtxt|Kurzweil|2005|p=265}}, {{Harvtxt|NRC|1999|pp=216–222}}, {{Harvtxt|Newquist|1994|pp=189–201}}]
However, several academic researchers became concerned that AI was no longer pursuing its original goal of creating versatile, fully intelligent machines. Beginning around 2002, they founded the subfield of [[artificial general intelligence]] (or "AGI"), which had several well-funded institutions by the 2010s.[[[Deep learning]] revolution, [[AlexNet]]: {{Harvtxt|Goldman|2022}}, {{Harvtxt|Russell|Norvig|2021|p=26}}, {{Harvtxt|McKinsey|2018}}]
For many specific tasks, other methods were abandoned.{{Efn|Matteo Wong wrote in [[The Atlantic]]: "Whereas for decades, computer-science fields such as natural-language processing, computer vision, and robotics used extremely different methods, now they all use a programming method called "deep learning". As a result, their code and approaches have become more similar, and their models are easier to integrate into one another."{{Sfnp|Wong|2023}}}}
Deep learning's success was based on both hardware improvements ([[Moore's law|faster computers]],[[[Moore's Law]] and AI: {{Harvtxt|Russell|Norvig|2021|pp=14, 27}}] [[graphics processing unit]]s, [[cloud computing]]{{Sfnp|Clark|2015b}}) and access to [[big data|large amounts of data]][[[Big data]]: {{Harvtxt|Russell|Norvig|2021|p=26}}] (including curated datasets,{{Sfnp|Clark|2015b}} such as [[ImageNet]]). Deep learning's success led to an enormous increase in interest and funding in AI.{{Efn|Jack Clark wrote in [[Bloomberg News|Bloomberg]]: "After a half-decade of quiet breakthroughs in artificial intelligence, 2015 has been a landmark year. Computers are smarter and learning faster than ever", and noted that the number of software projects that use machine learning at [[Google]] increased from a "sporadic usage" in 2012 to more than 2,700 projects in 2015.{{Sfnp|Clark|2015b}}}} The amount of machine learning research (measured by total publications) increased by 50% in the years 2015–2019.{{Sfnp|UNESCO|2021}}
[[File:20250202 "AI" (search term) on Google Trends.svg|thumb|The number of Google searches for the term "AI" accelerated in 2022.]]
In 2016, issues of [[algorithmic fairness|fairness]] and the misuse of technology were catapulted into center stage at machine learning conferences, publications vastly increased, funding became available, and many researchers re-focussed their careers on these issues. The [[AI alignment|alignment problem]] became a serious field of academic study.{{Sfnp|Christian|2020|pp=67, 73}}
In the late 2010s and early 2020s, [[artificial general intelligence|AGI]] companies began to deliver programs that created enormous interest. In 2015, [[AlphaGo]], developed by [[DeepMind]], beat the world champion [[Go player]]. The program taught only the game's rules and developed a strategy by itself. [[GPT-3]] is a [[large language model]] that was released in 2020 by [[OpenAI]] and is capable of generating high-quality human-like text.[{{Cite web |last=Sagar |first=Ram |date=2020-06-03 |title=OpenAI Releases GPT-3, The Largest Model So Far |url=https://analyticsindiamag.com/open-ai-gpt-3-language-model |url-status=live |archive-url=https://web.archive.org/web/20200804173452/https://analyticsindiamag.com/open-ai-gpt-3-language-model |archive-date=2020-08-04 |access-date=2023-03-15 |website=Analytics India Magazine}}] [[ChatGPT]], launched on November 30, 2022, became the fastest-growing consumer software application in history, gaining over 100 million users in two months.[{{Cite news |last=Milmo |first=Dan |date=2023-02-02 |title=ChatGPT reaches 100 million users two months after launch |url=https://www.theguardian.com/technology/2023/feb/02/chatgpt-100-million-users-open-ai-fastest-growing-app |access-date=2024-12-31 |work=The Guardian |language=en-GB |issn=0261-3077 |archive-date=3 February 2023 |archive-url=https://web.archive.org/web/20230203051356/https://www.theguardian.com/technology/2023/feb/02/chatgpt-100-million-users-open-ai-fastest-growing-app |url-status=live }}] It marked what is widely regarded as AI's breakout year, bringing it into the public consciousness.[{{Cite web |last=Gorichanaz |first=Tim |date=2023-11-29 |title=ChatGPT turns 1: AI chatbot's success says as much about humans as technology |url=https://theconversation.com/chatgpt-turns-1-ai-chatbots-success-says-as-much-about-humans-as-technology-218704 |access-date=2024-12-31 |website=The Conversation |language=en-US |archive-date=31 December 2024 |archive-url=https://web.archive.org/web/20241231073513/https://theconversation.com/chatgpt-turns-1-ai-chatbots-success-says-as-much-about-humans-as-technology-218704 |url-status=live }}] These programs, and others, inspired an aggressive [[AI boom]], where large companies began investing billions of dollars in AI research. According to AI Impacts, about $50 billion annually was invested in "AI" around 2022 in the U.S. alone and about 20% of the new U.S. Computer Science PhD graduates have specialized in "AI".{{Sfnp|DiFeliciantonio|2023}} About 800,000 "AI"-related U.S. job openings existed in 2022.{{Sfnp|Goswami|2023}} According to PitchBook research, 22% of newly funded [[Startup company|startups]] in 2024 claimed to be AI companies.[{{cite web | title=Nearly 1 in 4 new startups is an AI company | website=PitchBook | date=2024-12-24 | url=https://pitchbook.com/news/articles/nearly-1-in-4-new-startups-is-an-ai-company | access-date=2025-01-03}}]
== Philosophy ==
{{Main|Philosophy of artificial intelligence}}
Philosophical debates have historically sought to determine the nature of intelligence and how to make intelligent machines.[{{Cite web |last1=Grayling |first1=Anthony |last2=Ball |first2=Brian |date=2024-08-01 |title=Philosophy is crucial in the age of AI |url=https://theconversation.com/philosophy-is-crucial-in-the-age-of-ai-235907 |access-date=2024-10-04 |website=The Conversation |language=en-US |archive-date=5 October 2024 |archive-url=https://web.archive.org/web/20241005170243/https://theconversation.com/philosophy-is-crucial-in-the-age-of-ai-235907 |url-status=live }}] Another major focus has been whether machines can be conscious, and the associated ethical implications.[{{Cite web |last=Jarow |first=Oshan |date=2024-06-15 |title=Will AI ever become conscious? It depends on how you think about biology. |url=https://www.vox.com/future-perfect/351893/consciousness-ai-machines-neuroscience-mind |access-date=2024-10-04 |website=Vox |language=en-US |archive-date=21 September 2024 |archive-url=https://web.archive.org/web/20240921035218/https://www.vox.com/future-perfect/351893/consciousness-ai-machines-neuroscience-mind |url-status=live }}] Many other topics in philosophy are relevant to AI, such as [[epistemology]] and [[free will]].[{{Cite web |last=McCarthy |first=John |title=The Philosophy of AI and the AI of Philosophy |url=http://jmc.stanford.edu/articles/aiphil2.html |archive-url=https://web.archive.org/web/20181023181725/http://jmc.stanford.edu/articles/aiphil2.html |archive-date=2018-10-23 |access-date=2024-10-03 |website=jmc.stanford.edu}}] Rapid advancements have intensified public discussions on the philosophy and [[ethics of AI]].[Turing's original publication of the [[Turing test]] in "[[Computing machinery and intelligence]]": {{Harvtxt|Turing|1950}}
Historical influence and philosophical implications: {{Harvtxt|Haugeland|1985|pp=6–9}}, {{Harvtxt|Crevier|1993|p=24}}, {{Harvtxt|McCorduck|2004|pp=70–71}}, {{Harvtxt|Russell|Norvig|2021|pp=2, 984}}] Since we can only observe the behavior of the machine, it does not matter if it is "actually" thinking or literally has a "mind". Turing notes that [[Problem of other minds|we can not determine these things about other people]] but "it is usual to have a polite convention that everyone thinks."{{Sfnp|Turing|1950|loc=Under "The Argument from Consciousness"}}
[[File:Weakness of Turing test 1.svg|thumb|The Turing test can provide some evidence of intelligence, but it penalizes non-human intelligent behavior.[{{Cite web |last1=Kirk-Giannini |first1=Cameron Domenico |last2=Goldstein |first2=Simon |date=2023-10-16 |title=AI is closer than ever to passing the Turing test for 'intelligence'. What happens when it does? |url=https://theconversation.com/ai-is-closer-than-ever-to-passing-the-turing-test-for-intelligence-what-happens-when-it-does-214721 |access-date=2024-08-17 |website=The Conversation |archive-date=25 September 2024 |archive-url=https://web.archive.org/web/20240925040612/https://theconversation.com/ai-is-closer-than-ever-to-passing-the-turing-test-for-intelligence-what-happens-when-it-does-214721 |url-status=live }}]]]
[[Stuart J. Russell|Russell]] and [[Norvig]] agree with Turing that intelligence must be defined in terms of external behavior, not internal structure.{{Sfnp|Russell|Norvig|2021|pp=1–4}} However, they are critical that the test requires the machine to imitate humans. "[[Aeronautics|Aeronautical engineering]] texts", they wrote, "do not define the goal of their field as making 'machines that fly so exactly like [[pigeon]]s that they can fool other pigeons.{{' "}}{{Sfnp|Russell|Norvig|2021|p=3}} AI founder [[John McCarthy (computer scientist)|John McCarthy]] agreed, writing that "Artificial intelligence is not, by definition, simulation of human intelligence".{{Sfnp|Maker|2006}}
McCarthy defines intelligence as "the computational part of the ability to achieve goals in the world".{{Sfnp|McCarthy|1999}} Another AI founder, [[Marvin Minsky]], similarly describes it as "the ability to solve hard problems".{{Sfnp|Minsky|1986}} The leading AI textbook defines it as the study of agents that perceive their environment and take actions that maximize their chances of achieving defined goals.{{Sfnp|Russell|Norvig|2021|pp=1–4}} These definitions view intelligence in terms of well-defined problems with well-defined solutions, where both the difficulty of the problem and the performance of the program are direct measures of the "intelligence" of the machine—and no other philosophical discussion is required, or may not even be possible.
Another definition has been adopted by Google,[{{Cite web |title=What Is Artificial Intelligence (AI)? |url=https://cloud.google.com/learn/what-is-artificial-intelligence |url-status=live |archive-url=https://web.archive.org/web/20230731114802/https://cloud.google.com/learn/what-is-artificial-intelligence |archive-date=31 July 2023 |access-date=16 October 2023 |website=[[Google Cloud Platform]]}}] a major practitioner in the field of AI. This definition stipulates the ability of systems to synthesize information as the manifestation of intelligence, similar to the way it is defined in biological intelligence.
Some authors have suggested in practice, that the definition of AI is vague and difficult to define, with contention as to whether classical algorithms should be categorised as AI,[{{Cite web |title=One of the Biggest Problems in Regulating AI Is Agreeing on a Definition |url=https://carnegieendowment.org/posts/2022/10/one-of-the-biggest-problems-in-regulating-ai-is-agreeing-on-a-definition?lang=en |access-date=2024-07-31 |website=[[Carnegie Endowment for International Peace]]}}] with many companies during the early 2020s AI boom using the term as a marketing [[buzzword]], often even if they did "not actually use AI in a material way".[{{Cite web |title=AI or BS? How to tell if a marketing tool really uses artificial intelligence |url=https://www.thedrum.com/opinion/2023/03/30/ai-or-bs-how-tell-if-marketing-tool-really-uses-artificial-intelligence |access-date=2024-07-31 |website=The Drum}}]
=== Evaluating approaches to AI ===
No established unifying theory or [[paradigm]] has guided AI research for most of its history.{{Efn
|[[Nils Nilsson (researcher)|Nils Nilsson]] wrote in 1983: "Simply put, there is wide disagreement in the field about what AI is all about."{{Sfnp|Nilsson|1983|p=10}}}} The unprecedented success of statistical machine learning in the 2010s eclipsed all other approaches (so much so that some sources, especially in the business world, use the term "artificial intelligence" to mean "machine learning with neural networks"). This approach is mostly [[sub-symbolic]], [[soft computing|soft]] and [[artificial general intelligence|narrow]]. Critics argue that these questions may have to be revisited by future generations of AI researchers.
====Symbolic AI and its limits====
[[Symbolic AI]] (or "[[GOFAI]]"){{Sfnp|Haugeland|1985|pp=112–117}} simulated the high-level conscious reasoning that people use when they solve puzzles, express legal reasoning and do mathematics. They were highly successful at "intelligent" tasks such as algebra or IQ tests. In the 1960s, Newell and Simon proposed the [[physical symbol systems hypothesis]]: "A physical symbol system has the necessary and sufficient means of general intelligent action."[Physical symbol system hypothesis: {{Harvtxt|Newell|Simon|1976|p=116}}
Historical significance: {{Harvtxt|McCorduck|2004|p=153}}, {{Harvtxt|Russell|Norvig|2021|p=19}}]
However, the symbolic approach failed on many tasks that humans solve easily, such as learning, recognizing an object or commonsense reasoning. [[Moravec's paradox]] is the discovery that high-level "intelligent" tasks were easy for AI, but low level "instinctive" tasks were extremely difficult.[[[Moravec's paradox]]: {{Harvtxt|Moravec|1988|pp=15–16}}, {{Harvtxt|Minsky|1986|p=29}}, {{Harvtxt|Pinker|2007|pp=190–191}}] Philosopher [[Hubert Dreyfus]] had [[Dreyfus' critique of AI|argued]] since the 1960s that human expertise depends on unconscious instinct rather than conscious symbol manipulation, and on having a "feel" for the situation, rather than explicit symbolic knowledge.[[[Dreyfus' critique of AI]]: {{Harvtxt|Dreyfus|1972}}, {{Harvtxt|Dreyfus|Dreyfus|1986}}
Historical significance and philosophical implications: {{Harvtxt|Crevier|1993|pp=120–132}}, {{Harvtxt|McCorduck|2004|pp=211–239}}, {{Harvtxt|Russell|Norvig|2021|pp=981–982}}, {{Harvtxt|Fearn|2007|loc=chpt. 3}}] Although his arguments had been ridiculed and ignored when they were first presented, eventually, AI research came to agree with him.{{Efn|
Daniel Crevier wrote that "time has proven the accuracy and perceptiveness of some of Dreyfus's comments. Had he formulated them less aggressively, constructive actions they suggested might have been taken much earlier."{{Sfnp|Crevier|1993|p=125}}
}}[[[Neats vs. scruffies]], the historic debate: {{Harvtxt|McCorduck|2004|pp=421–424, 486–489}}, {{Harvtxt|Crevier|1993|p=168}}, {{Harvtxt|Nilsson|1983|pp=10–11}}, {{Harvtxt|Russell|Norvig|2021|p=24}}
A classic example of the "scruffy" approach to intelligence: {{Harvtxt|Minsky|1986}}
A modern example of neat AI and its aspirations in the 21st century: {{Harvtxt|Domingos|2015}}] but eventually was seen as irrelevant. Modern AI has elements of both.
==== Soft vs. hard computing ====
{{Main|Soft computing}}
Finding a provably correct or optimal solution is [[Intractability (complexity)|intractable]] for many important problems.[Searle's [[Chinese room]] argument: {{Harvtxt|Searle|1980}}. Searle's original presentation of the thought experiment., {{Harvtxt|Searle|1999}}.
Discussion: {{Harvtxt|Russell|Norvig|2021|pp=985}}, {{Harvtxt|McCorduck|2004|pp=443–445}}, {{Harvtxt|Crevier|1993|pp=269–271}}]
==== AI welfare and rights ====
It is difficult or impossible to reliably evaluate whether an advanced [[Sentient AI|AI is sentient]] (has the ability to feel), and if so, to what degree.[{{Cite web |last=Leith |first=Sam |date=2022-07-07 |title=Nick Bostrom: How can we be certain a machine isn't conscious? |url=https://www.spectator.co.uk/article/nick-bostrom-how-can-we-be-certain-a-machine-isnt-conscious |access-date=2024-02-23 |website=The Spectator |archive-date=26 September 2024 |archive-url=https://web.archive.org/web/20240926155639/https://www.spectator.co.uk/article/nick-bostrom-how-can-we-be-certain-a-machine-isnt-conscious/ |url-status=live }}] But if there is a significant chance that a given machine can feel and suffer, then it may be entitled to certain rights or welfare protection measures, similarly to animals.[{{Cite web |last=Thomson |first=Jonny |date=2022-10-31 |title=Why don't robots have rights? |url=https://bigthink.com/thinking/why-dont-robots-have-rights |access-date=2024-02-23 |website=Big Think |archive-date=13 September 2024 |archive-url=https://web.archive.org/web/20240913055336/https://bigthink.com/thinking/why-dont-robots-have-rights/ |url-status=live }}][{{Cite magazine |last=Kateman |first=Brian |date=2023-07-24 |title=AI Should Be Terrified of Humans |url=https://time.com/6296234/ai-should-be-terrified-of-humans |access-date=2024-02-23 |magazine=Time |archive-date=25 September 2024 |archive-url=https://web.archive.org/web/20240925041601/https://time.com/6296234/ai-should-be-terrified-of-humans/ |url-status=live }}] [[Sapience]] (a set of capacities related to high intelligence, such as discernment or [[self-awareness]]) may provide another moral basis for AI rights.[{{Cite news |last=Wong |first=Jeff |date=July 10, 2023 |title=What leaders need to know about robot rights |url=https://www.fastcompany.com/90920769/what-leaders-need-to-know-about-robot-rights |work=Fast Company |ref=none}}]
In 2017, the European Union considered granting "electronic personhood" to some of the most capable AI systems. Similarly to the legal status of companies, it would have conferred rights but also responsibilities.[{{Cite news |last=Hern |first=Alex |date=2017-01-12 |title=Give robots 'personhood' status, EU committee argues |url=https://www.theguardian.com/technology/2017/jan/12/give-robots-personhood-status-eu-committee-argues |access-date=2024-02-23 |work=The Guardian |issn=0261-3077 |archive-date=5 October 2024 |archive-url=https://web.archive.org/web/20241005171222/https://www.theguardian.com/technology/2017/jan/12/give-robots-personhood-status-eu-committee-argues |url-status=live }}] Critics argued in 2018 that granting rights to AI systems would downplay the importance of [[human rights]], and that legislation should focus on user needs rather than speculative futuristic scenarios. They also noted that robots lacked the autonomy to take part to society on their own.[{{Cite web |last=Dovey |first=Dana |date=2018-04-14 |title=Experts Don't Think Robots Should Have Rights |url=https://www.newsweek.com/robots-human-rights-electronic-persons-humans-versus-machines-886075 |access-date=2024-02-23 |website=Newsweek |archive-date=5 October 2024 |archive-url=https://web.archive.org/web/20241005171333/https://www.newsweek.com/robots-human-rights-electronic-persons-humans-versus-machines-886075 |url-status=live }}][{{Cite web |last=Cuddy |first=Alice |date=2018-04-13 |title=Robot rights violate human rights, experts warn EU |url=https://www.euronews.com/2018/04/13/robot-rights-violate-human-rights-experts-warn-eu |access-date=2024-02-23 |website=euronews |archive-date=19 September 2024 |archive-url=https://web.archive.org/web/20240919022327/https://www.euronews.com/2018/04/13/robot-rights-violate-human-rights-experts-warn-eu |url-status=live }}]
Progress in AI increased interest in the topic. Proponents of AI welfare and rights often argue that AI sentience, if it emerges, would be particularly easy to deny. They warn that this may be a [[Moral blindness|moral blind spot]] analogous to [[slavery]] or [[factory farming]], which could lead to [[Suffering risks|large-scale suffering]] if sentient AI is created and carelessly exploited.[The [[Intelligence explosion]] and [[technological singularity]]: {{Harvtxt|Russell|Norvig|2021|pp=1004–1005}}, {{Harvtxt|Omohundro|2008}}, {{Harvtxt|Kurzweil|2005}}
[[I. J. Good]]'s "intelligence explosion": {{Harvtxt|Good|1965}}
[[Vernor Vinge]]'s "singularity": {{Harvtxt|Vinge|1993}}]
However, technologies cannot improve exponentially indefinitely, and typically follow an [[S-shaped curve]], slowing when they reach the physical limits of what the technology can do.{{Sfnp|Russell|Norvig|2021|p=1005}}
=== Transhumanism ===
{{Main|Transhumanism}}
Robot designer [[Hans Moravec]], cyberneticist [[Kevin Warwick]] and inventor [[Ray Kurzweil]] have predicted that humans and machines may merge in the future into [[cyborg]]s that are more capable and powerful than either. This idea, called transhumanism, has roots in the writings of [[Aldous Huxley]] and [[Robert Ettinger]].[[[Transhumanism]]: {{Harvtxt|Moravec|1988}}, {{Harvtxt|Kurzweil|2005}}, {{Harvtxt|Russell|Norvig|2021|p=1005}}]
[[Edward Fredkin]] argues that "artificial intelligence is the next step in evolution", an idea first proposed by [[Samuel Butler (novelist)|Samuel Butler]]'s "[[Darwin among the Machines]]" as far back as 1863, and expanded upon by [[George Dyson (science historian)|George Dyson]] in his 1998 book ''[[Darwin Among the Machines#Evolution of Global Intelligence|Darwin Among the Machines: The Evolution of Global Intelligence]]''.[AI as evolution: [[Edward Fredkin]] is quoted in {{Harvtxt|McCorduck|2004|p=401}}, {{Harvtxt|Butler|1863}}, {{Harvtxt|Dyson|1998}}]
===Decomputing===
Arguments for ''decomputing'' have been raised by [[Dan McQuillan]] (''Resisting AI: An Anti-fascist Approach to Artificial Intelligence'', 2022), meaning an opposition to the sweeping application and expansion of artificial intelligence. Similar to [[degrowth]], the approach criticizes AI as an outgrowth of the systemic issues and capitalist world we live in. It argues that a different future is possible, in which distance between people is reduced rather than increased through AI intermediaries.[{{cite web | last=McQuillan | first=Dan | title=a gift to the far right | website=ComputerWeekly.com | date=2025-01-14 | url=https://www.computerweekly.com/opinion/Labours-AI-Action-Plan-a-gift-to-the-far-right | access-date=2025-01-22}}]
== In fiction ==
{{Main|Artificial intelligence in fiction}}
[[File:Capek play.jpg|thumb|upright=1.2|The word "robot" itself was coined by [[Karel Čapek]] in his 1921 play ''[[R.U.R.]]'', the title standing for "Rossum's Universal Robots".]]
Thought-capable artificial beings have appeared as storytelling devices since antiquity,[AI in myth: {{Harvtxt|McCorduck|2004|pp=4–5}}] and have been a persistent theme in [[science fiction]].{{Sfnp|McCorduck|2004|pp=340–400}}
A common [[Trope (literature)|trope]] in these works began with [[Mary Shelley]]'s ''[[Frankenstein]]'', where a human creation becomes a threat to its masters. This includes such works as [[2001: A Space Odyssey (novel)|Arthur C. Clarke's]] and [[2001: A Space Odyssey|Stanley Kubrick's]] ''2001: A Space Odyssey'' (both 1968), with [[HAL 9000]], the murderous computer in charge of the ''[[Discovery One]]'' spaceship, as well as ''[[The Terminator]]'' (1984) and ''[[The Matrix]]'' (1999). In contrast, the rare loyal robots such as Gort from ''[[The Day the Earth Stood Still]]'' (1951) and Bishop from ''[[Aliens (film)|Aliens]]'' (1986) are less prominent in popular culture.{{Sfnp|Buttazzo|2001}}
[[Isaac Asimov]] introduced the [[Three Laws of Robotics]] in many stories, most notably with the "[[Multivac]]" super-intelligent computer. Asimov's laws are often brought up during lay discussions of machine ethics;{{Sfnp|Anderson|2008}} while almost all artificial intelligence researchers are familiar with Asimov's laws through popular culture, they generally consider the laws useless for many reasons, one of which is their ambiguity.{{Sfnp|McCauley|2007}}
Several works use AI to force us to confront the fundamental question of what makes us human, showing us artificial beings that have [[sentience|the ability to feel]], and thus to suffer. This appears in [[Karel Čapek]]'s ''[[R.U.R.]]'', the films ''[[A.I. Artificial Intelligence]]'' and ''[[Ex Machina (film)|Ex Machina]]'', as well as the novel ''[[Do Androids Dream of Electric Sheep?]]'', by [[Philip K. Dick]]. Dick considers the idea that our understanding of human subjectivity is altered by technology created with artificial intelligence.{{Sfnp|Galvan|1997}}
== See also ==
* {{Annotated link|Artificial consciousness}}
* {{Annotated link|Artificial intelligence and elections}}
* {{Annotated link|Artificial intelligence content detection}}
* {{Annotated link|Behavior selection algorithm}}
* {{Annotated link|Business process automation}}
* {{Annotated link|Case-based reasoning}}
* {{Annotated link|Computational intelligence}}
* {{Annotated link|Digital immortality}}
* {{Annotated link|Emergent algorithm}}
* {{Annotated link|Female gendering of AI technologies}}
* {{Annotated link|Glossary of artificial intelligence}}
* {{Annotated link|Intelligence amplification}}
* {{Annotated link|Intelligent agent}}
* {{Annotated link|Mind uploading}}
* [[Organoid intelligence]] – Use of brain cells and brain organoids for intelligent computing
* {{Annotated link|Robotic process automation}}
* {{Annotated link|The Last Day (novel)|''The Last Day''}}
* {{Annotated link|Wetware computer}}
== Explanatory notes ==
{{Notelist}}
== References ==
{{Reflist}}
=== AI textbooks ===
The two most widely used textbooks in 2023 (see the [https://explorer.opensyllabus.org/result/field?id=Computer+Science Open Syllabus]):
* {{Cite book |last1=Russell |first1=Stuart J. |author-link=Stuart J. Russell |title=[[Artificial Intelligence: A Modern Approach]] |last2=Norvig |first2=Peter |author-link2=Peter Norvig |publisher=Pearson |date=2021 |isbn=978-0-1346-1099-3 |edition=4th |location=Hoboken |lccn=20190474}}
* {{Cite book |last1=Rich |first1=Elaine |author-link=Elaine Rich |title=Artificial Intelligence |last2=Knight |first2=Kevin |last3=Nair |first3=Shivashankar B |date=2010 |publisher=Tata McGraw Hill India |isbn=978-0-0700-8770-5 |edition=3rd |location=New Delhi |ref=none}}
The four most widely used AI textbooks in 2008:
{{Refbegin|indent=yes|30em}}
* {{Cite book |last1=Luger |first1=George |author-link=George Luger |url=https://archive.org/details/artificialintell0000luge |title=Artificial Intelligence: Structures and Strategies for Complex Problem Solving |last2=Stubblefield |first2=William |author-link2=William Stubblefield |date=2004 |publisher=Benjamin/Cummings |isbn=978-0-8053-4780-7 |edition=5th |access-date=17 December 2019 |url-access=registration |archive-url=https://web.archive.org/web/20200726220613/https://archive.org/details/artificialintell0000luge |archive-date=26 July 2020 |url-status=live}}
* {{Cite book |last=Nilsson |first=Nils |author-link=Nils Nilsson (researcher) |url=https://archive.org/details/artificialintell0000nils |title=Artificial Intelligence: A New Synthesis |date=1998 |publisher=Morgan Kaufmann |isbn=978-1-5586-0467-4 |access-date=18 November 2019 |url-access=registration |archive-url=https://web.archive.org/web/20200726131654/https://archive.org/details/artificialintell0000nils |archive-date=26 July 2020 |url-status=live}}
* {{Russell Norvig 2003}}.
* {{Cite book |last1=Poole |first1=David |author-link=David Poole (researcher) |url=https://archive.org/details/computationalint00pool |title=Computational Intelligence: A Logical Approach |last2=Mackworth |first2=Alan |author-link2=Alan Mackworth |last3=Goebel |first3=Randy |author-link3=Randy Goebel |date=1998 |publisher=Oxford University Press |isbn=978-0-1951-0270-3 |location=New York |access-date=22 August 2020 |archive-url=https://web.archive.org/web/20200726131436/https://archive.org/details/computationalint00pool |archive-date=26 July 2020 |url-status=live}} Later edition: {{Cite book |last1=Poole |first1=David |url=http://artint.info/index.html |title=Artificial Intelligence: Foundations of Computational Agents |last2=Mackworth |first2=Alan |author-link2=Alan Mackworth |date=2017 |publisher=Cambridge University Press |isbn=978-1-1071-9539-4 |edition=2nd |access-date=6 December 2017 |archive-url=https://web.archive.org/web/20171207013855/http://artint.info/index.html |archive-date=7 December 2017 |url-status=live}}
{{Refend}}
Other textbooks:
* {{Cite book |last=Ertel |first=Wolfgang |title=Introduction to Artificial Intelligence |date=2017 |publisher=Springer |isbn=978-3-3195-8486-7 |edition=2nd |ref=none}}
* {{Cite book |last1=Ciaramella |first1=Alberto |author-link=Alberto Ciaramella |title=Introduction to Artificial Intelligence: from data analysis to generative AI |last2=Ciaramella |first2=Marco |date=2024 |publisher=Intellisemantic Editions |isbn=978-8-8947-8760-3 |edition=1st |ref=none}}
=== History of AI ===
{{Refbegin|indent=yes|30em}}
* {{Crevier 1993}}
* {{McCorduck 2004}}
* {{Cite book |last=Newquist |first=H. P. |author-link=HP Newquist |title=The Brain Makers: Genius, Ego, And Greed In The Quest For Machines That Think |date=1994 |publisher=Macmillan/SAMS |isbn=978-0-6723-0412-5 |location=New York}}
* {{Cite book |last1= Harmon |first1=Paul |last2= Sawyer |first2=Brian |title=Creating Expert Systems for Business and Industry |date=1990 |publisher=John Wiley & Sons |isbn=0471614963 |location=New York}}
{{Refend}}
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{{Refend}}
== Further reading ==
{{Refbegin|indent=yes|30em}}
* [[David Autor|Autor, David H.]], "Why Are There Still So Many Jobs? The History and Future of Workplace Automation" (2015) 29(3) ''Journal of Economic Perspectives'' 3.
* {{Cite book |last=Berlinski |first=David |author-link=David Berlinski |url=https://archive.org/details/adventofalgorith0000berl |title=The Advent of the Algorithm |publisher=Harcourt Books |date=2000 |isbn=978-0-1560-1391-8 |oclc=46890682 |access-date=22 August 2020 |archive-url=https://web.archive.org/web/20200726215744/https://archive.org/details/adventofalgorith0000berl |archive-date=26 July 2020 |url-status=live }}
* Boyle, James, [https://direct.mit.edu/books/book/5859/The-LineAI-and-the-Future-of-Personhood The Line: AI and the Future of Personhood], [[MIT Press]], 2024.
* [[Kenneth Cukier|Cukier, Kenneth]], "Ready for Robots? How to Think about the Future of AI", ''[[Foreign Affairs]]'', vol. 98, no. 4 (July/August 2019), pp. 192–198. [[George Dyson (science historian)|George Dyson]], historian of computing, writes (in what might be called "Dyson's Law") that "Any system simple enough to be understandable will not be complicated enough to behave intelligently, while any system complicated enough to behave intelligently will be too complicated to understand." (p. 197.) Computer scientist [[Alex Pentland]] writes: "Current [[machine learning|AI machine-learning]] [[algorithm]]s are, at their core, dead simple stupid. They work, but they work by brute force." (p. 198.)
* {{Cite journal |last=Evans |first=Woody |author-link=Woody Evans |date=2015 |title=Posthuman Rights: Dimensions of Transhuman Worlds |journal=Teknokultura |volume=12 |issue=2 |doi=10.5209/rev_TK.2015.v12.n2.49072 |doi-access=free|s2cid=147612763 }}
* {{Cite web |last=Frank |first=Michael |date=September 22, 2023 |title=US Leadership in Artificial Intelligence Can Shape the 21st Century Global Order |url=https://thediplomat.com/2023/09/us-leadership-in-artificial-intelligence-can-shape-the-21st-century-global-order |access-date=2023-12-08 |website=[[The Diplomat (magazine)|The Diplomat]] |quote=Instead, the United States has developed a new area of dominance that the rest of the world views with a mixture of awe, envy, and resentment: artificial intelligence... From AI models and research to cloud computing and venture capital, U.S. companies, universities, and research labs – and their affiliates in allied countries – appear to have an enormous lead in both developing cutting-edge AI and commercializing it. The value of U.S. venture capital investments in AI start-ups exceeds that of the rest of the world combined. |archive-date=16 September 2024 |archive-url=https://web.archive.org/web/20240916014433/https://thediplomat.com/2023/09/us-leadership-in-artificial-intelligence-can-shape-the-21st-century-global-order/ |url-status=live }}
* Gertner, Jon. (2023) "Wikipedia's Moment of Truth: Can the online encyclopedia help teach A.I. chatbots to get their facts right — without destroying itself in the process?" ''New York Times Magazine'' (July 18, 2023) [https://www.nytimes.com/2023/07/18/magazine/wikipedia-ai-chatgpt.html online] {{Webarchive|url=https://web.archive.org/web/20230720125400/https://www.nytimes.com/2023/07/18/magazine/wikipedia-ai-chatgpt.html |date=20 July 2023 }}
* [[Gleick, James]], "The Fate of Free Will" (review of Kevin J. Mitchell, ''Free Agents: How Evolution Gave Us Free Will'', Princeton University Press, 2023, 333 pp.), ''[[The New York Review of Books]]'', vol. LXXI, no. 1 (18 January 2024), pp. 27–28, 30. "[[Agency (philosophy)|Agency]] is what distinguishes us from machines. For biological creatures, [[reason]] and [[motivation|purpose]] come from acting in the world and experiencing the consequences. Artificial intelligences – disembodied, strangers to blood, sweat, and tears – have no occasion for that." (p. 30.)
* Halpern, Sue, "The Coming Tech Autocracy" (review of [[Verity Harding]], ''AI Needs You: How We Can Change AI's Future and Save Our Own'', Princeton University Press, 274 pp.; [[Gary Marcus]], ''Taming Silicon Valley: How We Can Ensure That AI Works for Us'', MIT Press, 235 pp.; [[Daniela Rus]] and [[Gregory Mone]], ''The Mind's Mirror: Risk and Reward in the Age of AI'', Norton, 280 pp.; [[Madhumita Murgia]], ''Code Dependent: Living in the Shadow of AI'', Henry Holt, 311 pp.), ''[[The New York Review of Books]]'', vol. LXXI, no. 17 (7 November 2024), pp. 44–46. "'We can't realistically expect that those who hope to get rich from AI are going to have the interests of the rest of us close at heart,' ... writes [Gary Marcus]. 'We can't count on [[government]]s driven by [[campaign finance]] contributions [from tech companies] to push back.'... Marcus details the demands that citizens should make of their governments and the [[tech company|tech companies]]. They include [[Transparency (behavior)|transparency]] on how AI systems work; compensation for individuals if their data [are] used to train LLMs ([[large language model]])s and the right to consent to this use; and the ability to hold tech companies liable for the harms they cause by eliminating [[Section 230]], imposing cash penalties, and passing stricter [[product liability]] laws... Marcus also suggests... that a new, AI-specific federal agency, akin to the [[FDA]], the [[FCC]], or the [[Federal Trade Commission|FTC]], might provide the most robust oversight.... [T]he [[Fordham University|Fordham]] law professor [[Chinmayi Sharma]]... suggests... establish[ing] a professional licensing regime for engineers that would function in a similar way to [[medical license]]s, [[malpractice]] suits, and the [[Hippocratic oath]] in medicine. 'What if, like doctors,' she asks..., 'AI engineers also vowed to [[Primum non nocere|do no harm]]?'" (p. 46.)
* {{Cite news |last=Henderson |first=Mark |date=24 April 2007 |title=Human rights for robots? We're getting carried away |url=https://www.thetimes.com/uk/science/article/human-rights-for-robots-were-getting-carried-away-xfbdkpgwn0v |url-status=live |archive-url=https://web.archive.org/web/20140531104850/http://www.thetimes.co.uk/tto/technology/article1966391.ece |archive-date=31 May 2014 |access-date=31 May 2014 |work=The Times Online |location=London }}
* Hughes-Castleberry, Kenna, "A Murder Mystery Puzzle: The literary puzzle ''[[Cain's Jawbone]]'', which has stumped humans for decades, reveals the limitations of natural-language-processing algorithms", ''[[Scientific American]]'', vol. 329, no. 4 (November 2023), pp. 81–82. "This murder mystery competition has revealed that although NLP ([[natural-language processing]]) models are capable of incredible feats, their abilities are very much limited by the amount of [[context (linguistics)|context]] they receive. This [...] could cause [difficulties] for researchers who hope to use them to do things such as analyze [[ancient language]]s. In some cases, there are few historical records on long-gone [[civilization]]s to serve as [[training data]] for such a purpose." (p. 82.)
* [[Immerwahr, Daniel]], "Your Lying Eyes: People now use A.I. to generate fake videos indistinguishable from real ones. How much does it matter?", ''[[The New Yorker]]'', 20 November 2023, pp. 54–59. "If by '[[deepfakes]]' we mean realistic videos produced using artificial intelligence that actually deceive people, then they barely exist. The fakes aren't deep, and the deeps aren't fake. [...] A.I.-generated videos are not, in general, operating in our media as counterfeited evidence. Their role better resembles that of [[cartoon]]s, especially smutty ones." (p. 59.)
* Johnston, John (2008) ''The Allure of Machinic Life: Cybernetics, Artificial Life, and the New AI'', MIT Press.
* {{Cite journal |last1=Jumper |first1=John |last2=Evans |first2=Richard |last3=Pritzel |first3=Alexander |last4=Green |first4=Tim |last5=Figurnov |first5=Michael |last6=Ronneberger |first6=Olaf |last7=Tunyasuvunakool |first7=Kathryn |last8=Bates |first8=Russ |last9=Žídek |first9=Augustin |last10=Potapenko |first10=Anna |last11=Bridgland |first11=Alex |last12=Meyer |first12=Clemens |last13=Kohl |first13=Simon A. A. |last14=Ballard |first14=Andrew J. |last15=Cowie |first15=Andrew |last16=Romera-Paredes |first16=Bernardino |last17=Nikolov |first17=Stanislav |last18=Jain |first18=Rishub |last19=Adler |first19=Jonas |last20=Back |first20=Trevor |last21=Petersen |first21=Stig |last22=Reiman |first22=David |last23=Clancy |first23=Ellen |last24=Zielinski |first24=Michal |last25=Steinegger |first25=Martin |last26=Pacholska |first26=Michalina |last27=Berghammer |first27=Tamas |last28=Bodenstein |first28=Sebastian |last29=Silver |first29=David |last30=Vinyals |first30=Oriol |last31=Senior |first31=Andrew W. |last32=Kavukcuoglu |first32=Koray |last33=Kohli |first33=Pushmeet |last34=Hassabis |first34=Demis |display-authors=3 |date=26 August 2021 |title=Highly accurate protein structure prediction with AlphaFold |journal=Nature |volume=596 |issue=7873 |pages=583–589 |bibcode=2021Natur.596..583J |doi=10.1038/s41586-021-03819-2 |pmc=8371605 |pmid=34265844 |s2cid=235959867}}
* {{Cite journal |last1=LeCun |first1=Yann |last2=Bengio |first2=Yoshua |last3=Hinton |first3=Geoffrey |date=28 May 2015 |title=Deep learning |url=https://www.nature.com/articles/nature14539 |url-status=live |journal=Nature |volume=521 |issue=7553 |pages=436–444 |bibcode=2015Natur.521..436L |doi=10.1038/nature14539 |pmid=26017442 |s2cid=3074096 |archive-url=https://web.archive.org/web/20230605235832/https://www.nature.com/articles/nature14539 |archive-date=5 June 2023 |access-date=19 June 2023 }}
* Leffer, Lauren, "The Risks of Trusting AI: We must avoid humanizing machine-learning models used in scientific research", ''[[Scientific American]]'', vol. 330, no. 6 (June 2024), pp. 80–81.
* [[Jill Lepore|Lepore, Jill]], "The Chit-Chatbot: Is talking with a machine a conversation?", ''[[The New Yorker]]'', 7 October 2024, pp. 12–16.
* {{Cite web |last=Maschafilm |date=2010 |title=Content: Plug & Pray Film – Artificial Intelligence – Robots |url=http://www.plugandpray-film.de/en/content.html |url-status=live |archive-url=https://web.archive.org/web/20160212040134/http://www.plugandpray-film.de/en/content.html |archive-date=12 February 2016 |website=plugandpray-film.de }}
* [[Marcus, Gary]], "Artificial Confidence: Even the newest, buzziest systems of artificial general intelligence are stymmied by the same old problems", ''[[Scientific American]]'', vol. 327, no. 4 (October 2022), pp. 42–45.
* {{Cite book |last=Mitchell |first=Melanie |title=Artificial intelligence: a guide for thinking humans |date=2019 |publisher=Farrar, Straus and Giroux |isbn=978-0-3742-5783-5 |location=New York}}
* {{Cite journal |last1=Mnih |first1=Volodymyr |last2=Kavukcuoglu |first2=Koray |last3=Silver |first3=David |last4=Rusu |first4=Andrei A. |last5=Veness |first5=Joel |last6=Bellemare |first6=Marc G. |last7=Graves |first7=Alex |last8=Riedmiller |first8=Martin |last9=Fidjeland |first9=Andreas K. |last10=Ostrovski |first10=Georg |last11=Petersen |first11=Stig |last12=Beattie |first12=Charles |last13=Sadik |first13=Amir |last14=Antonoglou |first14=Ioannis |last15=King |first15=Helen |last16=Kumaran |first16=Dharshan |last17=Wierstra |first17=Daan |last18=Legg |first18=Shane |last19=Hassabis |first19=Demis |display-authors=3 |date=26 February 2015 |title=Human-level control through deep reinforcement learning |url=https://www.nature.com/articles/nature14236 |url-status=live |journal=Nature |volume=518 |issue=7540 |pages=529–533 |bibcode=2015Natur.518..529M |doi=10.1038/nature14236 |pmid=25719670 |s2cid=205242740 |archive-url=https://web.archive.org/web/20230619055525/https://www.nature.com/articles/nature14236 |archive-date=19 June 2023 |access-date=19 June 2023 }} Introduced [[Deep Q-learning|DQN]], which produced human-level performance on some Atari games.
* [[Eyal Press|Press, Eyal]], "In Front of Their Faces: Does facial-recognition technology lead police to ignore contradictory evidence?", ''[[The New Yorker]]'', 20 November 2023, pp. 20–26.
* {{Cite news |date=21 December 2006 |title=Robots could demand legal rights |url=http://news.bbc.co.uk/2/hi/technology/6200005.stm |url-status=live |archive-url=https://web.archive.org/web/20191015042628/http://news.bbc.co.uk/2/hi/technology/6200005.stm |archive-date=15 October 2019 |access-date=3 February 2011 |work=BBC News }}
* Roivainen, Eka, "AI's IQ: [[ChatGPT]] aced a [standard intelligence] test but showed that [[intelligence]] cannot be measured by [[IQ]] alone", ''[[Scientific American]]'', vol. 329, no. 1 (July/August 2023), p. 7. "Despite its high IQ, [[ChatGPT]] fails at tasks that require real humanlike reasoning or an understanding of the physical and social world.... ChatGPT seemed unable to reason logically and tried to rely on its vast database of... facts derived from online texts."
* Scharre, Paul, "Killer Apps: The Real Dangers of an AI Arms Race", ''[[Foreign Affairs]]'', vol. 98, no. 3 (May/June 2019), pp. 135–144. "Today's AI technologies are powerful but unreliable. Rules-based systems cannot deal with circumstances their programmers did not anticipate. Learning systems are limited by the data on which they were trained. AI failures have already led to tragedy. Advanced autopilot features in cars, although they perform well in some circumstances, have driven cars without warning into trucks, concrete barriers, and parked cars. In the wrong situation, AI systems go from supersmart to superdumb in an instant. When an enemy is trying to manipulate and hack an AI system, the risks are even greater." (p. 140.)
* {{Cite journal |last1=Schulz |first1=Hannes |last2=Behnke |first2=Sven |date=1 November 2012 |title=Deep Learning |url=https://www.researchgate.net/publication/230690795 |journal=KI – Künstliche Intelligenz |volume=26 |issue=4 |pages=357–363 |doi=10.1007/s13218-012-0198-z |issn=1610-1987 |s2cid=220523562 }}
* {{Cite journal |last1=Serenko |first1=Alexander |last2=Michael Dohan |date=2011 |title=Comparing the expert survey and citation impact journal ranking methods: Example from the field of Artificial Intelligence |url=http://www.aserenko.com/papers/JOI_AI_Journal_Ranking_Serenko.pdf |url-status=live |journal=Journal of Informetrics |volume=5 |issue=4 |pages=629–649 |doi=10.1016/j.joi.2011.06.002 |archive-url=https://web.archive.org/web/20131004212839/http://www.aserenko.com/papers/JOI_AI_Journal_Ranking_Serenko.pdf |archive-date=4 October 2013 |access-date=12 September 2013 }}
* {{Cite journal |last1=Silver |first1=David |last2=Huang |first2=Aja |last3=Maddison |first3=Chris J. |last4=Guez |first4=Arthur |last5=Sifre |first5=Laurent |last6=van den Driessche |first6=George |last7=Schrittwieser |first7=Julian |last8=Antonoglou |first8=Ioannis |last9=Panneershelvam |first9=Veda |last10=Lanctot |first10=Marc |last11=Dieleman |first11=Sander |last12=Grewe |first12=Dominik |last13=Nham |first13=John |last14=Kalchbrenner |first14=Nal |last15=Sutskever |first15=Ilya |last16=Lillicrap |first16=Timothy |last17=Leach |first17=Madeleine |last18=Kavukcuoglu |first18=Koray |last19=Graepel |first19=Thore |last20=Hassabis |first20=Demis |display-authors=3 |date=28 January 2016 |title=Mastering the game of Go with deep neural networks and tree search |url=https://www.nature.com/articles/nature16961 |url-status=live |journal=Nature |volume=529 |issue=7587 |pages=484–489 |bibcode=2016Natur.529..484S |doi=10.1038/nature16961 |pmid=26819042 |s2cid=515925 |archive-url=https://web.archive.org/web/20230618213059/https://www.nature.com/articles/nature16961 |archive-date=18 June 2023 |access-date=19 June 2023 }}
* [[Ben Tarnoff|Tarnoff, Ben]], "The Labor Theory of AI" (review of [[Matteo Pasquinelli]], ''The Eye of the Master: A Social History of Artificial Intelligence'', Verso, 2024, 264 pp.), ''[[The New York Review of Books]]'', vol. LXXII, no. 5 (27 March 2025), pp. 30–32. The reviewer, Ben Tarnoff, writes: "The strangeness at the heart of the [[generative AI]] boom is that nobody really knows how the technology works. We know how the [[large language model]]s within [[ChatGPT]] and its counterparts are trained, even if we don't always know which [[data]] they're being trained on: they are asked to predict the next string of characters in a sequence. But exactly how they arrive at any given [[prediction]] is a mystery. The [[computation]]s that occur inside the model are simply too intricate for any human to comprehend." (p. 32.)
* [[Ashish Vaswani|Vaswani, Ashish]], Noam Shazeer, Niki Parmar et al. "[[Attention is all you need]]." Advances in neural information processing systems 30 (2017). Seminal paper on [[transformer (machine learning model)|transformer]]s.
* Vincent, James, "Horny Robot Baby Voice: James Vincent on AI chatbots", ''[[London Review of Books]]'', vol. 46, no. 19 (10 October 2024), pp. 29–32. "[AI chatbot] programs are made possible by new technologies but rely on the timelelss human tendency to [[anthropomorphise]]." (p. 29.)
* {{Cite book |url=https://ec.europa.eu/info/sites/info/files/commission-white-paper-artificial-intelligence-feb2020_en.pdf |title=White Paper: On Artificial Intelligence – A European approach to excellence and trust |publisher=European Commission |date=2020 |location=Brussels |ref={{Harvid|European Commission|2020}} |access-date=20 February 2020 |archive-url=https://web.archive.org/web/20200220173419/https://ec.europa.eu/info/sites/info/files/commission-white-paper-artificial-intelligence-feb2020_en.pdf |archive-date=20 February 2020 |url-status=live }}
{{Refend}}
== External links ==
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[[Category:Artificial intelligence|*]]
[[Category:Computational fields of study]]
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[[Category:Intelligence by type]]
{{Short description|Computer ability}}
'''Machine perception''' is the capability of a computer system to interpret [[data]] in a manner that is similar to the way [[human]]s use their [[sense]]s to relate to the world around them.[{{Cite web|url=http://www.ccs.fau.edu/~hahn/mpcr/|title=Machine Perception & Cognitive Robotics Laboratory|website=www.ccs.fau.edu|access-date=2016-06-18}}] The basic method that the [[computer]]s take in and respond to their [[Environment (systems)|environment]] is through the attached [[Electronic hardware|hardware]]. Until recently [[Input (computer science)|input]] was limited to a keyboard, or a mouse, but advances in technology, both in hardware and [[software]], have allowed computers to take in [[Sensory nervous system|sensory]] input in a way similar to humans.[{{Cite web |last=Cotton2009-03-01T00:00:00+00:00 |first=Simon |title=If it smells - it's chemistry |url=https://edu.rsc.org/feature/if-it-smells-its-chemistry/2020168.article |access-date=2022-05-03 |website=RSC Education |language=en}}][{{Cite web |title=Artificial networks learn to smell like the brain |url=https://news.mit.edu/2021/artificial-networks-learn-smell-like-the-brain-1018 |access-date=2022-05-03 |website=MIT News {{!}} Massachusetts Institute of Technology |date=18 October 2021 |language=en}}]
The end goal of machine perception is to give machines the ability to [[Visual perception|see]], [[Feeling|feel]] and [[perceive]] the world as humans do and therefore for them to be able to [[Explainable artificial intelligence|explain]] in a human way why they are making their decisions, to warn us when it is failing and more importantly, the reason why it is failing.[{{cite web|url=https://www.ece.vt.edu/research/area/perception|title=Machine Perception Research - ECE - Virginia Tech|website=www.ECE.VT.edu|access-date=January 10, 2018|archive-date=March 7, 2021|archive-url=https://web.archive.org/web/20210307031656/https://ece.vt.edu/research/area/perception|url-status=dead}}] This [[Goal|purpose]] is very similar to the proposed purposes for [[artificial intelligence]] generally, except that machine perception would only grant machines limited [[sentience]], rather than bestow upon machines full [[consciousness]], [[self-awareness]], and [[intentionality]].
==Machine vision==
{{main|machine vision}}
[[Computer vision]] is a field that includes methods for acquiring, processing, analyzing, and understanding images and high-dimensional data from the real world to produce numerical or symbolic information, e.g., in the forms of decisions. Computer vision has many applications already in use today such as [[Facial recognition system|facial recognition]], geographical modeling, and even aesthetic judgment.[{{Cite book
|last=Tanguiane ([[Andranik Tangian|Tangian]])
|first=Andranick
|date=1993
|title= Artificial Perception and Music Recognition
|publisher=Springer|location=Berlin-Heidelberg}}][{{Cite journal
|last=Tanguiane (Tangian)|first=Andranick
|year=1994
|title= Principle of correlativity of perception and its applications to music recognition
|journal= Music Perception|volume=11|issue=4|pages=465–502
|doi=10.2307/40285634
|jstor=40285634
}}]
This area has a wide range of application including music recording and compression, speech synthesis and [[speech recognition]].[{{Cite journal
|last=Tangian |first=Andranik
|year=2001
|title= How do we think: modeling interactions of memory and thinking
|journal= Cognitive Processing
|volume=2 |pages=117–151
|url=https://publikationen.bibliothek.kit.edu/1000133287
|doi=10.5445/IR/1000133287|s2cid=237995668
}}][{{cite web|title=Machine Perception & Cognitive Robotics Laboratory|url=http://www.ccs.fau.edu/~hahn/mpcr/|website=ccs.FAU.edu|access-date=January 10, 2018}}]
Many commonly used devices such as a smartphones, voice translators and cars make use of some form of machine hearing. Present technology still has challenges in [[speech segmentation]]. This means it is occasionally unable to correctly split words within sentences especially when spoken in an atypical accent.
==Machine touch{{anchor|Machine touch}}==
[[File:SynTouch BioTac.jpg|thumb|left|A [[tactile sensor]]]]
Machine touch is an area of machine perception where tactile information is processed by a machine or computer. Applications include [[tactile sensor|tactile perception]] of surface properties and [[dexterity]] whereby tactile information can enable intelligent reflexes and interaction with the environment.[{{cite journal|title=Learning efficient haptic shape exploration with a rigid tactile sensor array, S. Fleer, A. Moringen, R. Klatzky, H. Ritter |year=2020 |doi=10.1371/journal.pone.0226880 |pmid=31896135 |doi-access=free |last1=Fleer |first1=S. |last2=Moringen |first2=A. |last3=Klatzky |first3=R. L. |last4=Ritter |first4=H. |journal=PLOS ONE |volume=15 |issue=1 |pages=e0226880 |pmc=6940144 }}] Though this could possibly be done through measuring when and where friction occurs and also the nature and intensity of the friction, machines however still do not have any way of measuring few ordinary physical human experiences including physical pain. For example, scientists have yet to invent a mechanical substitute for the [[Nociceptor]]s in the body and brain that are responsible for noticing and measuring physical human discomfort and suffering.
==Machine olfaction==
Scientists are developing computers known as [[machine olfaction]] which can recognize and measure [[Sense of smell|smells]] as well. Airborne [[Chemical substance|chemicals]] are sensed and classified with a device sometimes known as an [[electronic nose]].[{{Cite web |title=Using artificial intelligence to smell the roses: Study applies machine learning to olfaction with possible vast applications in flavors and fragrances |url=https://www.sciencedaily.com/releases/2020/07/200728182544.htm |access-date=2022-05-03 |website=ScienceDaily |language=en}}][{{Cite web |last=Marr |first=Bernard |title=Artificial Intelligence Is Developing A Sense Of Smell: What Could A Digital Nose Mean In Practice? |url=https://www.forbes.com/sites/bernardmarr/2021/05/10/artificial-intelligence-is-developing-a-sense-of-smell-what-could-a-digital-nose-mean-in-practice/ |access-date=2022-05-03 |website=Forbes |language=en}}]
== Machine taste ==
{{excerpt|Electronic tongue}}
== Future ==
Other than those listed above, some of the future hurdles that the science of machine perception still has to overcome include, but are not limited to:
- [[Embodied cognition]] - The theory that cognition is a full body experience, and therefore can only exist, and therefore be measure and analyzed, in fullness if all required human abilities and processes are working together through a mutually aware and supportive systems network.
- The [[Moravec's paradox]] (see the link)
- The [[Principle of similarity]] - The ability young children develop to determine what family a newly introduced stimulus falls under even when the said stimulus is different from the members with which the child usually associates said family with. (An example could be a child figuring that a chihuahua is a dog and house pet rather than vermin.)
- The [[Unconscious inference]]: The natural human behavior of determining if a new stimulus is dangerous or not, what it is, and then how to relate to it without ever requiring any new conscious effort.
- The innate human ability to follow the [[likelihood principle]] in order to learn from circumstances and others over time.
- The [[recognition-by-components theory]] - being able to mentally analyze and break even complicated mechanisms into manageable parts with which to interact with. For example: A person seeing both the cup and the handle parts that make up a mug full of hot cocoa, in order to use the handle to hold the mug so as to avoid being burned.
- The [[Unconscious inference|free energy principle]] - determining long before hand how much energy one can safely delegate to being aware of things outside one's self without the loss of the needed energy one requires for sustaining their life and function satisfactorily. This allows one to become both optimally aware of the world around them self without depleting their energy so much that they experience damaging stress, decision fatigue, and/or exhaustion.
==See also==
* [[Robotic sensing]]
* [[Sensor]]s
* [[Simultaneous localization and mapping|SLAM]]
*[[History of artificial intelligence]]
==References==
{{reflist|
[
{{cite journal|
author=Turk, Matthew |
journal=Chinese Journal of Computers |
volume= 12 |
date= 2000 |
title=Perceptive Media: Machine Perception and Human Computer Interaction|url=http://cs.ucsb.edu/~mturk/Papers/PerceptiveMedia.pdf}} pages 1235-1244]
[
{{cite book |doi=10.1109/CVPR.2011.5995467|chapter-url=https://dspace.sunyconnect.suny.edu/bitstream/handle/1951/55408/Dhar_grad.sunysb_0771M_10339.pdf?sequence=1|chapter = High level describable attributes for predicting aesthetics and interestingness|title = CVPR 2011|pages = 1657–1664|year = 2011|last1 = Dhar|first1 = Sagnik|last2 = Ordonez|first2 = Vicente|last3 = Berg|first3 = Tamara L.| hdl=1951/55408 |isbn = 978-1-4577-0394-2| s2cid=14609200 }}]
[{{Cite journal |doi = 10.1109/MSP.2010.937498|title = Machine Hearing: An Emerging Field [Exploratory DSP|journal = IEEE Signal Processing Magazine|volume = 27|issue = 5|pages = 131–139|year = 2010|last1 = Lyon|first1 = Richard|bibcode = 2010ISPM...27..131L| s2cid=13143070 }}]
[
{{cite web|
author=Malcolm Tatum|
url=http://www.wisegeek.com/what-is-machine-perception.htm|
date= October 3, 2012|
title=What is Machine Perception}}]
[
{{cite arXiv|
author=Alexander Serov|
date= January 29, 2013|
title=Subjective Reality and Strong Artificial Intelligence|
eprint=1301.6359|
class=cs.AI}}]
}}
{{DEFAULTSORT:Machine Perception}}
[[Category:Artificial intelligence]]
[[Category:Artificial intelligence engineering]]
{{Short description|Awareness of existence}}
{{Other uses|Consciousness (disambiguation)|Conscious (disambiguation)}}
{{Distinguish|Conscience|Conscientiousness}}
{{Cs1 config|name-list-style=vanc}}
{{Use American English|date=July 2023}}
[[Image:RobertFuddBewusstsein17Jh.png|thumb|Representation of consciousness from the [[17th century]] by [[Robert Fludd]], an English [[Paracelsianism|Paracelsian]] physician]]
'''Consciousness''', at its simplest, is [[awareness]] of a state or object, either internal to oneself or in one's external environment.[{{cite dictionary|title=consciousness|dictionary=Merriam-Webster|access-date=June 4, 2012|url= http://www.merriam-webster.com/dictionary/consciousness}}] However, its nature has led to millennia of analyses, explanations, and debate among philosophers, scientists, and theologians. Opinions differ about what exactly needs to be studied or even considered consciousness. In some explanations, it is synonymous with the [[mind]], and at other times, an aspect of it. In the past, it was one's "inner life", the world of [[introspection]], of private thought, [[imagination]], and [[volition (psychology)|volition]].[{{cite book|last=Jaynes|first=Julian|author-link=Julian Jaynes|title=The Origin of Consciousness in the Breakdown of the Bicameral Mind|publisher=Houghton Mifflin|orig-year=1976|year=2000|isbn=0-618-05707-2}}] Today, it often includes any kind of [[cognition]], [[experience]], feeling, or [[perception]]. It may be awareness, awareness of awareness, [[metacognition]], or [[self-awareness]], either continuously changing or not.[{{cite journal|last=Rochat|first=Philippe|title=Five levels of self-awareness as they unfold early in life|journal=Consciousness and Cognition|year=2003|volume=12|issue=4|pages=717–731|url=http://psychology.emory.edu/cognition/rochat/Five%20levels%20.pdf|archive-url=https://ghostarchive.org/archive/20221009/http://psychology.emory.edu/cognition/rochat/Five%20levels%20.pdf|archive-date=2022-10-09|url-status=live|doi=10.1016/s1053-8100(03)00081-3|pmid=14656513|s2cid=10241157}}][{{cite journal|author=P.A. Guertin|title=A novel concept introducing the idea of continuously changing levels of consciousness|journal=Journal of Consciousness Exploration & Research|year=2019|volume=10|issue=6|pages=406–412|url=https://jcer.com/index.php/jcj/article/view/829/825|access-date=2021-08-19|archive-date=2021-12-15|archive-url=https://web.archive.org/web/20211215112848/https://jcer.com/index.php/jcj/article/view/829/825|url-status=live}}] The disparate range of research, notions, and speculations raises a curiosity about whether the right questions are being asked.[{{cite journal|author-link= Peter Hacker|last= Hacker|first= P.M.S.|url= http://info.sjc.ox.ac.uk/scr/hacker/docs/ConsciousnessAChallenge.pdf|archive-url=https://ghostarchive.org/archive/20221009/http://info.sjc.ox.ac.uk/scr/hacker/docs/ConsciousnessAChallenge.pdf|archive-date=2022-10-09|url-status=live|title= The Sad and Sorry History of Consciousness: being, among other things, a challenge to the "consciousness-studies community"|journal= Royal Institute of Philosophy|volume=supplementary volume 70|date= 2012}}]
Examples of the range of descriptions, definitions or explanations are: ordered distinction between self and environment, simple [[wakefulness]], one's sense of selfhood or [[soul]] explored by "looking within"; being a metaphorical "[[stream of consciousness (psychology)|stream]]" of contents, or being a [[mental state]], [[mental event]], or [[mental process]] of the [[brain]].
==Etymology==
The words "conscious" and "consciousness" in the English language date to the 17th century, and the first recorded use of "conscious" as a simple adjective was applied figuratively to inanimate objects (''"the conscious Groves"'', 1643).[{{cite book|last=Barfield|first=Owen|title=History in English Words|date=1962|orig-date=1926|publisher=Faber and Faber Limited|location=London|edition=239 pgs. paper covered|author-link=Owen Barfield}}]{{rp|p=175}} It derived from the [[Latin]] ''conscius'' (''con-'' "together" and [[wikt:scio|''scio'']] "to know") which meant "knowing with" or "having joint or common knowledge with another", especially as in sharing a secret.[{{cite book|title=Studies in words|author =C. S. Lewis|year=1990|publisher=Cambridge University Press|chapter=Ch. 8: Conscience and conscious|isbn=978-0-521-39831-2|author-link =C. S. Lewis}}] [[Thomas Hobbes]] in ''[[Leviathan (Hobbes book)|Leviathan]]'' (1651) wrote: "Where two, or more men, know of one and the same fact, they are said to be Conscious of it one to another".[{{cite book|title=Leviathan: or, The Matter, Forme & Power of a Commonwealth, Ecclesiasticall and Civill|author=Thomas Hobbes|publisher=University Press|year=1904|url=https://archive.org/details/leviathan00hobbgoog|page=[https://archive.org/details/leviathan00hobbgoog/page/n62 39]|author-link=Thomas Hobbes}}] There were also many occurrences in Latin writings of the phrase ''conscius sibi'', which translates literally as "knowing with oneself", or in other words "sharing knowledge with oneself about something". This phrase has the figurative sense of "knowing that one knows", which is something like the modern English word "conscious", but it was rendered into English as "conscious to oneself" or "conscious unto oneself". For example, [[Archbishop Ussher]] wrote in 1613 of "being so conscious unto myself of my great weakness".[{{cite book|title=The whole works, Volume 2|author=[[James Ussher]], [[Charles Richard Elrington]]|page=417|year=1613|publisher=Hodges and Smith}}]
The Latin ''[[:la:conscientia|conscientia]]'', literally 'knowledge-with', first appears in Roman juridical texts by writers such as [[Cicero]]. It means a kind of shared knowledge with moral value, specifically what a witness knows of someone else's deeds.[{{cite book|title=Dictionary of Untranslatables. A Philosophical Lexicon|author=Barbara Cassin|publisher=Princeton University Press|isbn=978-0-691-13870-1|year=2014|page=[https://archive.org/details/dictionaryofuntr0000unse/page/176 176]|url=https://archive.org/details/dictionaryofuntr0000unse/page/176}}][{{cite journal| author=G. Molenaar|title=Seneca's Use of the Term Conscientia|journal=Mnemosyne| volume=22|issue=2|year=1969|pages=170–180|doi=10.1163/156852569x00670}}] Although [[René Descartes]] (1596–1650), writing in Latin, is generally taken to be the first philosopher to use ''conscientia'' in a way less like the traditional meaning and more like the way modern English speakers would use "conscience", his meaning is nowhere defined.[{{cite journal| author=Boris Hennig|title=Cartesian Conscientia|journal=British Journal for the History of Philosophy|year=2007|volume=15|issue=3|pages=455–484|doi=10.1080/09608780701444915|s2cid=218603781}}] In ''Search after Truth'' (''{{lang|la|Regulæ ad directionem ingenii ut et inquisitio veritatis per lumen naturale}}'', Amsterdam 1701) he wrote the word with a [[Gloss (annotation)|gloss]]: ''conscientiâ, vel interno testimonio'' (translatable as "conscience, or internal testimony").[Charles Adam, [[Paul Tannery]] (eds.), ''Oeuvres de Descartes'' X, [https://archive.org/stream/oeuvresdedescar10desc#page/524/mode/2up 524] (1908).][{{cite book|pages=205–206|title=Consciousness: from perception to reflection in the history of philosophy|isbn=978-1-4020-6081-6|publisher=Springer|editor1=Sara Heinämaa|editor2=Vili Lähteenmäki|editor3=Pauliina Remes|year=2007}}] It might mean the knowledge of the value of one's own thoughts.[{{cite web|title=An Essay Concerning Human Understanding (Chapter XXVII)|last=Locke|first=John|publisher=University of Adelaide|location=Australia|url=https://ebooks.adelaide.edu.au/l/locke/john/l81u/B2.27.html|access-date=August 20, 2010|archive-date=May 8, 2018|archive-url=https://web.archive.org/web/20180508053707/https://ebooks.adelaide.edu.au/l/locke/john/l81u/B2.27.html|url-status=dead}}][{{cite encyclopedia|url=https://www.britannica.com/EBchecked/topic/133274/consciousness|title=Science & Technology: consciousness|encyclopedia=Encyclopædia Britannica|access-date=August 20, 2010}}] The essay strongly influenced 18th-century [[British philosophy]], and Locke's definition appeared in [[Samuel Johnson]]'s celebrated ''[[A Dictionary of the English Language|Dictionary]]'' (1755).[{{cite book|title=A Dictionary of the English Language|author=Samuel Johnson|publisher=Knapton|year=1756|url=https://archive.org/details/dictionaryofengl01john|author-link=Samuel Johnson}}]
The French term ''conscience'' is defined roughly like English "consciousness" in the 1753 volume of [[Diderot]] and [[d'Alembert]]'s [[Encyclopédie]] as "the opinion or internal feeling that we ourselves have from what we do".[Jaucourt, Louis, chevalier de. "Consciousness." The Encyclopedia of Diderot & d'Alembert Collaborative Translation Project. Translated by Scott St. Louis. Ann Arbor: Michigan Publishing, University of Michigan Library, 2014. [http://hdl.handle.net/2027/spo.did2222.0002.986. Originally published as "Conscience," Encyclopédie ou Dictionnaire raisonné des sciences, des arts et des métiers], 3:902 (Paris, 1753).]
==Problem of definition==
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| quote = About forty meanings attributed to the term ''consciousness'' can be identified and categorized based on ''functions'' and ''experiences''. The prospects for reaching any single, agreed-upon, theory-independent definition of consciousness appear remote.[{{cite journal|last1 = Vimal|first1 = R. L. P.|last2 = Sansthana|first2 = D. A.|year = 2010|title = On the Quest of Defining Consciousness|url = http://sites.google.com/site/rlpvimal/Home/2010-Vimal-DefineC-LVCR-3-2.pdf|journal = Mind and Matter|volume = 8|issue = 1| pages = 93–121}}{{Dead link|date=January 2024}}]
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Scholars are divided as to whether [[Aristotle]] had a concept of consciousness. He does not use any single word or terminology that is clearly similar to the [[phenomenon]] or [[concept]] defined by John Locke. Victor Caston contends that Aristotle did have a concept more clearly similar to [[perception]].[{{cite book|last1=Caston|first1=Victor|title=Mind|date=2002|publisher=Oxford University Press|page=751|url=http://ancphil.lsa.umich.edu/-/downloads/faculty/caston/aristotle-consciousness.pdf|archive-url=https://ghostarchive.org/archive/20221009/http://ancphil.lsa.umich.edu/-/downloads/faculty/caston/aristotle-consciousness.pdf|archive-date=2022-10-09|url-status=live|chapter=Aristotle on Consciousness}}]
Modern dictionary definitions of the word ''consciousness'' evolved over several centuries and reflect a range of seemingly related meanings, with some differences that have been controversial, such as the distinction between ''inward awareness'' and ''perception'' of the physical world, or the distinction between ''conscious'' and ''unconscious'', or the notion of a ''mental entity'' or ''mental activity'' that is not physical.
The common-usage definitions of ''consciousness'' in ''[[Webster's Third New International Dictionary]]'' (1966) are as follows:
#* ''awareness or perception of an inward psychological or spiritual fact; intuitively perceived knowledge of something in one's inner self''
#* ''inward awareness of an external object, state, or fact''
#* ''concerned awareness;'' INTEREST, CONCERN—''often used with an attributive noun [e.g. class consciousness]''
#''the state or activity that is characterized by sensation, emotion, volition, or thought; mind in the broadest possible sense; something in nature that is distinguished from the physical''
#''the totality in psychology of sensations, perceptions, ideas, attitudes, and [[feelings]] of which an individual or a group is aware at any given time or within a particular time span—''compare STREAM OF CONSCIOUSNESS
#''waking life (as that to which one returns after sleep, trance, fever) wherein all one's mental powers have returned . . .''
#''the part of mental life or psychic content in psychoanalysis that is immediately available to the ego—''compare PRECONSCIOUS, UNCONSCIOUS
The ''[[Cambridge English Dictionary]]'' defines consciousness as "the state of understanding and realizing something".[{{cite dictionary|url=https://dictionary.cambridge.org/dictionary/english/consciousness|entry=consciousness|encyclopedia=Cambridge English Dictionary|publisher=Cambridge University Press|access-date=2018-10-23|archive-date=2021-03-07|archive-url=https://web.archive.org/web/20210307210954/https://dictionary.cambridge.org/dictionary/english/consciousness|url-status=live |title=Consciousness}}]
The ''[[Oxford Living Dictionary]]'' defines consciousness as "[t]he state of being aware of and responsive to one's surroundings", "[a] person's awareness or perception of something", and "[t]he fact of awareness by the mind of itself and the world".[{{cite dictionary|url=https://en.oxforddictionaries.com/definition/consciousness|archive-url=https://web.archive.org/web/20160925102008/https://en.oxforddictionaries.com/definition/consciousness|url-status=dead|archive-date=September 25, 2016|entry=consciousness|dictionary=Oxford Living Dictionary|publisher=Oxford University Press|title=Consciousness - definition of consciousness in English | Oxford Dictionaries}}]
Philosophers have attempted to clarify technical distinctions by using a [[jargon]] of their own. The corresponding entry in the ''[[Routledge Encyclopedia of Philosophy]]'' (1998) reads:
;'''Consciousness''':Philosophers have used the term ''consciousness'' for four main topics: knowledge in general, intentionality, introspection (and the knowledge it specifically generates) and phenomenal experience... Something within one's mind is 'introspectively conscious' just in case one introspects it (or is poised to do so). Introspection is often thought to deliver one's primary knowledge of one's mental life. An experience or other mental entity is 'phenomenally conscious' just in case there is 'something it is like' for one to have it. The clearest examples are: perceptual experience, such as tastings and seeings; bodily-sensational experiences, such as those of pains, tickles and itches; imaginative experiences, such as those of one's own actions or perceptions; and streams of thought, as in the experience of thinking 'in words' or 'in images'. Introspection and phenomenality seem independent, or dissociable, although this is controversial.[{{cite encyclopedia|author=Edward Craig|encyclopedia=Routledge Encyclopedia of Philosophy|publisher=Routledge|entry=Consciousness|year=1998|isbn=978-0-415-18707-7|author-link=Edward Craig (philosopher)}}]
===Traditional metaphors for mind===
During the early 19th century, the emerging field of [[geology]] inspired a popular [[metaphor]] that the mind likewise had hidden layers "which recorded the past of the individual".{{r|JJ76|p=3}} By 1875, most psychologists believed that "consciousness was but a small part of mental life",{{r|JJ76|p=3}} and this idea underlies the goal of [[Freudian psychology|Freudian therapy]], to expose the {{em|unconscious layer}} of the mind.
Other metaphors from various sciences inspired other analyses of the mind, for example: [[Johann Friedrich Herbart]] described ideas as being attracted and repulsed like magnets; [[John Stuart Mill]] developed the idea of "mental chemistry" and "mental compounds", and [[Edward B. Titchener]] sought the "structure" of the mind by analyzing its "elements". The abstract idea of ''states of consciousness'' mirrored the concept of [[states of matter]].
In 1892, [[William James]] noted that the "ambiguous word 'content' has been recently invented instead of 'object'" and that the metaphor of mind as a {{em|container}} seemed to minimize the dualistic problem of how "states of consciousness can {{em|know}}" things, or objects;{{r|WJames92|p=465}} by 1899 psychologists were busily studying the "contents of conscious experience by [[introspection]] and [[experiment]]".[{{cite encyclopedia|last1=Landesman|first1=Charles Jr.|editor1-last=Edwards|editor1-first=Paul|encyclopedia=The Encyclopedia of Philosophy|contribution=Consciousness|volume= 2|date=1967|publisher=Macmillan, Inc.|pages=191–195|edition=Reprint 1972}}]{{rp|191–192}}}} an activity seemingly distinct from that of perceiving the 'outer world' and its physical phenomena. In 1892 [[William James]] noted the distinction along with doubts about the inward character of the mind:{{blockquote|'Things' have been doubted, but thoughts and feelings have never been doubted. The outer world, but never the inner world, has been denied. Everyone assumes that we have direct introspective acquaintance with our thinking activity as such, with our consciousness as something inward and contrasted with the outer objects which it knows. Yet I must confess that for my part I cannot feel sure of this conclusion. [...] It seems as if consciousness as an inner activity were rather a ''postulate'' than a sensibly given fact...[{{cite book|last1=James|first1=William|title=Psychology|date=1948|orig-date=1892|publisher=Fine Editions Press, World Publishing Co.|location=Cleveland}}]{{rp|467}}}}
By the 1960s, for many philosophers and psychologists who talked about consciousness, the word no longer meant the 'inner world' but an indefinite, large category called ''[[awareness]]'', as in the following example:
{{blockquote|It is difficult for modern Western man to grasp that the Greeks really had no concept of consciousness in that they did not class together phenomena as varied as problem solving, remembering, imagining, perceiving, feeling pain, dreaming, and acting on the grounds that all these are manifestations of being aware or being conscious.[{{cite encyclopedia|last1=Peters|first1=R. S.|last2=Mace|first2=C. A.|editor1-last=Edwards|editor1-first=Paul|encyclopedia=The Encyclopedia of Philosophy|contribution=Psychology|volume= 7|date=1967|publisher=Macmillan, Inc.|pages=1–27|edition=Reprint 1972}}]{{rp|4}}}}
Many philosophers and scientists have been unhappy about the difficulty of producing a definition that does not involve circularity or fuzziness.[ In The ''Macmillan Dictionary of Psychology'' (1989 edition), [[Stuart Sutherland]] emphasized external awareness, and expressed a skeptical attitude more than a definition:
{{blockquote|'''Consciousness'''—The having of perceptions, thoughts, and [[feelings]]; awareness. The term is impossible to define except in terms that are unintelligible without a grasp of what consciousness means. Many fall into the trap of equating consciousness with [[self-consciousness]]—to be conscious it is only necessary to be aware of the external world. Consciousness is a fascinating but elusive phenomenon: it is impossible to specify what it is, what it does, or why it has evolved. Nothing worth reading has been written on it.][{{cite book|author=Stuart Sutherland|title=Macmillan Dictionary of Psychology|publisher=Macmillan|chapter=Consciousness|year=1989|isbn=978-0-333-38829-7|author-link=Stuart Sutherland}}]}}
Using 'awareness', however, as a definition or synonym of consciousness is not a simple matter:
{{blockquote|text=If awareness of the environment . . . is the criterion of consciousness, then even the protozoans are conscious. If awareness of awareness is required, then it is doubtful whether the great apes and human infants are conscious.[{{cite encyclopedia|last= Thomas|first= Garth J.|encyclopedia= Encyclopædia Britannica|date=1967|volume=6|pages=366|title= Consciousness}}]}}
In 1974, philosopher [[Thomas Nagel]] used 'consciousness', 'conscious experience', 'subjective experience' and the 'subjective character of experience' as synonyms for something that "occurs at many levels of animal life ... [although] it is difficult to say in general what provides evidence of it."[{{cite journal | last1 = Nagel | first1 = Thomas | year = 1974 | title = What Is It Like to Be a Bat? | journal = The Philosophical Review | volume = 83 | issue = 4| pages = 435–450 | doi=10.2307/2183914 | jstor=2183914 |url={{google books |plainurl=y |id=fBGPBRX3JsQC|page=165}}}}] Nagel's terminology also included what has been described as "the standard 'what it's like' locution"[Levine, Joseph (2010). Review of Uriah Kriegel, Subjective Consciousness: A Self-Representational Theory. ''Notre Dame Philosophical Reviews'' 2010 (3).] in reference to the impenetrable [[subjectivity]] of any organism's [[experience]] which Nagel referred to as "inner life" without implying any kind of introspection. On Nagel's approach, [[Peter Hacker]] commented:{{r|Hacker2002|p=158}} "Consciousness, thus conceived, is extended to the whole domain of 'experience'—of 'Life' {{em|subjectively understood}}." He regarded this as a "novel analysis of consciousness"{{r|Hacker2012|p=14}} and has been particularly critical of Nagel's terminology and its philosophical consequences.{{r|Hacker2012}} In 2002 he attacked Nagel's 'what it's like' phrase as "malconstructed" and meaningless English—it sounds as if it asks for an analogy, but does not—and he called Nagel's approach logically "misconceived" as a definition of consciousness.[{{cite journal |author-link= Peter Hacker |last= Hacker |first= P.M.S. |url=http://www.phps.at/texte/HackerP1.pdf |title= Is there anything it is like to be a bat? |journal= Philosophy |volume= 77 |date= 2002 |issue= 2 |pages= 157–174 |doi=10.1017/s0031819102000220}}] In 2012 Hacker went further and asserted that Nagel had "laid the groundwork for ... forty years of fresh confusion about consciousness" and that "the contemporary philosophical conception of consciousness that is embraced by the 'consciousness studies community' is incoherent".{{r|Hacker2012|p=13-15}}
===Influence on research===
Many philosophers have argued that consciousness is a unitary concept that is understood by the majority of people despite the difficulty philosophers have had defining it.[{{cite journal|author=Michael V. Antony|year=2001|title=Is ''consciousness'' ambiguous?|journal=Journal of Consciousness Studies|volume=8|pages=19–44}}] The term 'subjective experience', following Nagel, is amibiguous, as philosophers seem to differ from non-philosophers in their intuitions about its meaning.[{{cite journal |author=Justin Sytsma |author2=Edouard Machery |title=Two conceptions of subjective experience |journal=Philosophical Studies |year=2010 |volume=151 |issue=2 |pages=299–327 |doi=10.1007/s11098-009-9439-x|s2cid=2444730 |url=http://philsci-archive.pitt.edu/archive/00004888/01/Two_Conceptions_of_Subjective_Experience.pdf |archive-url=https://ghostarchive.org/archive/20221009/http://philsci-archive.pitt.edu/archive/00004888/01/Two_Conceptions_of_Subjective_Experience.pdf |archive-date=2022-10-09 |url-status=live}}] [[Max Velmans]] proposed that the "everyday understanding of consciousness" uncontroversially "refers to experience itself rather than any particular thing that we observe or experience" and he added that consciousness "is [therefore] exemplified by {{em|all}} the things that we observe or experience",{{r|Velmans2009|p=4}} whether thoughts, feelings, or perceptions. [[Max Velmans|Velmans]] noted however, as of 2009, that there was a deep level of "confusion and internal division"[{{cite journal|author=Max Velmans|title=How to define consciousness—and how not to define consciousness|journal=Journal of Consciousness Studies|year=2009|volume=16|pages=139–156|author-link=Max Velmans}}] among experts about the phenomenon of consciousness, because researchers lacked "a sufficiently well-specified use of the term...to agree that they are investigating the same thing".{{r|Velmans2009|p=3}} He argued additionally that "pre-existing theoretical commitments" to competing explanations of consciousness might be a source of bias.
Within the "modern consciousness studies" community the technical phrase 'phenomenal consciousness' is a common synonym for all forms of awareness, or simply '[[experience]]',{{r|Velmans2009|p=4|quote=In common usage, the term "consciousness" is often synonymous with "awareness", "conscious awareness", and "experience".}} without differentiating between inner and outer, or between higher and lower types. With advances in brain research, "the presence or absence of ''experienced phenomena''"{{r|Velmans2009|p=3}} of any kind underlies the work of those [[neuroscientist]]s who seek "to analyze the precise relation of [[Phenomenology (psychology)|conscious phenomenology]] to its associated information processing" in the brain.{{r|Velmans2009|p=10}} This [[neuroscience|neuroscientific]] goal is to find the "neural correlates of consciousness" (NCC). One criticism of this goal is that it begins with a theoretical commitment to the neurological origin of all "experienced phenomena" whether inner or outer.{{efn|"Investigating "how experience ensues from the brain", rather than exploring a factual claim, betrays a philosophical commitment".[{{cite journal|last1=Gomez-Marin|first1=Alex|last2=Arnau|first2=Juan|title=The False Problem of Consciousness|journal=Behavior of Organisms Laboratory|date=2019|url=http://philsci-archive.pitt.edu/15699/1/MS_GomezMarin_Arnau.pdf}}]}} Also, the fact that the easiest 'content of consciousness' to be so analyzed is "the experienced three-dimensional world (the phenomenal world) beyond the body surface"{{r|Velmans2009|p=4}} invites another criticism, that most consciousness research since the 1990s, perhaps because of bias, has focused on processes of [[perception|external perception]].[{{cite book|editor-last1=Engel|editor-first1=Andreas K.|last1=Frith|first1=Chris|last2=Metzinger|first2=Thomas|title= The Pragmatic Turn: Toward Action-Oriented Views in Cognitive Science|url=https://www.researchgate.net/publication/304657860|chapter=What's the Use of Consciousness? How the Stab of Conscience Made Us Really Conscious|pages=193–214|isbn= 9780262034326|doi= 10.7551/mitpress/9780262034326.003.0012|date=March 2016|author-link1=Chris Frith|author-link2=Thomas Metzinger}}]
From a [[history of psychology]] perspective, [[Julian Jaynes]] rejected popular but "superficial views of consciousness"{{r|JJ90|p=447}} especially those which equate it with "that vaguest of terms, [[experience]]".[{{cite book|last=Jaynes|first=Julian|date=1976|isbn=0-395-20729-0|author-link=Julian Jaynes|publisher=Houghton Mifflin|title=The Origin of Consciousness in the Breakdown of the Bicameral Mind|url=https://archive.org/details/originofconsciou0000unse|url-access=registration}}]{{rp|8}} In 1976 he insisted that if not for [[introspection]], which for decades had been ignored or taken for granted rather than explained, there could be no "conception of what consciousness is"{{r|JJ76|p=18}} and in 1990, he reaffirmed the traditional idea of the phenomenon called 'consciousness', writing that "its [[denotation|denotative definition]] is, as it was for René Descartes, John Locke, and [[David Hume]], what is introspectable".{{r|JJ90|p=450}} Jaynes saw consciousness as an important but small part of human mentality, and he asserted: "there can be no progress in the science of consciousness until ... what is introspectable [is] sharply distinguished"{{r|JJ90|p=447}} from the {{em|unconscious}} processes of [[cognition]] such as [[perception]], reactive [[awareness]] and [[attention]], and automatic forms of [[learning]], [[problem-solving]], and [[decision-making]].{{r|JJ76|p=21-47}}
The [[cognitive science]] point of view—with an inter-disciplinary perspective involving fields such as [[psychology]], [[linguistics]] and [[anthropology]][{{Cite book|url=https://books.google.com/books?id=PKCHAgAAQBAJ&q=Consciousness+in+anthropology&pg=PP1|title=Questions of Consciousness|last1=Cohen|first1=A. P.|last2=Rapport|first2=N.|publisher=Routledge|year=1995|isbn=978-1-134-80469-6|location=London}}]—requires no agreed definition of "consciousness" but studies the interaction of many processes besides perception. For some researchers, consciousness is linked to some kind of "selfhood", for example to certain pragmatic issues such as the feeling of agency and the effects of regret[{{cite book|editor-last1=Engel|editor-first1=Andreas K.|last1=Seth|first1=Anil|title= The Pragmatic Turn: Toward Action-Oriented Views in Cognitive Science |chapter=Action-Oriented Understanding of Consciousness and the Structure of Experience|pages=261–282|isbn=978-0-262-03432-6|doi= 10.7551/mitpress/9780262034326.003.0012|date=March 2016|author-link1=Anil Seth}}] Similarly [[Daniel Kahneman]], who focused on systematic errors in perception, memory and decision-making, has differentiated between two kinds of mental processes, or cognitive "systems":[{{cite book|first=Daniel|last=Kahneman|title=Thinking, Fast and Slow|url=https://books.google.com/books?id=ZuKTvERuPG8C|year=2011|publisher=Macmillan|isbn=978-1-429-96935-2}}] the "fast" activities that are primary, automatic and "cannot be turned off",{{r|Kahneman2011|p=22}} and the "slow", deliberate, effortful activities of a secondary system "often associated with the subjective experience of agency, choice, and concentration".{{r|Kahneman2011|p=13}} Kahneman's two systems have been described as "roughly corresponding to unconscious and conscious processes".[{{cite book|last=Kuijsten|first=Marcel|year=2016|editor-last=Kuijsten|editor-first=Marcel|chapter=Introduction|title=Gods, Voices, and the Bicameral Mind: The Theories of Julian Jaynes|pages=1–15|publisher=Julian Jaynes Society|isbn=978-0-979-07443-1|location=Henderson, NV}}]{{rp|8}} The two systems can interact, for example in sharing the control of attention.{{r|Kahneman2011|p=22}} While System 1 can be impulsive, "System 2 is in charge of self-control",{{r|Kahneman2011|p=26}} and "When we think of ourselves, we identify with System 2, the conscious, reasoning self that has beliefs, makes choices, and decides what to think about and what to do".{{r|Kahneman2011|p=21}}
Some have argued that we should eliminate the concept from our understanding of the mind, a position known as consciousness semanticism.[{{cite book|last=Anthis|first=Jacy|title=Biologically Inspired Cognitive Architectures 2021|chapter=Consciousness Semanticism: A Precise Eliminativist Theory of Consciousness|series=Studies in Computational Intelligence|year=2022|volume=1032|pages=20–41|doi=10.1007/978-3-030-96993-6_3|isbn=978-3-030-96992-9|chapter-url=https://philarchive.org/rec/ANTCSA|access-date=7 August 2022|archive-date=7 August 2022|archive-url=https://web.archive.org/web/20220807144036/https://link.springer.com/chapter/10.1007/978-3-030-96993-6_3|url-status=live}}]
In [[medicine]], a "level of consciousness" terminology is used to describe a patient's [[arousal]] and responsiveness, which can be seen as a continuum of states ranging from full alertness and [[Understanding|comprehension]], through disorientation, [[delirium]], loss of meaningful communication, and finally loss of movement in response to painful [[Stimulus (physiology)|stimuli]].[{{cite book|first=Güven|last=Güzeldere|title=The Nature of Consciousness: Philosophical Debates|year=1997|editor-first=Ned|editor-last=Block|editor2-first=Owen|editor2-last=Flanagan|editor3-first=Güven|editor3-last=Güzeldere|pages=1–67|location=Cambridge, MA|publisher=MIT Press}}] Issues of practical concern include how the level of consciousness can be assessed in severely ill, comatose, or anesthetized people, and how to treat conditions in which consciousness is impaired or disrupted.[{{cite journal|title=Late recovery from the minimally conscious state: ethical and policy implications|first1=J. J.|last1=Fins|first2=N. D.|last2=Schiff|first3=K. M.|last3=Foley|journal=Neurology|year=2007|volume=68|pages=304–307|pmid=17242341|doi=10.1212/01.wnl.0000252376.43779.96|issue=4|s2cid=32561349}}] The degree or level of consciousness is measured by standardized behavior observation scales such as the [[Glasgow Coma Scale]].
==Philosophy of mind==
While historically philosophers have defended various views on consciousness, surveys indicate that [[physicalism]] is now the dominant position among contemporary philosophers of mind.[{{cite web|url=https://philpapers.org/surveys/results.pl|title=PhilPapers Survey 2020|publisher=PhilPapers|access-date=2023-12-15}}] For an overview of the field, approaches often include both historical perspectives (e.g., Descartes, Locke, [[Immanuel Kant|Kant]]) and organization by key issues in contemporary debates. An alternative is to focus primarily on current philosophical stances and empirical findings.
===Coherence of the concept===
Philosophers differ from non-philosophers in their intuitions about what consciousness is.[{{cite journal|author=Justin Sytsma|author2=Edouard Machery|title=Two conceptions of subjective experience|journal=Philosophical Studies|year=2010|volume=151|issue=2|pages=299–327|doi=10.1007/s11098-009-9439-x|s2cid=2444730|url=http://philsci-archive.pitt.edu/archive/00004888/01/Two_Conceptions_of_Subjective_Experience.pdf|archive-url=https://ghostarchive.org/archive/20221009/http://philsci-archive.pitt.edu/archive/00004888/01/Two_Conceptions_of_Subjective_Experience.pdf|archive-date=2022-10-09|url-status=live}}] While most people have a strong intuition for the existence of what they refer to as consciousness,[ skeptics argue that this intuition is too narrow, either because the concept of consciousness is embedded in our intuitions, or because we all are illusions. [[Gilbert Ryle]], for example, argued that traditional understanding of consciousness depends on a [[dualism (philosophy of mind)|Cartesian dualist]] outlook that improperly distinguishes between mind and body, or between mind and world. He proposed that we speak not of minds, bodies, and the world, but of entities, or identities, acting in the world. Thus, by speaking of "consciousness" we end up leading ourselves by thinking that there is any sort of thing as consciousness separated from behavioral and linguistic understandings.][{{cite book|title=The Concept of Mind|author=Gilbert Ryle|publisher=University of Chicago Press|date=2000 |orig-date=1949|pages=156–163|isbn=978-0-226-73296-1|title-link=The Concept of Mind|author-link=Gilbert Ryle}}]
===Types===
[[Ned Block]] argues that discussions on consciousness have often failed properly to distinguish ''phenomenal consciousness'' from ''access consciousness''. The terms had been used before Block used them, but he adopted the short forms P-consciousness and A-consciousness.[{{cite book|title=The Nature of Consciousness: Philosophical Debates|editor=N. Block|editor2=O. Flanagan|editor3=G. Guzeldere|chapter=On a confusion about a function of consciousness|author=Ned Block|pages=375–415|year=1998|isbn=978-0-262-52210-6|publisher=MIT Press|chapter-url=http://cogprints.org/231/1/199712004.html|author-link=Ned Block|access-date=2011-09-10|archive-date=2011-11-03|archive-url=https://web.archive.org/web/20111103034117/http://cogprints.org/231/1/199712004.html|url-status=live}} Pages 230 and 231 in [https://www.nedblock.us/papers/1995_Function.pdf the version on the author's own website].] According to Block:
*P-consciousness is raw experience: it is moving, colored forms, sounds, sensations, emotions and feelings with our bodies and responses at the center. These experiences, considered independently of any impact on behavior, are called [[qualia]].
*A-consciousness is the phenomenon whereby information in our minds is accessible for verbal report, reasoning, and the control of behavior. So, when we [[perception|perceive]], information about what we perceive is access conscious; when we [[introspection|introspect]], information about our thoughts is access conscious; when we [[memory|remember]], information about the past is access conscious, and so on.
Block adds that P-consciousness does not allow of easy definition: he admits that he "cannot define P-consciousness in any remotely [[circular definition|noncircular]] way.[{{cite book|author=Daniel Dennett|year=2004|title=Consciousness Explained|page=375|publisher=Penguin|isbn=978-0-7139-9037-9|title-link=Consciousness Explained|author-link=Daniel Dennett}}] others have broadly accepted it. [[David Chalmers]] has argued that A-consciousness can in principle be understood in mechanistic terms, but that understanding P-consciousness is much more challenging: he calls this the [[hard problem of consciousness]].[{{cite journal|url=http://www.imprint.co.uk/chalmers.html|title=Facing up to the problem of consciousness|author=David Chalmers|journal=Journal of Consciousness Studies|volume=2|year=1995|pages=200–219|url-status=dead|archive-url=https://web.archive.org/web/20050308163649/http://www.imprint.co.uk/chalmers.html|archive-date=2005-03-08|author-link=David Chalmers}}]
Some philosophers believe that Block's two types of consciousness are not the end of the story. [[William Lycan]], for example, argued in his book ''Consciousness and Experience'' that at least eight clearly distinct types of consciousness can be identified (organism consciousness; control consciousness; consciousness ''of''; state/event consciousness; reportability; introspective consciousness; subjective consciousness; self-consciousness)—and that even this list omits several more obscure forms.[{{cite book|author=William Lycan|title=Consciousness and Experience|pages=1–4|year=1996|publisher=MIT Press|isbn=978-0-262-12197-2|author-link=William Lycan}}]
There is also debate over whether or not A-consciousness and P-consciousness always coexist or if they can exist separately. Although P-consciousness without A-consciousness is more widely accepted, there have been some hypothetical examples of A without P. Block, for instance, suggests the case of a "[[Philosophical zombie|zombie]]" that is computationally identical to a person but without any subjectivity. However, he remains somewhat skeptical concluding "I don't know whether there are any actual cases of A-consciousness without P-consciousness, but I hope I have illustrated their conceptual possibility".[{{cite journal|last= Block|first=Ned|year = 1995|title = How many concepts of consciousness?|url = https://pdfs.semanticscholar.org/6174/aff557977a75c5d76463871180f8d1befbbc.pdf|archive-url = https://web.archive.org/web/20200210172202/https://pdfs.semanticscholar.org/6174/aff557977a75c5d76463871180f8d1befbbc.pdf|url-status = dead|archive-date = 2020-02-10|journal = Behavioral and Brain Sciences|volume = 18|issue = 2| pages = 272–284|doi=10.1017/s0140525x00038486| s2cid = 41023484}}]
===Distinguishing consciousness from its contents===
[[Sam Harris]] observes: "At the level of your experience, you are not a body of cells, organelles, and atoms; you are consciousness and its ever-changing contents".[Harris, S. (12 October 2011). The mystery of consciousness. ''Sam Harris.'' https://www.samharris.org/blog/the-mystery-of-consciousness {{Webarchive|url=https://web.archive.org/web/20230423061921/https://www.samharris.org/blog/the-mystery-of-consciousness|date=2023-04-23}}] Seen in this way, consciousness is a subjectively experienced, ever-present field in which things (the contents of consciousness) come and go.
Christopher Tricker argues that this field of consciousness is symbolized by the mythical bird that opens the Daoist classic the [[Zhuangzi (book)|''Zhuangzi.'']] This bird's name is Of a Flock ([[Peng (mythology)|''peng'' 鵬]]), yet its back is countless thousands of miles across and its wings are like clouds arcing across the heavens. "Like Of a Flock, whose wings arc across the heavens, the wings of your consciousness span to the horizon. At the same time, the wings of every other being's consciousness span to the horizon. You are of a flock, one bird among kin."[Tricker, C. (2022). [https://thecicadaandthebird.com The cicada and the bird. The usefulness of a useless philosophy. Chuang Tzu's ancient wisdom translated for modern life.] {{Webarchive|url=https://web.archive.org/web/20230421032929/https://thecicadaandthebird.com/|date=2023-04-21}} Page 52. [https://books.google.com/books?id=YnCaEAAAQBAJ (Google Books)] {{Webarchive|url=https://web.archive.org/web/20230608153319/https://books.google.com/books?id=YnCaEAAAQBAJ|date=2023-06-08}}]
===Mind–body problem===
{{Main|Mind–body problem}}
[[Image:Descartes mind and body.gif|thumb|Illustration of [[mind–body dualism]] by [[René Descartes]]. Inputs are passed by the sensory organs to the [[pineal gland]], and from there to the immaterial [[Soul|spirit]].]]
Mental processes (such as consciousness) and physical processes (such as brain events) seem to be correlated, however the specific nature of the connection is unknown.
The first influential philosopher to discuss this question specifically was [[René Descartes|Descartes]], and the answer he gave is known as [[mind–body dualism]]. Descartes proposed that consciousness resides within an immaterial domain he called ''[[mental substance|res cogitans]]'' (the realm of thought), in contrast to the domain of material things, which he called ''[[res extensa]]'' (the realm of extension).[{{cite book|title=Philosophy of Man: selected readings|last=Dy|first=Manuel B. Jr.|publisher=Goodwill Trading Co.|year=2001|isbn=978-971-12-0245-3|page=97}}] He suggested that the interaction between these two domains occurs inside the brain, perhaps in a small midline structure called the [[pineal gland]].[{{cite web|title=Descartes and the Pineal Gland|publisher=Stanford University|date=November 5, 2008|url=http://plato.stanford.edu/entries/pineal-gland/|access-date=2025-02-07|archive-date=2019-12-16|archive-url=https://web.archive.org/web/20191216035157/https://plato.stanford.edu/entries/pineal-gland/|url-status=live}}]
Although it is widely accepted that Descartes explained the problem cogently, few later philosophers have been happy with his solution, and his ideas about the pineal gland have especially been ridiculed.[{{cite book|author=William Jaworski|title=Philosophy of Mind: A Comprehensive Introduction|publisher=John Wiley and Sons|year=2011|isbn=978-1-4443-3367-1|pages=5–11}}]
Since the dawn of Newtonian science with its vision of simple mechanical principles governing the entire universe, some philosophers have been tempted by the idea that consciousness could be explained in purely physical terms. The first influential writer to propose such an idea explicitly was [[Julien Offray de La Mettrie]], in his book ''[[Man a Machine]]'' (''L'homme machine''). His arguments, however, were very abstract.[{{cite book| editor=Ann Thomson|author=Julien Offray de La Mettrie|title=Machine man and other writings|publisher=Cambridge University Press|year=1996|isbn=978-0-521-47849-6|author-link=Julien Offray de La Mettrie}}] The most influential modern physical theories of consciousness are based on [[psychology]] and [[neuroscience]]. Theories proposed by neuroscientists such as [[Gerald Edelman]][{{cite book|title=Bright Air, Brilliant Fire: On the Matter of the Mind|author=Gerald Edelman|publisher=Basic Books|year=1993|isbn=978-0-465-00764-6|author-link=Gerald Edelman|url-access=registration|url=https://archive.org/details/brightairbrillia00gera}}] and [[António Damásio|Antonio Damasio]],[{{cite book|author=Antonio Damasio|year=1999|title=The Feeling of What Happens: Body and Emotion in the Making of Consciousness|location=New York|publisher=Harcourt Press|isbn=978-0-15-601075-7|author-link=Antonio Damasio|url=https://archive.org/details/feelingofwhathap00dama_0}}] and by philosophers such as Daniel Dennett,[{{cite book|author=Daniel Dennett|year=1991|title=Consciousness Explained|url=https://archive.org/details/consciousnessexp00denn|url-access=registration|location=Boston|publisher=Little & Company|isbn=978-0-316-18066-5|author-link=Daniel Dennett}}] seek to explain consciousness in terms of neural events occurring within the brain. Many other neuroscientists, such as [[Christof Koch]],[{{cite book| author=Christof Koch|year=2004|title=The Quest for Consciousness|location=Englewood, CO|publisher=Roberts & Company|isbn=978-0-9747077-0-9|author-link=Christof Koch}}] have explored the neural basis of consciousness without attempting to frame all-encompassing global theories. At the same time, [[computer scientist]]s working in the field of [[artificial intelligence]] have pursued the goal of creating digital computer programs that can [[Artificial consciousness|simulate or embody consciousness]].[Ron Sun and Stan Franklin, Computational models of consciousness: A taxonomy and some examples. In: P.D. Zelazo, M. Moscovitch, and E. Thompson (eds.), ''The Cambridge Handbook of Consciousness'', pp. 151–174. Cambridge University Press, New York. 2007]
A few theoretical physicists have argued that classical physics is intrinsically incapable of explaining the holistic aspects of consciousness, but that [[Quantum mechanics|quantum theory]] may provide the missing ingredients. Several theorists have therefore proposed [[quantum mind]] (QM) theories of consciousness.[{{cite book|title=Quantum Approaches to Consciousness|publisher=Stanford University|date=December 25, 2011|url=http://plato.stanford.edu/entries/qt-consciousness/|access-date=December 25, 2011|archive-date=August 8, 2021|archive-url=https://web.archive.org/web/20210808080906/https://plato.stanford.edu/entries/qt-consciousness/|url-status=live}}] Notable theories falling into this category include the [[holonomic brain theory]] of [[Karl H. Pribram|Karl Pribram]] and [[David Bohm]], and the [[Orch-OR|Orch-OR theory]] formulated by [[Stuart Hameroff]] and [[Roger Penrose]]. Some of these QM theories offer descriptions of phenomenal consciousness, as well as QM interpretations of access consciousness. None of the quantum mechanical theories have been confirmed by experiment. Recent publications by G. Guerreshi, J. Cia, S. Popescu, and H. Briegel[{{cite journal|doi=10.1103/PhysRevE.82.021921|pmid=20866851|last1=Cai|first1=J.|last2=Popescu|first2=S.|last3=Briegel|first3=H.|title=Persistent dynamic entanglement from classical motion: How bio-molecular machines can generate non-trivial quantum states|journal=Physical Review E|volume=82|issue=2|pages=021921|arxiv=0809.4906|bibcode=2010PhRvE..82b1921C|year=2010|s2cid=23336691}}] could falsify proposals such as those of Hameroff, which rely on [[quantum entanglement]] in protein. At the present time many scientists and philosophers consider the arguments for an important role of quantum phenomena to be unconvincing.[{{cite book|author=John Searle|year=1997|title=The Mystery of Consciousness|publisher=The New York Review of Books|pages=53–88|isbn=978-0-940322-06-6|author-link=John Searle}}] Empirical evidence is against the notion of quantum consciousness, an experiment about [[wave function collapse]] led by [[Catalina Curceanu]] in 2022 suggests that quantum consciousness, as suggested by [[Roger Penrose]] and [[Stuart Hameroff]], is highly implausible.[{{cite journal|last1=Derakhshani|first1=Maaneli|last2=Diósi|first2=Lajos|last3=Laubenstein|first3=Matthias|last4=Piscicchia|first4=Kristian|last5=Curceanu|first5=Catalina|title=At the crossroad of the search for spontaneous radiation and the Orch OR consciousness theory|journal=Physics of Life Reviews|date=September 2022|volume=42|pages=8–14|doi=10.1016/j.plrev.2022.05.004|pmid=35617922|bibcode=2022PhLRv..42....8D|url=https://www.sciencedirect.com/science/article/abs/pii/S1571064522000197}}]
Apart from the general question of the [[Hard problem of consciousness|"hard problem" of consciousness]] (which is, roughly speaking, the question of how mental experience can arise from a physical basis[{{cite book|title=The Consciousness Paradox: Consciousness, Concepts, and Higher-Order Thoughts|author= Rocco J. Gennaro|chapter-url=https://books.google.com/books?id=t-XgKMgzwk4C&pg=PA75|page=75|chapter=§4.4 The hard problem of consciousness|isbn=978-0-262-01660-5|year=2011|publisher=MIT Press}}]), a more specialized question is how to square the subjective notion that we are in control of our decisions (at least in some small measure) with the customary view of causality that subsequent events are caused by prior events. The topic of [[free will]] is the philosophical and scientific examination of this conundrum.
===Problem of other minds===
{{main|Problem of other minds}}
Many philosophers consider experience to be the essence of consciousness, and believe that experience can only fully be known from the inside, subjectively. The [[problem of other minds]] is a philosophical problem traditionally stated as the following [[Epistemology|epistemological]] question: Given that I can only observe the behavior of others, how can I know that others have minds?[{{cite web|last=Hyslop|first=Alec|date=14 January 2014|editor1-last=Zalta|editor1-first=Edward N.|editor2-last=Nodelman|editor2-first=Uri|title=Other minds|url=http://plato.stanford.edu/entries/other-minds/|access-date=May 26, 2015|website=[[Stanford Encyclopedia of Philosophy]]|publisher=Metaphysics Research Lab, Center for the Study of Language and Information, Stanford University|issn=1095-5054}}] The problem of other minds is particularly acute for people who believe in the possibility of [[philosophical zombie]]s, that is, people who think it is possible in principle to have an entity that is physically indistinguishable from a human being and behaves like a human being in every way but nevertheless lacks consciousness.[{{cite web|author=Robert Kirk|title=Zombies|publisher=Stanford Encyclopedia of Philosophy (Summer 2009 Edition)|editor=Edward N. Zalta|url=http://plato.stanford.edu/archives/sum2009/entries/zombies|access-date=2011-10-25|archive-date=2013-12-02|archive-url=https://web.archive.org/web/20131202074345/http://plato.stanford.edu/archives/sum2009/entries/zombies/|url-status=live}}] Related issues have also been studied extensively by Greg Littmann of the University of Illinois,[''The Culture and Philosophy of Ridley Scott'', Greg Littmann, pp. 133–144, Lexington Books (2013).] and by Colin Allen (a professor at the University of Pittsburgh) regarding the literature and research studying [[artificial intelligence]] in androids.[''Moral Machines'', Wendell Wallach and Colin Allen, 288 pages, Oxford University Press, USA (June 3, 2010), {{ISBN|0-19-973797-5}}.]
The most commonly given answer is that we attribute consciousness to other people because we see that they resemble us in appearance and behavior; we reason that if they look like us and act like us, they must be like us in other ways, including having experiences of the sort that we do.[ There are, however, a variety of problems with that explanation. For one thing, it seems to violate the [[Occam's razor|principle of parsimony]], by postulating an invisible entity that is not necessary to explain what we observe.][{{cite book|author=Alec Hyslop|chapter=The analogical inference to other minds|title=Other Minds|year=1995|publisher=Springer|isbn=978-0-7923-3245-9|pages=41–70}}] Some philosophers, such as Daniel Dennett in a research paper titled "The Unimagined Preposterousness of Zombies", argue that people who give this explanation do not really understand what they are saying.[{{cite journal|author=Daniel Dennett|title=The unimagined preposterousness of zombies|journal=Journal of Consciousness Studies|volume=2|year=1995|pages=322–325|author-link=Daniel Dennett}}] More broadly, philosophers who do not accept the possibility of zombies generally believe that consciousness is reflected in behavior (including verbal behavior), and that we attribute consciousness on the basis of behavior. A more straightforward way of saying this is that we attribute experiences to people because of what they can ''do'', including the fact that they can tell us about their experiences.[{{cite journal|author=Stevan Harnad|title=Why and how we are not zombies|journal=Journal of Consciousness Studies|year=1995|volume=1|pages=164–167|author-link=Stevan Harnad}}]
=== Qualia ===
{{Main|qualia}}
The term "qualia" was introduced in philosophical literature by [[C. I. Lewis]]. The word is derived from Latin and means "of what sort". It is basically a quantity or property of something as perceived or experienced by an individual, like the scent of rose, the taste of wine, or the pain of a headache. They are difficult to articulate or describe. The philosopher and scientist [[Daniel Dennett]] describes them as "the way things seem to us", while philosopher and cognitive scientist [[David Chalmers]] expanded on qualia as the "[[hard problem of consciousness]]" in the 1990s. When qualia is experienced, activity is simulated in the brain, and these processes are called [[neural correlates of consciousness]] (NCCs). Many scientific studies have been done to attempt to link particular brain regions with emotions or experiences.[{{Cite book |last1=Parsons |first1=Paul |title=50 Ideas You Really Need to Know: Science |last2=Dixon |first2=Gail |publisher=[[Quercus]] |year=2016 |isbn=978-1-78429-614-8 |location=London |pages=141–143 |language=en}}][Oxford English Dictionary, "qualia", 3rd ed., Oxford University Press, 2010. Accessed October 3, 2024. https://www.oed.com/search/dictionary/?scope=Entries&q=qualia.][{{Cite web |title=Qualia {{!}} Internet Encyclopedia of Philosophy |url=https://iep.utm.edu/qualia/#:~:text=The%20term%20%E2%80%9Cqualia%E2%80%9D%20(singular,properties%20of%20sense%2Ddata%20themselves. |access-date=4 October 2024 |website=Internet Encyclopedia of Philosophy}}]
Species which experience qualia are said to have [[sentience]], which is central to the [[animal rights movement]], because it includes the ability to experience pain and suffering.[{{cite web |title=Personal Identity - Internet Encyclopedia of Philosophy |url=http://www.iep.utm.edu/person-i/ |url-status=live |archive-url=https://web.archive.org/web/20170903032724/http://www.iep.utm.edu/person-i/ |archive-date=3 September 2017 |access-date=24 January 2025 |website=www.iep.utm.edu}}] This includes questions regarding whether someone is the "same person" from moment to moment. If that is the case, another question is what exactly the "identity carrier" is that makes a conscious being "the same" being from one moment to the next. The problem of determining personal identity also includes questions such as Benj Hellie's [[vertiginous question]], which can be summarized as "Why am I me and not someone else?".[{{cite journal|last=Hellie|first=Benj|year=2013|title=Against egalitarianism|journal=Analysis|volume=73|issue=2|pages=304–320|doi=10.1093/analys/ans101}}] The philosophical problems regarding the nature of personal identity have been extensively discussed by Thomas Nagel in his book ''[[The View from Nowhere]]''.
A common view of personal identity is that an individual has a continuous identity that persists from moment to moment, with an individual having a continuous identity consisting of a line segment stretching across time from birth to death. In the case of an afterlife as described in Abrahamic religions, one's personal identity is believed to stretch infinitely into the future, forming a ray or line. This notion of identity is similar to the form of dualism advocated by René Descartes. However, some philosophers argue that this common notion of personal identity is unfounded. [[Daniel Kolak]] has argued extensively against it in his book ''I am You''.[{{Cite book |last=Kolak |first=Daniel |url=https://digitalphysics.ru/pdf/Kaminskii_A_V/Kolak_I_Am_You.pdf |title=I Am You: The Metaphysical Foundations for Global Ethics |date=2007-11-03 |publisher=Springer Science & Business Media |isbn=978-1-4020-3014-7 |language=en |archive-url=https://web.archive.org/web/20240906163443/https://digitalphysics.ru/pdf/Kaminskii_A_V/Kolak_I_Am_You.pdf |archive-date=2024-09-06 |url-status=live}}] Kolak refers to the aforementioned notion of personal identity being linear as "Closed individualism". Another view of personal identity according to Kolak is "Empty individualism", in which one's personal identity only exists for a single moment of time. However, Kolak advocates for a view of personal identity called [[Open individualism]], in which all consciousness is in reality a single being and individual personal identity in reality does not exist at all. Another philosopher who has contested the notion of personal identity is [[Derek Parfit]]. In his book ''[[Reasons and Persons]]'',[{{Cite book |last=Parfit |first=Derek |url=https://archive.org/details/trent_0116300637661/page/n5/mode/2up |title=Reasons and persons |date=1984 |isbn=0-19-824615-3 |location=Oxford [Oxfordshire] |publisher=Clarendon Press |oclc=9827659}}] he describes a thought experiment known as the [[teletransportation paradox]]. In Buddhist philosophy, the concept of [[anattā]] refers to the idea that the self is an illusion.
Other philosophers have argued that Hellie's vertiginous question has a number of philosophical implications relating to the [[Metaphysics|metaphysical]] nature of consciousness. [[Christian List]] argues that the vertiginous question and the existence of first-personal facts is evidence against physicalism, and evidence against other third-personal metaphysical pictures, including standard versions of [[Mind–body dualism|dualism]].[{{cite web |url=https://philpapers.org/rec/LISTFA |title=The first-personal argument against physicalism |last=List |first=Christian |date=2023 |access-date=3 September 2024}}] List also argues that the vertiginous question implies a "quadrilemma" for theories of consciousness. He claims that at most three of the following metaphysical claims can be true: 'first-person [[Philosophical realism|realism]]', 'non-[[solipsism]]', 'non-fragmentation', and 'one world' – and at at least one of these four must be false.[{{cite web |url=https://philarchive.org/rec/LISAQF |title=A quadrilemma for theories of consciousness |last=List |first=Christian |date=2023 |publisher=The Philosophical Quarterly |access-date=24 January 2025}}] List has proposed a model he calls the "many-worlds theory of consciousness" in order to reconcile the subjective nature of consciousness without lapsing into solipsism.[{{cite web |url=https://philarchive.org/rec/LISTMT-2 |title=The many-worlds theory of consciousness |last=List |first=Christian |date=2023 |publisher=The Philosophical Quarterly |access-date=24 January 2025}}] Vincent Conitzer argues that the nature of identity is connected to [[A series and B series]] theories of time, and that A-theory being true implies that the "I" is metaphysically distinguished from other perspectives.[{{cite arXiv|last=Conitzer|first=Vincent |date=30 Aug 2020|title=The Personalized A-Theory of Time and Perspective|eprint=2008.13207v1|class=physics.hist-ph}}] Giovanni Merlo has argued that the subjectivist view of mental phenomena goes a considerable way towards solving various long-standing philosophical puzzles related to various aspects of consciousness, such as the unity of consciousness, the contents of self-awareness, and the problems with transmitting information related to the contents of subjective experience.[{{cite journal |last1=Merlo |first1=Giovanni |date=2016 |title=Subjectivism and the Mental |url=https://philarchive.org/rec/MERSAT-6 |journal=Dialectica |volume= 70|issue= 3|pages= 311–342|doi= 10.1111/1746-8361.12153|access-date=24 January 2025}}] Other philosophical theories regarding the metaphysical nature of self are Caspar Hare's theories of [[perspectival realism]],[{{cite journal |last=Hare |first=Caspar |date=September 2010 |title=Realism About Tense and Perspective |url=http://web.mit.edu/~casparh/www/Papers/CJHarePerspectivalRealism.pdf |journal=Philosophy Compass |volume=5 |issue=9 |pages=760–769 |doi=10.1111/j.1747-9991.2010.00325.x |hdl-access=free |hdl=1721.1/115229}}] in which things within perceptual awareness have a defining intrinsic property that exists absolutely and not relative to anything, and [[egocentric presentism]], in which the experiences of other individuals are not ''present'' in the way that one's current perspective is.[{{cite journal|last=Hare|first=Caspar|title=Self-Bias, Time-Bias, and the Metaphysics of Self and Time|journal=The Journal of Philosophy|date=July 2007|volume=104|issue=7|pages=350–373|doi=10.5840/jphil2007104717|url=http://web.mit.edu/~casparh/www/Papers/CJHareSelfBias2.pdf}}][{{cite book|last=Hare|first=Caspar|title=On Myself, and Other, Less Important Subjects|year=2009|publisher=Princeton University Press|isbn=9780691135311|url=http://press.princeton.edu/titles/8921.html}}]
==Scientific study==
For many decades, consciousness as a research topic was avoided by the majority of mainstream scientists, because of a general feeling that a phenomenon defined in subjective terms could not properly be studied using objective experimental methods.[{{cite book|author=Horst Hendriks-Jansen|title=Catching ourselves in the act: situated activity, interactive emergence, evolution, and human thought|year=1996|publisher=Massachusetts Institute of Technology|page=114|isbn=978-0-262-08246-4}}] In 1975 [[George Mandler]] published an influential psychological study which distinguished between slow, serial, and limited conscious processes and fast, parallel and extensive unconscious ones.[Mandler, G. "Consciousness: Respectable, useful, and probably necessary". In R. Solso (Ed.) ''Information processing and cognition'': NJ: LEA.] The Science and Religion Forum[{{Cite web|date=2021|title=Science and Religion Forum|url=https://www.srforum.org/about|url-status=live |archive-url=https://web.archive.org/web/20161103075415/http://srforum.org/about/|archive-date=2016-11-03}}] 1984 annual conference, '''From Artificial Intelligence to Human Consciousness''' identified the nature of consciousness as a matter for investigation; [[Donald Michie]] was a keynote speaker. Starting in the 1980s, an expanding community of neuroscientists and psychologists have associated themselves with a field called ''Consciousness Studies'', giving rise to a stream of experimental work published in books,[Mandler, G. Consciousness recovered: Psychological functions and origins of thought. Philadelphia: John Benjamins. 2002] journals such as ''[[Consciousness and Cognition]]'', ''Frontiers in Consciousness Research'', ''[[Psyche (consciousness journal)|Psyche]]'', and the ''[[Journal of Consciousness Studies]]'', along with regular conferences organized by groups such as the [[Association for the Scientific Study of Consciousness]][{{cite book|title=Toward a Science of Consciousness III: The Third Tucson Discussions and Debates|author=Stuart Hameroff|author2=Alfred Kaszniak|author3-link=David Chalmers|author3=David Chalmers|chapter=Preface|isbn=978-0-262-58181-3|publisher=MIT Press|year=1999|pages=xix–xx|author-link=Stuart Hameroff}}] and the [[Society for Consciousness Studies]].
Modern medical and psychological investigations into consciousness are based on psychological experiments (including, for example, the investigation of [[Priming (psychology)|priming]] effects using [[subliminal stimuli]]),[Lucido, R. J. (2023). Testing the consciousness causing collapse interpretation of quantum mechanics using subliminal primes derived from random fluctuations in radioactive decay. Journal of Consciousness Exploration & Research, 14(3), 185-194. https://doi.org/10.13140/RG.2.2.20344.72969] and on [[case studies]] of alterations in consciousness produced by trauma, illness, or drugs. Broadly viewed, scientific approaches are based on two core concepts. The first identifies the content of consciousness with the experiences that are reported by human subjects; the second makes use of the concept of consciousness that has been developed by neurologists and other medical professionals who deal with patients whose behavior is impaired. In either case, the ultimate goals are to develop techniques for assessing consciousness objectively in humans as well as other animals, and to understand the neural and psychological mechanisms that underlie it.[
===Measurement via verbal report===
[[File:Necker cube.svg|thumb|upright|The [[Necker cube]], an ambiguous image]]
Experimental research on consciousness presents special difficulties, due to the lack of a universally accepted [[operational definition]]. In the majority of experiments that are specifically about consciousness, the subjects are human, and the criterion used is verbal report: in other words, subjects are asked to describe their experiences, and their descriptions are treated as observations of the contents of consciousness.][{{cite book|author=Bernard Baars|title=A Cognitive Theory of Consciousness|year=1993|publisher=Cambridge University Press|isbn=978-0-521-42743-2| pages=15–18|author-link=Bernard Baars}}]
For example, subjects who stare continuously at a [[Necker cube]] usually report that they experience it "flipping" between two 3D configurations, even though the stimulus itself remains the same.[{{cite book|title=Perception: Theory, Development, and Organization|author=Paul Rooks|author2=Jane Wilson|year=2000|publisher=Psychology Press|isbn=978-0-415-19094-7|pages=25–26}}] The objective is to understand the relationship between the conscious awareness of stimuli (as indicated by verbal report) and the effects the stimuli have on brain activity and behavior. In several paradigms, such as the technique of [[response priming]], the behavior of subjects is clearly influenced by stimuli for which they report no awareness, and suitable experimental manipulations can lead to increasing priming effects despite decreasing prime identification (double dissociation).[{{cite journal|author=Thomas Schmidt|author2=Dirk Vorberg|title=Criteria for unconscious cognition: Three types of dissociation|journal=Perception and Psychophysics|volume=68|year=2006|pages=489–504|doi=10.3758/bf03193692|pmid=16900839|issue=3|doi-access=free}}]
Verbal report is widely considered to be the most reliable indicator of consciousness, but it raises a number of issues.[{{cite book|chapter=Quining qualia|author=Daniel Dennett|title=Consciousness in Modern Science|editor=A. Marcel|editor2=E. Bisiach|publisher=Oxford University Press|year=1992|chapter-url=http://cogprints.org/254/|access-date=2011-10-31|isbn=978-0-19-852237-9|author-link=Daniel Dennett|archive-date=2011-10-28|archive-url=https://web.archive.org/web/20111028195212/http://cogprints.org/254/|url-status=live}}] Daniel Dennett has argued for an approach he calls [[heterophenomenology]], which means treating verbal reports as stories that may or may not be true, but his ideas about how to do this have not been widely adopted.[{{cite journal|author=Daniel Dennett|year=2003|title=Who's on first? Heterophenomenology explained|journal=Journal of Consciousness Studies|volume=10|pages=19–30|author-link=Daniel Dennett}}] Another issue with verbal report as a criterion is that it restricts the field of study to humans who have language: this approach cannot be used to study consciousness in other species, pre-linguistic children, or people with types of brain damage that impair language. As a third issue, philosophers who dispute the validity of the [[Turing test]] may feel that it is possible, at least in principle, for verbal report to be dissociated from consciousness entirely: a philosophical zombie may give detailed verbal reports of awareness in the absence of any genuine awareness.[{{cite book|author=David Chalmers|title=The Conscious Mind|chapter-url=https://archive.org/details/consciousmindins00chal|chapter-url-access=registration|year=1996|chapter=Ch. 3: Can consciousness be reductively explained?|publisher=Oxford University Press|isbn=978-0-19-511789-9|author-link=David Chalmers}}]
Although verbal report is in practice the "gold standard" for ascribing consciousness, it is not the only possible criterion.[{{cite book|title=The Boundaries of Consciousness: Neurobiology and Neuropathology|chapter=Methods for studying unconscious learning|author=Arnaud Destrebecqz|author2=Philippe Peigneux|editor=Steven Laureys|year=2006|publisher=Elsevier|isbn=978-0-444-52876-6|pages=69–80}}] In medicine, consciousness is assessed as a combination of verbal behavior, arousal, brain activity, and purposeful movement. The last three of these can be used as indicators of consciousness when verbal behavior is absent.[{{cite journal|title=How to Make a Consciousness Meter|date=October 2017|journal=Scientific American|volume=317|issue=5|pages=28–33|doi=10.1038/scientificamerican1117-28|author=Christof Koch|pmid=29565878|bibcode=2017SciAm.317e..28K}}] The [[scientific literature]] regarding the neural bases of arousal and purposeful movement is very extensive. Their reliability as indicators of consciousness is disputed, however, due to numerous studies showing that alert human subjects can be induced to behave purposefully in a variety of ways in spite of reporting a complete lack of awareness.[{{cite journal|title=Human volition: towards a neuroscience of will|author=Patrick Haggard|journal=Nature Reviews Neuroscience|year=2008|volume=9|pages=934–946|pmid=19020512|doi=10.1038/nrn2497|issue=12|s2cid=1495720}}]
==== Mirror test and contingency awareness ====
{{Also see|Mirror test}}
[[File:Mirror Test on Octopus vulgaris.jpg|thumb|[[Mirror test]] subjected on a [[common octopus]]]]
Another approach applies specifically to the study of [[self-awareness]], that is, the ability to distinguish oneself from others. In the 1970s [[Gordon G. Gallup|Gordon Gallup]] developed an operational test for self-awareness, known as the [[mirror test]]. The test examines whether animals are able to differentiate between seeing themselves in a mirror versus seeing other animals. The classic example involves placing a spot of coloring on the skin or fur near the individual's forehead and seeing if they attempt to remove it or at least touch the spot, thus indicating that they recognize that the individual they are seeing in the mirror is themselves.[{{cite journal|author=Gordon Gallup|title=Chimpanzees: Self recognition|journal=Science|volume=167|pages=86–87|year=1970|doi=10.1126/science.167.3914.86|pmid=4982211|issue=3914|bibcode=1970Sci...167...86G|s2cid=145295899|author-link=Gordon G. Gallup}}] Humans (older than 18 months) and other [[Hominidae|great apes]], [[bottlenose dolphin]]s, [[orca]]s, [[Columbidae|pigeons]], [[Eurasian magpie|European magpies]] and [[elephants]] have all been observed to pass this test.[{{cite journal |author=David Edelman |author2=Anil Seth |year=2009 |title=Animal consciousness: a synthetic approach |journal=Trends in Neurosciences |volume=32 |issue=9 |pages=476–484 |doi=10.1016/j.tins.2009.05.008 |pmid=19716185 |s2cid=13323524}}] While some other animals like [[Pig|pigs]] have been shown to find food by looking into the mirror.[{{Cite journal |last1=Broom |first1=Donald M. |last2=Sena |first2=Hilana |last3=Moynihan |first3=Kiera L. |date= 2009|title=Pigs learn what a mirror image represents and use it to obtain information |url=https://linkinghub.elsevier.com/retrieve/pii/S0003347209003571 |journal=Animal Behaviour |language=en |volume=78 |issue=5 |pages=1037–1041 |doi=10.1016/j.anbehav.2009.07.027}}]
Contingency awareness is another such approach, which is basically the conscious understanding of one's actions and its effects on one's environment.[{{Cite web |title=Contingency Awareness - TalkSense |url=https://talksense.weebly.com/contingency-awareness.html#:~:text=Contingency%20Awareness%20(often%20referred%20to,actions%20elicit%20in%20the%20environment. |access-date=8 October 2024 |website=Weebly}}] It is recognized as a factor in self-recognition. The brain processes during contingency awareness and learning is believed to rely on an intact [[medial temporal lobe]] and age. A study done in 2020 involving [[Transcranial direct-current stimulation|transcranial direct current stimulation]], [[Magnetic resonance imaging]] (MRI) and eyeblink classical conditioning supported the idea that the [[Parietal lobe|parietal cortex]] serves as a substrate for contingency awareness and that age-related disruption of this region is sufficient to impair awareness.[{{Cite journal |last1=Cheng |first1=Dominic T. |last2=Katzenelson |first2=Alyssa M. |last3=Faulkner |first3=Monica L. |last4=Disterhoft |first4=John F. |last5=Power |first5=John M. |last6=Desmond |first6=John E. |date=4 March 2020 |title=Contingency awareness, aging, and the parietal lobe |journal=Neurobiology of Aging |language=en |volume=91 |pages=125–135 |doi=10.1016/j.neurobiolaging.2020.02.024 |pmc=7953809 |pmid=32241582}}]
===Neural correlates===
[[File:Neural Correlates Of Consciousness.jpg|thumb|upright=1.6|{{center|Schema of the neural processes underlying consciousness, from [[Christof Koch]]}}]]
A major part of the scientific literature on consciousness consists of studies that examine the relationship between the experiences reported by subjects and the activity that simultaneously takes place in their brains—that is, studies of the [[neural correlates of consciousness]]. The hope is to find that activity in a particular part of the brain, or a particular pattern of global brain activity, which will be strongly predictive of conscious awareness. Several brain imaging techniques, such as [[EEG]] and [[fMRI]], have been used for physical measures of brain activity in these studies.[{{cite book|author=Christof Koch|year=2004|title=The Quest for Consciousness|location=Englewood, CO|publisher=Roberts & Company|isbn=978-0-9747077-0-9|pages=16–19|author-link=Christof Koch}}]
Another idea that has drawn attention for several decades is that consciousness is associated with high-frequency (gamma band) [[neural oscillations|oscillations in brain activity]]. This idea arose from proposals in the 1980s, by Christof von der Malsburg and Wolf Singer, that gamma oscillations could solve the so-called [[binding problem]], by linking information represented in different parts of the brain into a unified experience.[{{cite journal|title=Binding by synchrony|author=Wolf Singer|journal=[[Scholarpedia]]|volume=2|issue=12|pages=1657|doi=10.4249/scholarpedia.1657|year=2007|bibcode=2007SchpJ...2.1657S|doi-access=free|s2cid=34682132}}] [[Rodolfo Llinás]], for example, proposed that consciousness results from [[recurrent thalamo-cortical resonance]] where the specific thalamocortical systems (content) and the non-specific (centromedial thalamus) thalamocortical systems (context) interact in the [[gamma wave|gamma]] band frequency via synchronous oscillations.[{{cite book|author=Rodolfo Llinás|year=2002|title=I of the vortex: from neurons to self|publisher=MIT Press|isbn=978-0-262-62163-2|author-link=Rodolfo Llinás|title-link=I of the vortex: from neurons to self}}]
A number of studies have shown that activity in primary sensory areas of the brain is not sufficient to produce consciousness: it is possible for subjects to report a lack of awareness even when areas such as the [[primary visual cortex|primary visual cortex (V1)]] show clear electrical responses to a stimulus.[Koch, ''The Quest for Consciousness'', pp. 105–116] Higher brain areas are seen as more promising, especially the [[prefrontal cortex]], which is involved in a range of higher cognitive functions collectively known as [[executive functions]].[{{Cite journal|last1=Baldauf|first1=D.|last2=Desimone|first2=R.|date=2014-04-25|title=Neural Mechanisms of Object-Based Attention|journal=Science|language=en|volume=344|issue=6182|pages=424–427|doi=10.1126/science.1247003|pmid=24763592|bibcode=2014Sci...344..424B|s2cid=34728448|issn=0036-8075|doi-access=free}}] There is substantial evidence that a "top-down" flow of neural activity (i.e., activity propagating from the frontal cortex to sensory areas) is more predictive of conscious awareness than a "bottom-up" flow of activity.[{{cite journal|title=A framework for consciousness|author=Francis Crick|author2=Christof Koch|year=2003|journal=Nature Neuroscience|volume=6|pages=119–126|pmid=12555104|url=http://papers.klab.caltech.edu/29/1/438.pdf|doi=10.1038/nn0203-119|issue=2|s2cid=13960489|url-status=dead|archive-url=https://web.archive.org/web/20120522054447/http://papers.klab.caltech.edu/29/1/438.pdf|archive-date=2012-05-22|author2-link=Christof Koch|author-link=Francis Crick}}] The prefrontal cortex is not the only candidate area, however: studies by [[Nikos Logothetis]] and his colleagues have shown, for example, that visually responsive neurons in parts of the [[temporal lobe]] reflect the visual perception in the situation when conflicting visual images are presented to different eyes (i.e., bistable percepts during binocular rivalry).[Koch, ''The Quest for Consciousness'', pp. 269–286] Furthermore, top-down feedback from higher to lower visual brain areas may be weaker or absent in the peripheral visual field, as suggested by some experimental data and theoretical arguments;[{{Cite journal|last=Zhaoping|first=Li|date=2019-10-01|title=A new framework for understanding vision from the perspective of the primary visual cortex|url=https://psyarxiv.com/ds34j/download|journal=Current Opinion in Neurobiology|series=Computational Neuroscience|volume=58|pages=1–10|doi=10.1016/j.conb.2019.06.001|pmid=31271931|s2cid=195806018|issn=0959-4388|access-date=2022-03-02}}] nevertheless humans can perceive visual inputs in the peripheral visual field arising from bottom-up V1 neural activities.[{{Cite journal|last=Zhaoping|first=Li|date=2020-07-30|title=The Flip Tilt Illusion: Visible in Peripheral Vision as Predicted by the Central-Peripheral Dichotomy|journal=i-Perception|volume=11|issue=4|pages=2041669520938408|doi=10.1177/2041669520938408|issn=2041-6695|pmc=7401056|pmid=32782769}}] Meanwhile, bottom-up V1 activities for the central visual fields can be vetoed, and thus made invisible to perception, by the top-down feedback, when these bottom-up signals are inconsistent with the brain's internal model of the visual world.[{{cite journal|author1=Biederlack J.|author2=Castelo-Branco M.|author3=Neuenschwander S.|author4=Wheeler D.W.|author5=Singer W.|author6=Nikolić D.|year = 2006|title = Brightness induction: Rate enhancement and neuronal synchronization as complementary codes|journal = Neuron|volume = 52|issue = 6| pages = 1073–1083|doi=10.1016/j.neuron.2006.11.012|pmid=17178409|s2cid=16732916|doi-access=free}}] An fMRI investigation suggested that these findings were strictly limited to the primary visual areas.[{{cite journal|author1=Williams Adrian L.|author2=Singh Krishna D.|author3=Smith Andrew T.|year = 2003|title = Surround modulation measured with functional MRI in the human visual cortex|journal = Journal of Neurophysiology|volume = 89|issue = 1| pages = 525–533|doi=10.1152/jn.00048.2002|pmid=12522199|citeseerx=10.1.1.137.1066}}] This indicates that, in the primary visual areas, changes in firing rates and synchrony can be considered as neural correlates of qualia—at least for some type of qualia.
In 2013, the perturbational complexity index (PCI) was proposed, a measure of the algorithmic complexity of the electrophysiological response of the cortex to [[transcranial magnetic stimulation]]. This measure was shown to be higher in individuals that are awake, in REM sleep or in a locked-in state than in those who are in deep sleep or in a vegetative state,[{{cite journal|author1=Adenauer G. Casali|author2=Olivia Gosseries|author3=Mario Rosanova|author4=Mélanie Boly|author5=Simone Sarasso|author6=Karina R. Casali|author7=Silvia Casarotto|author8=Marie-Aurélie Bruno|author9=Steven Laureys|author10-link=Giulio Tononi|author10=Giulio Tononi|author11=Marcello Massimini|title=A Theoretically based index of consciousness independent of sensory processing and behavior|journal=Science Translational Medicine|date=14 August 2013|volume=5|number=198|pages=198ra105|doi=10.1126/scitranslmed.3006294|pmid=23946194|hdl=2268/171542|s2cid=8686961|url=http://orbi.ulg.ac.be/jspui/handle/2268/171542|hdl-access=free}}{{Dead link|date=June 2023|bot=InternetArchiveBot|fix-attempted=yes}}] making it potentially useful as a quantitative assessment of consciousness states.
Assuming that not only humans but even some non-mammalian species are conscious, a number of evolutionary approaches to the problem of neural correlates of consciousness open up. For example, assuming that birds are conscious—a common assumption among neuroscientists and ethologists due to the extensive cognitive repertoire of birds—there are comparative neuroanatomical ways to validate some of the principal, currently competing, mammalian consciousness–brain theories. The rationale for such a comparative study is that the avian brain deviates structurally from the mammalian brain. So how similar are they? What homologs can be identified? The general conclusion from the study by Butler, et al.[{{cite journal|author1=Ann B. Butler|author2=Paul R. Manger|author3=B.I.B Lindahl|author4=Peter Århem|year=2005|title=Evolution of the neural basis of consciousness: a bird-mammal comparison|journal=BioEssays|volume=27|issue=9|pages=923–936|doi=10.1002/bies.20280|pmid=16108067}}] is that some of the major theories for the mammalian brain[{{cite journal|author=[[Francis Crick]] and [[Christof Koch]]|year=1995|title=Are we aware of neural activity in primary visual cortex?|journal=Nature|volume=375|pages=121–123|doi=10.1038/375121a0|pmid=7753166|issue=6527| bibcode=1995Natur.375..121C|s2cid=4262990}}][{{cite book| author=[[Gerald Edelman|Gerald M. Edelman]] and [[Giulio Tononi]]|year=2000|title=A Universe of Consciousness: How Matter Becomes Imagination|publisher=Basic Books|isbn=978-0-465-01376-0}}][{{cite journal|author=Rodney M.J. Cotterill|title=Cooperation of the basal ganglia, cerebellum, sensory cerebrum and hippocampus: possible implications for cognition, consciousness, intelligence and creativity|journal=Progress in Neurobiology|year=2001|volume=64|issue=1|pages=1–33|doi=10.1016/s0301-0082(00)00058-7|pmid=11250060|s2cid=206054149}}] also appear to be valid for the avian brain. The structures assumed to be critical for consciousness in mammalian brains have homologous counterparts in avian brains. Thus the main portions of the theories of [[Francis Crick|Crick]] and [[Christof Koch|Koch]],[{{cite journal| year=1982|author=J.C. Eccles|title=Animal consciousness and human self-consciousness|journal=Experientia|volume=38|issue=12|pages=1384–1391|doi=10.1007/bf01955747|pmid=7151952|s2cid=35174442|author-link=John Eccles (neurophysiologist)}}][{{cite journal| year=1990|author=John Eccles|title=A unitary hypothesis of mind-brain interaction in the cerebral cortex|journal=Proceedings of the Royal Society of London B|volume=240|issue=1299|pages=433–451|doi=10.1098/rspb.1990.0047|pmid=2165613|bibcode=1990RSPSB.240..433E|s2cid=23188208|author-link=John Eccles (neurophysiologist)}}] seems incompatible, since a structural homolog/analogue to the dendron has not been found in avian brains. The assumption of an avian consciousness also brings the reptilian brain into focus. The reason is the structural continuity between avian and reptilian brains, meaning that the phylogenetic origin of consciousness may be earlier than suggested by many leading neuroscientists.
[[Joaquin Fuster]] of UCLA has advocated the position of the importance of the prefrontal cortex in humans, along with the areas of Wernicke and Broca, as being of particular importance to the development of human language capacities neuro-anatomically necessary for the emergence of higher-order consciousness in humans.[Joaquin Fuster, ''The Prefrontal Cortex'', Second Edition.]
A study in 2016 looked at lesions in specific areas of the brainstem that were associated with [[coma]] and vegetative states. A small region of the rostral dorsolateral [[pontine tegmentum]] in the brainstem was suggested to drive consciousness through functional connectivity with two cortical regions, the left ventral [[anterior insular cortex]], and the pregenual [[anterior cingulate cortex]]. These three regions may work together as a triad to maintain consciousness.[{{Cite journal|last1=Fischer|first1=David B.|last2=Boes|first2=Aaron D.|last3=Demertzi|first3=Athena|last4=Evrard|first4=Henry C.|last5=Laureys|first5=Steven|last6=Edlow|first6=Brian L.|last7=Liu|first7=Hesheng|last8=Saper|first8=Clifford B.|last9=Pascual-Leone|first9=Alvaro|last10=Fox|first10=Michael D.|last11=Geerling|first11=Joel C.|date=2016-12-06|title=A human brain network derived from coma-causing brainstem lesions|journal=Neurology|language=en|volume=87|issue=23|pages=2427–2434|doi=10.1212/WNL.0000000000003404|issn=0028-3878|pmid=27815400|pmc=5177681}}]
===Models===
{{further|Models of consciousness}}
A wide range of empirical theories of consciousness have been proposed.[{{cite journal|last1=Northoff|first1=Georg|last2=Lamme|first2=Victor|title=Neural signs and mechanisms of consciousness: Is there a potential convergence of theories of consciousness in sight?|journal=Neuroscience and Biobehavioral Reviews|date=2020|volume=118|pages=568–587|doi=10.1016/j.neubiorev.2020.07.019|pmid=32783969|s2cid=221084519}}][{{cite journal|last1=Seth|first1=Anil K.|last2=Bayne|first2=Tim|title=Theories of consciousness|journal=Nature Reviews Neuroscience|date=2022|volume=23|issue=7|pages=439–452|doi=10.1038/s41583-022-00587-4|pmid=35505255|s2cid=242810797|url=http://sro.sussex.ac.uk/id/eprint/105030/1/SethBayne_NRN_accepted.pdf|access-date=2023-01-17|archive-date=2023-01-21|archive-url=https://web.archive.org/web/20230121221104/http://sro.sussex.ac.uk/id/eprint/105030/1/SethBayne_NRN_accepted.pdf|url-status=live}}][{{cite journal|last1=Doerig|first1=Adrian|last2=Schurger|first2=Aaron|last3=Herzog|first3=Michael H.|title=Hard criteria for empirical theories of consciousness|journal=Cognitive Neuroscience|date=2021|volume=12|issue=2|pages=41–62|doi=10.1080/17588928.2020.1772214|pmid=32663056|s2cid=220529998|doi-access=free|hdl=2066/228876|hdl-access=free}}] Adrian Doerig and colleagues list 13 notable theories,[{{cite book |last1=Baars |first1=Bernard J. |title=The Boundaries of Consciousness: Neurobiology and Neuropathology |year=2005 |isbn=9780444518514 |series=Progress in Brain Research |volume=150 |pages=45–53 |chapter=Global workspace theory of consciousness: Toward a cognitive neuroscience of human experience |citeseerx=10.1.1.456.2829 |doi=10.1016/S0079-6123(05)50004-9 |pmid=16186014}}][{{cite journal|last1=Dehaene|first1=Stanislas|last2=Naccache|first2=Lionel|title=Towards a cognitive neuroscience of consciousness: basic evidence and a workspace framework|journal=Cognition|date=2001|volume=79|issue=1–2|pages=1–37|url=http://zoo.cs.yale.edu/classes/cs671/12f/12f-papers/dehaene-consciousness.pdf|access-date=5 April 2019|doi=10.1016/S0010-0277(00)00123-2|pmid=11164022|s2cid=1762431|archive-date=13 July 2019|archive-url=https://web.archive.org/web/20190713125127/http://zoo.cs.yale.edu/classes/cs671/12f/12f-papers/dehaene-consciousness.pdf|url-status=live}}]
==== Integrated information theory ====
[[Integrated information theory]] (IIT), pioneered by neuroscientist [[Giulio Tononi]] in 2004, postulates that consciousness resides in the information being processed and arises once the information reaches a certain level of complexity. Additionally, IIT is one of the only leading theories of consciousness that attempts to create a 1:1 mapping between conscious states and precise, formal mathematical descriptions of those mental states. Proponents of this model suggest that it may provide a physical grounding for consciousness in neurons, as they provide the mechanism by which information is integrated. This also relates to the "[[hard problem of consciousness]]" proposed by [[David Chalmers]]. The theory remains controversial, because of its lack of credibility.{{clarify|date=October 2024}}[{{Cite journal |last1=Tononi |first1=Giulio |last2=Boly |first2=Melanie |last3=Massimini |first3=Marcello |last4=Koch |first4=Christof |date=July 2016 |title=Integrated information theory: from consciousness to its physical substrate |url=https://www.nature.com/articles/nrn.2016.44 |url-status=live |journal=Nature Reviews Neuroscience |language=en |volume=17 |issue=7 |pages=450–461 |doi=10.1038/nrn.2016.44 |issn=1471-0048 |pmid=27225071 |s2cid=21347087 |url-access=subscription |archive-url=https://web.archive.org/web/20230504082713/https://www.nature.com/articles/nrn.2016.44 |archive-date=2023-05-04 |access-date=2023-05-21}}][{{Cite journal |last=Lenharo |first=Mariana |date=2023-09-20 |title=Consciousness theory slammed as 'pseudoscience' — sparking uproar |url=https://www.nature.com/articles/d41586-023-02971-1 |journal=Nature |language=en |doi=10.1038/d41586-023-02971-1|pmid=37730789}}][{{cite journal|author1=Graziano, M.S.A.|author2=Kastner, S|year=2011|title=Human consciousness and its relationship to social neuroscience: A novel hypothesis|journal=Cog. Neurosci|volume=2|issue=2|pages=98–113|doi=10.1080/17588928.2011.565121|pmid=22121395|pmc=3223025}}] proposed the [[attention schema theory|"attention schema" theory of awareness]]. In that theory, specific cortical areas, notably in the superior temporal sulcus and the temporo-parietal junction, are used to build the construct of awareness and attribute it to other people. The same cortical machinery is also used to attribute awareness to oneself. Damage to these cortical regions can lead to deficits in consciousness such as [[hemispatial neglect]]. In the [[attention]] schema theory, the value of explaining the feature of awareness and attributing it to a person is to gain a useful predictive model of that person's attentional processing. [[Attention]] is a style of [[Information processing (psychology)|information processing]] in which a brain focuses its resources on a limited set of interrelated signals. Awareness, in this theory, is a useful, simplified schema that represents attentional states. To be aware of X is explained by constructing a model of one's attentional focus on X.
==== Entropic brain theory ====
The entropic brain is a theory of conscious states informed by neuroimaging research with [[psychedelic drugs]]. The theory suggests that the brain in primary states such as [[Rapid eye movement sleep|rapid eye movement]] (REM) sleep, early [[psychosis]] and under the influence of psychedelic drugs, is in a disordered state; normal waking consciousness constrains some of this freedom and makes possible [[metacognitive]] functions such as internal self-administered [[reality testing]] and [[self-awareness]].[{{cite journal|last1=Carhart-Harris|first1=R. L.|author1-link=Robin Carhart-Harris|last2=Friston|first2=K. J.|last3=Barker|first3=Eric L.|title=REBUS and the Anarchic Brain: Toward a Unified Model of the Brain Action of Psychedelics|journal=Pharmacological Reviews|date=20 June 2019|volume=71|issue=3|pages=316–344|doi=10.1124/pr.118.017160|pmid=31221820|pmc=6588209}}][{{cite journal|last1=Carhart-Harris|first1=Robin L.|title=The entropic brain – revisited|journal=Neuropharmacology|date=November 2018|volume=142|pages=167–178|doi=10.1016/j.neuropharm.2018.03.010|pmid=29548884|s2cid=4483591}}][{{cite journal|last1=Carhart-Harris|first1=Robin L.|last2=Leech|first2=Robert|last3=Hellyer|first3=Peter J.|last4=Shanahan|first4=Murray|last5=Feilding|first5=Amanda|last6=Tagliazucchi|first6=Enzo|last7=Chialvo|first7=Dante R.|last8=Nutt|first8=David|title=The entropic brain: a theory of conscious states informed by neuroimaging research with psychedelic drugs|journal=Frontiers in Human Neuroscience|date=2014|volume=8|pages=20|doi=10.3389/fnhum.2014.00020|pmid=24550805|pmc=3909994|doi-access=free}}][{{Cite web|url = https://mind-foundation.org/entropy-as-more-than-chaos/|title = Entropy as More than Chaos in the Brain: Expanding Field, Expanding Minds|date = 2018-06-22|access-date = 2019-07-05|archive-date = 2019-07-05|archive-url = https://web.archive.org/web/20190705111205/https://mind-foundation.org/entropy-as-more-than-chaos/|url-status = live}}] Criticism has included questioning whether the theory has been adequately tested.[{{cite journal|last1=Papo|first1=David|title=Commentary: The entropic brain: a theory of conscious states informed by neuroimaging research with psychedelic drugs|journal=Frontiers in Human Neuroscience|date=30 August 2016|volume=10|pages=423|doi=10.3389/fnhum.2016.00423|pmid=27624312|pmc=5004455|doi-access=free}}]
==== Projective consciousness model ====
In 2017, work by David Rudrauf and colleagues, including [[Karl Friston]], applied the [[active inference]] paradigm to consciousness, leading to the projective consciousness model (PCM), a model of how sensory data is integrated with priors in a process of projective transformation. The authors argue that, while their model identifies a key relationship between computation and phenomenology, it does not completely solve [[the hard problem of consciousness]] or completely close the [[explanatory gap]].[{{cite journal|author1=David Rudrauf|author2=Daniel Bennequin|author3=Isabela Granic|author4=Gregory Landini|author5=Karl Friston|author6=[[Kenneth Williford]]|year = 2017|title = A Mathematical Model of Embodied Consciousness|journal = Journal of Theoretical Biology|volume = 428|issue = 1| pages = 106–131|doi=10.1016/j.jtbi.2017.05.032|pmid=28554611|bibcode=2017JThBi.428..106R|s2cid=4476538|url=https://discovery.ucl.ac.uk/id/eprint/10057795/|hdl=2066/175365|hdl-access=free}}]
==== Claustrum being the conductor for consciousness ====
In 2004, a proposal was made by molecular biologist [[Francis Crick]] (co-discoverer of the double helix), which stated that to bind together an individual's experience, a conductor of an orchestra is required. Together with neuroscientist [[Christof Koch]], he proposed that this conductor would have to collate information rapidly from various regions of the brain. The duo reckoned that the [[claustrum]] was well suited for the task. However, Crick died while working on the idea.[{{Cite journal |last1=Koubeissi |first1=Mohamad Z. |last2=Bartolomei |first2=Fabrice |last3=Beltagy |first3=Abdelrahman |last4=Picard |first4=Fabienne |date= 2014|title=Electrical stimulation of a small brain area reversibly disrupts consciousness|url=https://linkinghub.elsevier.com/retrieve/pii/S1525505014002017 |journal=[[Epilepsy & Behavior]] |language=en |volume=37 |pages=32–35 |doi=10.1016/j.yebeh.2014.05.027|pmid=24967698}}]
===Biological function and evolution===
The emergence of consciousness during [[Evolution|biological evolution]] remains a topic of ongoing scientific inquiry. The survival value of consciousness is still a matter of exploration and understanding. While consciousness appears to play a crucial role in human cognition, decision-making, and self-awareness, its adaptive significance across different species remains a subject of debate.
Some people question whether consciousness has any survival value. Some argue that consciousness is a [[Spandrel (biology)|by-product of evolution]]. [[Thomas Henry Huxley]] for example defends in an essay titled "On the Hypothesis that Animals are [[Automata]], and its History" an [[epiphenomenalist]] theory of consciousness, according to which consciousness is a causally inert effect of neural activity—"as the steam-whistle which accompanies the work of a locomotive engine is without influence upon its machinery".[{{cite journal|author=T.H. Huxley|title=On the hypothesis that animals are automata, and its history|journal=The Fortnightly Review|volume=16|issue=253|pages=555–580|year=1874|author-link=T.H. Huxley|bibcode=1874Natur..10..362.|doi=10.1038/010362a0|doi-access=free}}] To this [[William James]] objects in his essay ''Are We Automata?'' by stating an evolutionary argument for mind-brain interaction implying that if the preservation and development of consciousness in the biological evolution is a result of [[natural selection]], it is plausible that consciousness has not only been influenced by neural processes, but has had a survival value itself; and it could only have had this if it had been efficacious.[{{cite journal|author=W. James|title=Are we automata?|journal=Mind|volume=4|issue=13|pages=1–22|year=1879|doi=10.1093/mind/os-4.13.1|author-link=William James|url=https://zenodo.org/record/1431809|access-date=2019-07-05|archive-date=2019-12-24|archive-url=https://web.archive.org/web/20191224150924/https://zenodo.org/record/1431809|url-status=live}}][{{cite journal|author=B.I.B. Lindahl|title=Consciousness and biological evolution|journal=Journal of Theoretical Biology|volume=187|issue=4|pages=613–629|year=1997|doi=10.1006/jtbi.1996.0394|pmid=9299304|bibcode=1997JThBi.187..613L}}] [[Karl Popper]] develops a similar evolutionary argument in the book ''The Self and Its Brain''.[{{cite book|title=The Self and Its Brain|author=[[Karl Popper|Karl R. Popper]], [[John Eccles (neurophysiologist)|John C. Eccles]]|publisher=Springer International|year=1977|isbn=978-0-387-08307-0|url-access=registration|url=https://archive.org/details/selfitsbrain0000popp}}]
Opinions are divided on when and how consciousness first arose. It has been argued that consciousness emerged (i) exclusively with the first humans, (ii) exclusively with the first mammals, (iii) independently in mammals and birds, or (iv) with the first reptiles.[{{cite book|author=Peter Århem|author2=B.I.B. Lindahl|author3=Paul R. Manger|author4=Ann B. Butler|year=2008|editor=Hans Liljenström|editor2=Peter Århem|chapter=On the origin of consciousness—some amniote scenarios|title=Consciousness Transitions: Phylogenetic, Ontogenetic, and Physiological Aspects|publisher=Elsevier.|chapter-url=https://books.google.com/books?id=OQGJz1DVQNMC&pg=PA77|isbn=978-0-444-52977-0}}] Other authors date the origins of consciousness to the first animals with nervous systems or early vertebrates in the Cambrian over 500 million years ago.[{{cite journal|last1=Feinberg|first1=TE|last2=Mallatt|first2=J|date=October 2013|title=The evolutionary and genetic origins of consciousness in the Cambrian Period over 500 million years ago.|journal=Frontiers in Psychology|doi=10.3389/fpsyg.2013.00667|pmid=24109460|volume=4|pages=667|pmc=3790330|doi-access=free}}] [[Donald Griffin]] suggests in his book ''Animal Minds'' a gradual evolution of consciousness.[{{Cite book |title=Metazoa |last=Godfrey Smith |first=Peter |year=2021 |isbn=9780008321239}}]
Regarding the primary function of conscious processing, a recurring idea in recent theories is that phenomenal states somehow integrate neural activities and information-processing that would otherwise be independent.[{{cite journal|author=Bernard Baars|title=The conscious access hypothesis: Origins and recent evidence|journal=Trends in Cognitive Sciences|volume=6|pages=47–52|pmid=11849615|doi=10.1016/S1364-6613(00)01819-2|issue=1|date=January 2002|s2cid=6386902|author-link=Bernard Baars}}] This has been called the ''integration consensus''. Another example has been proposed by Gerald Edelman called dynamic core hypothesis which puts emphasis on [[reentry (neural circuitry)|reentrant]] connections that reciprocally link areas of the brain in a massively parallel manner.[{{cite journal|last=Seth|first=Anil|author2=Eugene Izhikevich|author3=George Reeke|author4=Gerald Edelman|title=Theories and measures of consciousness: An extended framework|journal=Proceedings of the National Academy of Sciences|year=2006|volume=103|issue=28|doi=10.1073/pnas.0604347103|pages=10799–10804|pmid=16818879|pmc=1487169|bibcode=2006PNAS..10310799S|doi-access=free}}] Edelman also stresses the importance of the evolutionary emergence of higher-order consciousness in humans from the historically older trait of primary consciousness which humans share with non-human animals (see ''[[#Neural correlates|Neural correlates]]'' section above). These theories of integrative function present solutions to two classic problems associated with consciousness: differentiation and unity. They show how our conscious experience can discriminate between a virtually unlimited number of different possible scenes and details (differentiation) because it integrates those details from our sensory systems, while the integrative nature of consciousness in this view easily explains how our experience can seem unified as one whole despite all of these individual parts. However, it remains unspecified which kinds of information are integrated in a conscious manner and which kinds can be integrated without consciousness. Nor is it explained what specific causal role conscious integration plays, nor why the same functionality cannot be achieved without consciousness. Not all kinds of information are capable of being disseminated consciously (e.g., neural activity related to vegetative functions, reflexes, unconscious motor programs, low-level perceptual analyzes, etc.), and many kinds of information can be disseminated and combined with other kinds without consciousness, as in intersensory interactions such as the [[ventriloquism effect]].[{{cite journal|author=Ezequiel Morsella|year=2005|title=The function of phenomenal states: Supramodular Interaction Theory|journal=Psychological Review|volume=112|pages=1000–1021|pmid=16262477|issue=4|doi=10.1037/0033-295X.112.4.1000|s2cid=2298524|url=http://pdfs.semanticscholar.org/fdd7/81a15d0405a888abe4584a99ed9cbc6fb3ff.pdf|archive-url=https://web.archive.org/web/20201118022838/http://pdfs.semanticscholar.org/fdd7/81a15d0405a888abe4584a99ed9cbc6fb3ff.pdf|url-status=dead|archive-date=2020-11-18}}] Hence it remains unclear why any of it is conscious. For a review of the differences between conscious and unconscious integrations, see the article of Ezequiel Morsella.[{{cite book|author=S. Budiansky|title=If a Lion Could Talk: Animal Intelligence and the Evolution of Consciousness|year=1998|publisher=The Free Press|isbn=978-0-684-83710-9|url=https://archive.org/details/iflioncouldtalka00budi}}] Edelman has described this distinction as that of humans possessing higher-order consciousness while sharing the trait of primary consciousness with non-human animals (see previous paragraph). Thus, any examination of the evolution of consciousness is faced with great difficulties. Nevertheless, some writers have argued that consciousness can be viewed from the standpoint of [[evolutionary biology]] as an [[adaptation]] in the sense of a [[Phenotypic trait|trait]] that increases [[Fitness (biology)|fitness]].[{{cite journal|author=S. Nichols|author2=T. Grantham|title=Adaptive Complexity and Phenomenal Consciousness|year=2000|journal=Philosophy of Science|volume=67|issue=4|pages=648–670|doi=10.1086/392859|url=http://dingo.sbs.arizona.edu/~snichols/Papers/evolcons(final).pdf|citeseerx=10.1.1.515.9722|s2cid=16484193|access-date=2017-10-25|archive-url=https://web.archive.org/web/20170813055023/http://dingo.sbs.arizona.edu/~snichols/Papers/evolcons(final).pdf|archive-date=2017-08-13|url-status=dead}}] In his article "Evolution of consciousness", John Eccles argued that special anatomical and physical properties of the mammalian [[cerebral cortex]] gave rise to consciousness ("[a] psychon ... linked to [a] dendron through quantum physics").[{{cite journal|author=John Eccles|title=Evolution of consciousness|journal=Proc. Natl. Acad. Sci. USA|volume=89|issue=16|pages=7320–7324|year=1992|pmid=1502142|pmc=49701|doi=10.1073/pnas.89.16.7320|bibcode=1992PNAS...89.7320E|author-link=John Eccles (neurophysiologist)|doi-access=free}}] Bernard Baars proposed that once in place, this "recursive" circuitry may have provided a basis for the subsequent development of many of the functions that consciousness facilitates in higher organisms.[{{cite book|author=Bernard Baars|title=A Cognitive Theory of Consciousness|year=1993|publisher=Cambridge University Press|isbn=978-0-521-42743-2|author-link=Bernard Baars}}] [[Peter Carruthers (philosopher)|Peter Carruthers]] has put forth one such potential adaptive advantage gained by conscious creatures by suggesting that consciousness allows an individual to make distinctions between appearance and reality.[{{cite book|last=Carruthers|first=Peter|title=Phenomenal Consciousness: A Naturalistic Theory|year=2004|publisher=Cambridge University Press|location=Cambridge}}] This ability would enable a creature to recognize the likelihood that their perceptions are deceiving them (e.g. that water in the distance may be a mirage) and behave accordingly, and it could also facilitate the manipulation of others by recognizing how things appear to them for both cooperative and devious ends.
Other philosophers, however, have suggested that consciousness would not be necessary for any functional advantage in evolutionary processes.[{{cite journal|author=Owen Flanagan|author2=T.W. Polger|year=1995|title=Zombies and the function of consciousness|journal=Journal of Consciousness Studies|volume=2|pages=313–321|author-link=Owen Flanagan}}][{{cite journal|last=Rosenthal|first=David|title=Consciousness and its function|journal=Neuropsychologia|year=2008|volume=46|issue=3|pages=829–840|doi=10.1016/j.neuropsychologia.2007.11.012|pmid=18164042|s2cid=7791431}}] No one has given a causal explanation, they argue, of why it would not be possible for a functionally equivalent non-conscious organism (i.e., a philosophical zombie) to achieve the very same survival advantages as a conscious organism. If evolutionary processes are blind to the difference between function ''F'' being performed by conscious organism ''O'' and non-conscious organism ''O*'', it is unclear what adaptive advantage consciousness could provide.[{{cite book|author=Stevan Harnad|year=2002|chapter=Turing indistinguishability and the Blind Watchmaker|editor=J.H. Fetzer|title=Consciousness Evolving|publisher=John Benjamins|chapter-url=http://cogprints.org/1615|access-date=2011-10-26|author-link=Stevan Harnad|archive-date=2011-10-28|archive-url=https://web.archive.org/web/20111028162407/http://cogprints.org/1615/|url-status=live}}] As a result, an exaptive explanation of consciousness has gained favor with some theorists that posit consciousness did not evolve as an adaptation but was an [[exaptation]] arising as a consequence of other developments such as increases in brain size or cortical rearrangement.[{{cite journal|author1=Zack Robinson|author2=Corey J. Maley|author3=Gualtiero Piccinini| year = 2015|title = Is Consciousness a Spandrel?.|journal = Journal of the American Philosophical Association|volume = 1|issue = 2| pages = 365–383|doi = 10.1017/apa.2014.10|s2cid=170892645}}] Several scholars including [[Steven Pinker|Pinker]], [[Noam Chomsky|Chomsky]], [[Gerald Edelman|Edelman]], and [[Salvador Luria|Luria]] have indicated the importance of the emergence of human language as an important regulative mechanism of learning and memory in the context of the development of higher-order consciousness (see ''[[#Neural correlates|Neural correlates]]'' section above).
===Altered states===
{{Main|Altered state of consciousness}}
[[File:Abbot of Watkungtaphao in Phu Soidao Waterfall.jpg|thumb|upright|A Buddhist monk [[Meditation|meditating]]]]
There are some brain states in which consciousness seems to be absent, including dreamless sleep or coma. There are also a variety of circumstances that can change the relationship between the mind and the world in less drastic ways, producing what are known as altered states of consciousness. Some altered states occur naturally; others can be produced by drugs or brain damage.[{{cite journal|last=Vaitl|first=Dieter|s2cid=6909813|title=Psychobiology of altered states of consciousness|year=2005|journal=Psychological Bulletin|volume=131|pages=98–127|doi=10.1037/0033-2909.131.1.98|pmid=15631555|issue=1|url=https://pdfs.semanticscholar.org/09d8/95b85d772fb505144969310255c0cbdc74a7.pdf|archive-url=https://web.archive.org/web/20201022093127/https://pdfs.semanticscholar.org/09d8/95b85d772fb505144969310255c0cbdc74a7.pdf|url-status=dead|archive-date=2020-10-22}}] Altered states can be accompanied by changes in thinking, disturbances in the sense of time, feelings of loss of control, changes in emotional expression, alternations in body image and changes in meaning or significance.[{{cite book|last1=Schacter|first1=Daniel|last2=Gilbert|first2=Daniel|last3=Wegner|first3=Daniel|year=2011|title=Psychology 2nd Ed.|url=https://archive.org/details/psychology0000scha/page/190|location=New York|publisher=Worth Publishers|page=[https://archive.org/details/psychology0000scha/page/190 190]|isbn=978-1-4292-3719-2|access-date=27 October 2020}}]
The two most widely accepted altered states are [[sleep]] and [[dream]]ing. Although dream sleep and non-dream sleep appear very similar to an outside observer, each is associated with a distinct pattern of brain activity, metabolic activity, and eye movement; each is also associated with a distinct pattern of experience and cognition. During ordinary non-dream sleep, people who are awakened report only vague and sketchy thoughts, and their experiences do not cohere into a continuous narrative. During dream sleep, in contrast, people who are awakened report rich and detailed experiences in which events form a continuous progression, which may however be interrupted by bizarre or fantastic intrusions.[{{cite journal|last=Coenen|first=Anton|title=Subconscious Stimulus Recognition and Processing During Sleep|url=http://journalpsyche.org/files/0xbb10.pdf|year=2010|journal=Psyche: An Interdisciplinary Journal of Research on Consciousness|volume=16-2|url-status=live|archive-url=https://web.archive.org/web/20170611115233/http://journalpsyche.org/files/0xbb10.pdf|archive-date=2017-06-11}}]{{Failed verification|date=August 2021|reason=This source talks about responses to auditory stimuli during sleep, but not about dreams or the difference between dream and non-dream sleep.}} Thought processes during the dream state frequently show a high level of irrationality. Both dream and non-dream states are associated with severe disruption of memory: it usually disappears in seconds during the non-dream state, and in minutes after awakening from a dream unless actively refreshed.[{{cite book|last1= Hobson|first1=J. Allan|author-link1=Allan Hobson|last2=Pace-Schott|first2=Edward F.|last3=Stickgold|first3=Robert|author-link3=Robert Stickgold|year=2003|title=Sleep and Dreaming: Scientific Advances and Reconsiderations|editor1-last=Pace-Schott|editor1-first=Edward F.|editor2-last=Solms|editor2-first=Mark|editor3-last=Blagrove|editor3-first=Mark|editor4-last=Harnad|editor4-first=Stevan|publisher=Cambridge University Press|chapter=Dreaming and the brain: Toward a cognitive neuroscience of conscious states|isbn=978-0-521-00869-3|chapter-url=https://www.researchgate.net/publication/2599957|archive-url=https://web.archive.org/web/20210810234114/https://www.researchgate.net/profile/Edward-Pace-Schott/publication/2599957_Dreaming_and_the_Brain_Toward_a_Cognitive_Neuroscience_of_Conscious_States/links/02e7e52f240372e115000000/Dreaming-and-the-Brain-Toward-a-Cognitive-Neuroscience-of-Conscious-States.pdf|archive-date=2021-08-10|url-status=live}}]
Research conducted on the effects of partial epileptic seizures on consciousness found that patients who have partial epileptic seizures experience altered states of consciousness.[{{cite journal|author1=Johanson M.|author2=Valli K.|author3=Revonsuo A.|author4=Wedlund J.|year=2008|title=Content analysis of subjective experiences in partial epileptic seizures|journal=Epilepsy & Behavior|volume=12|issue=1|pages=170–182|doi=10.1016/j.yebeh.2007.10.002|pmid=18086461|s2cid =28276470}}][{{cite journal|author1=Johanson M.|author2=Valli K.|author3=Revonsuo A.|display-authors=etal|year=2008|title=Alterations in the contents of consciousness in partial epileptic seizures|journal=Epilepsy & Behavior|volume=13|issue=2| pages=366–371|doi=10.1016/j.yebeh.2008.04.014|pmid=18522873|s2cid=24473529}}] In partial epileptic seizures, consciousness is impaired or lost while some aspects of consciousness, often automated behaviors, remain intact. Studies found that when measuring the qualitative features during partial epileptic seizures, patients exhibited an increase in arousal and became absorbed in the experience of the seizure, followed by difficulty in focusing and shifting attention.
A variety of [[psychoactive drug]]s, including [[Ethanol|alcohol]], have notable effects on consciousness.[{{Cite book|date=31 July 1994|title=Diagnostic and statistical manual of mental disorders: DSM-IV|url=https://books.google.com/books?id=W-BGAAAAMAAJ|edition=DSM-IV-TR|location=Washington, DC|publisher=American Psychiatric Association|isbn=978-0-89042-025-6}}] These range from a simple dulling of awareness produced by [[sedative]]s, to increases in the intensity of sensory qualities produced by [[stimulant]]s, [[cannabis (drug)|cannabis]], [[empathogen-entactogen|empathogens–entactogens]] such as [[MDMA]] ("Ecstasy"), or most notably by the class of drugs known as [[psychedelic drug|psychedelics]].[ [[Lysergic acid diethylamide|LSD]], [[mescaline]], [[psilocybin]], [[N,N-Dimethyltryptamine|dimethyltryptamine]], and others in this group can produce major distortions of perception, including hallucinations; some users even describe their drug-induced experiences as mystical or spiritual in quality. The brain mechanisms underlying these effects are not as well understood as those induced by use of alcohol,][{{cite web|url=http://epublications.bond.edu.au/hss_pubs/10|title=The neurochemistry of psychedelic experiences|last=Lyvers|first=Michael|year=2003|publisher=ePublications@bond|format=PDF|access-date=2011-10-26|archive-date=2012-04-20|archive-url=https://web.archive.org/web/20120420042607/http://epublications.bond.edu.au/hss_pubs/10/|url-status=live}}]
There has been some research into physiological changes in yogis and people who practise various techniques of [[meditation]]. Some research with brain waves during meditation has reported differences between those corresponding to ordinary relaxation and those corresponding to meditation. It has been disputed, however, whether there is enough evidence to count these as physiologically distinct states of consciousness.[{{cite book|author1=M. Murphy|author2=S. Donovan|author3=E. Taylor|year=1997|title=The Physical and Psychological Effects of Meditation: A Review of Contemporary Research With a Comprehensive Bibliography, 1931–1996|publisher=Institute of Noetic Sciences}}]
The most extensive study of the characteristics of altered states of consciousness was made by psychologist [[Charles Tart]] in the 1960s and 1970s. Tart analyzed a state of consciousness as made up of a number of component processes, including exteroception (sensing the external world); [[interoception]] (sensing the body); input-processing (seeing meaning); emotions; memory; time sense; sense of identity; evaluation and cognitive processing; motor output; and interaction with the environment.[{{cite book|last=Tart|first=Charles|author-link=Charles Tart|year=2001|title=States of Consciousness|publisher=IUniverse.com|chapter=Ch. 2: The components of consciousness|chapter-url=http://www.psychedelic-library.org/soc2.htm|isbn=978-0-595-15196-7|access-date=5 October 2011|archive-date=6 November 2011|archive-url=https://web.archive.org/web/20111106032020/http://www.psychedelic-library.org/soc2.htm|url-status=live}}]{{self-published source|date=January 2023}} Each of these, in his view, could be altered in multiple ways by drugs or other manipulations. The components that Tart identified have not, however, been validated by empirical studies. Research in this area has not yet reached firm conclusions, but a recent questionnaire-based study identified eleven significant factors contributing to drug-induced states of consciousness: experience of unity; spiritual experience; blissful state; insightfulness; disembodiment; impaired control and cognition; anxiety; complex imagery; elementary imagery; audio-visual [[synesthesia]]; and changed meaning of percepts.[{{cite journal|last1=Studerus|first1=Erich|last2=Gamma|first2=Alex|last3=Vollenweider|first3=Franz X.|year=2010|editor-last=Bell|editor-first=Vaughan|title=Psychometric evaluation of the altered states of consciousness rating scale (OAV)|journal=[[PLOS One]]|volume=5|issue=8|pages=e12412|bibcode=2010PLoSO...512412S|doi=10.1371/journal.pone.0012412|pmc=2930851|pmid=20824211|doi-access=free}}]
==Medical aspects==
The medical approach to consciousness is scientifically oriented. It derives from a need to treat people whose brain function has been impaired as a result of disease, brain damage, toxins, or drugs. In medicine, conceptual distinctions are considered useful to the degree that they can help to guide treatments. The medical approach focuses mostly on the amount of consciousness a person has: in medicine, consciousness is assessed as a "level" ranging from coma and brain death at the low end, to full alertness and purposeful responsiveness at the high end.[{{cite book|title=The Neurology of Consciousness: Cognitive Neuroscience and Neuropathology|editor=Steven Laureys|editor2=Giulio Tononi|chapter=The neurological examination of consciousness|author=Hal Blumenfeld|year=2009|publisher=Academic Press|isbn=978-0-12-374168-4}}]
Consciousness is of concern to patients and physicians, especially [[neurology|neurologists]] and [[anesthesia|anesthesiologists]]. Patients may have disorders of consciousness or may need to be anesthetized for a surgical procedure. Physicians may perform consciousness-related interventions such as instructing the patient to sleep, administering [[general anesthesia]], or inducing [[induced coma|medical coma]].[ Also, [[bioethics|bioethicists]] may be concerned with the ethical implications of consciousness in medical cases of patients such as the [[Karen Ann Quinlan case]],][{{cite journal|vauthors=Kinney HC, Korein J, Panigrahy A, Dikkes P, Goode R|date=26 May 1994|issue=21|journal=N Engl J Med|pages=1469–1475|pmid=8164698|title=Neuropathological findings in the brain of Karen Ann Quinlan – the role of the thalamus in the persistent vegetative state|volume=330|doi=10.1056/NEJM199405263302101|s2cid=5112573|url=http://pdfs.semanticscholar.org/44a2/3798f5dc002a79512bfa9bff974bdbb611e1.pdf|archive-url=https://web.archive.org/web/20201118022837/http://pdfs.semanticscholar.org/44a2/3798f5dc002a79512bfa9bff974bdbb611e1.pdf|url-status=dead|archive-date=18 November 2020}}] while neuroscientists may study patients with impaired consciousness in hopes of gaining information about how the brain works.[Koch, ''The Quest for Consciousness'', pp. 216–226]
===Assessment===
In medicine, consciousness is examined using a set of procedures known as [[neuropsychological assessment]].[{{cite journal|author1=J.T. Giacino|author2=C.M. Smart|year=2007|doi=10.1097/WCO.0b013e3282f189ef|journal=Current Opinion in Neurology|pages=614–619|pmid=17992078|title=Recent advances in behavioral assessment of individuals with disorders of consciousness|volume=20|issue=6|s2cid=7097163}}] There are two commonly used methods for assessing the level of consciousness of a patient: a simple procedure that requires minimal training, and a more complex procedure that requires substantial expertise. The simple procedure begins by asking whether the patient is able to move and react to physical stimuli. If so, the next question is whether the patient can respond in a meaningful way to questions and commands. If so, the patient is asked for name, current location, and current day and time. A patient who can answer all of these questions is said to be "alert and oriented times four" (sometimes denoted "A&Ox4" on a medical chart), and is usually considered fully conscious.[{{cite book|title=Essentials of Abnormal Psychology|url=https://archive.org/details/isbn_9780495806134|url-access=registration|author=V. Mark Durand|author2=David H. Barlow|publisher=Cengage Learning|year=2009|isbn=978-0-495-59982-1|pages=[https://archive.org/details/isbn_9780495806134/page/74 74–75]}} Note: A patient who can additionally describe the current situation may be referred to as "oriented times four".]
The more complex procedure is known as a [[neurological examination]], and is usually carried out by a [[neurology|neurologist]] in a hospital setting. A formal neurological examination runs through a precisely delineated series of tests, beginning with tests for basic sensorimotor reflexes, and culminating with tests for sophisticated use of language. The outcome may be summarized using the [[Glasgow Coma Scale]], which yields a number in the range 3–15, with a score of 3 to 8 indicating coma, and 15 indicating full consciousness. The Glasgow Coma Scale has three subscales, measuring the best motor response (ranging from "no motor response" to "obeys commands"), the best eye response (ranging from "no eye opening" to "eyes opening spontaneously") and the best verbal response (ranging from "no verbal response" to "fully oriented"). There is also a simpler [[Paediatric Glasgow Coma Scale|pediatric]] version of the scale, for children too young to be able to use language.[
In 2013, an experimental procedure was developed to measure degrees of consciousness, the procedure involving stimulating the brain with a magnetic pulse, measuring resulting waves of electrical activity, and developing a consciousness score based on the complexity of the brain activity.][{{cite web|url=https://www.nbcnews.com/healthmain/new-tool-peeks-brain-measure-consciousness-6c10919906|title=New tool peeks into brain to measure consciousness|last=Neergaard|first=Lauren|date=August 14, 2013|publisher=Associated Press through NBC News|archive-url=https://web.archive.org/web/20130816144320/https://www.nbcnews.com/health/new-tool-peeks-brain-measure-consciousness-6C10919906|archive-date=August 16, 2013|access-date=March 2, 2022}}]
===Disorders===
Medical conditions that inhibit consciousness are considered [[disorders of consciousness]].[{{cite journal|author=Bernat JL|date=8 Apr 2006|doi=10.1016/S0140-6736(06)68508-5|issue=9517|journal=Lancet|pages=1181–1192|pmid=16616561|title=Chronic disorders of consciousness|volume=367|s2cid=13550675}}
][{{cite journal|author=Bernat JL|date=20 Jul 2010|doi=10.1212/WNL.0b013e3181e8e960|issue=3|journal=Neurology|pages=206–207|pmid=20554939|title=The natural history of chronic disorders of consciousness|volume=75|s2cid=30959964}}] [[Differential diagnosis]] of these disorders is an active area of [[biomedical research]].[{{cite journal|vauthors=Coleman MR, Davis MH, Rodd JM, Robson T, Ali A, Owen AM, Pickard JD|date=September 2009|doi=10.1093/brain/awp183|issue=9|journal=Brain|pages=2541–2552|pmid=19710182|title=Towards the routine use of brain imaging to aid the clinical diagnosis of disorders of consciousness|volume=132|doi-access=free}}][{{cite journal|vauthors=Monti MM, Vanhaudenhuyse A, Coleman MR, Boly M, Pickard JD, Tshibanda L, Owen AM, Laureys S|s2cid=13358991|date=18 Feb 2010|doi=10.1056/NEJMoa0905370|issue=7|journal=N Engl J Med|pages=579–589|pmid=20130250|title=Willful modulation of brain activity in disorders of consciousness|volume=362|url=http://pdfs.semanticscholar.org/560f/d2dd08c0532dcf5c61668690dd88d19d7114.pdf|archive-url=https://web.archive.org/web/20190224091809/http://pdfs.semanticscholar.org/560f/d2dd08c0532dcf5c61668690dd88d19d7114.pdf|url-status=dead|archive-date=24 February 2019}}][{{cite journal|vauthors=Seel RT, Sherer M, Whyte J, Katz DI, Giacino JT, Rosenbaum AM, Hammond FM, Kalmar K, Pape TL|date=December 2010|doi=10.1016/j.apmr.2010.07.218|issue=12|journal=Arch Phys Med Rehabil|pages=1795–1813|pmid=21112421|title=Assessment scales for disorders of consciousness: evidence-based recommendations for clinical practice and research|volume=91|display-authors=etal}}] Finally, [[brain death]] results in possible irreversible disruption of consciousness.[{{cite journal|last1=Prigatano|first1=George P.|title=Anosognosia: clinical and ethical considerations|journal=Current Opinion in Neurology|date=2009|volume=22|issue=6|pages=606–611|doi=10.1097/WCO.0b013e328332a1e7|pmid=19809315|s2cid=40751848}}] ''Anosognosia'' is a Greek-derived term meaning "unawareness of disease". This is a condition in which patients are disabled in some way, most commonly as a result of a [[stroke]], but either misunderstand the nature of the problem or deny that there is anything wrong with them.[{{cite book|editor=George Prigatano|editor2=[[Daniel Schacter]]|title=Awareness of Deficit After Brain Injury: Clinical and Theoretical Issues|publisher=Oxford University Press|year=1991|chapter=Introduction|author=George P. Prigatano|author2=Daniel Schacter|pages=3–16|isbn=978-0-19-505941-0|author2-link=Daniel Schacter}}] The most frequently occurring form is seen in people who have experienced a stroke damaging the [[parietal lobe]] in the right hemisphere of the brain, giving rise to a syndrome known as [[hemispatial neglect]], characterized by an inability to direct action or attention toward objects located to the left with respect to their bodies. Patients with hemispatial neglect are often paralyzed on the left side of the body, but sometimes deny being unable to move. When questioned about the obvious problem, the patient may avoid giving a direct answer, or may give an explanation that does not make sense. Patients with hemispatial neglect may also fail to recognize paralyzed parts of their bodies: one frequently mentioned case is of a man who repeatedly tried to throw his own paralyzed right leg out of the bed he was lying in, and when asked what he was doing, complained that somebody had put a dead leg into the bed with him. An even more striking type of anosognosia is [[Anton–Babinski syndrome]], a rarely occurring condition in which patients become blind but claim to be able to see normally, and persist in this claim in spite of all evidence to the contrary.[{{cite book|editor=George Prigatano|editor2=[[Daniel Schacter]]|title=Awareness of Deficit After Brain Injury: Clinical and Theoretical Issues|publisher=Oxford University Press|year=1991|chapter=Anosognosia: possible neuropsychological mechanisms|author=Kenneth M. Heilman|pages=53–62|isbn=978-0-19-505941-0}}]
==Outside human adults==
===In children===
{{See also|Theory of mind}}
Of the eight types of consciousness in the Lycan classification, some are detectable in utero and others develop years after birth. Psychologist and educator William Foulkes studied children's dreams and concluded that prior to the shift in cognitive maturation that humans experience during ages five to seven,[{{cite book|editor1=[[Arnold J. Sameroff]]|editor2=Marshall M. Haith|date=1996|title=The Five to Seven Year Shift: The Age of Reason and Responsibility|location=Chicago|publisher=University of Chicago Press}}] children lack the Lockean consciousness that Lycan had labeled "introspective consciousness" and that Foulkes labels "self-reflection".[{{cite book|last=Foulkes|first=David|date=1999|title=Children's Dreaming and the Development of Consciousness|page=13|location=Cambridge, Massachusetts|publisher=Harvard University Press|quote= In defining 'consciousness' as a self-reflective act, psychology loses much of the glamour and mystery of other areas of consciousness-study, but it also can proceed on a workaday basis without becoming paralyzed in pure abstraction.}}] In a 2020 paper, [[Katherine Nelson]] and [[Robyn Fivush]] use "autobiographical consciousness" to label essentially the same faculty, and agree with Foulkes on the timing of this faculty's acquisition. Nelson and Fivush contend that "language is the tool by which humans create a new, uniquely human form of consciousness, namely, autobiographical consciousness".[{{cite journal|last1=Nelson|first1=Katherine|last2=Fivush|first2=Robin|title=The Development of Autobiographical Memory, Autobiographical Narratives, and Autobiographical Consciousness|journal=Psychological Reports|year=2020|volume=123|issue=1|page=74|doi=10.1177/0033294119852574|pmid=31142189|s2cid=169038149|doi-access=free}}] [[Julian Jaynes]] had staked out these positions decades earlier.[{{cite book|last=Jaynes|first=Julian|title=The Origin of Consciousness in the Breakdown of the Bicameral Mind|publisher=Houghton Mifflin|orig-year=1976| year=2000|page=447|quote=''Consciousness is based on language''.... Consciousness is not the same as cognition and should be sharply distinguished from it.|isbn=0-618-05707-2}}][{{cite book|last=Jaynes|first=Julian|title=The Origin of Consciousness in the Breakdown of the Bicameral Mind|publisher=Houghton Mifflin|orig-year=1976| year=2000|page=450|quote=The basic connotative definition of consciousness is thus an analog 'I' narratizing in a functional mind-space. The denotative definition is, as it was for Descartes, Locke, and Hume, what is introspectable.|isbn=0-618-05707-2}}] Citing the developmental steps that lead the infant to autobiographical consciousness, Nelson and Fivush point to the acquisition of "[[theory of mind]]", calling theory of mind "necessary for autobiographical consciousness" and defining it as "understanding differences between one's own mind and others' minds in terms of beliefs, desires, emotions and thoughts". They write, "The hallmark of theory of mind, the understanding of false belief, occurs ... at five to six years of age".[{{cite journal|last1=Nelson|first1=Katherine|last2=Fivush|first2=Robin|title=The Development of Autobiographical Memory, Autobiographical Narratives, and Autobiographical Consciousness|journal=Psychological Reports|year=2020|volume=123|issue=1|pages=80–83|doi=10.1177/0033294119852574|pmid=31142189|s2cid=169038149|doi-access=free}}]
===In animals===
{{Main|Animal consciousness}}
The topic of animal consciousness is beset by a number of difficulties. It poses the problem of other minds in an especially severe form, because non-human animals, lacking the ability to express human language, cannot tell humans about their experiences.[{{cite web|author=Colin Allen|title=Animal consciousness|publisher=Stanford Encyclopedia of Philosophy (Summer 2011 Edition)|editor=Edward N. Zalta|url=http://plato.stanford.edu/archives/sum2011/entries/consciousness-animal/|access-date=2011-10-25|archive-date=2019-07-31|archive-url=https://web.archive.org/web/20190731010951/https://plato.stanford.edu/archives/sum2011/entries/consciousness-animal/|url-status=live}}] Also, it is difficult to reason objectively about the question, because a denial that an animal is conscious is often taken to imply that it does not feel, its life has no value, and that harming it is not morally wrong. Descartes, for example, has sometimes been blamed for mistreatment of animals due to the fact that he believed only humans have a non-physical mind.[{{cite journal|author=Peter Carruthers|title=Sympathy and subjectivity|journal=Australasian Journal of Philosophy|year=1999|volume=77|issue=4|pages=465–482|doi=10.1080/00048409912349231|author-link=Peter Carruthers (philosopher)}}] Most people have a strong intuition that some animals, such as cats and dogs, are conscious, while others, such as insects, are not; but the sources of this intuition are not obvious, and are often based on personal interactions with pets and other animals they have observed.[
[[File:Big-eared-townsend-fledermaus.jpg|right|thumb|[[Thomas Nagel]] argues that while a human might be able to imagine what it is like to be a [[bat]] by taking "the bat's point of view", it would still be impossible "to know what it is like for a [[bat]] to be a bat". (''[[Townsend's big-eared bat]] pictured''.)]]
Philosophers who consider subjective experience the essence of consciousness also generally believe, as a correlate, that the existence and nature of animal consciousness can never rigorously be known. Thomas Nagel spelled out this point of view in an influential essay titled "[[What Is it Like to Be a Bat?]]". He said that an organism is conscious "if and only if there is something that it is like to be that organism—something it is like ''for'' the organism"; and he argued that no matter how much we know about an animal's brain and behavior, we can never really put ourselves into the mind of the animal and experience its world in the way it does itself.][{{cite book| author=Thomas Nagel|title=Mortal Questions|chapter=Ch. 12 What is it like to be a bat?|publisher=Cambridge University Press|year=1991|isbn=978-0-521-40676-5|author-link=Thomas Nagel}}] Other thinkers, such as [[Douglas Hofstadter]], dismiss this argument as incoherent.[{{cite book|author=Douglas Hofstadter|chapter=Reflections on ''What Is It Like to Be a Bat?''|pages=[https://archive.org/details/mindsifantasiesr00hofs/page/403 403–414]|title=The Mind's I|editor=Douglas Hofstadter|editor2=[[Daniel Dennett]]|publisher=Basic Books|year=1981|isbn=978-0-7108-0352-8|title-link=The Mind's I|author-link=Douglas Hofstadter}}] Several psychologists and ethologists have argued for the existence of animal consciousness by describing a range of behaviors that appear to show animals holding beliefs about things they cannot directly perceive—[[Donald Griffin]]'s 2001 book ''Animal Minds'' reviews a substantial portion of the evidence.[{{cite book|title=Animal Minds: Beyond Cognition to Consciousness|author=Donald Griffin|publisher=University of Chicago Press|year=2001|isbn=978-0-226-30865-4|author-link=Donald Griffin}}]
On July 7, 2012, eminent scientists from different branches of neuroscience gathered at the [[University of Cambridge]] to celebrate the Francis Crick Memorial Conference, which deals with consciousness in humans and pre-linguistic consciousness in nonhuman animals. After the conference, they signed in the presence of [[Stephen Hawking]], the 'Cambridge Declaration on Consciousness', which summarizes the most important findings of the survey:
"We decided to reach a consensus and make a statement directed to the public that is not scientific. It's obvious to everyone in this room that animals have consciousness, but it is not obvious to the rest of the world. It is not obvious to the rest of the Western world or the Far East. It is not obvious to the society."[{{cite AV media|url=https://www.youtube.com/watch?v=RSbom5MsfNM| archive-url=https://ghostarchive.org/varchive/youtube/20211028/RSbom5MsfNM| archive-date=2021-10-28|title=Animal Consciousness Officially Recognized by Leading Panel of Neuroscientists|date=3 September 2012|via=YouTube}}{{cbignore}}]
"Convergent evidence indicates that non-human animals ..., including all mammals and birds, and other creatures, ... have the necessary neural substrates of consciousness and the capacity to exhibit intentional behaviors."[{{cite web|url=http://fcmconference.org/img/CambridgeDeclarationOnConsciousness.pdf|archive-url=https://ghostarchive.org/archive/20221009/http://fcmconference.org/img/CambridgeDeclarationOnConsciousness.pdf|archive-date=2022-10-09|url-status=live|title=Cambridge Declaration on Consciousness}}]
===In artificial intelligence===
{{Main|Artificial consciousness}}
The idea of an [[wikt:artifact|artifact]] made conscious is an ancient theme of mythology, appearing for example in the Greek myth of [[Pygmalion (mythology)|Pygmalion]], who carved a statue that was magically brought to life, and in medieval Jewish stories of the [[Golem]], a magically animated [[homunculus]] built of clay.[{{cite book|author=Moshe Idel|title=Golem: Jewish Magical and Mystical Traditions on the Artificial Anthropoid|year=1990|publisher=SUNY Press|isbn=978-0-7914-0160-6}} Note: In many stories the Golem was mindless, but some gave it emotions or thoughts.] However, the possibility of actually constructing a conscious machine was probably first discussed by [[Ada Lovelace]], in a set of notes written in 1842 about the [[Analytical Engine]] invented by [[Charles Babbage]], a precursor (never built) to modern electronic computers. Lovelace was essentially dismissive of the idea that a machine such as the Analytical Engine could think in a humanlike way. She wrote:
{{blockquote|It is desirable to guard against the possibility of exaggerated ideas that might arise as to the powers of the Analytical Engine. ... The Analytical Engine has no pretensions whatever to ''originate'' anything. It can do whatever we ''know how to order it'' to perform. It can ''follow'' analysis; but it has no power of ''anticipating'' any analytical relations or truths. Its province is to assist us in making ''available'' what we are already acquainted with.[{{cite web|author=Ada Lovelace|title=Sketch of The Analytical Engine, Note G|url=http://www.fourmilab.ch/babbage/sketch.html|author-link=Ada Lovelace|access-date=2011-09-10|archive-date=2010-09-13|archive-url=https://web.archive.org/web/20100913042032/http://www.fourmilab.ch/babbage/sketch.html|url-status=live}}]}}
One of the most influential contributions to this question was an essay written in 1950 by pioneering computer scientist [[Alan Turing]], titled ''[[Computing Machinery and Intelligence]]''. Turing disavowed any interest in terminology, saying that even "Can machines think?" is too loaded with spurious connotations to be meaningful; but he proposed to replace all such questions with a specific operational test, which has become known as the [[Turing test]].[{{cite book|author=Stuart Shieber|title=The Turing Test : Verbal Behavior as the Hallmark of Intelligence|publisher=MIT Press|year=2004|isbn=978-0-262-69293-9}}] To pass the test, a computer must be able to imitate a human well enough to fool interrogators. In his essay Turing discussed a variety of possible objections, and presented a counterargument to each of them. The Turing test is commonly cited in discussions of [[artificial intelligence]] as a proposed criterion for machine consciousness; it has provoked a great deal of philosophical debate. For example, Daniel Dennett and [[Douglas Hofstadter]] argue that anything capable of passing the Turing test is necessarily conscious,[{{cite book|author=Daniel Dennett|author2=Douglas Hofstadter|year=1985|title=The Mind's I|publisher=Basic Books|isbn=978-0-553-34584-1|author2-link=Douglas Hofstadter|author-link=Daniel Dennett|url=https://archive.org/details/mindsifantasiesr1982hofs}}] while [[David Chalmers]] argues that a [[philosophical zombie]] could pass the test, yet fail to be conscious.[{{cite book|author=David Chalmers|year=1997|title=The Conscious Mind: In Search of a Fundamental Theory|publisher=Oxford University Press|isbn=978-0-19-511789-9|author-link=David Chalmers}}] A third group of scholars have argued that with technological growth once machines begin to display any substantial signs of human-like behavior then the dichotomy (of human consciousness compared to human-like consciousness) becomes passé and issues of machine autonomy begin to prevail even as observed in its nascent form within contemporary industry and [[technology]].[{{cite book|author=Jürgen Schmidhuber|year=2009|title=Driven by Compression Progress: A Simple Principle Explains Essential Aspects of Subjective Beauty, Novelty, Surprise, Interestingness, Attention, Curiosity, Creativity, Art, Science, Music, Jokes|url=https://archive.org/details/arxiv-0812.4360|author-link=Jürgen Schmidhuber|bibcode=2008arXiv0812.4360S|arxiv=0812.4360}}] As an agent sees representation of itself recurring in the environment, the compression of this representation can be called consciousness.
[[File:John searle2.jpg|thumb|upright|John Searle in December 2005]]
In a lively exchange over what has come to be referred to as "the [[Chinese room]] argument", [[John Searle]] sought to refute the claim of proponents of what he calls "strong artificial intelligence (AI)" that a computer program can be conscious, though he does agree with advocates of "weak AI" that computer programs can be formatted to "simulate" conscious states. His own view is that consciousness has subjective, first-person causal powers by being essentially intentional due to the way human brains function biologically; conscious persons can perform computations, but consciousness is not inherently computational the way computer programs are. To make a Turing machine that speaks Chinese, Searle imagines a room with one monolingual English speaker (Searle himself, in fact), a book that designates a combination of Chinese symbols to be output paired with Chinese symbol input, and boxes filled with Chinese symbols. In this case, the English speaker is acting as a computer and the rulebook as a program. Searle argues that with such a machine, he would be able to process the inputs to outputs perfectly without having any understanding of Chinese, nor having any idea what the questions and answers could possibly mean. If the experiment were done in English, since Searle knows English, he would be able to take questions and give answers without any algorithms for English questions, and he would be effectively aware of what was being said and the purposes it might serve. Searle would pass the Turing test of answering the questions in both languages, but he is only conscious of what he is doing when he speaks English. Another way of putting the argument is to say that computer programs can pass the Turing test for processing the syntax of a language, but that the syntax cannot lead to semantic meaning in the way strong AI advocates hoped.[{{cite journal|author=John R. Searle|title=Is the brain's mind a computer program|journal=Scientific American|year=1990|volume= 262|issue=1|pages=26–31|url=http://www.cs.princeton.edu/courses/archive/spr06/cos116/Is_The_Brains_Mind_A_Computer_Program.pdf|archive-url=https://ghostarchive.org/archive/20221009/http://www.cs.princeton.edu/courses/archive/spr06/cos116/Is_The_Brains_Mind_A_Computer_Program.pdf|archive-date=2022-10-09|url-status=live|doi=10.1038/scientificamerican0190-26|pmid=2294583|bibcode=1990SciAm.262a..26S|author-link=John R. Searle}}][{{cite book| title=The Chinese Room Argument| url=http://plato.stanford.edu/entries/chinese-room| publisher=Metaphysics Research Lab, Stanford University| year=2019| access-date=2012-02-20| archive-date=2012-01-12| archive-url=https://web.archive.org/web/20120112034000/http://plato.stanford.edu/entries/chinese-room/| url-status=live}}]
In the literature concerning artificial intelligence, Searle's essay has been second only to Turing's in the volume of debate it has generated.[{{cite journal|author=John Searle|title=Minds, brains, and programs|journal=Behavioral and Brain Sciences|year=1980|volume=3|issue=3|pages=417–457|doi=10.1017/S0140525X00005756|display-authors=etal|citeseerx=10.1.1.83.5248|s2cid=55303721|author-link=John Searle}}] Searle himself was vague about what extra ingredients it would take to make a machine conscious: all he proposed was that what was needed was "causal powers" of the sort that the brain has and that computers lack. But other thinkers sympathetic to his basic argument have suggested that the necessary (though perhaps still not sufficient) extra conditions may include the ability to pass not just the verbal version of the Turing test, but the [[Robotics|robotic]] version,[{{cite web|author1=Graham Oppy|author2=David Dowe|year=2011|title=The Turing test|url=http://plato.stanford.edu/archives/spr2011/entries/turing-test|publisher=Stanford Encyclopedia of Philosophy (Spring 2011 Edition)|access-date=2011-10-26|archive-date=2013-12-02|archive-url=https://web.archive.org/web/20131202073948/http://plato.stanford.edu/archives/spr2011/entries/turing-test/|url-status=live}}] which requires [[Symbol grounding|grounding]] the robot's words in the robot's sensorimotor capacity to [[categorize]] and interact with the things in the world that its words are about, Turing-indistinguishably from a real person. Turing-scale robotics is an empirical branch of research on [[embodied cognition]] and [[situated cognition]].[{{cite journal|author=Margaret Wilson|title=Six views of embodied cognition|journal=Psychonomic Bulletin & Review|volume=9|issue=4|year=2002|pages=625–636|doi=10.3758/BF03196322|pmid=12613670|doi-access=free}}]
In 2014, Victor Argonov has suggested a non-Turing test for machine consciousness based on a machine's ability to produce philosophical judgments.[{{cite journal|author=Victor Argonov|title=Experimental Methods for Unraveling the Mind-body Problem: The Phenomenal Judgment Approach|journal=Journal of Mind and Behavior|volume=35|year=2014|pages=51–70|url=http://philpapers.org/rec/ARGMAA-2|access-date=2016-12-06|archive-date=2016-10-20|archive-url=https://web.archive.org/web/20161020014221/http://philpapers.org/rec/ARGMAA-2|url-status=live}}] He argues that a deterministic machine must be regarded as conscious if it is able to produce judgments on all problematic properties of consciousness (such as qualia or binding) having no innate (preloaded) philosophical knowledge on these issues, no philosophical discussions while learning, and no informational models of other creatures in its memory (such models may implicitly or explicitly contain knowledge about these creatures' consciousness). However, this test can be used only to detect, but not refute the existence of consciousness. A positive result proves that a machine is conscious but a negative result proves nothing. For example, absence of philosophical judgments may be caused by lack of the machine's intellect, not by absence of consciousness.
==Stream of consciousness==
{{Main|Stream of consciousness (psychology)}}
[[William James]] is usually credited with popularizing the idea that human consciousness flows like a stream, in his ''Principles of Psychology'' of 1890.
According to James, the "stream of thought" is governed by five characteristics:[{{cite book|author=William James|title=The Principles of Psychology, Volume 1|year=1890|publisher=H. Holt|page=225|author-link=William James}}]
# ''Every thought tends to be part of a personal consciousness.''
# ''Within each personal consciousness thought is always changing.''
# ''Within each personal consciousness thought is sensibly continuous.''
# ''It always appears to deal with objects independent of itself.''
# ''It is interested in some parts of these objects to the exclusion of others.''
A similar concept appears in Buddhist philosophy, expressed by the Sanskrit term ''Citta-saṃtāna'', which is usually translated as [[mindstream]] or "mental continuum". Buddhist teachings describe that consciousness manifests moment to moment as sense impressions and mental phenomena that are continuously changing.[{{cite journal|author= Karunamuni N.D.|title=The Five-Aggregate Model of the Mind|journal=SAGE Open|volume=5|issue=2|pages=215824401558386|date=May 2015|doi=10.1177/2158244015583860|doi-access=free}}] The teachings list six triggers that can result in the generation of different mental events.[{{cite book|title=Losing the Clouds, Gaining the Sky: Buddhism and the Natural Mind|chapter=Taming the mindstream|author=Dzogchen Rinpoche|editor=Doris Wolter|year=2007|publisher=Wisdom Publications|isbn=978-0-86171-359-2|pages=[https://archive.org/details/losingcloudsgain0000unse/page/81 81–92]|chapter-url=https://archive.org/details/losingcloudsgain0000unse/page/81}}]
===Narrative form===
In the West, the primary impact of the idea has been on literature rather than science: "[[stream of consciousness (narrative mode)|stream of consciousness as a narrative mode]]" means writing in a way that attempts to portray the moment-to-moment thoughts and experiences of a character. This technique perhaps had its beginnings in the monologues of Shakespeare's plays and reached its fullest development in the novels of [[James Joyce]] and [[Virginia Woolf]], although it has also been used by many other noted writers.[{{cite book|author=Robert Humphrey|title=Stream of Consciousness in the Modern Novel|date=1992 |orig-date=1954|publisher=University of California Press|isbn=978-0-520-00585-3|pages=23–49}}]
Here, for example, is a passage from Joyce's ''[[Ulysses (novel)|Ulysses]]'' about the thoughts of Molly Bloom:
{{blockquote|Yes because he never did a thing like that before as ask to get his breakfast in bed with a couple of eggs since the City Arms hotel when he used to be pretending to be laid up with a sick voice doing his highness to make himself interesting for that old faggot Mrs Riordan that he thought he had a great leg of and she never left us a farthing all for masses for herself and her soul greatest miser ever was actually afraid to lay out 4d for her methylated spirit telling me all her ailments she had too much old chat in her about politics and earthquakes and the end of the world let us have a bit of fun first God help the world if all the women were her sort down on bathingsuits and lownecks of course nobody wanted her to wear them I suppose she was pious because no man would look at her twice I hope Ill never be like her a wonder she didnt want us to cover our faces but she was a well-educated woman certainly and her gabby talk about Mr Riordan here and Mr Riordan there I suppose he was glad to get shut of her.[{{cite book|author=James Joyce|title=Ulysses|year=1990|publisher=BompaCrazy.com|page=620|author-link=James Joyce}}]}}
==Spiritual approaches==
{{Further|Higher consciousness}}
The [[Upanishads]] hold the oldest recorded map of consciousness, as explored by sages through meditation.[{{Cite book |last=Thompson |first=Evan |url=https://books.google.com/books?id=q_vpBAAAQBAJ |title=Waking, Dreaming, Being: Self and Consciousness in Neuroscience, Meditation, and Philosophy |date=2014-11-18 |publisher=Columbia University Press |isbn=978-0-231-53831-2 |pages=19 |language=en}}]
The Canadian psychiatrist [[Richard Maurice Bucke]], author of the 1901 book ''[[Cosmic Consciousness|Cosmic Consciousness: A Study in the Evolution of the Human Mind]]'', distinguished between three types of consciousness: 'Simple Consciousness', awareness of the body, possessed by many animals; 'Self Consciousness', awareness of being aware, possessed only by humans; and 'Cosmic Consciousness', awareness of the life and order of the universe, possessed only by humans who have attained "intellectual enlightenment or illumination".[{{cite book|author=Richard Maurice Bucke|title=Cosmic Consciousness: A Study in the Evolution of the Human Mind|publisher=Innes & Sons|year=1905|url=https://archive.org/details/cosmicconsciousn01buck|pages=[https://archive.org/details/cosmicconsciousn01buck/page/n19 1]–2|author-link=Richard Maurice Bucke}}]
Another thorough account of the spiritual approach is [[Ken Wilber]]'s 1977 book ''The Spectrum of Consciousness'', a comparison of western and eastern ways of thinking about the mind. Wilber described consciousness as a spectrum with ordinary awareness at one end, and more profound types of awareness at higher levels.[{{cite book|author=Ken Wilber|title=The Spectrum of Consciousness|publisher=Motilal Banarsidass|year=2002|isbn=978-81-208-1848-4|pages=3–16|author-link=Ken Wilber}}]
Other examples include the various levels of spiritual consciousness presented by [[Prem Saran Satsangi]] and [[Stuart Hameroff]].[{{cite book|editor1-link=Prem Saran Satsangi|editor1-last=Satsangi|editor1-first=Prem Saran|editor2-link=Stuart Hameroff|editor2-last=Hameroff|editor2-first=Stuart|year=2016|title=Consciousness: Integrating Eastern and Western Perspectives|publisher=New Age Books|isbn=978-81-7822-493-0}}]
==See also==
{{Cols|colwidth=26em}}
* {{annotated link|Animal consciousness}}
* {{annotated link|Bicameral mentality}}
* {{annotated link|Chaitanya (consciousness)|Chaitanya}}
* {{annotated link|Claustrum}}
* {{annotated link|Habenula}}
* {{annotated link|Models of consciousness}}
* {{annotated link|Plant perception (paranormal)|Plant perception}}
* {{annotated link|Sakshi (witness)|Sakshi}}
* {{annotated link|Vertiginous question}}
{{Colend}}
==Notes==
{{Notelist|30em}}
==References==
{{Reflist}}
==Further reading==
{{Div col|colwidth=30em}}
* {{cite book|last1=Dehaene|first1=Stanislas|author1-link=Stanislas Dehaene|title=Consciousness and the Brain: Deciphering How the Brain Codes Our Thoughts|date=2014|publisher=Viking Press|isbn=978-0-670-02543-5|ref=none}}
* {{cite book|last1=Frankish|first1=Keith|author1-link=Keith Frankish|title=Consciousness: The Basics|date=2021|publisher=Routledge|isbn=978-1-138-65598-0|ref=none}}
* {{cite book|last=Harley|first=Trevor|title=The Science of Consciousness: Waking, Sleeping, and Dreaming|year=2021|publisher=Cambridge University Press|doi=10.1017/9781316408889|isbn=978-1-107-56330-8|s2cid=233977060|ref=none}}
* {{cite book|last1=Irvine|first1=Elizabeth|title=Consciousness as a Scientific Concept: A Philosophy of Science Perspective|date=2013|publisher=Springer|location=Dordrecht, Netherlands|isbn=978-94-007-5172-9|doi=10.1007/978-94-007-5173-6|ref=none}}
* {{cite book|last=Koch|first=Christof|author-link=Christof Koch|title= The Feeling of Life Itself: Why Consciousness Is Widespread but Can't Be Computed|year=2019|publisher=MIT Press|isbn=978-0-262-04281-9|ref=none}}
* {{cite book|editor1-last=Overgaard|editor1-first=Morten|editor2-last=Mogensen|editor2-first=Jesper|editor2-link=Jesper Mogensen|editor3-last=Kirkeby-Hinrup|editor3-first=Asger|title=Beyond Neural Correlates of Consciousness|date=2021|publisher=Routledge|isbn=978-1-138-63798-6|ref=none}}
* {{cite book|last1=Prinz|first1=Jesse|author1-link=Jesse Prinz|title=The Conscious Brain: How Attention Engenders Experience|date=2012|publisher=Oxford University Press|isbn=9780195314595|doi=10.1093/acprof:oso/9780195314595.001.0001|ref=none}}
* {{cite book|editor1-last=Schneider|editor1-first=Susan|editor2-last=Velmans|editor2-first=Max|editor1-link=Susan Schneider|editor2-link=Max Velmans|title=The Blackwell Companion to Consciousness|date=2017|publisher=Wiley-Blackwell|isbn=978-0-470-67406-2|edition=2nd|ref=none}}
* {{cite book|last1=Seth|first1=Anil|author1-link=Anil Seth|title=Being You: A New Science of Consciousness|date=2021|publisher=Penguin Random House|isbn=978-1-5247-4287-4|ref=none}}
* {{cite book|last1=Thompson|first1=Evan|author1-link=Evan Thompson|title=Waking, Dreaming, Being: Self and Consciousness in Neuroscience, Meditation, and Philosophy|date=2014|publisher=Columbia University Press|isbn=978-0-231-13695-2|ref=none}}
* {{cite book|editor1-last=Zelazo|editor1-first=Philip David|editor1-link=Philip David Zelazo|editor2-last=Moscovitch|editor2-first=Morris|editor2-link=Morris Moscovitch|editor3-last=Thompson|editor3-first=Evan|editor3-link=Evan Thompson|title=The Cambridge Handbook of Consciousness|year=2007|publisher=Cambridge University Press|isbn=978-0-521-67412-6|doi=10.1017/CBO9780511816789|ref=none}}
{{Div col end}}
===Articles===
*Lewis, Ralph. ''[https://www.psychologytoday.com/intl/blog/finding-purpose/202308/an-overview-of-the-leading-theories-of-consciousness An Overview of the Leading Theories of Consciousness].Organizing and comparing the major candidate theories in the field.'' Psychology Today, November 25, 2023.
==External links==
{{Spoken Wikipedia|En-Consciousness-article.ogg|date=2023-07-30}}
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* {{Wikibooks inline|Consciousness Studies}}
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* {{Wiktionary-inline|Consciousness}}
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{{Mental processes}}
{{Spirituality-related topics}}
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[[Category:Theory of mind]]
{{short description|Ability to attribute mental states to oneself and others}}
{{cs1 config|name-list-style=vanc|display-authors=6}}
{{Distinguish|Philosophy of mind}}
{{use dmy dates|date=April 2023}}
In [[psychology]] and [[philosophy]], '''theory of mind''' (often abbreviated to ToM) refers to the capacity to understand other individuals by ascribing [[mental state]]s to them. A theory of mind includes the understanding that others' [[beliefs]], [[desires]], [[intentions]], [[emotions]], and [[thoughts]] may be different from one's own.[{{cite journal |doi=10.1037/a0016923 |title=Do humans have two systems to track beliefs and belief-like states?|year=2009|last1=Apperly|first1=Ian A.|last2=Butterfill|first2=Stephen A.|journal=Psychological Review |volume=116|issue=4|pages=953–970|pmid=19839692}}] Possessing a functional theory of mind is crucial for success in everyday human [[social interaction]]s. People utilize a theory of mind when [[analyzing]], [[Value judgment|judging]], and [[inferring]] other people's behaviors.
Theory of mind was first conceptualized by researchers evaluating the presence of [[theory of mind in animals]].[{{Cite journal |last1=Premack |first1=David |last2=Woodruff |first2=Guy |date=December 1978 |title=Does the chimpanzee have a theory of mind? |url=https://www.cambridge.org/core/product/identifier/S0140525X00076512/type/journal_article |journal=Behavioral and Brain Sciences |language=en |volume=1 |issue=4 |pages=515–526 |doi=10.1017/S0140525X00076512 |issn=0140-525X}}][{{Cite journal |last=Towner |first=S. |date=2010-03-01 |title=Concept of mind in non-human primates |url=https://academic.oup.com/biohorizons/article-lookup/doi/10.1093/biohorizons/hzq011 |journal=Bioscience Horizons |language=en |volume=3 |issue=1 |pages=96–104 |doi=10.1093/biohorizons/hzq011 |issn=1754-7431|doi-access=free }}] Today, theory of mind research also investigates factors affecting theory of mind in humans, such as whether drug and alcohol consumption, [[language development]], cognitive delays, age, and culture can affect a person's capacity to display theory of mind.
It has been proposed that deficits in theory of mind may occur in people with [[autism]],{{r|r1=See the review and meta-analyses by [[Morton Ann Gernsbacher]] regarding many failed replications of classic theory of mind studies[{{cite journal |last1=Gernsbacher |first1=Morton Ann |last2=Yergeau |first2=Melanie |title=Empirical failures of the claim that autistic people lack a theory of mind |journal=Archives of Scientific Psychology |publisher=American Psychological Association |volume=7 |issue=1 |date=2019-12-09 |issn=2169-3269 |doi=10.1037/arc0000067 |doi-access=free |pages=102–118 |pmid=31938672 |pmc=6959478 }}
Supporting documentation: {{cite journal |url=https://osf.io/3r2qy/ |doi=10.17605/OSF.IO/3R2QY |year=2018 |last1=Gernsbacher |first1=Morton Ann |title=Critical Review of Autism and Theory and Mind: A Tech Report |journal=Open Science Framework}}]}} [[anorexia nervosa]],[{{Cite journal |last1=Bora |first1=Emre |last2=Köse |first2=Sezen |date=2016-07-18 |title=Meta-analysis of theory of mind in anorexia nervosa and bulimia nervosa: A specific İmpairment of cognitive perspective taking in anorexia nervosa? |url=http://dx.doi.org/10.1002/eat.22572 |journal=International Journal of Eating Disorders |volume=49 |issue=8 |pages=739–740 |doi=10.1002/eat.22572 |pmid=27425037 |hdl=11343/291969 |issn=0276-3478|hdl-access=free }}] [[schizophrenia]], [[dysphoria]], [[addiction]],[{{cite journal|title=Theory of Mind Impairments in Women With Cocaine Addiction|first1=Breno|last1=Sanvicente-Vieira|first2=Bruno|last2=Kluwe-Schiavon|first3=Rhiannon|last3=Corcoran|first4=Rodrigo|last4=Grassi-Oliveira|date=1 March 2017|journal=[[Journal of Studies on Alcohol and Drugs]]|publisher=[[Rutgers University]]|location=New Brunswick, New Jersey|volume=78|issue=2|pages=258–267|pmid=28317506|doi=10.15288/jsad.2017.78.258}}] and [[brain damage]] caused by [[alcohol's neurotoxicity]].[{{cite journal |first1=Jennifer|last1=Uekermann|first2=Irene|last2=Daum |title=Social cognition in alcoholism: a link to prefrontal cortex dysfunction? |journal=[[Addiction (journal)|Addiction]] |publisher=[[Wiley-Blackwell]]|location=London, England|volume=103 |issue=5 |pages=726–35 |date=May 2008 |pmid=18412750 |doi=10.1111/j.1360-0443.2008.02157.x }}][{{Unbulleted list citebundle
|1={{Cite journal|date=April 2018|title=Emotion recognition and its relation to prefrontal function and network in heroin plus nicotine dependence: a pilot study |journal=[[Neurophotonics]]|publisher=[[SPIE]]|location=Bellingham, Washington|volume=5 |issue=2|pages=025011|pmid=29901032|pmc=5993953 |last1=Ieong |first1=Hada Fong-ha |last2=Yuan|first2=Zhen |doi=10.1117/1.NPh.5.2.025011}}
|2={{cite journal |last1=Gernsbacher |first1=Morton Ann |last2=Yergeau |first2=Melanie |title=Empirical Failures of the Claim That Autistic People Lack a Theory of Mind |journal=Archives of Scientific Psychology |date=2019 |volume=7 |issue=1 |pages=102–118 |doi=10.1037/arc0000067 |pmid=31938672 |pmc=6959478 |issn=2169-3269}} }}] [[Neuroimaging]] shows that the [[prefrontal cortex|medial prefrontal cortex]] (mPFC), the posterior [[superior temporal sulcus]] (pSTS), the [[precuneus]], and the [[amygdala]] are associated with theory of mind tasks. Patients with [[frontal lobe]] or [[temporoparietal junction]] lesions find some theory of mind tasks difficult. One's theory of mind develops in childhood as the [[prefrontal cortex]] develops.[{{cite journal |last1=Premack |first1=David |last2=Woodruff |first2=Guy |title=Does the chimpanzee have a theory of mind? |journal=Behavioral and Brain Sciences |volume=1 |issue=4 |pages=515–526 |doi=10.1017/S0140525X00076512 |date=December 1978 |doi-access=free }}] It is typically assumed others have minds analogous to one's own; this assumption is based on three reciprocal social interactions, as observed in [[joint attention]],[{{cite book |last=Baron-Cohen |first=Simon |author-link=Simon Baron-Cohen |contribution=Precursors to a theory of mind: Understanding attention in others |editor-last=Whiten |editor-first=Andrew |title=Natural theories of mind: evolution, development, and simulation of everyday mindreading |pages=233–251 |publisher=B. Blackwell |location=Oxford, UK Cambridge, Massachusetts |year=1991 |isbn=978-0-631-17194-2}}] the functional use of language,[Bruner, J. S. (1981). "Intention in the structure of action and interaction". In L. P. Lipsitt & C. K. Rovee-Collier (Eds.), ''Advances in infancy research'', Vol. 1, pp. 41–56. Norwood, New Jersey: Ablex Publishing Corporation.] and the understanding of others' emotions and actions.[Gordon, R. M. (1996). "'Radical' simulationism". In P. Carruthers & P. K. Smith, Eds. ''Theories of theories of mind''. Cambridge: Cambridge University Press.] Theory of mind allows one to attribute thoughts, desires, and intentions to others, to predict or explain their actions, and to posit their intentions. It enables one to understand that mental states can be the cause of—and can be used to explain and predict—the behavior of others.[{{Unbulleted list citebundle
|1={{cite journal |last1=Courtin |first1=C. |year=2000 |title=The impact of sign language on the cognitive development of deaf children: The case of theories of mind |journal=Journal of Deaf Studies and Deaf Education |volume=5 |issue =3 |pages=266–276 |doi=10.1093/deafed/5.3.266 |pmid=15454505 |doi-access=free }}
|2={{cite journal |last1=Courtin |first1=C. |last2=Melot |first2=A.-M. |year=2005 |title=Metacognitive development of deaf children: Lessons from the appearance-reality and false belief tasks |journal=Developmental Science |volume=8 |issue=1 |pages=16–25 |pmid=15647063 |doi=10.1111/j.1467-7687.2005.00389.x }}
|3={{cite journal |last1=Macaulay |first1=C. E. |last2=Ford |first2=R. M. |title=Family influences on the cognitive development of profoundly deaf children: Exploring the effects of socioeconomic status and siblings|journal=Journal of Deaf Studies and Deaf Education |date=2013 |volume=4 |issue=18 |pages=545–562 |doi=10.1093/deafed/ent019 |pmid=23614903 |url=https://academic.oup.com/jdsde/article/18/4/545/559674?login=true |access-date=18 May 2021|doi-access=free }} }}] If a person does not have a mature theory of mind, it may be a sign of cognitive or developmental impairment.[Demetriou, A., Mouyi, A., & Spanoudis, G. (2010). "The development of mental processing", Nesselroade, J. R. (2010). "Methods in the study of life-span human development: Issues and answers". In W. F. Overton (Ed.), ''Biology, cognition and methods across the life-span'', Volume 1 of the ''Handbook of life-span development'' (pp. 36–55), Editor-in-chief: R. M. Lerner. Hoboken, New Jersey: Wiley.]
[[Empathy]]—the recognition and understanding of the states of mind of others, including their beliefs, desires, and particularly emotions—is a related concept. Empathy is often characterized as the ability to "put oneself into another's shoes". Recent [[ethology|neuro-ethological]] studies of animal behavior suggest that rodents may exhibit empathetic abilities.[de Waal, Franz B. M. (2007), "Commiserating Mice". ''Scientific American'', 24 June 2007.] While empathy is known as emotional perspective-taking, theory of mind is defined as cognitive perspective-taking.[{{Cite journal|last1=Hynes|first1=Catherine A.|last2=Baird|first2=Abigail A.|last3=Grafton|first3=Scott T.|title=Differential role of the orbital frontal lobe in emotional versus cognitive perspective-taking|journal=Neuropsychologia|volume=44|issue=3|pages=374–383|doi=10.1016/j.neuropsychologia.2005.06.011|pmid=16112148|year=2006|s2cid=13159903}}]
Research on theory of mind, in humans and animals, adults and children, normally and atypically developing, has grown rapidly in the years since [[David Premack|Premack]] and Guy Woodruff's 1978 paper, "Does the chimpanzee have a theory of mind?".[Blackledge, J. T. (2003). "An introduction to relational frame theory: Basics and applications". ''The Behavior Analyst Today'', 3(4), 421–433. https://doi.org/10.1037/h0099997.] According to this view, empathy and perspective-taking comprise a complex set of derived relational abilities based on learning to discriminate and respond verbally to ever more complex relations between self, others, place, and time, and through established relations.[Hayes, S. C., Barnes-Holmes, D., & Roche, B. (2001). ''Relational frame theory: A post-Skinnerian account of human language and cognition''. New York: Kluwer Academic/Plenum.][Rehfeldt, R. A., and Barnes-Holmes, Y., (2009). [https://books.google.com/books?id=_7dtHoHcwoUC&q=%22theory+of+mind%22 ''Derived Relational Responding: Applications for learners with autism and other developmental disabilities''. Oakland, California: New Harbinger.] ''Google Books''.][McHugh, L. & Stewart, I. (2012). [https://books.google.com/books?id=sl_QvE902k4C&q=%22theory+of+mind%22 ''The self and perspective-taking: Contributions and applications from modern behavioral science''. Oakland, California: New Harbinger.] ''Google Books''.]
==Philosophical and psychological roots==
{{Confusing|section|talk=|reason=it relies heavily upon technical terms that are not explained|date=July 2023}}
Discussions of theory of mind have their roots in philosophical debate from the time of [[René Descartes]]' ''[[Second Meditation]]'', which set the foundations for considering the science of the mind.
Two differing approaches in philosophy for explaining theory of mind are [[theory-theory]] and [[simulation theory of empathy|simulation theory]].[{{Cite journal |last=Apperly |first=Ian A. |date=2008-04-01 |title=Beyond Simulation–Theory and Theory–Theory: Why social cognitive neuroscience should use its own concepts to study "theory of mind" |url=https://www.sciencedirect.com/science/article/abs/pii/S0010027707002120 |journal=Cognition |volume=107 |issue=1 |pages=266–283 |doi=10.1016/j.cognition.2007.07.019 |pmid=17868666 |issn=0010-0277}}] Theory-theory claims that individuals use "theories" grounded in [[folk psychology]] to reason about others' minds. According to theory-theory, these folk psychology theories are developed automatically and innately by concepts and rules we have for ourselves, and then instantiated through social interactions.[Carruthers, P. (1996). "Simulation and self-knowledge: a defence of the theory-theory". In P. Carruthers & P.K. Smith, Eds. ''Theories of theories of mind''. Cambridge: Cambridge University Press.] In contrast, simulation-theory argues that individuals simulate the internal states of others to build mental models for their cognitive processes. A basic example of this is someone imagining themselves in the position of another person to infer the other person's thoughts and feelings.[{{Citation |last=Röska-Hardy |first=Louise |title=Theory Theory (Simulation Theory, Theory of Mind) |date=2009 |encyclopedia=Encyclopedia of Neuroscience |pages=4064–4067 |editor-last=Binder |editor-first=Marc D. |url=https://link.springer.com/referenceworkentry/10.1007/978-3-540-29678-2_5984 |access-date=2024-12-03 |place=Berlin, Heidelberg |publisher=Springer |language=en |doi=10.1007/978-3-540-29678-2_5984 |isbn=978-3-540-29678-2 |editor2-last=Hirokawa |editor2-first=Nobutaka |editor3-last=Windhorst |editor3-first=Uwe}}] Theory of mind is also closely related to [[Social perception|person perception]] and [[Attribution (psychology)|attribution theory]] from [[social psychology]].
It is common and intuitive to assume that others have minds. People [[anthropomorphism|anthropomorphize]] non-human animals, inanimate objects, and even natural phenomena. [[Daniel Dennett]] referred to this tendency as taking an "[[intentional stance]]" toward things: we assume they have intentions, to help predict their future behavior.[Dennett, D. (1987). ''The Intentional Stance''. Cambridge: MIT Press.] However, there is an important distinction between taking an "intentional stance" toward something and entering a "shared world" with it. The intentional stance is a functional relationship, describing the use of a theory due to its practical utility, rather than the accuracy of its representation of the world. As such, it is something people resort to during interpersonal interactions. A shared world is directly perceived and its existence structures reality itself for the perceiver. It is not just a lens, through which the perceiver views the world; it in many ways constitutes the cognition, as both its object and the blueprint used to structure perception into understanding.
The philosophical roots of another perspective, the [[relational frame theory]] (RFT) account of theory of mind, arise from contextual psychology, which refers to the study of organisms (both human and non-human) interacting in and with a historical and current situational context. It is an approach based on [[contextualism]], a philosophy in which any event is interpreted as an ongoing act inseparable from its current and historical context and in which [[pragmatism|a radically functional approach to truth and meaning]] is adopted. As a variant of contextualism, RFT focuses on the construction of practical, scientific knowledge. This scientific form of contextual psychology is virtually synonymous with the philosophy of operant psychology.[{{cite web |title=Functional Contextualism |publisher=Association for Contextual Behavioral Science |url=http://www.contextualpsychology.org/functional_contextualism_0 |first=Eric |last=Fox |access-date=March 29, 2014}}]
==Development==
The study of which animals are capable of attributing knowledge and mental states to others, as well as the development of this ability in human [[ontogeny]] and [[phylogenetics|phylogeny]], identifies several behavioral precursors to theory of mind. Understanding attention, understanding of others' intentions, and imitative experience with others are hallmarks of a theory of mind that may be observed early in the development of what later becomes a full-fledged theory.
[[Simon Baron-Cohen]] proposed that infants' understanding of attention in others acts as a critical precursor to the development of theory of mind.[{{cite journal |last1=Dennett |first1=Daniel C. |year=1987 |title=Reprint of Intentional systems in cognitive ethology: The Panglossian paradigm defended (to p. 260) |journal=The Brain and Behavioral Sciences |volume=6 |issue=3 |pages=343–390 |doi=10.1017/s0140525x00016393 |s2cid=32108464 }}] as an understanding that others' actions are goal-directed and arise from particular beliefs or desires. Both two and three-year-old children could discriminate when an experimenter intentionally or accidentally marked a box with stickers.[{{cite journal |last1=Call |first1=J. |last2=Tomasello |first2=M. |year=1998 |title=Distinguishing intentional from accidental actions in orangutans (Pongo pygmaeus), chimpanzees (Pan troglodytes), and human children (Homo sapiens) |journal=Journal of Comparative Psychology |volume=112 |issue=2 |pages=192–206 |doi=10.1037/0735-7036.112.2.192 |pmid=9642787 }}] Even earlier in development, [[Andrew N. Meltzoff]] found that 18-month-old infants could perform target tasks involving the manipulation of objects that adult experimenters attempted and failed, suggesting the infants could represent the object-manipulating behavior of adults as involving goals and intentions.[{{cite journal |last1=Meltzoff |first1=A. |year=1995 |title=Understanding the intentions of others: Re-enactment of intended acts by 18-month-old children |journal=Developmental Psychology |volume=31 |issue=5 |pages=838–850 |doi=10.1037/0012-1649.31.5.838 |pmid=25147406 |pmc=4137788 }}] While attribution of intention and knowledge is investigated in young humans and nonhuman animals to detect precursors to a theory of mind, Gagliardi et al. have pointed out that even adult humans do not always act in a way consistent with an attributional perspective (i.e., based on attribution of knowledge to others).[{{cite journal |last1=Gagliardi |first1=J. L. |year=1995 |title=Seeing and knowing: Knowledge attribution versus stimulus control in adult humans (Homo sapiens) |journal=Journal of Comparative Psychology |volume=109 |issue=2 |pages=107–114 |doi=10.1037/0735-7036.109.2.107 |pmid=7758287 |last2=Kirkpatrick-Steger |first2=K. K. |last3=Thomas |first3=J |last4=Allen|first4=G. J. |last5=Blumberg |first5=M. S. }}] In their experiment, adult human subjects attempted to choose the container baited with a small object from a selection of four containers when guided by confederates who could not see which container was baited.
Research in developmental psychology suggests that an infant's ability to imitate others lies at the origins of both theory of mind and other social-cognitive achievements like [[perspective-taking]] and empathy.[{{cite book |last=Meltzoff |first=Andrew N. |contribution=Imitation as a mechanism of social cognition: Origins of empathy, theory of mind, and the representation of action |editor-last=Goswami |editor-first=Usha |title=Blackwell handbook of childhood cognitive development |pages=6–25 |publisher=Blackwell Publishers |location=Malden, Massachusetts |year=2003 |isbn=978-0-631-21840-1}}] According to Meltzoff, the infant's innate understanding that others are "like me" allows them to recognize the equivalence between the physical and mental states apparent in others and those felt by the self. For example, the infant uses their own experiences, orienting their head and eyes toward an object of interest to understand the movements of others who turn toward an object; that is, they will generally attend to objects of interest or significance. Some researchers in comparative disciplines have hesitated to put too much weight on imitation as a critical precursor to advanced human social-cognitive skills like mentalizing and empathizing, especially if true imitation is no longer employed by adults. A test of imitation by Alexandra Horowitz found that adult subjects imitated an experimenter demonstrating a novel task far less closely than children did. Horowitz points out that the precise psychological state underlying imitation is unclear and cannot, by itself, be used to draw conclusions about the mental states of humans.[{{cite journal |last1=Horowitz |first1=Alexandra C. |year=2003 |title=Do humans ape? or Do apes human? Imitation and intention in humans and other animals |journal=Journal of Comparative Psychology |volume=17 |issue=3 |pages=325–336 |citeseerx=10.1.1.688.3721 |doi=10.1037/0735-7036.117.3.325 |pmid=14498809|s2cid=14929964 }}]
While much research has been done on infants, theory of mind develops continuously throughout childhood and into late adolescence as the [[synapse]]s in the prefrontal cortex develop. The prefrontal cortex is thought to be involved in planning and decision-making.[{{cite journal |last1=Laghi |first1=Fiorenzo |year=2016 |title=The Role of Nice and Nasty Theory of Mind in Teacher-Selected Peer Models for Adolescents with Autism Spectrum Disorders |journal=Measurement and Evaluation in Counseling and Development |volume=49 |issue=3 |pages=207–216 |doi=10.1177/0748175615596784 |last2=Lonigro |first2=Antonia |last3=Levanto |first3=Simona |last4=Ferraro |first4=Maurizio |last5=Baumgartner |first5=Emma |last6=Baiocco |first6=Roberto |s2cid=147180970 }}] Children seem to develop theory of mind skills sequentially. The first skill to develop is the ability to recognize that others have diverse desires. Children are able to recognize that others have diverse beliefs soon after. The next skill to develop is recognizing that others have access to different knowledge bases. Finally, children are able to understand that others may have false beliefs and that others are capable of hiding emotions. While this sequence represents the general trend in skill acquisition, it seems that more emphasis is placed on some skills in certain cultures, leading to more valued skills to develop before those that are considered not as important. For example, in [[individualistic]] cultures such as the United States, a greater emphasis is placed on the ability to recognize that others have different opinions and beliefs. In a [[collectivistic]] culture, such as China, this skill may not be as important and therefore may not develop until later.[{{cite journal |last1=Etel |first1=Evren |year=2015 |title=Social Competence, Theory of Mind, and Executive Function in Institution-reared Turkish Children |journal=International Journal of Behavioral Development |volume=39 |issue=6 |pages=519–529 |doi=10.1177/0165025414556095 |last2=Yagmurlu |first2=Bilge |s2cid=147324302 }}]
===Language===
There is evidence that the development of theory of mind is closely intertwined with language development in humans. One meta-analysis showed a moderate to strong correlation (''r'' = 0.43) between performance on theory of mind and language tasks.[{{cite journal |last1=Milligan|first1=Karen|last2=Astington|first2=Janet Wilde|last3=Dack|first3=Lisa Ain |title=Language and theory of mind: meta-analysis of the relation between language ability and false-belief understanding |journal=[[Child Development (journal)|Child Development]] |volume=78 |issue=2 |pages=622–646 |doi=10.1111/j.1467-8624.2007.01018.x |pmid=17381794 |date=March–April 2007 }}] Both language and theory of mind begin to develop around the same time in children (between ages two and five), but many other abilities develop during this same time period as well, and they do not produce such high correlations with one another nor with theory of mind.
Pragmatic theories of communication assume that infants must possess an understanding of beliefs and mental states of others to infer the communicative content that proficient language users intend to convey.[{{Cite book |first=Dan |last=Sperber |title=Relevance: communication and cognition |date=2001 |publisher=Blackwell Publishers |author2=Wilson, Deirdre|isbn=978-0-631-19878-9 |edition=2nd |location=Oxford |oclc=32589501}}] Since spoken phrases can have different meanings depending on context, theory of mind can play a crucial role in understanding the intentions of others and inferring the meaning of words. Some empirical results suggest that even 13-month-old infants have an early capacity for communicative mind-reading that enables them to infer what relevant information is transferred between communicative partners, which implies that human language relies at least partially on theory of mind skills.[{{Cite journal |last1=Tauzin |first1=Tibor |last2=Gergely |first2=György |date=2018-06-22 |title=Communicative mind-reading in preverbal infants |journal=Scientific Reports |language=En |volume=8 |issue=1 |pages=9534 |bibcode=2018NatSR...8.9534T |doi=10.1038/s41598-018-27804-4 |issn=2045-2322 |pmc=6015048 |pmid=29934630}}]
Carol A. Miller posed further possible explanations for this relationship. Perhaps the extent of verbal communication and conversation involving children in a family could explain theory of mind development. Such language exposure could help introduce a child to the different mental states and perspectives of others.[{{cite journal |last=Miller |first=Carol A. |title=Developmental relationships between language and theory of mind |journal=American Journal of Speech-Language Pathology |volume=15 |issue=2 |pages=142–154 |doi=10.1044/1058-0360(2006/014) |pmid=16782686 |date=May 2006 |s2cid=28828189 }}] Empirical findings indicate that participation in family discussion predicts scores on theory of mind tasks,[{{cite journal |last1=Ruffman |first1=Ted |last2=Slade |first2=Lance |last3=Crowe |first3=Elena |title=The relation between children's and mothers' mental state language and theory-of-mind understanding |journal=[[Child Development (journal)|Child Development]] |volume=73 |issue=3 |pages=734–751 |doi=10.1111/1467-8624.00435 |pmid=12038548 |date=May–June 2002 }} [https://web.psy.otago.ac.nz/pdfs/Ted%27s%20PDF%27s/2002ChiDev.pdf Pdf.] {{Webarchive|url=https://web.archive.org/web/20210308035716/https://web.psy.otago.ac.nz/pdfs/Ted%27s%20PDF%27s/2002ChiDev.pdf |date=8 March 2021 }}] and that deaf children who have hearing parents and may not be able to communicate with their parents much during early years of development tend to score lower on theory of mind tasks.[{{cite journal |last1=Woolfe |first1=Tyron |last2=Want |first2=Stephen C. |last3=Siegal |first3=Michael |title=Signposts to development: theory of mind in deaf children |journal=[[Child Development (journal)|Child Development]] |volume=73 |issue=3 |pages=768–778 |doi=10.1111/1467-8624.00437 |pmid=12038550 |date=May–June 2002 |citeseerx=10.1.1.70.4337 }} [http://www.tyronwoolfe.co.uk/wp-content/uploads/2013/12/Signposts_Child_Development.pdf Pdf.]]
Another explanation of the relationship between language and theory of mind development has to do with a child's understanding of mental-state words such as "think" and "believe". Since a mental state is not something that one can observe from behavior, children must learn the meanings of words denoting mental states from verbal explanations alone, requiring knowledge of the syntactic rules, semantic systems, and pragmatics of a language.[{{cite journal |last1=Moore |first1=Chris |last2=Pure |first2=Kiran |last3=Furrow |first3=David |title=Children's understanding of the modal expression of speaker certainty and uncertainty and its relation to the development of a representational theory of mind |journal=[[Child Development (journal)|Child Development]] |volume=61 |issue=3 |pages=722–730 |doi=10.1111/j.1467-8624.1990.tb02815.x |pmid=2364747 |jstor=1130957 |date=June 1990 }}]
A third hypothesis is that the ability to distinguish a whole sentence ("Jimmy thinks the world is flat") from its embedded complement ("the world is flat") and understand that one can be true while the other can be false is related to theory of mind development. Recognizing these complements as being independent of one another is a relatively complex syntactic skill and correlates with increased scores on theory of mind tasks in children.[{{cite journal |last1=de Villiers |first1=Jill G. |last2=Pyers |first2=Jennie E. |title=Complements to cognition: a longitudinal study of the relationship between complex syntax and false-belief-understanding |journal=Cognitive Development |volume=17 |issue=1 |pages=1037–1060 |doi=10.1016/S0885-2014(02)00073-4 |date=January–March 2002 }}]
There is also evidence that the areas of the brain responsible for language and theory of mind are closely connected. The [[temporoparietal junction]] (TPJ) is involved in the ability to acquire new vocabulary, as well as to perceive and reproduce words. The TPJ also contains areas that specialize in recognizing faces, voices, and biological motion, and in theory of mind. Since all of these areas are located so closely together, it is reasonable to suspect that they work together. Studies have reported an increase in activity in the TPJ when patients are absorbing information through reading or images regarding other peoples' beliefs but not while observing information about physical control stimuli.[{{cite journal|last=Saxe|first=R|author2=Kanwisher, N |title=People thinking about thinking people. The role of the temporo-parietal junction in "theory of mind".|journal=NeuroImage|date=August 2003|volume=19|issue=4|pages=1835–42|pmid=12948738|doi=10.1016/S1053-8119(03)00230-1|s2cid=206118958}}]
===Theory of mind in adults===
Adults have theory of mind concepts that they developed as children (concepts such as belief, desire, knowledge, and intention). They use these concepts to meet the diverse demands of social life, ranging from snap decisions about how to trick an opponent in a competitive game, to keeping up with who knows what in a fast-moving conversation, to judging the guilt or innocence of the accused in a court of law.[{{Cite book|title=Mindreaders: the cognitive basis of "theory of mind"|first=Ian|last=Apperly|date=2011|publisher=Psychology Press|isbn=978-0-203-83392-6|location=Hove|oclc=705929873}}]
Boaz Keysar, Dale Barr, and colleagues found that adults often failed to ''use'' their theory of mind abilities to interpret a speaker's message, and acted as if unaware that the speaker lacked critical knowledge about a task. In one study, a confederate instructed adult participants to rearrange objects, some of which were not visible to the confederate, as part of a communication game. Only objects that were visible to both the confederate and the participant were part of the game. Despite knowing that the confederate could not see some of the objects, a third of the participants still tried to move those objects.[{{Cite journal|last1=Keysar|first1=Boaz|last2=Lin|first2=Shuhong|last3=Barr|first3=Dale J|date=2003-08-01|title=Limits on theory of mind use in adults|journal=Cognition|volume=89|issue=1|pages=25–41|doi=10.1016/S0010-0277(03)00064-7|pmid=12893123|s2cid=8523033|issn=0010-0277}}] Other studies show that adults are prone to [[egocentric bias]]es, with which they are influenced by their own beliefs, knowledge, or preferences when judging those of other people, or that they neglect other people's perspectives entirely.[{{Cite journal|last1=Royzman|first1=Edward B.|last2=Cassidy|first2=Kimberly Wright|last3=Baron|first3=Jonathan|date=2003|title="I know, you know": Epistemic egocentrism in children and adults.|journal=Review of General Psychology|language=en|volume=7|issue=1|pages=38–65|doi=10.1037/1089-2680.7.1.38|s2cid=197665718|issn=1089-2680}}] There is also evidence that adults with greater memory, [[Inhibitory control|inhibitory capacity]], and motivation are more likely to use their theory of mind abilities.[{{Unbulleted list citebundle
|1={{Cite journal|last=Brown-Schmidt|first=Sarah|date=2009-10-01|title=The role of executive function in perspective taking during online language comprehension|journal=Psychonomic Bulletin & Review|language=en|volume=16|issue=5|pages=893–900|doi=10.3758/PBR.16.5.893|pmid=19815795|issn=1531-5320|doi-access=free}}
|2={{Cite journal|last1=Epley|first1=Nicholas|last2=Keysar|first2=Boaz|last3=Van Boven|first3=Leaf|last4=Gilovich|first4=Thomas|date=2004|title=Perspective Taking as Egocentric Anchoring and Adjustment |journal=Journal of Personality and Social Psychology|language=en |volume=87|issue=3|pages=327–339|doi=10.1037/0022-3514.87.3.327|pmid=15382983|issn=1939-1315|citeseerx=10.1.1.315.8009|s2cid=18087684 }} }}]
In contrast, evidence about indirect effects of thinking about other people's mental states suggests that adults may sometimes use their theory of mind automatically. Agnes Kovacs and colleagues measured the time it took adults to detect the presence of a ball as it was revealed from behind an occluder. They found that adults' speed of response was influenced by whether another person (the "agent") in the scene thought there was a ball behind the occluder, even though adults were not asked to pay attention to what the agent thought.[{{Cite journal|last1=Kovacs|first1=Agnes|last2=Teglas|first2=Erno|last3=Endress|first3=Ansgar Denis|date=2010-12-24|title=The Social Sense: Susceptibility to Others' Beliefs in Human Infants and Adults|journal=Science|language=en|volume=330|issue=6012|pages=1830–1834|doi=10.1126/science.1190792|issn=0036-8075|pmid=21205671|bibcode=2010Sci...330.1830K|s2cid=2908352}}]
Dana Samson and colleagues measured the time it took adults to judge the number of dots on the wall of a room. They found that adults responded more slowly when another person standing in the room happened to see fewer dots than they did, even when they had never been asked to pay attention to what the person could see.[{{Cite journal|last1=Samson|first1=Dana|last2=Apperly|first2=Ian A.|last3=Braithwaite|first3=Jason J.|last4=Andrews|first4=Benjamin J.|last5=Bodley Scott|first5=Sarah E.|date=2010|title=Seeing it their way: Evidence for rapid and involuntary computation of what other people see|journal=Journal of Experimental Psychology: Human Perception and Performance|volume=36|issue=5|pages=1255–1266|doi=10.1037/a0018729|pmid=20731512|issn=1939-1277}}] It has been questioned whether these "altercentric biases" truly reflect automatic processing of what another person is thinking or seeing or, instead, reflect attention and memory effects cued by the other person, but not involving any representation of what they think or see.[{{Cite journal|last=Heyes|first=Celia|title=Submentalizing: I Am Not Really Reading Your Mind|journal=Current Perspectives on Psychological Science|volume=9|issue=2|pages=131–143|doi=10.1177/1745691613518076|pmid=26173251|year=2014|s2cid=206778161}}]
Different theories seek to explain such results. If theory of mind is automatic, this would help explain how people keep up with the theory of mind demands of competitive games and fast-moving conversations. It might also explain evidence that human infants and some non-human species sometimes appear capable of theory of mind, despite their limited resources for memory and cognitive control.[{{Cite journal|last1=Apperly|first1=Ian A.|last2=Butterfill|first2=Stephen A.|date=2009|title=Do humans have two systems to track beliefs and belief-like states?|journal=Psychological Review|volume=116|issue=4|pages=953–970|doi=10.1037/a0016923|pmid=19839692|issn=1939-1471|citeseerx=10.1.1.377.3254}}] in common with "two systems" accounts in many other areas of psychology.[{{Cite book|title=Thinking, fast and slow|last=Kahneman|first=Daniel|isbn=978-0-374-27563-1|edition=1st|location=New York|publisher=Farrar, Straus and Giroux|oclc=706020998|date=2011-10-25}}] In this account, "system 1" is cognitively efficient and enables theory of mind for a limited but useful set of circumstances. "System 2" is cognitively effortful, but enables much more flexible theory of mind abilities. Philosopher [[Peter Carruthers (philosopher)|Peter Carruthers]] disagrees, arguing that the same core theory of mind abilities can be used in both simple and complex ways.[{{Cite journal|last=Carruthers|first=Peter|date=2017-03-01|title=Mindreading in adults: evaluating two-systems views|journal=Synthese|language=en|volume=194|issue=3|pages=673–688|doi=10.1007/s11229-015-0792-3|s2cid=6049635|issn=1573-0964}}] The account has been criticized by Celia Heyes who suggests that "system 1" theory of mind abilities do not require representation of mental states of other people, and so are better thought of as "sub-mentalizing".[{{Cite journal|last1=Henry|first1=Julie D.|last2=Phillips|first2=Louise H.|last3=Ruffman|first3=Ted|last4=Bailey|first4=Phoebe E.|title=A meta-analytic review of age differences in theory of mind|journal=Psychology and Aging|language=en|volume=28|issue=3|pages=826–839|doi=10.1037/a0030677|pmid=23276217|year=2013}}] However, the decline in other cognitive functions is even stronger, suggesting that social cognition is better preserved. In contrast to theory of mind, empathy shows no impairments in aging.[{{Cite journal|last1=Reiter|first1=Andrea M. F.|last2=Kanske|first2=Philipp|last3=Eppinger|first3=Ben|last4=Li|first4=Shu-Chen|date=2017-09-08|title=The Aging of the Social Mind - Differential Effects on Components of Social Understanding|journal=Scientific Reports|language=En|volume=7|issue=1|pages=11046|doi=10.1038/s41598-017-10669-4|pmid=28887491|pmc=5591220|issn=2045-2322|bibcode=2017NatSR...711046R}}][{{Cite journal |last1=Stietz |first1=Julia |last2=Pollerhoff |first2=Lena |last3=Kurtz |first3=Marcel |last4=Li |first4=Shu-Chen |last5=Reiter |first5=Andrea M. F. |last6=Kanske |first6=Philipp |title=The ageing of the social mind: replicating the preservation of socio-affective and the decline of socio-cognitive processes in old age |journal=Royal Society Open Science |year=2021 |volume=8 |issue=8 |pages=210641 |doi=10.1098/rsos.210641 |pmc=8386516 |pmid=34457343|bibcode=2021RSOS....810641S }}]
There are two kinds of theory of mind representations: cognitive (concerning mental states, beliefs, thoughts, and intentions) and affective (concerning the emotions of others). Cognitive theory of mind is further separated into first order (e.g., I think she thinks that) and second order (e.g. he thinks that she thinks that). There is evidence that cognitive and affective theory of mind processes are functionally independent from one another.[{{cite journal |last= Kalbe |first= Elke |year= 2010 |title= Dissociating Cognitive from Affective Theory of Mind: A TMS Study |journal= Cortex |volume= 46 |issue=6 |pages= 769–780 |doi= 10.1016/j.cortex.2009.07.010 |pmid= 19709653 |s2cid= 16815856 }}] In studies of Alzheimer's disease, which typically occurs in older adults, patients display impairment with second order cognitive theory of mind, but usually not with first order cognitive or affective theory of mind. However, it is difficult to discern a clear pattern of theory of mind variation due to age. There have been many discrepancies in the data collected thus far, likely due to small sample sizes and the use of different tasks that only explore one aspect of theory of mind. Many researchers suggest that theory of mind impairment is simply due to the normal decline in cognitive function.[{{cite journal |last1=Duval |first1=Céline |year=2011 |title=Age Effects on Different Components of Theory of Mind |journal=Consciousness and Cognition |volume=20 |issue=3 |pages=627–642 |doi=10.1016/j.concog.2010.10.025 |pmid=21111637 |last2=Piolino |first2=Pascale |last3=Benjanin |first3=Alexandre |last4=Eustache |first4=Francis |last5=Desgranges |first5=Béatrice |s2cid=7877493 }}]
=== Cultural variations ===
Researchers propose that five key aspects of theory of mind develop sequentially for all children between the ages of three and five:[{{Cite journal|last1=Wellman|first1=Henry M.|last2=Liu|first2=David|date=2004-03-01|title=Scaling of Theory-of-Mind Tasks|journal=Child Development|language=en|volume=75|issue=2|pages=523–541|doi=10.1111/j.1467-8624.2004.00691.x|pmid=15056204|s2cid=5562001 |issn=1467-8624}}] diverse desires, diverse beliefs, knowledge access, false beliefs, and hidden emotions.[{{Cite journal|last1=Shahaeian|first1=Ameneh|last2=Peterson|first2=Candida C.|last3=Slaughter|first3=Virginia|last4=Wellman|first4=Henry M.|title=Culture and the sequence of steps in theory of mind development|journal=Developmental Psychology|language=en|volume=47|issue=5|pages=1239–1247|doi=10.1037/a0023899|pmid=21639620|year=2011}}] and studies with children in Canada, India, Peru, Samoa, and Thailand indicate that they all pass the false belief task at around the same time, suggesting that children develop theory of mind consistently around the world.[{{cite journal |last1=Callaghan |first1=T. |last2=Rochat |first2=P. |last3=Lillard |first3=A. |last4=Claux |first4=M. L. |last5=Odden |first5=H. |last6=Itakura |first6=S. |last7=Singh |first7=S. |year=2005 |title=Synchrony in the onset of mental-state reasoning: Evidence from five cultures |journal=Psychological Science |volume=16 |issue=5 |pages=378–384 |doi=10.1111/j.0956-7976.2005.01544.x |pmid=15869697 |s2cid=1183819 }}]
However, children from [[Iran]] and [[China]] develop theory of mind in a slightly different order. Although they begin the development of theory of mind around the same time, toddlers from these countries understand knowledge access before Western children but take longer to understand diverse beliefs.[{{Cite journal|doi=10.1111/j.1467-9280.2006.01830.x|title=Scaling of Theory-of-Mind Understandings in Chinese Children|year=2006|last1=Wellman|first1=Henry M.|last2=Fang|first2=Fuxi|last3=Liu|first3=David|last4=Zhu|first4=Liqi|last5=Liu|first5=Guoxiong|journal=Psychological Science|volume=17|issue=12|pages=1075–1081|pmid=17201790|s2cid=18632127}}] Researchers believe this swap in the developmental order is related to the culture of [[Collectivism and individualism|collectivism]] in Iran and China, which emphasizes interdependence and shared knowledge as opposed to the culture of [[individualism]] in Western countries, which promotes individuality and accepts differing opinions. Because of these different cultural values, Iranian and Chinese children might take longer to understand that other people have different beliefs and opinions. This suggests that the development of theory of mind is not universal and solely determined by innate brain processes but also influenced by social and cultural factors.[The German word ''Umwelt'' means "environment" or "surrounding world"] of the pre-verbal child.
=== False-belief task ===
One of the most important milestones in theory of mind development is the ability to attribute ''false belief'': in other words, to understand that other people can believe things which are not true. To do this, it is suggested, one must understand how knowledge is formed, that people's beliefs are based on their knowledge, that mental states can differ from reality, and that people's behavior can be predicted by their mental states. Numerous versions of false-belief task have been developed, based on the initial task created by Wimmer and Perner (1983).[{{cite journal |last1=Wimmer |first1=H. |last2=Perner |first2=J. |year=1983 |title=Beliefs about beliefs: Representation and constraining function of wrong beliefs in young children's understanding of deception |journal=Cognition |volume=13 |issue=1 |pages=103–128 |doi=10.1016/0010-0277(83)90004-5 |pmid=6681741 |s2cid=17014009 }}]
In the most common version of the false-belief task (often called the [[Sally–Anne test|Sally-Anne test]]), children are told a story about Sally and Anne. Sally has a marble, which she places into her basket, and then leaves the room. While she is out of the room, Anne takes the marble from the basket and puts it into the box. The child being tested is then asked where Sally will look for the marble once she returns. The child passes the task if she answers that Sally will look in the basket, where Sally put the marble; the child fails the task if she answers that Sally will look in the box. To pass the task, the child must be able to understand that another's mental representation of the situation is different from their own, and the child must be able to predict behavior based on that understanding.[{{cite journal|last1=O'Brien |first1=Karen |last2=Slaughter |first2=Virginia |last3=Peterson |first3=Candida C |title=Sibling influences on theory of mind development for children with ASD |journal=Journal of Child Psychology and Psychiatry |date=2011 |volume=52 |issue=6 |pages=713–719 |doi=10.1111/j.1469-7610.2011.02389.x |pmid=21418062 |url=https://acamh.onlinelibrary.wiley.com/doi/abs/10.1111/j.1469-7610.2011.02389.x |access-date=18 May 2021}}] Another example depicts a boy who leaves chocolate on a shelf and then leaves the room. His mother puts it in the fridge. To pass the task, the child must understand that the boy, upon returning, holds the false belief that his chocolate is still on the shelf.[{{cite book |last=Mitchell |first=Peter |contribution=Acquiring a theory of mind |editor-last1=Slater |editor-first1=Alan |editor-last2=Bremner |editor-first2=J. Gavin |title=An introduction to developmental psychology |pages=381–406 |publisher=John Wiley & Sons Inc. |location=Hoboken, New Jersey |edition= 3rd |year=2011 |isbn=978-1-118-76720-7}}]
The results of research using false-belief tasks have been called into question: most typically developing children are able to pass the tasks from around age four.[{{cite journal |author=Roessler, Johannes |title=When the Wrong Answer Makes Perfect Sense - How the Beliefs of Children Interact With Their Understanding of Competition, Goals and the Intention of Others |journal=University of Warwick Knowledge Centre |year=2013 |url=http://www2.warwick.ac.uk/knowledge/culture/when-the-wrong-answer-makes-perfect-sense-how-the-beliefs-of-children-interact-with-their-understanding-of-competition-goals-and-the-intention-of-others |access-date=2013-08-15 |url-status=dead |archive-url=https://web.archive.org/web/20131203165128/http://www2.warwick.ac.uk/knowledge/culture/when-the-wrong-answer-makes-perfect-sense-how-the-beliefs-of-children-interact-with-their-understanding-of-competition-goals-and-the-intention-of-others |archive-date=3 December 2013}}] Yet early studies asserted that 80% of children diagnosed with autism were unable to pass this test, while children with other disabilities like [[Down syndrome]] were able to.[{{cite journal |last1=Baron-Cohen |first1=Simon |last2=Leslie |first2=Alan M. |last3=Frith |first3=Uta |title=Does the autistic child have a "theory of mind"? |journal=[[Cognition (journal)|Cognition]] |volume=21 |issue=1 |pages=37–46 |doi=10.1016/0010-0277(85)90022-8 |pmid=2934210 |date=October 1985 |s2cid=14955234 |url=http://ruccs.rutgers.edu/images/personal-alan-leslie/publications/Baron-Cohen%20Leslie%20%26%20Frith%201985.pdf |archive-url=https://web.archive.org/web/20170928145836/http://ruccs.rutgers.edu/images/personal-alan-leslie/publications/Baron-Cohen%20Leslie%20%26%20Frith%201985.pdf |archive-date=2017-09-28 }}] However this assertion could not be replicated by later studies.[{{Cite journal |last1=Gernsbacher |first1=Morton Ann |last2=Yergeau |first2=Melanie |date=2019 |title=Empirical Failures of the Claim That Autistic People Lack a Theory of Mind |journal=[[Archives of Scientific Psychology]] |language=en |volume=7 |issue=1 |pages=102–118 |doi=10.1037/arc0000067 |pmc=6959478 |pmid=31938672 }}][{{Cite journal |last1=Ozonoff |first1=Sally |last2=Pennington |first2=Bruce F. |last3=Rogers |first3=Sally J. |date=1991 |title=Executive Function Deficits in High-Functioning Autistic Individuals: Relationship to Theory of Mind |url=https://onlinelibrary.wiley.com/doi/10.1111/j.1469-7610.1991.tb00351.x |journal=Journal of Child Psychology and Psychiatry |language=en |volume=32 |issue=7 |pages=1081–1105 |doi=10.1111/j.1469-7610.1991.tb00351.x |pmid=1787138 |issn=0021-9630|access-date=2023-11-22}}][{{Cite journal |last1=Oswald |first1=Donald P. |last2=Ollendick |first2=Thomas H. |date=1989 |title=Role taking and social competence in autism and mental retardation |url=http://link.springer.com/10.1007/BF02212723 |journal=Journal of Autism and Developmental Disorders |language=en |volume=19 |issue=1 |pages=119–127 |doi=10.1007/BF02212723 |pmid=2708295 |s2cid=46444974 |issn=0162-3257}}][{{Cite journal |last1=Tager-Flusberg |first1=Helen |last2=Sullivan |first2=Kate |date=1994 |title=A second look at second-order belief attribution in autism |url=http://link.springer.com/10.1007/BF02172139 |journal=Journal of Autism and Developmental Disorders |language=en |volume=24 |issue=5 |pages=577–586 |doi=10.1007/BF02172139 |pmid=7814307 |s2cid=25194344 |issn=0162-3257}}] It instead was concluded that children fail these tests due to a lack of understanding of extraneous processes and a basic lack of mental processing capabilities.[{{Cite journal |last1=Scott |first1=Rose M. |last2=Baillargeon |first2=Renée |date=2017 |title=Early False-Belief Understanding |url=https://linkinghub.elsevier.com/retrieve/pii/S1364661317300189 |journal=Trends in Cognitive Sciences |volume=21 |issue=4 |pages=237–249 |doi=10.1016/j.tics.2017.01.012 |pmid=28259555 |issn=1364-6613}}]
Adults may also struggle with false beliefs, for instance when they show [[hindsight bias]].[Mitchell, P. (2011). "Acquiring a Theory of Mind". In Alan Slater, & Gavin Bremner (eds.) ''An Introduction to Developmental Psychology'': Second Edition, BPS Blackwell. page 371] In one experiment, adult subjects who were asked for an independent assessment were unable to disregard information on actual outcome. Also in experiments with complicated situations, when assessing others' thinking, adults can fail to correctly disregard certain information that they have been given.[{{cite journal |journal=Child Development |year=1988 |volume=59 |issue=1 |pages=26–37 |doi=10.2307/1130386 |pmid=3342716 |last1=Gopnik |first1=Alison |author-link=Alison Gopnik |last2=Aslington |first2= Janet W. |title=Children's understanding of representational change and its relation to the understanding of false belief and the appearance-reality distinction. |jstor=1130386 }}] Though the use of such implicit tests has yet to reach a consensus on their validity and reproducibility of study results.[{{Cite journal |last=Rakoczy |first=Hannes |date=2022 |title=Foundations of theory of mind and its development in early childhood |url=https://www.nature.com/articles/s44159-022-00037-z |journal=Nature Reviews Psychology |language=en |volume=1 |issue=4 |pages=223–235 |doi=10.1038/s44159-022-00037-z |issn=2731-0574}}]
===Other tasks===
The "false-photograph" task[{{Unbulleted list citebundle
|1={{cite journal |last1=Zaitchik |first1=D. |year=1990 |title=When representations conflict with reality: the preschooler's problem with false beliefs and 'false' photographs |journal=Cognition |volume=35 |issue=1 |pages=41–68 |doi=10.1016/0010-0277(90)90036-J |pmid=2340712 |s2cid=1799960 }}
|2={{cite journal |last1=Leslie |first1=A. |last2=Thaiss |first2=L. |year=1992 |title=Domain specificity in conceptual development |journal=Cognition |volume=43 |issue=3 |pages=225–51 |doi=10.1016/0010-0277(92)90013-8 |pmid=1643814 |s2cid=17296136 }} }}] also measures theory of mind development. In this task, children must reason about what is represented in a photograph that differs from the current state of affairs. Within the false-photograph task, either a location or identity change exists.[{{cite journal |last1=Sabbagh |first1=M.A. |last2=Moses |first2=L.J. |year=2006 |title=Executive functioning and preschoolers' understanding of false beliefs, false photographs, and false signs |journal=Child Development |volume=77 |issue=4 |pages=1034–1049 |doi=10.1111/j.1467-8624.2006.00917.x |pmid=16942504 |last3=Shiverick |first3=S }}] In the location-change task, the examiner puts an object in one location (e.g. chocolate in an open green cupboard), whereupon the child takes a Polaroid photograph of the scene. While the photograph is developing, the examiner moves the object to a different location (e.g. a blue cupboard), allowing the child to view the examiner's action. The examiner asks the child two control questions: "When we first took the picture, where was the object?" and "Where is the object now?" The subject is also asked a "false-photograph" question: "Where is the object in the picture?" The child passes the task if he/she correctly identifies the location of the object in the picture and the actual location of the object at the time of the question. However, the last question might be misinterpreted as "Where in this room is the object that the picture depicts?" and therefore some examiners use an alternative phrasing.[{{Cite journal |last1=Apperly |first1=Ian A. |last2=Samson |first2=Dana |last3=Chiavarino |first3=Claudia |last4=Bickerton |first4=Wai-Ling |last5=Humphreys |first5=Glyn W. |date=2007-05-01 |title=Testing the domain-specificity of a theory of mind deficit in brain-injured patients: Evidence for consistent performance on non-verbal, "reality-unknown" false belief and false photograph tasks |url=https://www.sciencedirect.com/science/article/pii/S0010027706000825 |journal=Cognition |language=en |volume=103 |issue=2 |pages=300–321 |doi=10.1016/j.cognition.2006.04.012 |pmid=16781700 |s2cid=7377954 |issn=0010-0277}}]
To make it easier for animals, young children, and individuals with classical [[autism]] to understand and perform theory of mind tasks, researchers have developed tests in which verbal communication is de-emphasized: some whose administration does not involve verbal communication on the part of the examiner, some whose successful completion does not require verbal communication on the part of the subject, and some that meet both of those standards. One category of tasks uses a preferential-looking paradigm, with [[looking time]] as the dependent variable. For instance, nine-month-old infants prefer looking at behaviors performed by a human hand over those made by an inanimate hand-like object.[Woodward, "Infants selectively encode the goal object of an actor's reach", ''Cognition'' (1998)] Other paradigms look at rates of imitative behavior, the ability to replicate and complete unfinished goal-directed acts,[Leslie, A. M. (1991). "Theory of mind impairment in autism". In A. Whiten (Ed.), ''Natural theories of mind: Evolution, development and simulation of everyday mindreading'' (pp. 63–77). Oxford: Basil Blackwell.]
===Early precursors===
Research on the early precursors of theory of mind has invented ways to observe preverbal infants' understanding of other people's mental states, including perception and beliefs. Using a variety of experimental procedures, studies show that infants from their first year of life have an implicit understanding of what other people see[{{cite journal |doi=10.1080/15248370701612951 |title=Out of Sight is Not Out of Mind: Developmental Changes in Infants' Understanding of Visual Perception During the Second Year |year=2007 |last1=Poulin-Dubois |first1=Diane |last2=Sodian |first2=Beate |last3=Metz |first3=Ulrike |last4=Tilden |first4=Joanne |last5=Schoeppner |first5=Barbara |journal=Journal of Cognition and Development |volume=8 |issue=4 |pages=401–425|s2cid=143291042 }}] and what they know.[{{cite journal |doi=10.1126/science.1107621 |title=Do 15-Month-Old Infants Understand False Beliefs? |year=2005 |last1=Onishi |first1=K. H. |journal=Science |volume=308 |issue=5719 |pages=255–8 |pmid=15821091 |last2=Baillargeon |first2=R |pmc=3357322|bibcode=2005Sci...308..255O }}][{{Cite journal|last1=Kovács|first1=Ágnes Melinda|last2=Téglás|first2=Ernő|last3=Endress|first3=Ansgar Denis|date=2010-12-24|title=The Social Sense: Susceptibility to Others' Beliefs in Human Infants and Adults|journal=Science|language=en|volume=330|issue=6012|pages=1830–1834|doi=10.1126/science.1190792|issn=0036-8075|pmid=21205671|bibcode=2010Sci...330.1830K|s2cid=2908352}}] A popular paradigm used to study infants' theory of mind is the violation-of-expectation procedure, which exploits infants' tendency to look longer at unexpected and surprising events compared to familiar and expected events. The amount of time they look at an event gives researchers an indication of what infants might be inferring, or their implicit understanding of events. One study using this paradigm found that 16-month-olds tend to attribute beliefs to a person whose visual perception was previously witnessed as being "reliable", compared to someone whose visual perception was "unreliable". Specifically, 16-month-olds were trained to expect a person's excited vocalization and gaze into a container to be associated with finding a toy in the reliable-looker condition or an absence of a toy in the unreliable-looker condition. Following this training phase, infants witnessed, in an object-search task, the same persons searching for a toy either in the correct or incorrect location after they both witnessed the location of where the toy was hidden. Infants who experienced the reliable looker were surprised and therefore looked longer when the person searched for the toy in the incorrect location compared to the correct location. In contrast, the looking time for infants who experienced the unreliable looker did not differ for either search locations. These findings suggest that 16-month-old infants can differentially attribute beliefs about a toy's location based on the person's prior record of visual perception.[{{cite journal |doi=10.1037/a0016715 |title=The effect of a looker's past reliability on infants' reasoning about beliefs |year=2009 |last1=Poulin-Dubois |first1=Diane |last2=Chow |first2=Virginia |journal=Developmental Psychology |volume=45 |issue=6 |pages=1576–82 |pmid=19899915|s2cid=6916359 }}]
===Methodological problems===
With the methods used to test theory of mind, it has been experimentally shown that very simple robots that only react by reflexes and are not built to have any complex cognition at all can pass the tests for having theory of mind abilities that psychology textbooks assume to be exclusive to humans older than four or five years. Whether such a robot passes the test is influenced by completely non-cognitive factors such as placement of objects and the structure of the robot body influencing how the reflexes are conducted. It has therefore been suggested that theory of mind tests may not actually test cognitive abilities.[Pfeifer, Rolf and Josh Bongard (2006). ''How the Body Shapes the Way We Think: A New View of Intelligence''. ]
Furthermore, early research into theory of mind in autistic children[M Botha. [https://web.archive.org/web/20201209062325/http://epubs.surrey.ac.uk/854098/7/Autistic%20Community%20Connectedness%20as%20a%20Buffer%20Against%20Minority%20Stress%20-%20M%20Botha.pdf "Autistic community connectedness as a buffer against the effects of minority stress."] (2020)
"I will argue that literature regarding "theory of mind" has constituted EV. Researchers, based on one experiment, with a small sample of autistic children (20) (mean chronological age = 11, estimated verbal ability age = 5), argued that autistic individuals lacked "theory of mind", which is to say, they lacked the ability to infer their own and others minds, that this was a universal effect and unique to autism (Baron-Cohen, Leslie, & Frith, 1985). Four autistic participants (20%) passed the experiment, demonstrating theory of mind, sixteen did not, yet it was claimed to be a universal effect which was unique to autism. It was hypothesised instead that the kids who passed may not "really" be autistic, instead of theory of mind having limits in its ability to explain autism. The available evidence has never been that it was universal (autistic children who passed the test were deemed to be outliers and an exception to rule, despite making up between 20–25% of the sample completing the task, reliably (Baron-Cohen, Leslie, & Frith, 1985; Yirmiya et al., 1998)."]
==Deficits==
Theory of mind impairment, or ''[[mind-blindness]]'', describes a difficulty someone would have with perspective-taking. Individuals with theory of mind impairment struggle to see phenomena from any other perspective than their own.[{{cite book |author=Moore, S. |year=2002 |title=Asperger Syndrome and the Elementary School Experience |publisher=Shawnee Mission, Kansas: Autism Asperger Publishing Company}}] Individuals who experience a theory of mind deficit have difficulty determining the intentions of others, lack understanding of how their behavior affects others, and have a difficult time with social reciprocity.[{{cite book |author=Baker, J. |year=2003 |title=Social Skills Training: for children and adolescents with Asperger Syndrome and Social-Communication Problems |publisher=Mission, Kansas: Autism Asperger Publishing Company}}] Theory of mind deficits have been observed in people with [[autism spectrum]] disorders, [[schizophrenia]], [[nonverbal learning disorder]] and along with people under the influence of alcohol and narcotics, sleep-deprived people, and people who are experiencing severe emotional or physical pain. Theory of mind deficits have also been observed in deaf children who are late signers (i.e. are born to hearing parents), but such a deficit is due to the delay in language learning, not any cognitive deficit, and therefore disappears once the child learns sign language.[{{cite journal |last1=Peterson |first1=Candida |year=2016 |title=Peer Social Skills and Theory of Mind in Children with Autism, Deafness, or Typical Development |journal=Developmental Psychology |volume=52 |issue=1 |pages=46–57 |doi=10.1037/a0039833 |pmid=26524383 |last2=Slaughter |first2=Virginia |last3=Moore |first3=Chris |last4=Wellman |first4=Henry }}]
===Autism===
In 1985 [[Simon Baron-Cohen]], [[Alan M. Leslie]], and [[Uta Frith]] suggested that children with [[autism]] do not employ theory of mind and that autistic children have particular difficulties with tasks requiring the child to understand another person's beliefs.[{{cite journal |author=Happe, F. G. |year=1995 |title=The role of age and verbal ability in the theory of mind task performance of subjects with autism |journal=Child Development |volume=66 |issue=3 |pages=843–55 |doi=10.2307/1131954 |jstor=1131954 |pmid=7789204}}] Although in a 2019 review, Gernsbacher and Yergeau argued that "the claim that autistic people lack a theory of mind is empirically questionable", as there have been numerous failed replications of classic ToM studies and the meta-analytical effect sizes of such replications were minimal to small.[{{cite book |last=Baron-Cohen |first=Simon |contribution=Precursors to a theory of mind: Understanding attention in others |editor-last=Whiten |editor-first=Andrew |title=Natural theories of mind: Evolution, development, and simulation of everyday mindreading |pages=233–251 |publisher=Basil Blackwell |location=Cambridge, Massachusetts |year=1991 |isbn=978-0-631-17194-2}}] Researchers who study the relationship between autism and theory of mind attempt to explain the connection in a variety of ways. One account assumes that theory of mind plays a role in the attribution of mental states to others and in childhood pretend play.[{{cite book |last=Leslie |first=Alan M. |chapter=Theory of mind impairment in autism |editor-last=Whiten |editor-first=Andrew |title=Natural theories of mind: Evolution, development, and simulation of everyday mindreading |publisher=Basil Blackwell |location=Cambridge, Massachusetts |year=1991 |isbn=978-0-631-17194-2}}] According to Leslie,[{{cite book |last=Hobson |first=R.P. |title=Autism and the development of mind |publisher=Lawrence Erlbaum |location=Hillsdale, N.J. |year=1995 |isbn=978-0-86377-239-9}}] in which deficits in theory of mind in autistic people result from a distortion in understanding and responding to emotions. He suggests that typically developing individuals, unlike autistic individuals, are born with a set of skills (such as social referencing ability) that later lets them comprehend and react to other people's feelings. Other scholars emphasize that autism involves a specific developmental delay, so that autistic children vary in their deficiencies, because they experience difficulty in different stages of growth. Very early setbacks can alter proper advancement of joint-attention behaviors, which may lead to a failure to form a full theory of mind.[{{cite journal |last1=Dapretto |first1=M. |year=2006 |title=Understanding emotions in others: mirror neuron dysfunction in children with autism spectrum disorders |journal=Nature Neuroscience |volume=9 |issue=1 |pages=28–30 |doi=10.1038/nn1611 |pmid=16327784 |last2=Davies |first2=M. S. |last3=Pfeifer |first3=J. H. |last4=Scott |first4=A. A. |last5=Sigman |first5=M |last6=Bookheimer |first6=S. Y. |last7=Iacoboni |first7=M |pmc=3713227 }}] A binary view regarding theory of mind contributes to the [[Sanism|stigmatization]] of autistic adults who do possess perspective-taking capacity, as the assumption that autistic people do not have empathy can become a rationale for [[dehumanization]].[{{cite journal |last=Yergeau |first= Melanie|date= 2013|title=Clinically Significant Disturbance: On Theorists Who Theorize Theory of Mind |url=https://dsq-sds.org/article/view/3876/3405 |journal= Disability Studies Quarterly |volume=33 |issue= 4|doi= 10.18061/dsq.v33i4.3876|quote=I will say something about autism, and someone will assert that nothing I've said matters or applies to anything. Because I am self-centered. Because I do not have the capacity to intuit other minds or to understand the life experiences of others. |doi-access=free}}]
Tine et al. report that autistic children score substantially lower on measures of social theory of mind (i.e., "reasoning about ''others{{'}}'' mental states", p. 1) in comparison to children diagnosed with [[Asperger syndrome]].[{{cite journal |doi=10.1155/2012/505393 |pmid=22934174 |pmc=3420603 |title=Unique Theory of Mind Differentiation in Children with Autism and Asperger Syndrome |year=2012 |last1=Tine |first1=Michele |last2=Lucariello |first2=Joan |journal=Autism Research and Treatment |volume=2012 |pages=1–11|doi-access=free }}]
Generally, children with more advanced theory of mind abilities display more advanced social skills, greater adaptability to new situations, and greater cooperation with others. As a result, these children are typically well-liked. However, "children may use their mind-reading abilities to manipulate, outwit, tease, or trick their peers."[{{cite journal |last=Astington |first=J. W. |year=2003 |title=Sometimes necessary, never sufficient: False-belief understanding and social competence |journal=Individual Differences in Theory of Mind: Implications for Typical and Atypical Development |pages=13–38}}] Individuals possessing inferior theory of mind skills, such as children with autism spectrum disorder, may be socially rejected by their peers since they are unable to communicate effectively. [[Social rejection]] has been proven to negatively impact a child's development and can put the child at greater risk of developing depressive symptoms.[{{cite journal |last1=Chung |first1=K. |year=2007 |title=Peer-mediated social skills training program for young children with high-functioning autism |journal=Research in Developmental Disabilities |volume=28 |issue=4 |pages=423–436 |doi=10.1016/j.ridd.2006.05.002 |pmid=16901676 |last2=Reavis |first2=S. |last3=Mosconi |first3=M. |last4=Drewry |first4=J. |last5=Matthews |first5=T. |last6=Tassé |first6=M. J. }}]
Peer-mediated interventions (PMI) are a school-based treatment approach for children and adolescents with autism spectrum disorder in which peers are trained to be role models in order to promote social behavior. Laghi et al. studied whether analysis of prosocial (nice) and antisocial (nasty) theory-of-mind behaviors could be used, in addition to teacher recommendations, to select appropriate candidates for PMI programs. Selecting children with advanced theory-of-mind skills who use them in prosocial ways will theoretically make the program more effective. While the results indicated that analyzing the social uses of theory of mind of possible candidates for a PMI program may increase the program's efficacy, it may not be a good predictor of a candidate's performance as a role model.[{{Cite journal|last1=Fletcher-Watson|first1=Sue|last2=McConnell|first2=Fiona|last3=Manola|first3=Eirini|last4=McConachie|first4=Helen|date=2014-03-21|title=Interventions based on the Theory of Mind cognitive model for autism spectrum disorder (ASD)|journal=The Cochrane Database of Systematic Reviews|volume=2014 |issue=3|pages=CD008785|doi=10.1002/14651858.CD008785.pub2|issn=1469-493X|pmc=6923148|pmid=24652601}}]
Some 21st century studies have shown that the results of some studies of theory of mind tests on autistic people may be misinterpreted based on the [[double empathy problem]], which proposes that rather than autistic people specifically having trouble with theory of mind, autistic people and non-autistic people have equal difficulty understanding one-another due to their neurological differences.[{{Cite journal |last=Milton |first=Damian E. M. |author-link=Damian Milton |date=2012-10-01 |title=On the ontological status of autism: the 'double empathy problem' |url=https://doi.org/10.1080/09687599.2012.710008 |journal=Disability & Society |volume=27 |issue=6 |pages=883–887 |doi=10.1080/09687599.2012.710008 |s2cid=54047060 |issn=0968-7599}}] Studies have shown that autistic adults perform better in theory of mind tests when paired with other autistic adults[{{Cite journal |last1=Crompton |first1=Catherine J. |last2=Sharp |first2=Martha |last3=Axbey |first3=Harriet |last4=Fletcher-Watson |first4=Sue |last5=Flynn |first5=Emma G. |last6=Ropar |first6=Danielle |date=2020-10-23 |title=Neurotype-Matching, but Not Being Autistic, Influences Self and Observer Ratings of Interpersonal Rapport |journal=Frontiers in Psychology |volume=11 |pages=586171 |doi=10.3389/fpsyg.2020.586171 |issn=1664-1078 |pmc=7645034 |pmid=33192918|doi-access=free }}] as well as possibly autistic close family members.[{{Cite journal |last1=Sucksmith |first1=E. |last2=Allison |first2=C. |last3=Baron-Cohen |first3=S. |last4=Chakrabarti |first4=B. |last5=Hoekstra |first5=R. A. |date=2013-01-01 |title=Empathy and emotion recognition in people with autism, first-degree relatives, and controls |journal=Neuropsychologia |language=en |volume=51 |issue=1 |pages=98–105 |doi=10.1016/j.neuropsychologia.2012.11.013 |pmid=23174401 |pmc=6345368 |issn=0028-3932}}] Academics who acknowledge the double empathy problem also propose that it is likely autistic people understand non-autistic people to a higher degree than vice-versa, due to the necessity of functioning in a non-autistic society.[{{Cite journal |last=Chown |first=Nicholas |date=2014-11-26 |title=More on the ontological status of autism and double empathy |url=http://www.tandfonline.com/doi/abs/10.1080/09687599.2014.949625 |journal=Disability & Society |language=en |volume=29 |issue=10 |pages=1672–1676 |doi=10.1080/09687599.2014.949625 |s2cid=143826899 |issn=0968-7599}}]
===Psychopathy===
[[Psychopathy]] is another deficit that is of large importance when discussing theory of mind. While psychopathic individuals show impaired emotional behavior including a lack of emotional responsiveness to others and deficient empathy, as well as impaired social behavior, there are many controversies regarding psychopathic individuals' theory of mind.[{{Cite journal |last1=Shamay-Tsoory |first1=Simone G. |last2=Harari |first2=Hagai |last3=Aharon-Peretz |first3=Judith |last4=Levkovitz |first4=Yechiel |date=May 2010 |title=The role of the orbitofrontal cortex in affective theory of mind deficits in criminal offenders with psychopathic tendencies |url=https://pubmed.ncbi.nlm.nih.gov/19501818/ |journal=Cortex; A Journal Devoted to the Study of the Nervous System and Behavior |volume=46 |issue=5 |pages=668–677 |doi=10.1016/j.cortex.2009.04.008 |issn=1973-8102 |pmid=19501818}}] Many different studies provide contradictory information on a correlation between theory of mind impairment and psychopathic individuals.
There have been some speculations made about the similarities between individuals with autism and psychopathic individuals in the theory of mind performance. In this study in 2008, the Happé's advanced test of theory of mind was presented to a group of 25 psychopaths, and 25 non-psychopaths [[Imprisonment|incarcerated]]. This test showed that there was not a difference in the performance of the task for the psychopaths and non-psychopaths. However, they were able to see that the psychopaths were performing significantly better than the most highly able adult autistic population.[{{Cite journal |last1=Blair |first1=James |last2=Sellars |first2=Carol |last3=Strickland |first3=Ian |last4=Clark |first4=Fiona |last5=Williams |first5=Akintude |last6=Smith |first6=Margaret |last7=Jones |first7=Lawrence |date=May 1996 |title=Theory of Mind in the psychopath |url=http://www.tandfonline.com/doi/abs/10.1080/09585189608409914 |journal=The Journal of Forensic Psychiatry |language=en |volume=7 |issue=1 |pages=15–25 |doi=10.1080/09585189608409914 |issn=0958-5184}}] This shows that there is not a similarity between individuals with autism and psychopathic individuals.
There have been repetitive suggestions regarding the possibility that a deficient or biased grasp of others’ mental states, or theory of mind, could potentially contribute to antisocial behavior, aggression, and psychopathy.[{{Cite journal |last1=Richell |first1=R. A. |last2=Mitchell |first2=D. G. V. |last3=Newman |first3=C. |last4=Leonard |first4=A. |last5=Baron-Cohen |first5=S. |last6=Blair |first6=R. J. R. |date=2003 |title=Theory of mind and psychopathy: can psychopathic individuals read the 'language of the eyes'? |url=https://pubmed.ncbi.nlm.nih.gov/12559146/ |journal=Neuropsychologia |volume=41 |issue=5 |pages=523–526 |doi=10.1016/s0028-3932(02)00175-6 |issn=0028-3932 |pmid=12559146}}] In one study named ‘Reading the Mind in the Eyes’, the participants view photographs of an individual’s eye and had to attribute a mental state, or emotion, to the individual. This is an interesting test because [[Magnetic resonance imaging]] studies showed that this task produced increased activity in the dorsolateral prefrontal and the left medial frontal cortices, the superior temporal gyrus, and the left amygdala. There is extensive literature suggesting amygdala dysfunction in psychopathy however, this test shows that both groups of psychopathic and non-psychopathic adults performed equally well on the test.[{{Cite journal |last1=Song |first1=Zhaorong |last2=Jones |first2=Andrew |last3=Corcoran |first3=Rhiannon |last4=Daly |first4=Natasha |last5=Abu-Akel |first5=Ahmad |last6=Gillespie |first6=Steven M. |date=August 2023 |title=Psychopathic traits and theory of mind task performance: A systematic review and meta-analysis |url=https://pubmed.ncbi.nlm.nih.gov/37172923/ |journal=Neuroscience and Biobehavioral Reviews |volume=151 |pages=105231 |doi=10.1016/j.neubiorev.2023.105231 |issn=1873-7528 |pmid=37172923}}] This study used past studies to show that there is a relationship between psychopathic individuals and theory of mind impairments.
In 2009 a study was conducted to test whether impairment in the emotional aspects of theory of mind rather that the general theory of mind abilities may account for some of the impaired social behavior in psychopathy.[{{cite journal |last1=Sprong |first1=M. |last2=Schothorst |first2=P. |last3=Vos |first3=E. |last4=Hox |first4=J. |last5=Van Engeland |first5=H. |year=2007 |title=Theory of mind in schizophrenia |journal=British Journal of Psychiatry |volume=191 |issue=1 |pages=5–13 |doi=10.1192/bjp.bp.107.035899 |pmid=17602119 |doi-access=free }}] This [[meta-analysis]] showed significant and stable deficit of theory of mind in people with schizophrenia. They performed poorly on false-belief tasks, which test the ability to understand that others can hold false beliefs about events in the world, and also on intention-inference tasks, which assess the ability to infer a character's intention from reading a short story. Schizophrenia patients with [[negative symptoms]], such as lack of emotion, motivation, or speech, have the most impairment in theory of mind and are unable to represent the mental states of themselves and of others. Paranoid schizophrenic patients also perform poorly because they have difficulty accurately interpreting others' intentions. The meta-analysis additionally showed that IQ, gender, and age of the participants do not significantly affect the performance of theory of mind tasks.[{{cite journal |last1=Ng |first1=R. |last2=Fish |first2=S. |last3=Granholm |first3=E. |year=2015 |title=Insight and theory of mind in schizophrenia |journal=Psychiatry Research |volume=225 |issue=1–2 |pages=169–174 |doi=10.1016/j.psychres.2014.11.010 |pmid=25467703 |pmc=4269286}}] Insight requires theory of mind; a patient must be able to adopt a third-person perspective and see the self as others do.[{{cite journal |last1=Konstantakopoulos |first1=G. |last2=Ploumpidis |first2=D. |last3=Oulis |first3=P. |last4=Patrikelis |first4=P. |last5=Nikitopoulou |first5=S. |last6=Papadimitriou |first6=G. N. |last7=David |first7=A. S. |year=2014 |title=The relationship between insight and theory of mind in schizophrenia |journal=Schizophrenia Research |volume=152 |issue=1 |pages=217–222 |doi=10.1016/j.schres.2013.11.022 |pmid=24321712 |s2cid=9566263 }}] A patient with good insight can accurately self-represent, by comparing himself with others and by viewing himself from the perspective of others.[{{cite journal |last1=Cassetta |first1=B. |last2=Goghari |first2=V. |year=2014 |title=Theory of mind reasoning in schizophrenia patients and non-psychotic relatives |journal=Psychiatry Research |volume=218 |issue=1–2 |pages=12–19 |doi=10.1016/j.psychres.2014.03.043 |pmid=24745472 |s2cid=13944284 }}] The meta-analysis conducted by Sprong et al. showed that patients in remission still had impairment in theory of mind. This indicates that the deficit is not merely a consequence of the active phase of schizophrenia.[{{cite journal |last1=Mehta |first1=U. M. |last2=Bhagyavathi |first2=H. D. |last3=Kumar |first3=C. N. |last4=Thirthalli |first4=J. |last5=Gangadhar |first5=B. N. |year=2014 |title=Cognitive deconstruction of parenting in schizophrenia: The role of theory of mind |journal=Australian & New Zealand Journal of Psychiatry |volume=48 |issue=3 |pages=249–258 |doi=10.1177/0004867413500350 |pmid=23928275 |s2cid=206399183 }}] Compared with healthy mothers, mothers with schizophrenia are found to be more remote, quiet, self-absorbed, insensitive, unresponsive, and to have fewer satisfying interactions with their children.[{{cite journal |last1=Lee |first1=L. |last2=Harkness |first2=K. L. |last3=Sabbagh |first3=M. A. |last4=Jacobson |first4=J. A. |year=2005 |title=Mental state decoding abilities in clinical depression |journal=Journal of Affective Disorders |volume=86 |pages=247–58 |doi=10.1016/j.jad.2005.02.007 |pmid=15935244 |issue=2–3}}] Theory of mind decoding is the ability to use information available in the immediate environment (e.g., facial expression, tone of voice, body posture) to accurately label the mental states of others. The opposite pattern, enhanced theory of mind, is observed in individuals vulnerable to depression, including those individuals with past [[Major depressive disorder|major depressive disorder (MDD)]],[{{Cite journal |last1=Harkness |first1=Kate L. |last2=Jacobson |first2=Jill A. |last3=Duong |first3=David |last4=Sabbagh |first4=Mark A. |date=April 2010 |title=Mental state decoding in past major depression: Effect of sad versus happy mood induction |url=http://dx.doi.org/10.1080/02699930902750249 |journal=Cognition & Emotion |volume=24 |issue=3 |pages=497–513 |doi=10.1080/02699930902750249 |s2cid=40376607 |issn=0269-9931}}] dysphoric individuals,[{{cite journal |last1=Harkness |first1=K. L. |last2=Sabbagh |first2=M. A. |last3=Jacobson |first3=J. A. |last4=Chowdrey |first4=N. K. |last5=Chen |first5=T. |year=2005 |title=Enhanced accuracy of mental state decoding in dysphoric college students |journal=Cognition and Emotion |volume=19 |issue=7 |pages=999–1025 |doi=10.1080/02699930541000110 |s2cid=144573653 }}] and individuals with a maternal history of MDD.[{{cite journal |last1=Harkness |first1=K. L. |last2=Washburn |first2=D. |last3=Theriault |first3=J. |last4=Lee |first4=L. |last5=Sabbagh |first5=M. A |year=2011 |title=Maternal history of depression is associated with enhanced theory of mind ability in depressed and non-depressed women |journal=Psychiatry Research |volume=189 |pages=91–96 |doi=10.1016/j.psychres.2011.06.007 |pmid=21733579 |issue=1 |s2cid=22903698 }}]
===Developmental language disorder===
Children diagnosed with [[developmental language disorder]] (DLD) exhibit much lower scores on reading and writing sections of standardized tests, yet have a normal nonverbal IQ. These language deficits can be any specific deficits in lexical semantics, syntax, or pragmatics, or a combination of multiple problems. Such children often exhibit poorer social skills than normally developing children, and seem to have problems decoding beliefs in others. A recent meta-analysis confirmed that children with DLD have substantially lower scores on theory of mind tasks compared to typically developing children.[{{cite journal |last1=Nilsson |first1=Kristine Kahr |last2=de López |first2=Kristine Jensen |title=Theory of mind in children with specific language impairment: A systematic review and meta-analysis |journal=[[Child Development (journal)|Child Development]] |volume=87 |issue=1 |pages=143–153 |doi=10.1111/cdev.12462 |pmid=26582261 |date=January–February 2016 }}] This strengthens the claim that language development is related to theory of mind.
==Brain mechanisms==
=== In non autistic people ===
Research on theory of mind in [[autism]] led to the view that mentalizing abilities are subserved by dedicated mechanisms that can—in some cases—be impaired while general cognitive function remains largely intact.
[[Neuroimaging]] research supports this view, demonstrating specific brain regions are consistently engaged during theory of mind tasks. [[Positron emission tomography]] (PET) research on theory of mind, using verbal and pictorial story comprehension tasks, identifies a set of brain regions including the [[prefrontal cortex|medial prefrontal cortex]] (mPFC), and area around posterior [[superior temporal sulcus]] (pSTS), and sometimes [[precuneus]] and [[amygdala]]/[[Brodmann area 38|temporopolar cortex]].[{{cite journal |doi=10.1016/S1364-6613(02)00025-6 |title=Functional imaging of 'theory of mind' |year=2003 |last1=Gallagher |first1=Helen L. |last2=Frith |first2=Christopher D. |journal=Trends in Cognitive Sciences |volume=7 |issue=2 |pages=77–83 |pmid=12584026|citeseerx=10.1.1.319.778 |s2cid=14873867 }}][{{Cite journal |last1=Schurz |first1=Matthias |last2=Radua |first2=Joaquim |last3=Tholen |first3=Matthias G. |last4=Maliske |first4=Lara |last5=Margulies |first5=Daniel S. |last6=Mars |first6=Rogier B. |last7=Sallet |first7=Jerome |last8=Kanske |first8=Philipp |date=March 2021 |title=Toward a hierarchical model of social cognition: A neuroimaging meta-analysis and integrative review of empathy and theory of mind. |url=http://dx.doi.org/10.1037/bul0000303 |journal=Psychological Bulletin |language=en |volume=147 |issue=3 |pages=293–327 |doi=10.1037/bul0000303 |pmid=33151703 |hdl=2066/226714 |s2cid=226272359 |issn=1939-1455|hdl-access=free }}] Research on the neural basis of theory of mind has diversified, with separate lines of research focusing on the understanding of beliefs, intentions, and more complex properties of minds such as psychological traits.
Studies from [[Rebecca Saxe]]'s lab at MIT, using a false-belief versus false-photograph task contrast aimed at isolating the mentalizing component of the false-belief task, have consistently found activation in the mPFC, precuneus, and temporoparietal junction (TPJ), right-lateralized.[{{cite journal |doi=10.1016/S1053-8119(03)00230-1 |title=People thinking about thinking peopleThe role of the temporo-parietal junction in "theory of mind" |year=2003 |last1=Saxe |first1=R |last2=Kanwisher |first2=N |journal=NeuroImage |volume=19 |issue=4 |pages=1835–42 |pmid=12948738|title-link=Temporoparietal junction |s2cid=206118958 }}][{{cite journal |doi=10.1080/17470910601000446 |title=Reading minds versus following rules: Dissociating theory of mind and executive control in the brain |year=2006 |last1=Saxe |first1=Rebecca |last2=Schulz |first2=Laura E. |author2-link=Laura Schulz |last3=Jiang |first3=Yuhong V. |journal=Social Neuroscience |volume=1 |issue=3–4 |pages=284–98 |pmid=18633794|citeseerx=10.1.1.392.1433 |s2cid=10733339 }}] In particular, Saxe et al. proposed that the right TPJ ([[rTPJ]]) is selectively involved in representing the beliefs of others.[{{cite journal |doi=10.1111/j.1467-9280.2006.01768.x |title=It's the Thought That Counts: Specific Brain Regions for One Component of Theory of Mind |year=2006 |last1=Saxe |first1=R. |last2=Powell |first2=L. J. |journal=Psychological Science |volume=17 |issue=8 |pages=692–9 |pmid=16913952|s2cid=4656022 }}] Some debate exists, as the same rTPJ region is consistently activated during spatial reorienting of visual attention;[{{cite journal |doi=10.1177/1073858407304654 |title=The Role of the Right Temporoparietal Junction in Social Interaction: How Low-Level Computational Processes Contribute to Meta-Cognition |year=2007 |last1=Decety |first1=J. |last2=Lamm |first2=C. |journal=The Neuroscientist |volume=13 |issue=6 |pages=580–93 |pmid=17911216|s2cid=37026268 }}][{{cite journal |doi=10.1093/cercor/bhm051 |title=Activity in Right Temporo-Parietal Junction is Not Selective for Theory-of-Mind |year=2007 |last1=Mitchell |first1=J. P. |journal=Cerebral Cortex |volume=18 |issue=2 |pages=262–71 |pmid=17551089|doi-access=free }}] [[Jean Decety]] from the University of Chicago and Jason Mitchell from Harvard thus propose that the rTPJ subserves a more general function involved in both false-belief understanding and attentional reorienting, rather than a mechanism specialized for social cognition. However, it is possible that the observation of overlapping regions for representing beliefs and attentional reorienting may simply be due to adjacent, but distinct, neuronal populations that code for each. The resolution of typical fMRI studies may not be good enough to show that distinct/adjacent neuronal populations code for each of these processes. In a study following Decety and Mitchell, Saxe and colleagues used higher-resolution fMRI and showed that the peak of activation for attentional reorienting is approximately 6–10 mm above the peak for representing beliefs. Further corroborating that differing populations of neurons may code for each process, they found no similarity in the patterning of fMRI response across space.[{{cite journal |doi=10.1371/journal.pone.0004869 |title=Distinct Regions of Right Temporo-Parietal Junction Are Selective for Theory of Mind and Exogenous Attention |year=2009 |editor1-last=Lauwereyns |editor1-first=Jan |last1=Scholz |first1=Jonathan |last2=Triantafyllou |first2=Christina |last3=Whitfield-Gabrieli |first3=Susan |last4=Brown |first4=Emery N. |last5=Saxe |first5=Rebecca |journal=PLOS ONE |volume=4 |issue=3 |pages=e4869 |pmid=19290043 |pmc=2653721|bibcode=2009PLoSO...4.4869S |doi-access=free }}]
Using single-cell recordings in the human [[dorsomedial prefrontal cortex]] (dmPFC), researchers at [[Massachusetts General Hospital|MGH]] identified neurons that encode information about others' beliefs, which were distinct from self-beliefs, across different scenarios in a false-belief task. They further showed that these neurons could provide detailed information about others' beliefs, and could accurately predict these beliefs' verity.[{{Cite journal |author=Jamali, Mohsen |author2=Grannan, Benjamin L. |author3=Fedorenko, Evelina |author4=Saxe, Rebecca |author5=Báez-Mendoza, Raymundo |author6=Williams, Ziv M. |title=Single-neuronal predictions of others' beliefs in humans |journal=Nature |year=2021 |volume=591 |issue=7851 |pages=610–614 |doi=10.1038/s41586-021-03184-0 |pmid=33505022 |pmc=7990696 |bibcode=2021Natur.591..610J}}] These findings suggest a prominent role of distinct neuronal populations in the dmPFC in theory of mind complemented by the TPJ and pSTS.
Functional imaging also illuminates the detection of mental state information in animations of moving geometric shapes similar to those used in Heider and Simmel (1944),[Heider F, & Simmel M (1944). An experimental study of apparent behavior. The American Journal of Psychology, 57, 243–259.] which typical humans automatically perceive as social interactions laden with intention and emotion. Three studies found remarkably similar patterns of activation during the perception of such animations versus a random or deterministic motion control: mPFC, pSTS, [[fusiform face area]] (FFA), and amygdala were selectively engaged during the theory of mind condition.[{{Unbulleted list citebundle
|1={{cite journal |doi=10.1006/nimg.2000.0612 |title=Movement and Mind: A Functional Imaging Study of Perception and Interpretation of Complex Intentional Movement Patterns |year=2000 |last1=Castelli |first1=Fulvia |last2=Happé |first2=Francesca |last3=Frith |first3=Uta |last4=Frith |first4=Chris |journal=NeuroImage |volume=12 |issue=3 |pages=314–25 |pmid=10944414|s2cid=22294793 }}
|2={{cite journal |doi=10.1080/02643290342000005 |title=Neural Foundations for Understanding Social and Mechanical Concepts |year=2003 |last1=Martin |first1=Alex |last2=Weisberg |first2=Jill |journal=Cognitive Neuropsychology |volume=20 |issue=3–6 |pages=575–87 |pmid=16648880 |pmc=1450338}}
|3={{cite journal |doi=10.1098/rstb.2002.1208 |title=The role of the fusiform face area in social cognition: Implications for the pathobiology of autism |year=2003 |last1=Schultz |first1=R. T. |last2=Grelotti |first2=D. J. |last3=Klin |first3=A. |last4=Kleinman |first4=J. |last5=Van Der Gaag |first5=C. |last6=Marois |first6=R. |last7=Skudlarski |first7=P. |journal=Philosophical Transactions of the Royal Society B: Biological Sciences |volume=358 |issue=1430 |pages=415–427 |pmid=12639338 |pmc=1693125}}}}] Another study presented subjects with an animation of two dots moving with a parameterized degree of intentionality (quantifying the extent to which the dots chased each other), and found that pSTS activation correlated with this parameter.[{{cite journal |doi=10.1016/j.neuron.2004.12.052 |title=Activation in Posterior Superior Temporal Sulcus Parallels Parameter Inducing the Percept of Animacy |year=2005 |last1=Schultz |first1=Johannes |last2=Friston |first2=Karl J. |last3=O'Doherty |first3=John |last4=Wolpert |first4=Daniel M. |last5=Frith |first5=Chris D. |journal=Neuron |volume=45 |issue=4 |pages=625–35 |pmid=15721247|s2cid=9435424 |doi-access=free }}]
A separate body of research implicates the posterior superior temporal sulcus in the perception of intentionality in human action. This area is also involved in perceiving biological motion, including body, eye, mouth, and point-light display motion.[{{cite journal |doi=10.1016/S1364-6613(00)01501-1 |title=Social perception from visual cues: Role of the STS region |year=2000 |last1=Allison |first1=Truett |last2=Puce |first2=Aina |last3=McCarthy |first3=Gregory |journal=Trends in Cognitive Sciences |volume=4 |issue=7 |pages=267–278 |pmid=10859571|s2cid=11942671 }}] One study found increased pSTS activation while watching a human lift his hand versus having his hand pushed up by a piston (intentional versus unintentional action).[{{cite journal |doi=10.1080/17470910701476686 |title=Perceived causality influences brain activity evoked by biological motion |year=2008 |last1=Morris |first1=James P. |last2=Pelphrey |first2=Kevin A. |last3=McCarthy |first3=Gregory |journal=Social Neuroscience |volume=3 |pages=16–25 |pmid=18633843 |issue=1|s2cid=24726037 }}] Several studies found increased pSTS activation when subjects perceive a human action that is incongruent with the action expected from the actor's context and inferred intention. Examples would be: a human performing a reach-to-grasp motion on empty space next to an object, versus grasping the object;[{{cite journal |doi=10.1162/0898929042947900 |title=Grasping the Intentions of Others: The Perceived Intentionality of an Action Influences Activity in the Superior Temporal Sulcus during Social Perception |year=2004 |last1=Pelphrey |first1=Kevin A. |last2=Morris |first2=James P. |last3=McCarthy |first3=Gregory |journal=Journal of Cognitive Neuroscience |volume=16 |issue=10 |pages=1706–16 |pmid=15701223|s2cid=207576449 |url=https://cdr.lib.unc.edu/downloads/wd376534w }}] a human shifting eye gaze toward empty space next to a checkerboard target versus shifting gaze toward the target;[{{cite journal |doi=10.1016/j.neuroimage.2005.03.027 |title=Taking an "intentional stance" on eye-gaze shifts: A functional neuroimaging study of social perception in children |year=2005 |last1=Mosconi |first1=Matthew W. |last2=Mack |first2=Peter B. |last3=McCarthy |first3=Gregory |last4=Pelphrey |first4=Kevin A. |journal=NeuroImage |volume=27 |pages=247–52 |pmid=16023041 |issue=1|s2cid=25792636 }}] an unladen human turning on a light with his knee, versus turning on a light with his knee while carrying a pile of books;[{{cite journal |doi=10.1016/j.cub.2007.11.057 |title=Investigating Action Understanding: Inferential Processes versus Action Simulation |year=2007 |last1=Brass |first1=Marcel |last2=Schmitt |first2=Ruth M. |last3=Spengler |first3=Stephanie |last4=Gergely |first4=György |journal=Current Biology |volume=17 |issue=24 |pages=2117–21 |pmid=18083518|s2cid=14318837 |doi-access=free |bibcode=2007CBio...17.2117B }}] and a walking human pausing as he passes behind a bookshelf, versus walking at a constant speed.[{{cite journal |doi=10.1016/j.neuropsychologia.2004.04.015 |title=A region of right posterior superior temporal sulcus responds to observed intentional actions |year=2004 |last1=Saxe |first1=R |last2=Xiao |first2=D.-K |last3=Kovacs |first3=G |last4=Perrett |first4=D.I |last5=Kanwisher |first5=N |journal=Neuropsychologia |volume=42 |issue=11 |pages=1435–46 |pmid=15246282|s2cid=15079818 }}] In these studies, actions in the "congruent" case have a straightforward goal, and are easy to explain in terms of the actor's intention. The incongruent actions, on the other hand, require further explanation (why would someone twist empty space next to a gear?), and apparently demand more processing in the STS. This region is distinct from the temporoparietal area activated during false belief tasks.[{{Unbulleted list citebundle
|1={{cite journal|last1=Rowe|first1=Andrea D|last2=Bullock|first2=Peter R|last3=Polkey|first3=Charles E|last4=Morris|first4=Robin G|title='Theory of mind' impairments and their relationship to executive functioning following frontal lobe excisions|journal=Brain|date=2001|volume=124|issue=3|pages=600–616|doi=10.1093/brain/124.3.600|pmid=11222459|doi-access=free}}
|2={{cite journal |doi=10.1038/nn1223 |title=Left temporoparietal junction is necessary for representing someone else's belief |year=2004 |last1=Samson |first1=Dana |last2=Apperly |first2=Ian A |last3=Chiavarino |first3=Claudia |last4=Humphreys |first4=Glyn W |journal=Nature Neuroscience |volume=7 |issue=5 |pages=499–500 |pmid=15077111|s2cid=9818818 }} }}] This shows that theory of mind abilities are associated with specific parts of the human brain. However, the fact that the [[medial prefrontal cortex]] and temporoparietal junction are necessary for theory of mind tasks does not imply that these regions are specific to that function.[{{cite journal |doi=10.1080/17470910601029221 |title=What's domain-specific about theory of mind? |year=2006 |last1=Stone |first1=Valerie E. |last2=Gerrans |first2=Philip |journal=Social Neuroscience |volume=1 |issue=3–4 |pages=309–19 |pmid=18633796|s2cid=24446270 }}] TPJ and mPFC may subserve more general functions necessary for Theory of Mind.
Research by [[Vittorio Gallese]], Luciano Fadiga, and [[Giacomo Rizzolatti]][{{cite journal |doi=10.1146/annurev.neuro.27.070203.144230 |title=The Mirror-Neuron System |year=2004 |last1=Rizzolatti |first1=Giacomo |last2=Craighero |first2=Laila |journal=Annual Review of Neuroscience |volume=27 |pages=169–92 |pmid=15217330 |issue=1|s2cid=1729870 }}] shows that some sensorimotor [[neuron]]s, referred to as [[mirror neuron]]s and first discovered in the [[premotor cortex]] of [[rhesus monkey]]s, may be involved in action understanding. Single-electrode recording revealed that these neurons fired when a monkey performed an action, as well as when the monkey viewed another agent performing the same action. [[fMRI]] studies with human participants show brain regions (assumed to contain mirror neurons) that are active when one person sees another person's goal-directed action.[{{cite journal |doi=10.1371/journal.pbio.0030079 |title=Grasping the Intentions of Others with One's Own Mirror Neuron System |year=2005 |last1=Iacoboni |first1=Marco |last2=Molnar-Szakacs |first2=Istvan |last3=Gallese |first3=Vittorio |last4=Buccino |first4=Giovanni |last5=Mazziotta |first5=John C. |last6=Rizzolatti |first6=Giacomo |journal=PLOS Biology |volume=3 |issue=3 |pages=e79 |pmid=15736981 |pmc=1044835 |doi-access=free }}] These data led some authors to suggest that mirror neurons may provide the basis for theory of mind in the brain, and to support [[simulation theory of mind reading]].[{{cite journal |doi=10.1016/S1364-6613(98)01262-5 |title=Mirror neurons and the simulation theory of mind-reading |year=1998 |last1=Gallese |first1=V |journal=Trends in Cognitive Sciences |volume=2 |issue=12 |pages=493–501 |pmid=21227300 |last2=Goldman |first2=A|s2cid=10108122 }}]
There is also evidence against a link between mirror neurons and theory of mind. First, [[macaque|macaque monkeys]] have mirror neurons but do not seem to have a 'human-like' capacity to understand theory of mind and belief. Second, fMRI studies of theory of mind typically report activation in the mPFC, temporal poles, and TPJ or STS,[{{cite journal |doi=10.1098/rstb.2002.1218 |title=Development and neurophysiology of mentalizing |year=2003 |last1=Frith |first1=U. |last2=Frith |first2=C. D. |journal=Philosophical Transactions of the Royal Society B: Biological Sciences |volume=358 |issue=1431 |pages=459–73 |pmid=12689373 |pmc=1693139}}] but those brain areas are not part of the mirror neuron system. Some investigators, like developmental psychologist [[Andrew Meltzoff]] and neuroscientist [[Jean Decety]], believe that mirror neurons merely facilitate learning through imitation and may provide a precursor to the development of theory of mind.[{{Unbulleted list citebundle
|1={{cite journal |doi=10.1098/rstb.2002.1261 |title=What imitation tells us about social cognition: A rapprochement between developmental psychology and cognitive neuroscience |year=2003 |last1=Meltzoff |first1=A. N. |last2=Decety |first2=J. |journal=Philosophical Transactions of the Royal Society B: Biological Sciences |volume=358 |issue=1431 |pages=491–500 |pmid=12689375 |pmc=1351349}}
|2={{cite journal |doi=10.3758/BF03193831 |title=Weaving the fabric of social interaction: Articulating developmental psychology and cognitive neuroscience in the domain of motor cognition |year=2006 |last1=Sommerville |first1=Jessica A. |last2=Decety |first2=Jean |journal=Psychonomic Bulletin & Review |volume=13 |issue=2 |pages=179–200 |pmid=16892982|s2cid=14689479}} }}] Others, like philosopher [[Shaun Gallagher]], suggest that mirror-neuron activation, on a number of counts, fails to meet the definition of simulation as proposed by the simulation theory of mindreading.[{{cite journal|doi=10.1080/17470910601183549 |title=Simulation trouble |year=2007 |last1=Gallagher |first1=Shaun |journal=Social Neuroscience |volume=2 |issue=3–4 |pages=353–65 |pmid=18633823|s2cid=205924856 }}][{{cite book |doi=10.1007/978-1-59745-479-7_16 |chapter=Neural Simulation and Social Cognition |year=2008 |last1=Gallagher |first1=Shaun |title=Mirror Neuron Systems |isbn=978-1-934115-34-3 |pages=355–371 }}]
===In autism===
Several neuroimaging studies have looked at the neural basis for theory of mind impairment in subjects with [[Asperger syndrome]] and [[high-functioning autism]] (HFA). The first PET study of theory of mind in autism (also the first neuroimaging study using a task-induced activation paradigm in autism) replicated a prior study in non autistic individuals, which employed a story-comprehension task.[{{Unbulleted list citebundle
|1={{cite journal |last1=Happe |year=1996 |title='Theory of mind' in the brain. Evidence from a PET scan study of Asperger syndrome |journal=NeuroReport |volume=8 |issue=1 |pages=197–201 |doi=10.1097/00001756-199612200-00040 |pmid=9051780 |first1=F |last2=Ehlers |first2=S |last3=Fletcher |first3=P |last4=Frith |first4=U |last5=Johansson |first5=M |last6=Gillberg |first6=C |last7=Dolan |first7=R |last8=Frackowiak |first8=R |last9=Frith |first9=C |hdl=21.11116/0000-0001-A166-6 |s2cid=2970614 |hdl-access=free }}
|2={{cite journal |last1=Fletcher |year=1995 |title=Other minds in the brain: a functional imaging study of 'theory of mind' in story comprehension |journal=Cognition |volume=57 |issue=2 |pages=109–128 |doi=10.1016/0010-0277(95)00692-R |pmid=8556839 |first1=P. C. |last2=Happé |first2=F |last3=Frith |first3=U |last4=Baker |first4=S. C. |last5=Dolan |first5=R. J. |last6=Frackowiak |first6=R. S. |last7=Frith |first7=C. D. |hdl=21.11116/0000-0001-A1FA-F |s2cid=16321133 |hdl-access=free }} }}] This study found displaced and diminished [[Prefrontal cortex|mPFC]] activation in subjects with autism. However, because the study used only six subjects with autism, and because the spatial resolution of PET imaging is relatively poor, these results should be considered preliminary.
A subsequent fMRI study scanned normally developing adults and adults with HFA while performing a "reading the mind in the eyes" task: viewing a photo of a human's eyes and choosing which of two adjectives better describes the person's mental state, versus a gender discrimination control.[{{cite journal |last1=Baron-Cohen |first1=Simon |display-authors=etal |title=Social intelligence in the normal and autistic brain: an fMRI study |journal=[[European Journal of Neuroscience]] |volume=11 |issue=6 |pages=1891–1898 |doi=10.1046/j.1460-9568.1999.00621.x |pmid=10336657 |date=June 1999 |s2cid=9436565 }}] The authors found activity in [[orbitofrontal cortex]], STS, and amygdala in normal subjects, and found less amygdala activation and abnormal STS activation in subjects with autism.
A more recent PET study looked at brain activity in individuals with HFA and Asperger syndrome while viewing Heider-Simmel animations (see above) versus a random motion control.[{{cite journal |last1=Castelli |year=2002 |title=Autism, Asperger syndrome and brain mechanisms for the attribution of mental states to animated shapes |journal=Brain |volume=125 |issue=Pt 8 |pages=1839–1849 |doi=10.1093/brain/awf189 |pmid=12135974 |first1=F |last2=Frith |first2=C |last3=Happé |first3=F |last4=Frith |first4=U |doi-access=free }}] In contrast to normally-developing subjects, those with autism showed little STS or FFA activation, and less [[Prefrontal cortex|mPFC]] and amygdala activation. Activity in [[extrastriate cortex|extrastriate regions]] V3 and LO was identical across the two groups, suggesting intact lower-level visual processing in the subjects with autism. The study also reported less functional connectivity between STS and V3 in the autism group. However decreased temporal correlation between activity in STS and V3 would be expected simply from the lack of an evoked response in STS to intent-laden animations in subjects with autism. A more informative analysis would be to compute functional connectivity after regressing out evoked responses from all-time series.
A subsequent study, using the incongruent/congruent gaze-shift paradigm described above, found that in high-functioning adults with autism, posterior STS (pSTS) activation was undifferentiated while they watched a human shift gaze toward a target and then toward adjacent empty space.[{{cite journal |last1=Pelphrey |year=2005 |title=Neural basis of eye gaze processing deficits in autism |journal=Brain |volume=128 |issue=Pt 5 |pages=1038–1048 |doi=10.1093/brain/awh404 |pmid=15758039 |first1=K. A. |last2=Morris |first2=J. P. |last3=McCarthy |first3=G |doi-access=free }}] The lack of additional STS processing in the incongruent state may suggest that these subjects fail to form an expectation of what the actor should do given contextual information, or that feedback about the violation of this expectation does not reach STS. Both explanations involve an impairment or deficit in the ability to link eye gaze shifts with intentional explanations. This study also found a significant anticorrelation between STS activation in the incongruent-congruent contrast and social subscale score on the [[Autism Diagnostic Interview-Revised]], but not scores on the other subscales.
An fMRI study demonstrated that the right [[temporoparietal junction]] (rTPJ) of higher-functioning adults with autism was not more selectively activated for mentalizing judgments when compared to physical judgments about self and other.[{{cite journal |journal=NeuroImage |year=2011 |volume=56 |issue=3 |pages=1832–1838 |doi=10.1016/j.neuroimage.2011.02.067 |pmid=21356316 |vauthors=Lombardo MV, Chakrabarti B, Bullmore ET, Baron-Cohen S |collaboration=MRC AIMS Consortium |title=Specialization of right temporo-parietal junction for mentalizing and its relation to social deficits in autism |s2cid=14782731 }}] rTPJ selectivity for mentalizing was also related to individual variation on clinical measures of social impairment: individuals whose rTPJ was increasingly more active for mentalizing compared to physical judgments were less socially impaired, while those who showed little to no difference in response to mentalizing or physical judgments were the most socially impaired. This evidence builds on work in typical development that suggests rTPJ is critical for representing mental state information, whether it is about oneself or others. It also points to an explanation at the neural level for the pervasive [[mind-blindness]] difficulties in autism that are evident throughout the lifespan.[{{cite journal |journal=Science |year=2009 |volume=325 |issue=5942 |pages=883–885 |doi=10.1126/science.1176170 |pmid=19608858 |vauthors=Senju A, Southgate V, White S, Frith U |title=Mindblind eyes: an absence of spontaneous theory of mind in Asperger syndrome |bibcode=2009Sci...325..883S |s2cid=9747918 |url=https://eprints.bbk.ac.uk/id/eprint/2566/1/2566.pdf }}]
===In schizophrenia===
The brain regions associated with theory of mind include the [[superior temporal gyrus]] (STS), the temporoparietal junction (TPJ), the medial prefrontal cortex ([[Prefrontal cortex|mPFC]]), the precuneus, and the amygdala.[{{cite journal |last1=Pedersen |first1=A. |last2=Koelkebeck |first2=K. |last3=Brandt |first3=M. |last4=Wee |first4=M. |last5=Kueppers |first5=K. A. |last6=Kugel |first6=H. |last7=Kohl |first7=W. |last8=Bauer |first8=J. |last9=Ohrmann |first9=P. |year=2012 |title=Theory of mind in patients with schizophrenia: Is mentalizing delayed? |journal=Schizophrenia Research |volume=137 |issue=1–3 |pages=224–229 |doi=10.1016/j.schres.2012.02.022 |pmid=22406281 |s2cid=3167761 }}] The reduced activity in the mPFC of individuals with schizophrenia is associated with theory of mind deficit and may explain impairments in social function among people with schizophrenia.[{{cite journal |last1=Dodell-Feder |first1=D. |last2=Tully |first2=L. M. |last3=Lincoln |first3=S. H. |last4=Hooker |first4=C. I. |year=2013 |title=The neural basis of theory of mind and its relationship to social functioning and social anhedonia in individuals with schizophrenia |journal=NeuroImage: Clinical |volume=4 |pages=154–163 |doi=10.1016/j.nicl.2013.11.006 |pmid=24371798 |pmc=3871293 }}] Increased neural activity in mPFC is related to better perspective-taking, emotion management, and increased social functioning.[{{cite journal |last1=Baron-Cohen |first1=Simon |last2=Wheelwright |first2=Sally |last3=Hill |first3=Jacqueline |last4=Raste |first4=Yogini |last5=Plumb |first5=Ian |title=The "Reading the Mind in the Eyes" Test revised version: a study with normal adults, and adults with Asperger syndrome or high-functioning autism |journal=[[Journal of Child Psychology and Psychiatry]] |volume=42 |issue=2 |pages=241–251 |doi=10.1111/1469-7610.00715 |pmid=11280420 |date=February 2001 |s2cid=3016793 |url=http://depts.washington.edu/uwcssc/sites/default/files/hw00/d40/uwcssc/sites/default/files/Mind%20in%20the%20Eyes%20Scale_0.pdf}}] (RME), are possibly drivers of successful group performance.[{{Cite journal|last1=Woolley|first1=Anita Williams|last2=Chabris|first2=Christopher F.|last3=Pentland|first3=Alex|last4=Hashmi|first4=Nada|last5=Malone|first5=Thomas W.|date=2010-10-29|title=Evidence for a Collective Intelligence Factor in the Performance of Human Groups|journal=Science|volume=330|issue=6004|pages=686–688|doi=10.1126/science.1193147|pmid=20929725|bibcode=2010Sci...330..686W|s2cid=74579|doi-access=free}}] High group average scores on the RME are correlated with the [[collective intelligence]] factor ''c'', defined as a group's ability to perform a wide range of mental tasks,[{{Cite journal|last1=Engel|first1=David|last2=Woolley|first2=Anita Williams|last3=Jing|first3=Lisa X.|last4=Chabris|first4=Christopher F.|last5=Malone|first5=Thomas W.|date=2014-12-16|title=Reading the Mind in the Eyes or Reading between the Lines? Theory of Mind Predicts Collective Intelligence Equally Well Online and Face-To-Face|journal=PLOS ONE|volume=9|issue=12|pages=e115212 |doi=10.1371/journal.pone.0115212 |pmc=4267836|pmid=25514387|bibcode=2014PLoSO...9k5212E|doi-access=free}}] a group intelligence measure similar to the [[G factor (psychometrics)|''g'' factor for general individual intelligence]]. RME is a theory of mind test for adults[{{cite journal |last1=Hallerbäck |first1=Maria Unenge |last2=Lugnegård |first2=Tove |last3=Hjärthag |first3=Fredrik |last4=Gillberg |first4=Christopher |title=The Reading the Mind in the Eyes Test: test-retest reliability of a Swedish version |journal=Cognitive Neuropsychiatry |volume=14 |issue=2 |pages=127–143 |doi=10.1080/13546800902901518 |pmid=19370436 |date=2009 |s2cid=28946179 }}] and constantly differentiates control groups from individuals with functional autism or [[Asperger syndrome]].[{{Cite journal|last1=Pinkham|first1=Amy E.|last2=Penn|first2=David L.|last3=Green|first3=Michael F.|last4=Buck|first4=Benjamin|last5=Healey|first5=Kristin|last6=Harvey|first6=Philip D.|date=2014-07-01|title=The Social Cognition Psychometric Evaluation Study: Results of the Expert Survey and RAND Panel|journal=Schizophrenia Bulletin|volume=40|issue=4|pages=813–823|doi=10.1093/schbul/sbt081|pmc=4059426|pmid=23728248}}]
==Evolution==
The evolutionary origin of theory of mind remains obscure. While many theories make claims about its role in the development of human language and social cognition, few of them specify in detail any evolutionary neurophysiological precursors. One theory claims that theory of mind has its roots in two defensive reactions—immobilization stress and [[Apparent death|tonic immobility]]—which are implicated in the handling of stressful encounters and also figure prominently in mammalian childrearing practice.[{{Cite journal |last=Tsoukalas |first=Ioannis |year=2017 |title=Theory of Mind: Towards an Evolutionary Theory |journal=Evolutionary Psychological Science |volume=4 |pages=38–66 |doi=10.1007/s40806-017-0112-x |doi-access=free}}[https://drive.google.com/file/d/1CCwSs2TrvPwwSU8rDyUkvtLYAuYfylMD/view?usp=sharing Pdf.]] Their combined effect seems capable of producing many of the hallmarks of theory of mind, such as eye-contact, gaze-following, inhibitory control, and intentional attributions.
==Non-human==
{{see also|Animal consciousness|Theory of mind in animals}}
An open question is whether non-human animals have a [[genetics|genetic]] endowment and [[social psychology|social]] environment that allows them to acquire a theory of mind like human children do.[{{cite book |last1=Ristau |first1=Carolyn A. |year=1991 |chapter=Aspects of the cognitive ethology of an injury-feigning bird, the piping plovers |chapter-url=https://books.google.com/books?id=bKzhZYiQfZEC&pg=PA91 |editor1-first=Carolyn A. |editor1-last=Ristau |title=Cognitive Ethology: Essays in Honor of Donald R. Griffin |pages=91–126 |location=Hillsdale, New Jersey |publisher=Lawrence Erlbaum |isbn=978-1-134-99085-6}}] and dogs,[{{cite journal |doi=10.1007/s10071-008-0175-y |title=Attention to attention in domestic dog (Canis familiaris) dyadic play |year=2008 |last1=Horowitz |first1=Alexandra |journal=Animal Cognition |volume=12 |pages=107–18 |pmid=18679727 |issue=1|s2cid=207050813 }}] which show preliminary evidence of understanding attention—one precursor of theory of mind—in others.
There has been some controversy over the interpretation of evidence purporting to show theory of mind ability—or inability—in animals.[{{cite journal |doi=10.1016/S1364-6613(03)00053-6 |title=Chimpanzee minds: Suspiciously human? |year=2003 |last1=Povinelli |first1=Daniel J. |last2=Vonk |first2=Jennifer |journal=Trends in Cognitive Sciences |volume=7 |issue=4 |pages=157–160 |pmid=12691763|citeseerx=10.1.1.494.1478 |s2cid=3473587 }}] For example, Povinelli ''et al.''[{{cite journal |last1=Povinelli |first1=D. J. |last2=Nelson |first2=K. E. |last3=Boysen |first3=S. T. |year=1990 |title=Inferences about guessing and knowing by chimpanzees (''Pan troglodytes'') |url=https://animalstudiesrepository.org/acwp_asie/143 |journal=Journal of Comparative Psychology |volume=104 |issue=3 |pages=203–210 |doi=10.1037/0735-7036.104.3.203 |pmid=2225758 }}] presented chimpanzees with the choice of two experimenters from whom to request food: one who had seen where food was hidden, and one who, by virtue of one of a variety of mechanisms (having a bucket or bag over his head, a blindfold over his eyes, or being turned away from the baiting) does not know, and can only guess. They found that the animals failed in most cases to differentially request food from the "knower". By contrast, Hare, Call, and Tomasello found that subordinate chimpanzees were able to use the knowledge state of dominant rival chimpanzees to determine which container of hidden food they approached.[{{cite journal |last1=Hare |first1=B. |last2=Call |first2=J. |last3=Tomasello |first3=M. |year=2001 |title=Do chimpanzees know what conspecifics know and do not know? |journal=Animal Behaviour |volume=61 |issue=1 |pages=139–151 |doi=10.1006/anbe.2000.1518 |pmid=11170704 |s2cid=3402554 }}] William Field and [[Sue Savage-Rumbaugh]] believe that bonobos have developed theory of mind, and cite their communications with a captive bonobo, [[Kanzi]], as evidence.[{{cite news|last=Hamilton|first=Jon|title=A Voluble Visit with Two Talking Apes|url=https://www.npr.org/2006/07/08/5503685/a-voluble-visit-with-two-talking-apes|access-date=21 March 2012|newspaper=NPR|date=8 July 2006}}]
In one experiment, ravens (''[[Common raven|Corvus corax]]'') took into account visual access of unseen conspecifics. The researchers argued that "ravens can generalize from their own perceptual experience to infer the possibility of being seen".[{{cite journal |title=Ravens attribute visual access to unseen competitors |author1=Thomas Bugnyar|author2=Stephan A. Reber|author3=Cameron Buckner |journal=Nature Communications |year=2015 |volume=7 |pages=10506 |doi=10.1038/ncomms10506 |pmid=26835849 |pmc=4740864 |bibcode=2016NatCo...710506B }}]
Evolutionary anthropologist Christopher Krupenye studied the existence of theory of mind, and particularly false beliefs, in non-human primates.[{{cite journal |title=Great apes anticipate that other individuals will act according to false beliefs |author1=Christopher Krupenye|author2=Fumihiro Kano|author3=Satoshi Hirata|author4=Josep Call|author5=Michael Tomasello |journal=Science |year=2016 |volume=354 |issue=6308 |pages=110–114 |doi=10.1126/science.aaf8110 |pmid=27846501|bibcode=2016Sci...354..110K |hdl=10161/13632 |doi-access=free |hdl-access=free }}]
[[Keren Haroush]] and [[Ziv Williams]] outlined the case for a group of [[neuron]]s in primates' brains that uniquely predicted the choice selection of their interacting partner. These primates' neurons, located in the [[anterior cingulate cortex]] of rhesus monkeys, were observed using single-unit recording while the monkeys played a variant of the iterative [[prisoner's dilemma]] game.[{{cite journal|vauthors=Haroush K, Williams Z|year=2015|title=Neuronal Prediction of Opponent's Behavior during Cooperative Social Interchange in Primates|journal=Cell|volume=160|issue=6|pages=1233–1245|doi=10.1016/j.cell.2015.01.045|pmc=4364450|pmid=25728667}}] By identifying cells that represent the yet unknown intentions of a game partner, Haroush & Williams' study supports the idea that theory of mind may be a fundamental and generalized process, and suggests that ''[[anterior cingulate cortex]]'' neurons may act to complement the function of mirror neurons during [[social interchange]].[{{cite journal|vauthors=Sanfey AG, Civai C, Vavra P|year=2015|title=Predicting the other in cooperative interactions|url=http://researchopen.lsbu.ac.uk/1326/1/Sanfey_Civai_Vavra_TiCS_2015.pdf|journal=Trends Cogn. Sci.|volume=19|issue=7|pages=364–365|doi=10.1016/j.tics.2015.05.009|pmid=26055140|s2cid=20942680}}]
==See also==
{{div col|colwidth=22em}}
* [[Attribution bias]]
* [[Cephalopod intelligence]]
* [[Cetacean intelligence]]
* [[Eliminative materialism]]
* [[Empathy]]
* [[Folk psychology]]
* [[Grounding in communication]]
* [[Intentional stance]]
* [[Joint attention]]
* [[Mental body]]
* [[Mentalization]]
* [[Mini-SEA]]
* [[Origin of language]]
* [[Perspective-taking]]
* [[Quantum mind]]
* [[Relational frame theory]]
* [[Self-awareness]]
* [[Social neuroscience]]
* [[Embodied cognition]]
* [[Space mapping]]
* ''[[The Mind of an Ape]]''
* [[Turing test]]
* [[Type physicalism]]
* [[Interpersonal accuracy]]
{{div col end}}
==References==
{{reflist|30em}}
==Further reading==
* Excerpts taken from: Davis, E. (2007) "Mental Verbs in Nicaraguan Sign Language and the Role of Language in Theory of Mind". Undergraduate senior thesis, Barnard College, Columbia University.
==External links==
{{Wikibooks|Consciousness}}
* [https://huxta.com/theory-of-mind-eye-test/ Eye Test Simon Baron Cohen] {{Webarchive|url=https://web.archive.org/web/20201021014446/https://huxta.com/theory-of-mind-eye-test/ |date=21 October 2020 }}
* [http://plato.stanford.edu/entries/computational-mind/ The Computational Theory of Mind]
* [http://plato.stanford.edu/entries/mind-identity/ The Identity Theory of Mind]
* [https://web.archive.org/web/20050502042438/http://www.psychology.nottingham.ac.uk/staff/plm/c81ind/lecture6.pdf Sally-Anne and Smarties tests]
* [http://www.contextualpsychology.org/functional_contextualism_0/ Functional Contextualism]
* [http://www.iep.utm.edu/theomind/ Theory of Mind] article in the ''[[Internet Encyclopedia of Philosophy]]''
* [http://www.autism-help.org/points-theory-of-mind-research.htm Research into Theory of mind]
{{Evolutionary psychology}}
{{philosophy of mind}}
[[Category:Theory of mind| ]]
[[Category:Cognitive science]]
[[Category:Concepts in epistemology]]
[[Category:Concepts in metaphysics]]
[[Category:Concepts in the philosophy of mind]]
[[Category:Metaphysics of mind]]
[[Category:Ontology]]
[[Category:Psychological theories]]
{{Short description|Branch of philosophy}}
{{Distinguish|Theory of mind}}
{{Philosophy sidebar|expanded=Branches}}
The '''philosophy of mind''' is a branch of [[philosophy]] that deals with the nature of the [[mind]] and its relation to the [[human body|body]] and the [[Reality|external world]].
The [[mind–body problem]] is a paradigmatic issue in philosophy of mind, although a number of other issues are addressed, such as the [[hard problem of consciousness]] and the nature of particular mental states.[{{cite book
|last= Kim|first= Jaegwan|editor= Honderich, Ted|chapter=Emergent properties|page=240|title= Oxford Companion to Philosophy|year= 1995|publisher= Oxford University Press|location= Oxford|isbn= 978-0-19-866132-0|chapter-url=https://books.google.com/books?id=sI4YAAAAIAAJ&q=editions:qiO-uKvXxpQC}}][Siegel, S.: ''The Contents of Visual Experience''. New York: Oxford University Press. 2010.][Macpherson, F. & Haddock, A., editors, ''Disjunctivism: Perception, Action, Knowledge'', Oxford: Oxford University Press, 2008.] Aspects of the mind that are studied include [[mental event]]s, [[mental function]]s, [[mental property|mental properties]], [[consciousness]] and [[neural correlates of consciousness|its neural correlates]], the ontology of the mind, the nature of [[cognition]] and of [[thought]], and the relationship of the mind to the body.
[[Dualism (philosophy of mind)|Dualism]] and [[monism]] are the two central [[schools of thought]] on the mind–body problem, although nuanced views have arisen that do not fit one or the other category neatly.
* Dualism finds its entry into [[Western philosophy]] thanks to [[René Descartes]] in the [[17th century]].[{{cite book|author=Descartes, René|title=Discourse on Method and Meditations on First Philosophy|publisher=Hacket Publishing Company|isbn=978-0-87220-421-8|year=1998|title-link=Discourse on Method and Meditations on First Philosophy }}] Substance dualists like Descartes argue that the mind is an independently existing [[substance (philosophy)|substance]], whereas [[Property dualism|property dualists]] maintain that the mind is a group of independent properties that [[emergentism|emerge]] from and cannot be reduced to the brain, but that it is not a distinct substance.[Hart, W.D. (1996) "Dualism", in Samuel Guttenplan (org) ''A Companion to the Philosophy of Mind'', Blackwell, Oxford, 265–7.]
* Monism is the position that mind and body are [[ontology|ontologically]] indiscernible entities, not dependent substances. This view was espoused by the 17th-century rationalist [[Baruch Spinoza]].[Spinoza, Baruch (1670) ''[[Tractatus Theologico-Politicus]]'' (A Theologico-Political Treatise).] [[Physicalism|Physicalists]] argue that only entities postulated by physical theory exist, and that mental processes will eventually be explained in terms of these entities as physical theory continues to evolve. Physicalists maintain various positions on the prospects of [[Physicalism#Reductionism|reducing mental properties to physical properties]] (many of whom adopt compatible forms of property dualism),[{{cite journal|last1=Schneider|first1=Susan|title=Non-Reductive Physicalism and the Mind Problem1|journal=Noûs|volume=47|issue=1|year=2013|pages=135–153|issn=0029-4624|doi=10.1111/j.1468-0068.2011.00847.x}}][{{cite journal|last1=DePaul|first1=Michael|last2=Baltimore|first2=Joseph A.|title=Type Physicalism and Causal Exclusion|journal=Journal of Philosophical Research|volume=38|year=2013|pages=405–418|issn=1053-8364|doi=10.5840/jpr20133821|url=https://philpapers.org/rec/BALTPA-2}}][{{cite book|author1=S. C. Gibb|author2=E. J. Lowe|author3=R. D. Ingthorsson|title=Mental Causation and Ontology|url=https://books.google.com/books?id=-sBoAgAAQBAJ&pg=PA58|date=21 March 2013|publisher=OUP Oxford|isbn=978-0-19-165255-4|page=58}}][{{cite journal|last1=Demircioglu|first1=Erhan|title=Supervenience And Reductive Physicalism|journal=European Journal of Analytic Philosophy|volume=7|issue=1|year=2011|pages=25–35}}][{{cite web|last1=Francescotti|first1=Robert|title=Supervenience and Mind|website=The Internet Encyclopedia of Philosophy|url=http://www.iep.utm.edu/supermin/|issn=2161-0002|access-date=2014-08-10|url-status=live|archive-url=https://web.archive.org/web/20140717140600/http://www.iep.utm.edu/supermin/|archive-date=2014-07-17}}][{{cite journal|last1=Gibb|first1=Sophie|s2cid=55120533|title=Closure Principles and the Laws of Conservation of Energy and Momentum|journal=Dialectica|volume=64|issue=3|year=2010|pages=363–384|issn=0012-2017|doi=10.1111/j.1746-8361.2010.01237.x}} See also {{cite journal|last1=Dempsey|first1=L. P.|title=Consciousness, Supervenience, and Identity: Marras and Kim on the Efficacy of Conscious Experience|journal=Dialogue|volume=51|issue=3|year=2012|pages=373–395|doi=10.1017/s0012217312000662|s2cid=147060838}} See also {{cite journal|last1=Baltimore|first1=J. A.|title=Defending the piggyback principle against Shapiro and Sober's empirical approach|journal=Dialectica|volume=175|issue=2|year=2010|pages=151–168|doi=10.1007/s11229-009-9467-2|s2cid=13314992|url=https://philpapers.org/rec/BALDTP }}] and the ontological status of such mental properties remains unclear.[{{cite journal|last1=McLaughlin|first1=Brian|last2=Bennett|first2=Karen|title=Supervenience|website=The Stanford Encyclopedia of Philosophy (Spring 2014 Edition)|editor=Edward N. Zalta|url=http://plato.stanford.edu/archives/spr2014/entries/supervenience/|date=2014|access-date=2014-08-10}}][{{cite journal|last1=Megill|first1=Jason|title=A Defense of Emergence|journal=Axiomathes|volume=23|issue=4|year=2012|pages=597–615|issn=1122-1151|doi=10.1007/s10516-012-9203-2|s2cid=170226477}}] [[idealism (philosophy)|Idealists]] maintain that the mind is all that exists and that the external world is either mental itself, or an illusion created by the mind. [[neutral monism|Neutral monists]] such as [[Ernst Mach]] and [[William James]] argue that events in the world can be thought of as either mental (psychological) or physical depending on the network of relationships into which they enter, and dual-aspect monists such as [[Baruch Spinoza|Spinoza]] adhere to the position that there is some other, neutral substance, and that both matter and mind are properties of this unknown substance. The most common monisms in the 20th and 21st centuries have all been variations of physicalism; these positions include [[behaviorism]], the [[type physicalism|type identity theory]], [[anomalous monism]] and [[functionalism (philosophy of mind)|functionalism]].[Kim, J., "Mind–Body Problem", ''Oxford Companion to Philosophy''. Ted Honderich (ed.). Oxford:Oxford University Press. 1995.]
Most modern philosophers of mind adopt either a [[Physicalism#Reductionism|reductive physicalist]] or [[Physicalism#Reductionism|non-reductive physicalist]] position, maintaining in their different ways that the mind is not something separate from the body.[Pinel, J. ''Psychobiology'', (1990) Prentice Hall, Inc. {{ISBN|88-15-07174-1}}][LeDoux, J. (2002) ''The Synaptic Self: How Our Brains Become Who We Are'', New York:Viking Penguin. {{ISBN|88-7078-795-8}}][Russell, S. and Norvig, P. ''[[Artificial Intelligence: A Modern Approach]]'', New Jersey:Prentice Hall. {{ISBN|0-13-103805-2}}][Dawkins, R. ''The Selfish Gene'' (1976) Oxford:Oxford University Press. ISBN] Reductive physicalists assert that all mental states and properties will eventually be explained by scientific accounts of physiological processes and states.[{{cite book|author=Churchland, Patricia|title=Neurophilosophy: Toward a Unified Science of the Mind–Brain|publisher=MIT Press|year=1986|isbn=978-0-262-03116-5 }}][{{cite journal|author=Churchland, Paul|title=Eliminative Materialism and the Propositional Attitudes|journal=Journal of Philosophy|year=1981|pages=67–90|doi=10.2307/2025900|volume=78|issue=2|jstor=2025900}}][{{cite journal|author=Smart, J.J.C.|title=Sensations and Brain Processes|journal=Philosophical Review|year=1956}}] Non-reductive physicalists argue that although the mind is not a separate substance, mental properties [[supervenience|supervene]] on physical properties, or that the predicates and vocabulary used in mental descriptions and explanations are indispensable, and cannot be reduced to the language and lower-level explanations of physical science.[{{cite book|author=Donald Davidson|title=Essays on Actions and Events|publisher=Oxford University Press|year=1980|isbn=978-0-19-924627-4 }}][Putnam, Hilary (1967). "[http://www.phil.uu.nl/~joel/3027/3027PutnamPsychPredicates.pdf Psychological Predicates]", in W. H. Capitan and D. D. Merrill, eds., ''Art, Mind and Religion'' (Pittsburgh: University of Pittsburgh Press.)] Continued [[neuroscientific]] progress has helped to clarify some of these issues; however, they are far from being resolved. Modern philosophers of mind continue to ask how the subjective qualities and the [[intentionality]] of mental states and properties can be explained in naturalistic terms.[{{cite book|author=Dennett, Daniel|title=The intentional stance|publisher=MIT Press|location=Cambridge, Mass.|year=1998|isbn=978-0-262-54053-7|url=https://archive.org/details/intentionalstanc00dani }}][{{cite book|author=Searle, John|title=Intentionality. A Paper on the Philosophy of Mind|publisher=Nachdr. Suhrkamp|location=Frankfurt a. M.|year=2001|isbn=978-3-518-28556-5 }}]
The problems of physicalist theories of the mind have led some contemporary philosophers to assert that the traditional view of substance dualism should be defended. From this perspective, this theory is coherent, and problems such as "the interaction of mind and body" can be rationally resolved.[{{Cite journal|last=Mousavirad|first=Seyyed Jaaber|date=2023-11-29|title=Coherence of Substance Dualism|url=https://www.pdcnet.org/pdc/bvdb.nsf/purchase?openform&fp=ipq&id=ipq_2023_0063_0001_0033_0042|journal=International Philosophical Quarterly|language=en|volume=63|issue=1|pages=33–42|doi=10.5840/ipq20231114214}}]
==Mind–body problem==
{{Main|Mind–body problem}}
[[File:Descartes mind and body.gif|thumb|200px|right|Illustration of mind–body dualism by [[René Descartes]]. Inputs are passed by the sensory organs to the [[pineal gland]], and from there to the immaterial [[Soul|spirit]].]]
The mind–body problem concerns the explanation of the relationship that exists between [[mind]]s, or [[mental processes]], and bodily states or processes.[{{cite web|url=http://www.experiencefestival.com/a/Sankhya/id/23117|title=Sankhya:Hindu philosophy: The Sankhya|author=Sri Swami Sivananda|archive-url=https://web.archive.org/web/20060515215340/http://www.experiencefestival.com/a/Sankhya/id/23117|archive-date=May 15, 2006 }}] Specifically, the [[Yoga Sutra]] of [[Patanjali]] presents an analytical approach to the nature of the mind.
In Western philosophy, the earliest discussions of dualist ideas are in the writings of [[Plato]] who suggested that humans' ''intelligence'' (a faculty of the mind or soul) could not be identified with, or explained in terms of, their physical body.[{{cite book
|author = Plato
|editor1=E.A. Duke|editor2=W.F. Hicken|editor3=W.S.M. Nicoll|editor4=D.B. Robinson|editor5=J.C.G. Strachan|title = Phaedo
|year = 1995
|publisher = Clarendon Press
|isbn = 978-1-4065-4150-2
}}][Robinson, H. (1983): "Aristotelian dualism", Oxford Studies in Ancient Philosophy 1, 123–44.] However, the best-known version of dualism is due to [[René Descartes]] (1641), and holds that the mind is a non-extended, non-physical substance, a "[[mental substance|res cogitans]]".[Jackson, F. (1982) "Epiphenomenal Qualia." Reprinted in Chalmers, David ed. :2002. ''Philosophy of Mind: Classical and Contemporary Readings''. Oxford University Press.] Mental events have a subjective quality, whereas physical events do not. So, for example, one can reasonably ask what a burnt finger feels like, or what a blue sky looks like, or what nice music sounds like to a person. But it is meaningless, or at least odd, to ask what a surge in the uptake of [[glutamate]] in the dorsolateral portion of the [[prefrontal cortex]] feels like.
Philosophers of mind call the subjective aspects of mental events "[[qualia]]" or "raw feels".[{{cite journal|author=Nagel, T.|title=What is it like to be a bat?|journal=Philosophical Review|volume=83|issue=4|pages=435–456|year=1974|url=http://www.esalq.usp.br/lepse/imgs/conteudo_thumb/What-Is-It-Like-to-Be-a-Bat-1.pdf|doi=10.2307/2183914|jstor=2183914 }}]
If consciousness (the mind) can exist independently of physical reality (the brain), one must explain how physical memories are created concerning consciousness. Dualism must therefore explain how consciousness affects physical reality. One possible explanation is that of a miracle, proposed by [[Arnold Geulincx]] and [[Nicolas Malebranche]], where all mind–body interactions require the direct intervention of God.
Another argument that has been proposed by [[C. S. Lewis]][{{cite book|author=Lewis, C.S|title=Miracles |date=1999 |orig-date=1947 |isbn=978-0-688-17369-2 |url=https://archive.org/details/giftofmiraclesma00mill |location=New York |publisher=W. Morrow & Co. }}] is the [[Argument from Reason]]: if, as monism implies, all of our thoughts are the effects of physical causes, then we have no reason for assuming that they are also the [[consequent]] of a reasonable ground. Knowledge, however, is apprehended by reasoning from ground to consequent. Therefore, if monism is correct, there would be no way of knowing this—or anything else—we could not even suppose it, except by a fluke.
The [[p-zombie|zombie argument]] is based on a [[thought experiment]] proposed by Todd Moody, and developed by [[David Chalmers]] in his book ''[[The Conscious Mind]]''. The basic idea is that one can imagine one's body, and therefore conceive the existence of one's body, without any conscious states being associated with this body. Chalmers' argument is that it seems possible that such a being could exist because all that is needed is that all and only the things that the physical sciences describe about a zombie must be true of it. Since none of the concepts involved in these sciences make reference to consciousness or other mental phenomena, and any physical entity can be by definition described scientifically via [[physics]], the move from conceivability to possibility is not such a large one.[{{cite book|author=Chalmers, David|title=The Conscious Mind|publisher=Oxford University Press|year=1997|isbn=978-0-19-511789-9}}] Others such as Dennett have [[Philosophical zombie#Criticism|argued]] that the notion of a philosophical zombie is an incoherent,[{{cite journal|author=Dennett, Daniel|title=The unimagined preposterousness of zombies|year=1995|journal=Journal of Consciousness Studies|volume=2|pages=322–6|url=http://pp.kpnet.fi/seirioa/cdenn/unzombie.htm|archive-url=https://web.archive.org/web/20170515115656/http://pp.kpnet.fi/seirioa/cdenn/unzombie.htm|archive-date=2017-05-15|access-date=2017-04-27 }}] or unlikely,[{{cite book|author=Dennett, Daniel|title=Consciousness Explained|publisher=Little, Brown and Co.|year=1991|page=[https://archive.org/details/consciousnessexp00denn/page/95 95]|isbn=978-0-316-18065-8|url=https://archive.org/details/consciousnessexp00denn/page/95 }}] concept. It has been argued under physicalism that one must either believe that anyone including oneself might be a zombie, or that no one can be a zombie—following from the assertion that one's own conviction about being (or not being) a zombie is a product of the physical world and is therefore no different from anyone else's. This argument has been expressed by Dennett who argues that "Zombies think they are conscious, think they have qualia, think they suffer pains—they are just 'wrong' (according to this lamentable tradition) in ways that neither they nor we could ever discover!"[{{cite journal |last1=Elitzur |first1=Avshalom |date=2009 |title=Consciousness makes a difference: A reluctant dualist's confession |url=https://philarchive.org/rec/ELICMA |journal=Irreducibly Conscious. Selected Papers on Consciousness |volume= |issue= |pages= |doi= |access-date=15 February 2025}}]
[[Christian List]] argues that the existence of first-person perspectives is evidence against physicalist views of consciousness.[{{cite web |url=https://philpapers.org/rec/LISTFA |title=The first-personal argument against physicalism |last=List |first=Christian |date=2023 |website= |publisher= |access-date=15 February 2025 |quote=}}] According to List, first-personal phenomenal facts cannot supervene on third-person physical facts. However, List argues that this also refutes versions of dualism that have purely third-personal metaphysics. List has proposed a model he calls the "many-worlds theory of consciousness" in order to reconcile the subjective nature of consciousness without lapsing into solipsism.[{{cite web |url=https://philarchive.org/rec/LISTMT-2 |title=The many-worlds theory of consciousness |last=List |first=Christian |date=2023 |website= |publisher=The Philosophical Quarterly |access-date=15 February 2025 |quote=}}]
====Interactionist dualism====
[[File:Frans Hals - Portret van René Descartes.jpg|thumb|Portrait of [[René Descartes]] by [[Frans Hals]] (1648)]]
Interactionist dualism, or simply interactionism, is the particular form of dualism first espoused by Descartes in the ''Meditations''.[{{cite book|author1=Popper, Karl|author2=Eccles, John|name-list-style=amp|title=The Self and Its Brain|publisher=Springer Verlag|year=2002|isbn=978-3-492-21096-6 }}] It is the view that mental states, such as beliefs and desires, causally interact with physical states.[Dennett D., (1991), ''Consciousness Explained'', Boston: Little, Brown & Company][Stich, S., (1983), ''From Folk Psychology to Cognitive Science''. Cambridge, MA: [[MIT Press]] (Bradford)][Ryle, G., 1949, The Concept of Mind, New York: Barnes and Noble] For example, [[Joseph Agassi]] suggests that several scientific discoveries made since the early 20th century have undermined the idea of privileged access to one's own ideas. [[Sigmund Freud|Freud]] claimed that a psychologically-trained observer can understand a person's unconscious motivations better than the person himself does. [[Pierre Duhem|Duhem]] has shown that a philosopher of science can know a person's methods of discovery better than that person herself does, while [[Bronisław Malinowski|Malinowski]] has shown that an anthropologist can know a person's customs and habits better than the person whose customs and habits they are. He also asserts that modern psychological experiments that cause people to see things that are not there provide grounds for rejecting Descartes' argument, because scientists can describe a person's perceptions better than the person themself can.[{{cite book|author=Agassi, J.|title=Privileged Access; ''Science in Flux, Boston Stidues in the Philosophy of Science'', 80|publisher=Reidel|location=Dordrecht|year=1975}}][{{cite book|author=Agassi, J.|title=La Scienza in Divenire|publisher=Armando|location=Rome|year=1997}}]
====Other forms of dualism====
[[File:DualismCausationViews3.svg|400px|thumb|Four varieties of dualism. The arrows indicate the direction of the causal interactions. Occasionalism is not shown.]]
=====Psychophysical parallelism=====
[[Psychophysical parallelism]], or simply '''parallelism''', is the view that mind and body, while having distinct ontological statuses, do not causally influence one another. Instead, they run along parallel paths (mind events causally interact with mind events and brain events causally interact with brain events) and only seem to influence each other.[{{cite web
|url = http://plato.stanford.edu/archives/fall2003/entries/dualism/
|title = Dualism
|access-date = 2006-09-25
|last = Robinson
|first = Howard
|date = 2003-08-19
|website = The Stanford Encyclopedia of Philosophy (Fall 2003 Edition)
|publisher = Center for the Study of Language and Information, Stanford University
}}] This view was most prominently defended by [[Gottfried Leibniz]]. Although Leibniz was an ontological monist who believed that only one type of substance, the [[Monad (Greek philosophy)|monad]], exists in the universe, and that everything is reducible to it, he nonetheless maintained that there was an important distinction between "the mental" and "the physical" in terms of causation. He held that God had arranged things in advance so that minds and bodies would be in harmony with each other. This is known as the doctrine of [[pre-established harmony]].[{{cite book |last=Leibniz |first=Gottfried Wilhelm |title=The Discourse on Metaphysics: Correspondence with Arnauld/Monadology |date=1980 |orig-date=1714 |isbn=978-0-87548-030-5 |publisher=Open Court}}]
=====Occasionalism=====
[[Occasionalism]] is the view espoused by [[Nicholas Malebranche]] as well as Islamic philosophers such as [[Al-Ghazali|Abu Hamid Muhammad ibn Muhammad al-Ghazali]] that asserts all supposedly causal relations between physical events, or between physical and mental events, are not really causal at all. While body and mind are different substances, causes (whether mental or physical) are related to their effects by an act of God's intervention on each specific occasion.[{{cite web
|url = http://plato.stanford.edu/archives/sum2002/entries/malebranche/
|title = Nicolas Malebranche
|access-date = 2006-09-25
|last = Schmaltz
|first = Tad
|year = 2002
|website = The Stanford Encyclopedia of Philosophy (Summer 2002 Edition)
|publisher = Center for the Study of Language and Information, Stanford University
}}]
=====Property dualism=====
[[Property dualism]] is the view that the world is constituted of one kind of [[substance theory|substance]] – the physical kind – and there exist two distinct kinds of properties: [[physical properties]] and [[mental properties]]. It is the view that non-physical, mental properties (such as beliefs, desires and emotions) inhere in some physical bodies (at least, brains). Sub-varieties of property dualism include:
#[[Emergent materialism]] asserts that when matter is organized in the appropriate way (i.e., in the way that living human bodies are organized), mental properties emerge in a way not fully accountable for by physical laws.[{{cite book|last=Chalmers|first=David|author-link=David Chalmers|title=The Conscious Mind|url=https://archive.org/details/consciousmindins00chal|url-access=registration|publisher=Oxford University Press|year=1996|isbn = 978-0-19-511789-9 }}] but it was already suggested in the 19th century by [[William James]].
#[[Epiphenomenalism]] is a doctrine first formulated by [[Thomas Henry Huxley]].[Huxley, T. H. [1874] "On the Hypothesis that Animals are Automata, and its History", ''The Fortnightly Review'', n.s.16:555–580. Reprinted in ''Method and Results: Essays by Thomas H. Huxley'' (New York: D. Appleton and Company, 1898).] It consists of the view that mental phenomena are causally ineffectual, where one or more mental states do not have any influence on physical states or mental phenomena are the effects, but not the causes, of physical phenomena. Physical events can cause other physical and mental events, but mental events cannot cause anything since they are just causally inert by-products (i.e., epiphenomena) of the physical world.[{{cite journal|author=Jackson, Frank|s2cid=19000667|title=What Mary didn't know|journal=Journal of Philosophy|volume=83|issue=5|year=1986|pages=291–295|doi=10.2307/2026143|jstor=2026143 }}]
#[[Property dualism#Non-reductive Physicalism|Non-reductive physicalism]] is the view that mental properties form a separate ontological class to physical properties: mental states (such as qualia) are not reducible to physical states. The ontological stance towards qualia in the case of non-reductive physicalism does not imply that qualia are causally inert; this is what distinguishes it from epiphenomenalism.
#[[Panpsychism]] is the view that all matter has a mental aspect, or, alternatively, all objects have a unified center of experience or point of view. Superficially, it seems to be a form of property dualism, since it regards everything as having both mental and physical properties. However, some panpsychists say that mechanical behaviour is derived from the primitive mentality of atoms and molecules—as are sophisticated mentality and organic behaviour, the difference being attributed to the presence or absence of [[complexity|complex]] structure in a compound object. So long as the ''reduction'' of non-mental properties to mental ones is in place, panpsychism is not a (strong) form of property dualism; otherwise it is.
=====Dual aspect theory=====
[[Dual aspect theory]] or dual-aspect monism is the view that the [[mind|mental]] and the [[nature|physical]] are two aspects of, or perspectives on, the same substance. (Thus it is a mixed position, which is monistic in some respects). In modern philosophical writings, the theory's relationship to [[neutral monism]] has become somewhat ill-defined, but one proffered distinction says that whereas neutral monism allows the context of a given group of neutral elements and the relationships into which they enter to determine whether the group can be thought of as mental, physical, both, or neither, dual-aspect theory suggests that the mental and the physical are manifestations (or aspects) of some underlying substance, entity or process that is itself neither mental nor physical as normally understood. Various formulations of dual-aspect monism also require the mental and the physical to be complementary, mutually irreducible and perhaps inseparable (though distinct).[{{cite journal|last1 = Atmanspacher|first1 = H|year = 2012|title = Dual-aspect monism a la Pauli and Jung|url = https://www.researchgate.net/publication/262956033|journal = Journal of Consciousness Studies|volume = 19|issue = 9–10|pages = 96–120 }}][{{cite journal|last1 = Velmans|first1 = M|year = 2012|title = Reflexive Monism: psychophysical relations among mind, matter and consciousness|url = https://www.academia.edu/2053423|journal = Journal of Consciousness Studies|volume = 19|issue = 9–10|pages = 143–165|url-status = live|archive-url = https://web.archive.org/web/20171111113509/http://www.academia.edu/2053423/Reflexive_Monism_Psychophysical_relations_among_mind_matter_and_consciousness|archive-date = 2017-11-11 }}][Leopold Stubenberg. [http://plato.stanford.edu/entries/neutral-monism/#9.4 "Neutral Monism and the Dual Aspect Theory"]. ''Stanford Encyclopedia of Philosophy.'']
===== Experiential dualism =====
This is a philosophy of mind that regards the degrees of freedom between mental and physical well-being as not synonymous thus implying an experiential dualism between body and mind. An example of these disparate degrees of freedom is given by [[B. Alan Wallace|Allan Wallace]] who notes that it is "experientially apparent that one may be physically uncomfortable—for instance, while engaging in a strenuous physical workout—while mentally cheerful; conversely, one may be mentally distraught while experiencing physical comfort".[{{Cite book|title=Consciousness At The Crossroads: Conversations With The Dalai Lama On Brain Science And Buddhism|last=Wallace|first=Allen|publisher=Snow Lion|year=1999|isbn=978-0-545-22720-9}}] Experiential dualism notes that our subjective experience of merely seeing something in the physical world seems qualitatively different from mental processes like grief that comes from losing a loved one. This philosophy is a proponent of causal dualism, which is defined as the dual ability for mental states and physical states to affect one another. Mental states can cause changes in physical states and vice versa.
However, unlike cartesian dualism or some other systems, experiential dualism does not posit two fundamental substances in reality: mind and matter. Rather, experiential dualism is to be understood as a conceptual framework that gives credence to the qualitative difference between the experience of mental and physical states. Experiential dualism is accepted as the conceptual framework of [[Madhyamaka|Madhyamaka Buddhism]].
Madhayamaka Buddhism goes further, finding fault with the monist view of physicalist philosophies of mind as well in that these generally posit matter and energy as the fundamental substance of reality. Nonetheless, this does not imply that the cartesian dualist view is correct, rather Madhyamaka regards as error any affirming view of a fundamental substance to reality.In denying the independent self-existence of all the phenomena that make up the world of our experience, the Madhyamaka view departs from both the substance dualism of Descartes and the substance monism—namely, physicalism—that is characteristic of modern science. The physicalism propounded by many contemporary scientists seems to assert that the real world is composed of physical things-in-themselves, while all mental phenomena are regarded as mere appearances, devoid of any reality in and of themselves. Much is made of this difference between appearances and reality.
Indeed, physicalism, or the idea that matter is the only fundamental substance of reality, is explicitly rejected by Buddhism.In the Madhyamaka view, mental events are no more or less real than physical events. In terms of our common-sense experience, differences of kind do exist between physical and mental phenomena. While the former commonly have mass, location, velocity, shape, size, and numerous other physical attributes, these are not generally characteristic of mental phenomena. For example, we do not commonly conceive of the feeling of affection for another person as having mass or location. These physical attributes are no more appropriate to other mental events such as sadness, a recalled image from one's childhood, the visual perception of a rose, or consciousness of any sort. Mental phenomena are, therefore, not regarded as being physical, for the simple reason that they lack many of the attributes that are uniquely characteristic of physical phenomena. Thus, Buddhism has never adopted the physicalist principle that regards only physical things as real.
===Monist solutions to the mind–body problem===
In contrast to [[Mind-body dualism|dualism]], [[monism]] does not accept any fundamental divisions. The fundamentally disparate nature of reality has been central to forms of eastern philosophies for over two millennia. In [[Indian philosophy|Indian]] and [[Chinese philosophy]], monism is integral to how experience is understood. Today, the most common forms of monism in Western philosophy are [[physicalism|physicalist]].[{{cite web
|url = http://plato.stanford.edu/archives/win2005/entries/physicalism/
|title = Physicalism
|access-date = 2006-09-24
|last = Stoljar
|first = Daniel
|year = 2005
|website = The Stanford Encyclopedia of Philosophy (Winter 2005 Edition)
|publisher = Center for the Study of Language and Information, Stanford University
}}] However, a variety of formulations (see below) are possible. Another form of monism, [[idealism]], states that the only existing substance is mental. Although pure idealism, such as that of [[George Berkeley]], is uncommon in contemporary Western philosophy, a more sophisticated variant called [[panpsychism]], according to which mental experience and properties may be at the foundation of physical experience and properties, has been espoused by some philosophers such as [[Alfred North Whitehead]][Cf. [[Michel Weber]] and Anderson Weekes (eds.), ''[https://www.academia.edu/279961/Process_Approaches_to_Consciousness_in_Psychology_Neuroscience_and_Philosophy_of_Mind Process Approaches to Consciousness in Psychology, Neuroscience, and Philosophy of Mind (Whitehead Psychology Nexus Studies II)] {{webarchive|url=https://web.archive.org/web/20150408022540/http://www.academia.edu/279961/Process_Approaches_to_Consciousness_in_Psychology_Neuroscience_and_Philosophy_of_Mind|date=2015-04-08 }}'', Albany, New York, State University of New York Press, 2009.] and [[David Ray Griffin]].[Russell, Bertrand (1918) ''Mysticism and Logic and Other Essays'', London: Longmans, Green.] A third possibility is to accept the existence of a basic substance that is neither physical nor mental. The mental and physical would then both be properties of this neutral substance. Such a position was adopted by Baruch Spinoza[{{cite book|last=Mach|first=Ernst|orig-date=1886|title=Die Analyse der Empfindungen und das Verhältnis des Physischen zum Psychischen|edition=Fifth|trans-title=The Analysis of Sensations and the Relation of Physical to the Psychical|location=New York|publisher=Dover|year=1959|language=en}}] in the 19th century. This [[neutral monism]], as it is called, resembles property dualism.
====Physicalistic monisms====
=====Behaviorism=====
{{Main|Behaviorism}}
Behaviorism dominated philosophy of mind for much of the 20th century, especially the first half.[{{cite book|author=Skinner, B.F.|title=Beyond Freedom & Dignity|publisher=Bantam/Vintage Books|location=New York|year=1972|isbn=978-0-553-14372-0}}]
Parallel to these developments in psychology, a philosophical behaviorism (sometimes called logical behaviorism) was developed.[{{cite book|author=Ryle, Gilbert|title=The Concept of Mind|publisher=Chicago University Press|location=Chicago|date=1984 |orig-date=1949|isbn=978-0-226-73295-4 }}]
Philosophical behaviorism has fallen out of favor since the latter half of the 20th century, coinciding with the rise of [[cognitivism (psychology)|cognitivism]].[{{cite journal|author=Place, Ullin|title=Is Consciousness a Brain Process?|journal=British Journal of Psychology|year=1956|doi = 10.1111/j.2044-8295.1956.tb00560.x|pmid=13304279|volume=47|issue=1|pages=44–50|s2cid=36940527 }}] as a direct reaction to the failure of behaviorism. These philosophers reasoned that, if mental states are something material, but not behavioral, then mental states are probably identical to internal states of the brain. In very simplified terms: a mental state ''M'' is nothing other than brain state ''B''. The mental state "desire for a cup of coffee" would thus be nothing more than the "firing of certain neurons in certain brain regions".[Smart, J.J.C, [http://plato.stanford.edu/archives/sum2002/entries/malebranche "Identity Theory"], ''The Stanford Encyclopedia of Philosophy'' (Summer 2002 Edition), Edward N. Zalta (ed.)] Anomalous monism (see below) and most other non-reductive physicalisms are token-identity theories.[{{cite book|author=Davidson, D.|title=Subjective, Intersubjective, Objective|publisher=Oxford University Press|location=Oxford|year=2001|isbn=978-88-7078-832-7 }}] Despite these problems, there is a renewed interest in the type identity theory today, primarily due to the influence of [[Jaegwon Kim]].[Block, Ned. "What is functionalism" in ''Readings in Philosophy of Psychology'', 2 vols. Vol 1. (Cambridge: Harvard, 1980).] At about the same time or slightly after, [[D.M. Armstrong]] and [[David Kellogg Lewis]] formulated a version of functionalism that analyzed the mental concepts of folk psychology in terms of functional roles.[Armstrong, D., 1968, ''A Materialist Theory of the Mind'', Routledge.] Finally, [[Ludwig Wittgenstein|Wittgenstein]]'s idea of meaning as use led to a version of functionalism as a theory of meaning, further developed by [[Wilfrid Sellars]] and [[Gilbert Harman]]. Another one, [[Functionalism (philosophy of mind)#Psychofunctionalism|psychofunctionalism]], is an approach adopted by the [[Naturalism (philosophy)#Metaphysical naturalism|naturalistic philosophy of mind]] associated with Jerry Fodor and [[Zenon Pylyshyn]].
Mental states are characterized by their causal relations with other mental states and with sensory inputs and behavioral outputs. Functionalism abstracts away from the details of the physical implementation of a mental state by characterizing it in terms of non-mental functional properties. For example, a kidney is characterized scientifically by its functional role in filtering blood and maintaining certain chemical balances.[{{cite journal|last1=Di Francesco M. & Marraffa M.|title=The Unconscious, consciousness, and the Self illusion|journal=Dialogues in Philosophy, Mental and Neuro Sciences|date=2013|volume=6|issue=1|pages=10–22|url=http://www.crossingdialogues.com/Ms-A13-01.pdf|url-status=live|archive-url=https://web.archive.org/web/20170303051022/http://www.crossingdialogues.com/Ms-A13-01.pdf|archive-date=2017-03-03}}]
Davidson uses the thesis of [[supervenience]]: mental states supervene on physical states, but are not reducible to them. "Supervenience" therefore describes a functional dependence: there can be no change in the mental without some change in the physical–causal reducibility between the mental and physical without ontological reducibility.[{{cite journal|last1 = Stanton|first1 = W.L.|year = 1983|title = Supervenience and Psychological Law in Anomalous Monism|journal = Pacific Philosophical Quarterly|volume = 64|pages = 72–9|doi = 10.1111/j.1468-0114.1983.tb00185.x }}]
=====Weak emergentism=====
{{Main|Emergentism}}
Weak emergentism is a form of "non-reductive physicalism" that involves a layered view of nature, with the layers arranged in terms of increasing complexity and each corresponding to its own special science. Some philosophers{{who?|date=September 2020}} hold that emergent properties causally interact with more fundamental levels, while others maintain that higher-order properties simply supervene over lower levels without direct causal interaction. The latter group therefore holds a less strict, or "weaker", definition of emergentism, which can be rigorously stated as follows: a property P of composite object O is emergent if it is metaphysically impossible for another object to lack property P if that object is composed of parts with intrinsic properties identical to those in O and has those parts in an identical configuration.{{citation needed|date=September 2020}}
Sometimes emergentists use the example of water having a new property when Hydrogen H and Oxygen O combine to form H2O (water). In this example there "emerges" a new property of a transparent liquid that would not have been predicted by understanding hydrogen and oxygen as gases. This is analogous to physical properties of the brain giving rise to a mental state. Emergentists try to solve the notorious mind–body gap this way. One problem for emergentism is the idea of [[causal closure]] in the world that does not allow for a mind-to-body causation.[Jaegwon Kim, Philosophy of Mind, Westview Press; 2 edition (July 8, 2005) {{ISBN|0-8133-4269-4}}]
=====Eliminative materialism=====
{{Main|Eliminative materialism}}
If one is a materialist and believes that all aspects of our common-sense psychology will find reduction to a mature [[cognitive neuroscience]], and that non-reductive materialism is mistaken, then one can adopt a final, more radical position: eliminative materialism.
There are several varieties of eliminative materialism, but all maintain that our common-sense "[[folk psychology]]" badly misrepresents the nature of some aspect of cognition. Eliminativists such as [[Patricia Churchland|Patricia]] and [[Paul Churchland]] argue that while folk psychology treats cognition as fundamentally sentence-like, the non-linguistic vector/matrix model of neural network theory or [[connectionism]] will prove to be a much more accurate account of how the brain works.[{{cite book|last1=Anthis|first1=Jacy|chapter=Consciousness Semanticism: A Precise Eliminativist Theory of Consciousness|title=Biologically Inspired Cognitive Architectures 2021|series=Studies in Computational Intelligence|date=2022|volume=1032|pages=20–41|doi=10.1007/978-3-030-96993-6_3|isbn=978-3-030-96992-9|chapter-url=https://philarchive.org/rec/ANTCSA|access-date=7 August 2022}}]
===Mysterianism===
{{Main|New mysterianism}}
Some philosophers take an epistemic approach and argue that the mind–body problem is currently unsolvable, and perhaps will always remain unsolvable to human beings. This is usually termed [[New mysterianism]]. [[Colin McGinn]] holds that human beings are [[Cognitive closure (philosophy)|cognitively closed]] in regards to their own minds. According to McGinn human minds lack the concept-forming procedures to fully grasp how mental properties such as [[consciousness]] arise from their causal basis.[McGinn, Colin. [https://www.jstor.org/stable/2254848 "Can We Solve the Mind–Body Problem?"] {{webarchive|url=https://web.archive.org/web/20161226060901/http://www.jstor.org/stable/2254848|date=2016-12-26 }}, ''Mind'', New Series, Vol. 98, No. 391, July 1989 (pp. 349–366), p. 350.
*Reprinted in O'Connor, Timothy and Robb, David. [https://books.google.com/books?id=BlSDUzfMxo0C&pg=PA438 "Colin McGinn, Can We Solve the Mind–Body Problem?"], ''Philosophy of Mind: Contemporary Readings''. Routledge, 2003, p. 438ff.] An example would be how an elephant is cognitively closed in regards to particle physics.
A more moderate conception has been expounded by [[Thomas Nagel]], which holds that the mind–body problem is currently unsolvable at the present stage of scientific development and that it might take a future scientific [[paradigm shift]] or revolution to bridge the [[explanatory gap]]. Nagel posits that in the future a sort of "objective [[phenomenology (philosophy)|phenomenology]]" might be able to bridge the gap between subjective conscious experience and its physical basis.[[http://www.iep.utm.edu/hard-con/#SH3b "Hard problem of Consciousness"] {{webarchive|url=https://web.archive.org/web/20150420211306/http://www.iep.utm.edu/hard-con/|date=2015-04-20 }}, ''The Internet Encyclopedia of Philosophy'', Josh Weisberg]
===Linguistic criticism of the mind–body problem===
Each attempt to answer the mind–body problem encounters substantial problems. Some philosophers argue that this is because there is an underlying conceptual confusion.[{{cite book|author=Hacker, Peter|title=Philosophical Foundations of Neuroscience|publisher=Blackwel Pub.|year=2003|isbn=978-1-4051-0838-6 }}] These philosophers, such as [[Ludwig Wittgenstein]] and his followers in the tradition of linguistic criticism, therefore reject the problem as illusory.[{{cite book|author=Wittgenstein, Ludwig|title=Philosophical Investigations|publisher=Macmillan|location=New York |date=1974 |orig-date=1954 |isbn=978-0-631-14660-5 |url=https://archive.org/details/preliminarystudi00witt }}] They argue that it is an error to ask how mental and biological states fit together. Rather it should simply be accepted that human experience can be described in different ways—for instance, in a mental and in a biological vocabulary. Illusory problems arise if one tries to describe the one in terms of the other's vocabulary or if the mental vocabulary is used in the wrong contexts.[{{cite book|author=Putnam, Hilary|title=The Threefold Cord: Mind, Body, and World|publisher=Columbia University Press|location=New York|year=2000|isbn=978-0-231-10286-5 }}]
===Naturalism and its problems===
The thesis of physicalism is that the mind is part of the material (or physical) world. Such a position faces the problem that the mind has certain properties that no other material thing seems to possess. Physicalism must therefore explain how it is possible that these properties can nonetheless emerge from a material thing. The project of providing such an explanation is often referred to as the "[[naturalism (philosophy)|naturalization]] of the mental".[Hubert Dreyfus, "Critique of Descartes I" (recorded lecture), University of California at Berkeley, Sept. 18, 2007.]
This problem of explaining introspective first-person aspects of mental states and consciousness in general in terms of third-person quantitative neuroscience is called the [[explanatory gap]].[[[Joseph Levine (philosopher)|Joseph Levine]], ''Materialism and Qualia: The Explanatory Gap'', in: ''Pacific Philosophical Quarterly'', vol. 64, no. 4, October, 1983, 354–361] There are several different views of the nature of this gap among contemporary philosophers of mind. [[David Chalmers]] and the early [[Frank Cameron Jackson|Frank Jackson]] interpret the gap as [[ontology|ontological]] in nature; that is, they maintain that qualia can never be explained by science because [[physicalism]] is false. There are two separate categories involved and one cannot be reduced to the other.[Jackson, F. (1986) "What Mary didn't Know", Journal of Philosophy, 83, 5, pp. 291–295.] An alternative view is taken by philosophers such as [[Thomas Nagel]] and [[Colin McGinn]]. According to them, the gap is [[epistemology|epistemological]] in nature. For Nagel, science is not yet able to explain subjective experience because it has not yet arrived at the level or kind of knowledge that is required. We are not even able to formulate the problem coherently.[
McGinn, C. "Can the Mind-Body Problem Be Solved", ''Mind'', New Series, Volume 98, Issue 391, pp. 349–366. a [http://art-mind.org/review/IMG/pdf/McGinn_1989_Mind-body-problem_M.pdf (online)] {{Webarchive|url=https://web.archive.org/web/20070928101441/http://art-mind.org/review/IMG/pdf/McGinn_1989_Mind-body-problem_M.pdf|date=2007-09-28 }}
] Other philosophers liquidate the gap as purely a semantic problem. This semantic problem, of course, led to the famous "''Qualia Question''", which is: ''Does Red cause Redness''?
====Intentionality====
{{Main|Intentionality}}
[[File:John Searle 2002.jpg|thumb|[[John Searle]]—one of the most influential philosophers of mind, proponent of [[biological naturalism]] (Berkeley 2002)]]
[[Intentionality]] is the capacity of mental states to be directed towards (''about'') or be in relation with something in the external world.[{{cite book|author=Fodor, Jerry|title=Psychosemantics. The problem of meaning in the philosophy of mind|publisher=MIT Press|location=Cambridge|year=1993|isbn=978-0-262-06106-3 }}] It would not make any sense to say that a natural process is true or false. But mental ideas or judgments are true or false, so how then can mental states (ideas or judgments) be natural processes? The possibility of assigning semantic value to ideas must mean that such ideas are about facts. Thus, for example, the idea that [[Herodotus]] was a historian refers to Herodotus and to the fact that he was a historian. If the fact is true, then the idea is true; otherwise, it is false. But where does this relation come from? In the brain, there are only electrochemical processes and these seem not to have anything to do with Herodotus.[Siegel, S. (2011). "[http://plato.stanford.edu/archives/win2011/entries/perception-contents/ The Contents of Perception]", ''Stanford Encyclopedia of Philosophy'' (Winter 2011 Edition), Edward N. Zalta (ed.).]
==Philosophy of mind and science==
[[File:Phrenology1.jpg|thumb|upright=1.2|A phrenological [[Brain mapping|mapping]] of the [[brain]] – [[phrenology]] was among the first attempts to correlate mental functions with specific parts of the brain although it is now widely discredited.]]
Humans are corporeal beings and, as such, they are subject to examination and description by the natural sciences. Since mental processes are intimately related to bodily processes (e.g., [[embodied cognition]] theory of mind), the descriptions that the natural sciences furnish of human beings play an important role in the philosophy of mind.[Pinker, S. (1997) ''How the Mind Works''. tr. It: ''Come Funziona la Mente''. Milan:Mondadori, 2000. {{ISBN|88-04-49908-7}}]
===Neurobiology===
{{Main|Neuroscience}}
The theoretical background of biology, as is the case with modern [[natural science]]s in general, is fundamentally materialistic. The objects of study are, in the first place, physical processes, which are considered to be the foundations of mental activity and behavior.[Bear, M. F. et al. Eds. (1995). ''Neuroscience: Exploring The Brain''. Baltimore, Maryland, Williams and Wilkins. {{ISBN|0-7817-3944-6}}] The increasing success of biology in the explanation of mental phenomena can be seen by the absence of any empirical refutation of its fundamental presupposition: "there can be no change in the mental states of a person without a change in brain states."[{{cite book|author=Pinel, J.P.J|title=Psychobiology|publisher=Prentice Hall|year=1997|isbn=978-88-15-07174-3 }}] [[Cognitive neuroscience]] studies the correlations between mental processes and neural processes.[{{cite book|author=Metzinger, Thomas|title=Being No One – The Self Model Theory of Subjectivity|url=https://archive.org/details/beingnooneselfmo00metz|url-access=limited|publisher=MIT Press|location=Cambridge|year=2003|pages=[https://archive.org/details/beingnooneselfmo00metz/page/n363 349]–366|isbn=978-0-262-13417-0 }}]
[[File:Functional magnetic resonance imaging.jpg|thumb|Since the 1980s, sophisticated [[neuroimaging]] procedures, such as [[fMRI]] (above), have furnished increasing knowledge about the workings of the human brain, shedding light on ancient philosophical problems.]]
The [[methodology|methodological]] breakthroughs of the neurosciences, in particular the introduction of high-tech neuroimaging procedures, has propelled scientists toward the elaboration of increasingly ambitious research programs: one of the main goals is to describe and comprehend the neural processes which correspond to mental functions (see: [[neural correlate]]).[{{cite book|author=Churchland, Patricia |title=Neurophilosophy : Toward a Unified Science of the Mind-Brain|location=Cambridge, MA|publisher=MIT Press|isbn=978-0-262-53085-9|year=1989 }}]
An unsolved question in neuroscience and the philosophy of mind is the [[binding problem]], which is the problem of how objects, background, and abstract or emotional features are combined into a single experience.[{{Cite journal|last1 = Revonsuo|first1 = A.|last2 = Newman|first2 = J.|title = Binding and consciousness.|journal = Conscious Cogn|volume = 8|issue = 2|pages = 123–7|date=Jun 1999|doi = 10.1006/ccog.1999.0393|pmid = 10447994|s2cid = 32430180}}] It is considered a "problem" because no complete model exists. The binding problem can be subdivided into the four areas of [[sensory perception|perception]], neuroscience, cognitive science, and the philosophy of mind. It includes general considerations on coordination, the subjective unity of perception, and variable binding.[{{cite journal|last1=Feldman|first1=Jerome|year=2012|title=The neural binding problem|journal=Cognitive Neurodynamics|volume=7|issue=1|pages=1–11|doi=10.1007/s11571-012-9219-8|pmc=3538094|pmid=24427186}}] Another related problem is known as the boundary problem.[{{cite journal |last1=Gómez-Emilsson |first1=Andrés |last2=Percy |first2=Chris |date=3 August 2023 |title=Don't forget the boundary problem! How EM field topology can address the overlooked cousin to the binding problem for consciousness |journal=Front Hum Neurosci |volume= 17|issue= |pages= |doi=10.3389/fnhum.2023.1233119 |doi-access=free |pmid=37600559 |pmc=10435742 }}] The boundary problem is essentially the inverse of the binding problem, and asks how binding stops occurring and what prevents other neurological phenomena from being included in first-person perspectives, giving first-person perspectives hard boundaries.
===Computer science===
{{Main|Computer science}}
Computer science concerns itself with the automatic processing of [[information]] (or at least with physical systems of symbols to which information is assigned) by means of such things as [[computer]]s.[{{cite book|author=Sipser, M.|title=Introduction to the Theory of Computation|location=Boston, Mass.|publisher=PWS Publishing Co.|isbn=978-0-534-94728-6|year=1998|url=https://archive.org/details/introductiontoth00sips }}] From the beginning, [[computer programmer]]s have been able to develop programs that permit computers to carry out tasks for which organic beings need a mind. A simple example is multiplication. It is not clear whether computers could be said to have a mind. Could they, someday, come to have what we call a mind? This question has been propelled into the forefront of much philosophical debate because of investigations in the field of [[artificial intelligence]] (AI).
Within AI, it is common to distinguish between a modest research program and a more ambitious one: this distinction was coined by [[John Searle]] in terms of a [[philosophy of artificial intelligence#Strong AI vs. weak AI|weak AI and strong AI]]. The exclusive objective of "weak AI", according to Searle, is the successful simulation of mental states, with no attempt to make computers become conscious or aware, etc. The objective of strong AI, on the contrary, is a computer with consciousness similar to that of human beings.[{{cite journal|author=Searle, John|title=Minds, Brains and Programs|journal=The Behavioral and Brain Sciences|volume=3|issue=3|pages=417–424|year=1980|url=http://cogprints.org/7150/1/10.1.1.83.5248.pdf|doi=10.1017/S0140525X00005756|s2cid=55303721 }}] The program of strong AI goes back to one of the pioneers of computation [[Alan Turing]]. As an answer to the question "Can computers think?", he formulated the famous [[Turing test]].[{{Turing 1950}}] Turing believed that a computer could be said to "think" when, if placed in a room by itself next to another room that contained a human being and with the same questions being asked of both the computer and the human being by a third party human being, the computer's responses turned out to be indistinguishable from those of the human. Essentially, Turing's view of machine intelligence followed the behaviourist model of the mind—intelligence is as intelligence does. The Turing test has received many criticisms, among which the most famous is probably the [[Chinese room]] [[thought experiment]] formulated by Searle.[{{cite book|author1=Russell, S.|author2=Norvig, R.|name-list-style=amp|title=Artificial Intelligence:A Modern Approach|location=New Jersey|publisher=Prentice Hall, Inc.|year=1995|isbn=978-0-13-103805-9 }}]
===Psychology===
{{Main|Psychology}}
Psychology is the science that investigates mental states directly. It uses generally empirical methods to investigate concrete mental states like [[joy]], [[fear]] or [[Obsessive–compulsive disorder|obsessions]]. Psychology investigates the laws that bind these mental states to each other or with inputs and outputs to the human organism.[{{cite web|url=http://www.psychology.org|title=Encyclopedia of Psychology|url-status=live|archive-url=https://web.archive.org/web/20080513103646/http://www.psychology.org/|archive-date=2008-05-13|date=2019-03-07 }}]
An example of this is the [[Perception|psychology of perception]]. Scientists working in this field have discovered general principles of the [[Form perception|perception of forms]]. A law of the psychology of forms says that objects that move in the same direction are perceived as related to each other.[Thagard, Paul, [http://plato.stanford.edu/archives/fall2008/entries/cognitive-science/ Cognitive Science], The Stanford Encyclopedia of Philosophy (Fall 2008 Edition), Edward N. Zalta (ed.).] It spans many levels of analysis, from low-level learning and decision mechanisms to high-level logic and planning; from neural circuitry to modular brain organization. Over the years, cognitive science has evolved from a representational and information processing approach to explaining the mind to embrace an [[Embodied cognition|embodied]] perspective of it. Accordingly, bodily processes play a significant role in the acquisition, development, and shaping of cognitive capabilities.[{{Cite book|last1=Calvo|first1=Paco|url=https://books.google.com/books?id=jxnhqHuo3gQC|title=Handbook of Cognitive Science: An Embodied Approach|last2=Gomila|first2=Toni|date=2008|publisher=Elsevier|isbn=978-0-08-091487-9|language=en}}] For instance, [[Mark Rowlands|Rowlands]] (2012) argues that cognition is enactive, [[Embodied cognition|embodied]], embedded, affective and (potentially) extended. The position is taken that the "classical sandwich" of cognition sandwiched between perception and action is artificial; cognition has to be seen as a product of a strongly coupled interaction that cannot be divided this way.[{{cite book|author=Mark Rowlands|author-link=Mark Rowlands|chapter=Chapter 3: The mind embedded|pages=51 ''ff''|year=2010|isbn=978-0-262-01455-7|publisher=MIT Press|chapter-url=https://books.google.com/books?id=AiwjpL-0hDgC&pg=PA51|title=The new science of the mind: From extended mind to embodied phenomenology}}][{{cite book|author1=Dave Ward|author2=Mog Stapleton|year=2012|chapter-url=https://books.google.com/books?id=Y1E7FogqvJ0C&pg=PA89|chapter=Es are good. Cognition as enacted, embodied, embedded, affective and extended|editor=Fabio Paglieri|title=Consciousness in Interaction: The role of the natural and social context in shaping consciousness|publisher=John Benjamins Publishing|pages=89 ''ff''|isbn=978-90-272-1352-5 }} [http://philpapers.org/archive/WAREAG.pdf On-line version here] {{webarchive|url=https://web.archive.org/web/20140410040010/http://philpapers.org/archive/WAREAG.pdf|date=2014-04-10 }}.]
===Near-death research===
{{Main|Near-death studies}}
In the field of near-death research, the following phenomenon, among others, occurs: For example, during some brain operations the brain is artificially and measurably deactivated. Nevertheless, some patients report during this phase that they have perceived what is happening in their surroundings, that is, that they have had consciousness. Patients also report experiences during a cardiac arrest. There is the following problem: As soon as the brain is no longer supplied with blood and thus with oxygen after a cardiac arrest, the brain ceases its normal operation after about 15 seconds, that is, the brain falls into a state of unconsciousness.[J. M. Luce: ''Chronic disorders of consciousness following coma: Part one: medical issues.'' In: ''Chest.'' Band 144, Nummer 4, Oktober 2013, S. 1381–1387, [[doi:10.1378/chest.13-0395]], {{PMID|24081351}} (Review).]
==Philosophy of mind in the continental tradition==
Most of the discussion in this article has focused on one style or tradition of philosophy in modern [[Western culture]], usually called [[analytic philosophy]] (sometimes described as Anglo-American philosophy).[{{cite book|author=Dummett, M.|title=Origini della Filosofia Analitica|publisher=Einaudi|year=2001|isbn=978-88-06-15286-4 }}] Many other schools of thought exist, however, which are sometimes subsumed under the broad (and vague) label of [[continental philosophy]].[{{cite book|author=Hegel, G.W.F|title=Phenomenology of Spirit|isbn=978-0-19-503169-0|year=1983|publisher=Oxford University Press }}, translated by A.V. Miller with analysis of the text and foreword by J. N. Findlay (Oxford: Clarendon Press, 1977) {{ISBN|0-19-824597-1}} .] the third part of his ''[[Encyclopedia of the Philosophical Sciences]]'', Hegel discusses three distinct types of mind: the "subjective mind/spirit", the mind of an individual; the "objective mind/spirit", the mind of society and of the State; and the "Absolute mind/spirit", the position of religion, art, and philosophy. See also Hegel's ''[[The Phenomenology of Spirit]]''. Nonetheless, Hegel's work differs radically from the style of [[Anglosphere|Anglo-American]] philosophy of mind.
In 1896, [[Henri Bergson]] made in ''[[Matter and Memory]]'' "Essay on the relation of body and spirit" a forceful case for the ontological difference of body and mind by reducing the problem to the more definite one of memory, thus allowing for a solution built on the ''empirical test case'' of [[aphasia]].
In modern times, the two main schools that have developed in response or opposition to this Hegelian tradition are phenomenology and existentialism. Phenomenology, founded by [[Edmund Husserl]], focuses on the contents of the human mind (see [[noema]]) and how processes shape our experiences.[{{cite book|author=Husserl, Edmund|title=Logische Untersuchungen|isbn=978-3-05-004391-3|year=2008|publisher=Akademie Verlag Berlin }} trans.: Giovanni Piana. Milan: EST. {{ISBN|88-428-0949-7}}] Existentialism, a school of thought founded upon the work of [[Søren Kierkegaard]], focuses on Human predicament and how people deal with the situation of being alive. Existential-phenomenology represents a major branch of continental philosophy (they are not contradictory), rooted in the work of Husserl but expressed in its fullest forms in the work of [[Martin Heidegger]], [[Jean-Paul Sartre]], [[Simone de Beauvoir]] and [[Maurice Merleau-Ponty]]. See Heidegger's ''[[Being and Time]]'', Merleau-Ponty's ''[[Phenomenology of Perception]]'', Sartre's ''[[Being and Nothingness]]'', and Simone de Beauvoir's ''[[The Second Sex]]''.
==Topics related to the philosophy of mind==
There are countless subjects that are affected by the ideas developed in the philosophy of mind. Clear examples of this are the nature of [[death]] and its definitive character, the nature of [[emotion]], of [[perception]] and of [[memory]]. Questions about what a [[person]] is and what his or her [[Personal identity|identity]] have to do with the philosophy of mind. There are two subjects that, in connection with the philosophy of the mind, have aroused special attention: [[free will]] and the [[self (philosophy)|self]].[{{cite web|url=http://www.ucl.ac.uk/~uctytho/dfwIntroIndex.htm|title=Philosopher Ted Honderich's Determinism web resource|url-status=live|archive-url=https://web.archive.org/web/20080516062050/http://www.ucl.ac.uk/~uctytho/dfwIntroIndex.htm|archive-date=2008-05-16 }}]
This argumentation is rejected, on the one hand, by the [[compatibilism|compatibilists]]. Those who adopt this position suggest that the question "Are we free?" can only be answered once we have determined what the term "free" means. The opposite of "free" is not "caused" but "compelled" or "coerced". It is not appropriate to identify freedom with indetermination. A free act is one where the agent could have done otherwise if it had chosen otherwise. In this sense a person can be free even though determinism is true.[Russell, Paul, ''Freedom and Moral Sentiment: Hume's Way of Naturalizing Responsibility'' Oxford University Press: New York & Oxford, 1995.] More recently,{{When|date=July 2024}} this position was defended, for example, by [[Daniel Dennett]].[{{cite book|author=Dennett, Daniel|title=The Varieties of Free Will Worth Wanting|publisher=Bradford Books–MIT Press|location=Cambridge MA|year=1984|isbn=978-0-262-54042-1|url-access=registration|url=https://archive.org/details/elbowroom00dani }}]
On the other hand, there are also many [[incompatibilism|incompatibilists]] who reject the argument because they believe that the will is free in a stronger sense called [[Libertarianism (metaphysics)|libertarianism]].[{{cite book |first=René |last=Descartes |date=1989 |orig-date=1649 |title=Passions of the Soul |translator=S. H. Voss |publisher=Hackett Publishing Company |isbn=978-0-87220-035-7}}] b) determined by indeterministic natural law only, or c) determined by indeterministic natural law in line with the subjective effort of physically non-reducible agency.[{{cite journal|last=Kane|first=Robert|year=2009|title=Libertarianism|journal=Philosophical Studies|volume=144|issue=1|page=39|doi= 10.1007/s11098-009-9365-y|s2cid=262782420 }}] Under Libertarianism, the will does not have to be deterministic and, therefore, it is potentially free. Critics of the second proposition (b) accuse the incompatibilists of using an incoherent concept of freedom. They argue as follows: if our will is not determined by anything, then we desire what we desire by pure chance. And if what we desire is purely accidental, we are not free. So if our will is not determined by anything, we are not free.[{{cite book|author1=Dennett, C.|author2=Hofstadter, D.R.|name-list-style=amp|title=The Mind's I|publisher=Bantam Books|year=1981|isbn=978-0-553-01412-9|url=https://archive.org/details/mindsi00doug }}] The idea of a self as an immutable essential nucleus derives from the idea of an [[soul|immaterial soul]]. Such an idea is unacceptable to modern philosophers with physicalist orientations and their general skepticism of the concept of "self" as postulated by [[David Hume]], who could never catch himself ''not'' doing, thinking or feeling anything.[{{cite book|author=Searle, John|title=Mind: A Brief Introduction|publisher=Oxford University Press Inc, USA|date=1 November 2004|isbn=978-0-19-515733-8 }}] However, in the light of empirical results from [[developmental psychology]], [[developmental biology]] and [[neuroscience]], the idea of an essential inconstant, material nucleus—an integrated representational system distributed over changing patterns of synaptic connections—seems reasonable.[{{cite book|author=LeDoux, Joseph|title=The Synaptic Self|location=New York|publisher=Viking Penguin|year=2002|isbn=978-88-7078-795-5 }}]
One question central to the philosophy of personal identity is Benj Hellie's [[vertiginous question]]. The vertiginous question asks why, of all the subjects of experience out there, ''this'' one—the one corresponding to the human being referred to as Benj Hellie—is the one whose experiences are ''live''? (The reader is supposed to substitute their own case for Hellie's.)[{{cite journal|last=Hellie|first=Benj|year=2013|title=Against egalitarianism|journal=Analysis|volume=73|issue=2|pages=304–320|doi=10.1093/analys/ans101}}] In other words: Why am I me and not someone else? A common response to the question is that it reduces to "Why are Hellie's experiences live from Hellie's perspective," and thus the entire question is a tautology. However, Hellie argues, through a parable, that this response leaves something out. His parable describes two situations, one reflecting a broad global constellation view of the world and everyone's phenomenal features, and one describing an embedded view from the perspective of a single subject. Caspar Hare has discussed similar ideas with the concepts of [[egocentric presentism]][{{cite journal|last=Hare|first=Caspar|title=Self-Bias, Time-Bias, and the Metaphysics of Self and Time|journal=The Journal of Philosophy|date=July 2007|volume=104|issue=7|pages=350–373|doi=10.5840/jphil2007104717|url=http://web.mit.edu/~casparh/www/Papers/CJHareSelfBias2.pdf}}][{{cite book|last=Hare|first=Caspar|title=On Myself, and Other, Less Important Subjects|year=2009|publisher=Princeton University Press|isbn=9780691135311|url=http://press.princeton.edu/titles/8921.html}}] and [[perspectival realism]].[{{cite journal |last=Hare |first=Caspar |date=September 2010 |title=Realism About Tense and Perspective |url=http://web.mit.edu/~casparh/www/Papers/CJHarePerspectivalRealism.pdf |journal=Philosophy Compass |volume=5 |issue=9 |pages=760–769 |doi=10.1111/j.1747-9991.2010.00325.x |hdl-access=free |hdl=1721.1/115229}}]
In his book ''I am You: The Metaphysical Foundations for Global Ethics'', [[Daniel Kolak]] advocates for a philosophy he calls [[open individualism]].[{{Cite book |last=Kolak |first=Daniel |url=https://digitalphysics.ru/pdf/Kaminskii_A_V/Kolak_I_Am_You.pdf |title=I Am You: The Metaphysical Foundations for Global Ethics |date=2007-11-03 |publisher=Springer Science & Business Media |isbn=978-1-4020-3014-7 |language=en |archive-url=https://web.archive.org/web/20240906163443/https://digitalphysics.ru/pdf/Kaminskii_A_V/Kolak_I_Am_You.pdf |archive-date=2024-09-06 |url-status=live}}] Open individualism states that individual personal identity is an illusion and all individual conscious minds are in reality the same being, similar to the idea of [[anattā]] in Buddhist philosophy. Kolak describes three opposing philosophical views of personal identity: closed individualism, empty individualism, and open individualism. Closed individualism is considered to be the default view of personal identity, which is that one's personal identity consists of a ray or line traveling through time, and that one has a [[future self]]. Empty individualism is another view, which is that personal identity exists, but one's "identity" only persists for an infinitesimally small amount of time, and the "you" that will exist in the future is an ontologically different being from the "you" that exists now. Similar ideas have been discussed by [[Derek Parfit]] in the book ''[[Reasons and Persons]]'' with thought experiments such as the [[teletransportation paradox]].[{{Cite book |last=Parfit |first=Derek |url=https://archive.org/details/trent_0116300637661/page/n5/mode/2up |title=Reasons and persons |date=1984 |isbn=0-19-824615-3 |location=Oxford [Oxfordshire] |publisher=Clarendon Press |oclc=9827659}}]
Thomas Nagel further discusses the philosophy of self and perspective in the book ''[[The View from Nowhere]]''. It contrasts passive and active points of view in how humanity interacts with the world, relying either on a subjective perspective that reflects a point of view or an objective perspective that takes a more detached perspective.[{{cite book |last1=McGinn |first1=Colin |title=Minds and Bodies: Philosophers and Their Ideas |date=1997 |publisher=Oxford University Press |isbn=978-0-19-511355-6 }}{{pn|date=January 2022}}] Nagel describes the objective perspective as the "view from nowhere", one where the only valuable ideas are ones derived independently.[{{cite book |last1=Thomas |first1=Alan |title=Thomas Nagel |date=2015 |publisher=Routledge |isbn=978-1-317-49418-8 }}{{pn|date=February 2025}}]
==See also==
{{Portal|Philosophy}}
{{Cols}}
* Artificial philosophy
* [[Animal consciousness]]
* [[Artificial consciousness]]
* [[Chinese Room]]
* [[Collective intentionality]]
* [[Computational theory of mind]]
* [[Embodied cognition]]
* [[Intension]]
* [[Intention]]
* [[Mind]]
* [[Outline of human intelligence]]
* [[Outline of thought]]
* [[Philosophy of artificial intelligence]]
* [[Theory of mind]]
* [[Theory of mind in animals]]
{{Colend}}
==References==
{{Reflist}}
==Further reading==
{{Div col}}
* [http://www.ucl.ac.uk/philosophy/LPSG/ The London Philosophy Study Guide] {{Webarchive|url=https://web.archive.org/web/20090923081848/http://www.ucl.ac.uk/philosophy/LPSG/Language.htm|date=2009-09-23 }} offers many suggestions on what to read, depending on the student's familiarity with the subject: [http://www.ucl.ac.uk/philosophy/LPSG/Mind.htm Philosophy of Mind] {{Webarchive|url=https://web.archive.org/web/20200615172950/http://www.ucl.ac.uk/philosophy/LPSG/Mind.htm|date=2020-06-15 }}
* [[Richard Rorty]], ''[[Philosophy and the Mirror of Nature]]'' (Princeton, 1980), p. 120, 125.
* Pedro Jesús Teruel, ''Mente, cerebro y antropología en Kant'' (Madrid, 2008). {{ISBN|978-84-309-4688-4}}.
* David J. Ungs, ''Better than one; how we each have two minds'' (London, 2004). {{ISBN|978-1-78220-173-1}}
* [[Alfred North Whitehead]] ''Science and the Modern World'' (1925; reprinted London, 1985), pp. 68–70.
* [[Edwin Burtt]] ''The Metaphysical Foundations of Modern Physical Science'', 2nd ed. (London, 1932), pp. 318–19.
* [[Felix Deutsch]] (ed.) ''On the Mysterious Leap from the Mind to the Body'' (New York, 1959).
* [[Herbert Feigl]] ''[http://ditext.com/feigl/mp/mp.html The "Mental" and the "Physical": The Essay and a Postscript (1967)]'', in H. Feigl et al., (eds.), ''Minnesota Studies in the Philosophy of Science'' (Minneapolis, 1958), Vol. 2, pp. 370–497, at p. 373.
* Nap Mabaquiao, Jr., [https://web.archive.org/web/20170331021010/http://www.vibebookstore.com/mind-science-and-computation.html Mind, Science and Computation] (with foreword by [[Tim Crane]]). Manila: De La Salle University Publishing House, 2012.
* [[Celia Green]] ''The Lost Cause: Causation and the Mind–Body Problem''. (Oxford: Oxford Forum, 2003). Applies a sceptical view on [[causality]] to the problems of interactionism.
* Gyatso, [[Geshe Kelsang Gyatso]], ''Understanding the Mind'': The Nature and Power of the Mind, [[Tharpa Publications]] (2nd. ed., 1997) {{ISBN|978-0-948006-78-4}}
* [https://web.archive.org/web/20160304105534/https://www.uibk.ac.at/psychologie/humanethologie/einfuehrung-in-die-humanethologie/dateien/medicus_engl_cover.pdf Gerhard Medicus. Being Human – Bridging the Gap between the Sciences of Body and Mind. Berlin (2015): VWB]
* [https://doi.org/10.25651/1.2022.0005 Gerhard Medicus (2017). Being Human – Bridging the Gap between the Sciences of Body and Mind, Berlin VWB]
*Scott Robert Sehon, [https://web.archive.org/web/20121011021421/http://mitpress.mit.edu/catalog/item/default.asp?ttype=2&tid=10693 Teleological Realism: Mind, Agency and Explanation]. Cambridge: MIT University Press, 2005.
{{Div col end}}
==External links==
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*{{PhilPapers|category|philosophy-of-mind}}
*{{InPho|taxonomy|2183}}
*{{cite IEP|url-id=theomind/|title=Theory of Mind}}
*[http://consc.net/guide.html Guide to Philosophy of Mind], compiled by David Chalmers.
*[https://web.archive.org/web/20071027060927/http://consc.net/mindpapers/ MindPapers: A Bibliography of the Philosophy of Mind and the Science of Consciousness], compiled by David Chalmers (Editor) & David Bourget (Assistant Editor).
*[https://web.archive.org/web/20130121124039/http://philosophy.uwaterloo.ca/MindDict/ Dictionary of Philosophy of Mind], edited by Chris Eliasmith.
*[https://web.archive.org/web/20090208071843/http://galilean-library.org/manuscript.php?postid=43792 An Introduction to the Philosophy of Mind], by Paul Newall, aimed at beginners.
*[http://consc.net/online.html A list of online papers on consciousness and philosophy of mind], compiled by David Chalmers
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{{short description|Technology and methods used to provide imaging-based automatic inspection and analysis}}
[[File:AutovisionIIatRDT.jpg|thumb|Early [[Automatix]] (now part of [[Omron]]) machine vision system Autovision II from 1983 being demonstrated at a trade show. Camera on tripod is pointing down at a light table to produce backlit image shown on screen, which is then subjected to [[blob extraction]].]]
'''Machine vision''' is the technology and methods used to provide [[image|imaging]]-based [[automation|automatic]] inspection and analysis for such applications as automatic inspection, [[process control]], and robot guidance, usually in industry. Machine vision refers to many technologies, software and hardware products, integrated systems, actions, methods and expertise. Machine vision as a [[systems engineering]] discipline can be considered distinct from [[computer vision]], a form of [[computer science]]. It attempts to integrate existing technologies in new ways and apply them to solve real world problems. The term is the prevalent one for these functions in industrial automation environments but is also used for these functions in other environment vehicle guidance.
The overall machine vision process includes planning the details of the requirements and project, and then creating a solution. During run-time, the process starts with imaging, followed by automated [[image analysis|analysis]] of the image and extraction of the required information.
==Definition==
Definitions of the term "Machine vision" vary, but all include the technology and methods used to extract information from an image on an automated basis, as opposed to [[image processing]], where the output is another image. The information extracted can be a simple good-part/bad-part signal, or more a complex set of data such as the identity, position and orientation of each object in an image. The information can be used for such applications as automatic inspection and robot and process guidance in industry, for security monitoring and vehicle guidance.[{{cite book|url=https://books.google.com/books?id=tppFDwAAQBAJ|title=Machine Vision Algorithms and Applications|author=Steger|first=Carsten|author2=Markus Ulrich|author3=Christian Wiedemann|date=2018|publisher=[[Wiley-VCH]]|edition=2nd|isbn=978-3-527-41365-2|location=Weinheim|page=1|access-date=2018-01-30}}][{{cite book | author= Beyerer, Jürgen| author2= Puente León, Fernando| author3= Frese, Christian| name-list-style= amp |title= Machine Vision - Automated Visual Inspection: Theory, Practice and Applications | publisher=[[Springer Science+Business Media|Springer]] |location=Berlin | date=2016 |isbn=978-3-662-47793-9 | url=https://www.springer.com/book/9783662477939 |access-date=2016-10-11|doi=10.1007/978-3-662-47794-6}}][{{cite book|author=Graves, Mark|author2=Bruce G. Batchelor|name-list-style=amp | title=Machine Vision for the Inspection of Natural Products | page=5 |date=2003|publisher=[[Springer Science+Business Media|Springer]]|isbn=978-1-85233-525-0 | url=https://books.google.com/books?id=PXwz4MDCkYsC&pg=PA5 |access-date=2010-11-02}}][{{cite journal |last=Holton|first=W. Conard | title= By Any Other Name |url= http://www.vision-systems.com/articles/print/volume-15/issue-10/Departments/Inside_Vision/by-any-other-name.html |access-date=2013-03-05|journal = Vision Systems Design |date=October 2010|issue=10|volume=15|issn=1089-3709}}] Machine vision is practically the only term used for these functions in industrial automation applications; the term is less universal for these functions in other environments such as security and vehicle guidance. Machine vision as a [[systems engineering]] discipline can be considered distinct from [[computer vision]], a form of basic [[computer science]]; machine vision attempts to integrate existing technologies in new ways and apply them to solve real world problems in a way that meets the requirements of industrial automation and similar application areas.[{{cite web|last1=Owen-Hill|first1=Alex|title=Robot Vision vs Computer Vision: What's the Difference? |url=http://www.roboticstomorrow.com/article/2016/07/robot-vision-vs-computer-vision-whats-the-difference/8484/|publisher=Robotics Tomorrow|date=July 21, 2016}}] The term is also used in a broader sense by trade shows and trade groups such as the Automated Imaging Association and the European Machine Vision Association. This broader definition also encompasses products and applications most often associated with image processing.[ The primary uses for machine vision are automatic inspection and [[industrial robot]]/process guidance.][{{rp|6–10}}][{{cite news|last1=Lückenhaus|first1=Maximilian|title=Machine Vision in IIoT|url=http://www.qualitymag.com/articles/93296-machine-vision-in-iiot|work=Quality Magazine|date=May 1, 2016|language=en}}] In more recent times the terms computer vision and machine vision have converged to a greater degree. [ ''Computer Vision'' Principles, algorithms, Applications, Learning 5th Edition by E.R. Davies Academic Press, Elselvier 2018 ISBN 978-0-12-809284-2]{{rp|13}} See [[glossary of machine vision]].
==Imaging based automatic inspection and sorting==
The primary uses for machine vision are imaging-based automatic inspection and sorting and robot guidance.;[{{rp|6–10}} in this section the former is abbreviated as "automatic inspection". The overall process includes planning the details of the requirements and project, and then creating a solution.][{{cite journal | author=Dechow, David | title=Integration: Making it Work | journal=Vision & Sensors | date=January 2009 | pages=16–20 | url=http://www.visionsensorsmag.com/Articles/Feature_Article/BNP_GUID_9-5-2006_A_10000000000000496708 | archive-url=https://web.archive.org/web/20200314042314/http://www.visionsensorsmag.com/Articles/Feature_Article/BNP_GUID_9-5-2006_A_10000000000000496708 | url-status=dead | archive-date=2020-03-14 | access-date=2012-05-12 }}] This section describes the technical process that occurs during the operation of the solution.
===Methods and sequence of operation===
The first step in the automatic inspection sequence of operation is [[digital imaging|acquisition of an image]], typically using cameras, lenses, and lighting that has been designed to provide the differentiation required by subsequent processing.[{{cite book|title=Handbook of Machine Vision | author=Hornberg, Alexander |page=427| date= 2006|publisher=[[Wiley-VCH]]|isbn=978-3-527-40584-8|url=https://books.google.com/books?id=x_1IauK-M2cC&pg=PA427|access-date=2010-11-05}}][{{cite book | author=Demant C.| author2=Streicher-Abel B.| author3=Waszkewitz P.| name-list-style=amp| title=Industrial Image Processing: Visual Quality Control in Manufacturing| publisher=Springer-Verlag | date=1999 | isbn=3-540-66410-6}}{{Page needed|date=May 2012}}] MV [[software]] packages and programs developed in them then employ various [[digital image processing]] techniques to extract the required information, and often make decisions (such as pass/fail) based on the extracted information.[{{cite book|title=Handbook of Machine Vision | author=Hornberg, Alexander |page=429| date= 2006|publisher=Wiley-VCH|isbn=978-3-527-40584-8|url=https://books.google.com/books?id=x_1IauK-M2cC&pg=PA429|access-date=2010-11-05}}]
===Equipment===
The components of an automatic inspection system usually include lighting, a camera or other imager, a processor, software, and output devices.[{{cite web|last1=Cognex|title=Introduction to Machine Vision|url=http://www.assemblymag.com/ext/resources/White_Papers/Sep16/Introduction-to-Machine-Vision.pdf|publisher=Assembly Magazine|access-date=9 February 2017|date=2016}}]{{rp|11–13}}
===Imaging===
The imaging device (e.g. camera) can either be separate from the main image processing unit or combined with it in which case the combination is generally called a [[smart camera]] or smart sensor.[{{cite book | title = Smart Cameras | editor = Belbachir, Ahmed Nabil| publisher = Springer | date = 2009 | isbn = 978-1-4419-0952-7}}{{page needed|date=December 2012}}][{{cite journal| url=http://www.vision-systems.com/articles/print/volume-18/issue-2/departments/leading-edge-views/explore-the-fundamentals-of-machine-vision-part-i.html | title=Explore the Fundamentals of Machine Vision: Part 1| volume=18 | issue=2 | date=February 2013 |author=Dechow, David |journal=Vision Systems Design |pages=14–15| access-date=2013-03-05}}] Inclusion of the full processing function into the same enclosure as the camera is often referred to as embedded processing.[''Critical Considerations for Embedded Vision Design'' by Dave Rice and Amber Thousand ''Photonics Spectra'' magazine published by Laurin Publishing Co. July 2019 issue Pages 60-64] When separated, the connection may be made to specialized intermediate hardware, a custom processing appliance, or a [[frame grabber]] within a computer using either an analog or standardized digital interface ([[Camera Link]], [[CoaXPress]]).[{{cite journal| url=http://www.vision-systems.com/articles/2011/05/coaxpress-standard-camera-frame-grabber-support.html | title=CoaXPress standard gets camera, frame grabber support | date= May 31, 2011 |author=Wilson, Andrew |journal=Vision Systems Design |access-date=2012-11-28}}][{{cite journal| url=http://www.vision-systems.com/articles/2012/11/cameras-certified-as-compliant-with-coaxpress-standard.html | title=Cameras certified as compliant with CoaXPress standard | author=Wilson, Dave |journal=Vision Systems Design | date= November 12, 2012 |access-date=2013-03-05}}][{{cite journal |author=Dinev, Petko |title=Digital or Analog? Selecting the Right Camera for an Application Depends on What the Machine Vision System is Trying to Achieve |journal=Vision & Sensors |date=March 2008 |pages=10–14 |url=http://www.visionsensorsmag.com/Articles/Feature_Article/BNP_GUID_9-5-2006_A_10000000000000276728 |archive-url=https://web.archive.org/web/20200314042249/http://www.visionsensorsmag.com/Articles/Feature_Article/BNP_GUID_9-5-2006_A_10000000000000276728 |url-status=dead |archive-date=2020-03-14 |access-date=2012-05-12 }}] MV implementations also use digital cameras capable of direct connections (without a framegrabber) to a computer via [[IEEE 1394|FireWire]], [[USB]] or [[Gigabit Ethernet]] interfaces.[{{cite journal | url=http://www.vision-systems.com/articles/print/volume-16/issue-12/features/looking-to-the-future-of-vision.html | title=Product Focus - Looking to the Future of Vision | author=Wilson, Andrew | journal=Vision Systems Design |volume=16| issue=12 | date=December 2011 |access-date=2013-03-05}}]
While conventional (2D visible light) imaging is most commonly used in MV, alternatives include [[Multispectral image|multispectral imaging]], [[hyperspectral imaging]], imaging various infrared bands,[{{cite journal |author=Wilson, Andrew | title=The Infrared Choice | journal= Vision Systems Design |date= April 2011 |pages=20–23 | url=http://www.vision-systems.com/articles/print/volume-16/issue-4/features/the-infrared-choice.html |volume=16 |issue=4|access-date=2013-03-05}}] line scan imaging, [[3D imaging]] of surfaces and X-ray imaging.[{{cite journal|journal= [[NASA Tech Briefs]] |volume= 35 |issue= 6 |date= June 2011 |title=Machine Vision Fundamentals, How to Make Robots See|author=Turek, Fred D. |pages=60–62 |url= http://www.techbriefs.com/privacy-footer-69/10531 | access-date=2011-11-29}}] Key differentiations within MV 2D visible light imaging are monochromatic vs. color, [[frame rate]], resolution, and whether or not the imaging process is simultaneous over the entire image, making it suitable for moving processes.[West, Perry ''High Speed, Real-Time Machine Vision '' CyberOptics, pages 1-38]
Though the vast majority of machine vision applications are solved using two-dimensional imaging, machine vision applications utilizing 3D imaging are a growing niche within the industry.[{{cite journal |title=3D Machine Vison Comes into Focus |author=Murray, Charles J |journal=[[Design News]] |date=February 2012 |url=http://www.designnews.com/document.asp?doc_id=237971 |access-date=2012-05-12 |url-status=dead |archive-url=https://web.archive.org/web/20120605095256/http://www.designnews.com/document.asp?doc_id=237971 |archive-date=2012-06-05 }}][{{cite book|pages=410–411|author=Davies, E.R. | edition=4th | date=2012 | title=Computer and Machine Vision: Theory, Algorithms, Practicalities | publisher=Academic Press| isbn=9780123869081 | url=https://books.google.com/books?id=AhVjXf2yKtkC&pg=PA410 | access-date=2012-05-13}}] The most commonly used method for 3D imaging is scanning based triangulation which utilizes motion of the product or image during the imaging process. A laser is projected onto the surfaces of an object. In machine vision this is accomplished with a scanning motion, either by moving the workpiece, or by moving the camera & laser imaging system. The line is viewed by a camera from a different angle; the deviation of the line represents shape variations. Lines from multiple scans are assembled into a [[depth map]] or point cloud.[ Stereoscopic vision is used in special cases involving unique features present in both views of a pair of cameras.][''3-D Imaging: A practical Overview for Machine Vision'' By Fred Turek & Kim Jackson Quality Magazine, March 2014 issue, Volume 53/Number 3 Pages 6-8] Other 3D methods used for machine vision are [[Time-of-flight camera|time of flight]] and grid based.[ One method is grid array based systems using pseudorandom structured light system as employed by the Microsoft Kinect system circa 2012.][http://research.microsoft.com/en-us/people/fengwu/depth-icip-12.pdf HYBRID STRUCTURED LIGHT FOR SCALABLE DEPTH SENSING Yueyi Zhang, Zhiwei Xiong, Feng Wu University of Science and Technology of China, Hefei, China Microsoft Research Asia, Beijing, China][R.Morano, C.Ozturk, R.Conn, S.Dubin, S.Zietz, J.Nissano, "Structured light using pseudorandom codes", IEEE Transactions on Pattern Analysis and Machine Intelligence 20 (3)(1998)322–327]
===Image processing===
After an image is acquired, it is processed.[{{cite book| author= Davies, E.R. | title=Machine Vision - Theory Algorithms Practicalities | edition=2nd |publisher= Harcourt & Company | isbn=978-0-12-206092-2 | date=1996}}{{Page needed|date=May 2012}}.] Central processing functions are generally done by a [[CPU]], a [[GPU]], a [[FPGA]] or a combination of these.[ Deep learning training and inference impose higher processing performance requirements.][''Finding the optimal hardware for deep learining inference in machine vision'' by Mike Fussell Vision Systems Design magazine September 2019 issue pages 8-9] Multiple stages of processing are generally used in a sequence that ends up as a desired result. A typical sequence might start with tools such as filters which modify the image, followed by extraction of objects, then extraction (e.g. measurements, reading of codes) of data from those objects, followed by communicating that data, or comparing it against target values to create and communicate "pass/fail" results. Machine vision image processing methods include;
* [[Image stitching|Stitching]]/[[Image registration|Registration]]: Combining of adjacent 2D or 3D images.{{citation needed|date=April 2013}}
* Filtering (e.g. [[Morphological image processing|morphological filtering]])[{{cite book | author=Demant C.| author2=Streicher-Abel B.| author3=Waszkewitz P.| name-list-style=amp| title=Industrial Image Processing: Visual Quality Control in Manufacturing| publisher=Springer-Verlag | date=1999 | page=39 | isbn=3-540-66410-6}}]
* Thresholding: Thresholding starts with setting or determining a gray value that will be useful for the following steps. The value is then used to separate portions of the image, and sometimes to transform each portion of the image to simply black and white based on whether it is below or above that grayscale value.[{{cite book | author=Demant C.| author2=Streicher-Abel B.| author3=Waszkewitz P.| name-list-style=amp| title=Industrial Image Processing: Visual Quality Control in Manufacturing| publisher=Springer-Verlag | date=1999 | page=96 | isbn=3-540-66410-6}}]
* Pixel counting: counts the number of light or dark [[pixel]]s{{citation needed|date=April 2013}}
* [[Segmentation (image processing)|Segmentation]]: Partitioning a [[digital image]] into multiple [[Image segment|segments]] to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze.[[[Linda Shapiro|Linda G. Shapiro]] and George C. Stockman (2001): “Computer Vision”, pp 279-325, New Jersey, Prentice-Hall, {{ISBN|0-13-030796-3}}][Lauren Barghout. Visual Taxometric approach Image Segmentation using Fuzzy-Spatial Taxon Cut Yields Contextually Relevant Regions. Information Processing and Management of Uncertainty in Knowledge-Based
Systems. CCIS Springer-Verlag. 2014]
* [[Edge detection]]: finding object edges [{{cite book | author=Demant C.| author2=Streicher-Abel B.| author3=Waszkewitz P.| name-list-style=amp| title=Industrial Image Processing: Visual Quality Control in Manufacturing| publisher=Springer-Verlag | date=1999 | page=108 | isbn=3-540-66410-6}}]
* Color Analysis: Identify parts, products and items using color, assess quality from color, and isolate [[Feature (computer vision)|features]] using color.[
* [[blob extraction|Blob detection and extraction]]: inspecting an image for discrete blobs of connected pixels (e.g. a black hole in a grey object) as image landmarks.][{{cite book | author=Demant C.| author2=Streicher-Abel B.| author3=Waszkewitz P.| name-list-style=amp| title=Industrial Image Processing: Visual Quality Control in Manufacturing| publisher=Springer-Verlag | date=1999 | page=95 | isbn=3-540-66410-6}}]
* [[Artificial neural network|Neural network]] / [[deep learning]] / [[machine learning]] processing: weighted and self-training multi-variable decision making [{{cite journal | author=Turek, Fred D. |title=Introduction to Neural Net Machine Vision |url= http://www.vision-systems.com/articles/print/volume-12/issue-3/features/introduction-to-neural-net-machine-vision.html |access-date=2013-03-05|journal = Vision Systems Design |date= March 2007 |volume=12|number=3}}] Circa 2019 there is a large expansion of this, using deep learning and machine learning to significantly expand machine vision capabilities. The most common result of such processing is classification. Examples of classification are object identification,"pass fail" classification of identified objects and OCR.[{{cite book | author=Demant C.| author2=Streicher-Abel B.| author3=Waszkewitz P.| name-list-style=amp| title=Industrial Image Processing: Visual Quality Control in Manufacturing| publisher=Springer-Verlag | date=1999 | page=111 | isbn=3-540-66410-6}}]
* [[Barcode]], [[Data Matrix]] and "[[2D barcode]]" reading [{{cite book | author=Demant C.| author2=Streicher-Abel B.| author3=Waszkewitz P.| name-list-style=amp| title=Industrial Image Processing: Visual Quality Control in Manufacturing| publisher=Springer-Verlag | date=1999 | page=125 | isbn=3-540-66410-6}}]
* [[Optical character recognition]]: automated reading of text such as serial numbers [{{cite book | author=Demant C.| author2=Streicher-Abel B.| author3=Waszkewitz P.| name-list-style=amp| title=Industrial Image Processing: Visual Quality Control in Manufacturing| publisher=Springer-Verlag | date=1999 | page=132 | isbn=3-540-66410-6}}]
* [[Metrology|Gauging/Metrology]]: measurement of object dimensions (e.g. in [[pixel]]s, [[inch]]es or [[millimeter]]s) [{{cite book | author=Demant C.| author2=Streicher-Abel B.| author3=Waszkewitz P.| name-list-style=amp| title=Industrial Image Processing: Visual Quality Control in Manufacturing| publisher=Springer-Verlag | date=1999 | page=191 | isbn=3-540-66410-6}}]
*Comparison against target values to determine a "pass or fail" or "go/no go" result. For example, with code or bar code verification, the read value is compared to the stored target value. For gauging, a measurement is compared against the proper value and tolerances. For verification of alpha-numberic codes, the OCR'd value is compared to the proper or target value. For inspection for blemishes, the measured size of the blemishes may be compared to the maximums allowed by quality standards.[ These decisions may in turn trigger mechanisms that reject failed items or sound an alarm. Other common outputs include object position and orientation information for robot guidance systems.][ Additionally, output types include numerical measurement data, data read from codes and characters, counts and classification of objects, displays of the process or results, stored images, alarms from automated space monitoring MV systems, and [[process control]] signals.][West, Perry ''A Roadmap For Building A Machine Vision System'' Pages 1-35][ This also includes user interfaces, interfaces for the integration of multi-component systems and automated data interchange.][{{cite book|title=Handbook of Machine Vision | author=Hornberg, Alexander |page=709| date= 2006|publisher=[[Wiley-VCH]]|isbn=978-3-527-40584-8|url=https://books.google.com/books?id=x_1IauK-M2cC&pg=PA709|access-date=2010-11-05}}]
==Deep learning==
The term [[deep learning]] has variable meanings, most of which can be applied to techniques used in machine vision for over 20 years. However the usage of the term in "machine vision" began in the later 2010s with the advent of the capability to successfully apply such techniques to entire images in the industrial machine vision space.[''The Place for Deep Learning in Machine Vision'' Quality Magazine May 2022 issue, Volume 61, Number 5 Published by BNP Media II] Conventional machine vision usually requires the "physics" phase of a machine vision automatic inspection solution to create reliable ''simple'' differentiation of defects. An example of "simple" differentiation is that the defects are dark and the good parts of the product are light. A common reason why some applications were not doable was when it was impossible to achieve the "simple"; deep learning removes this requirement, in essence "seeing" the object more as a human does, making it now possible to accomplish those automatic applications.[ The system learns from a large amount of images during a training phase and then executes the inspection during run-time use which is called "inference".][
==Imaging based robot guidance==
Machine vision commonly provides location and orientation information to a robot to allow the robot to properly grasp the product. This capability is also used to guide motion that is simpler than robots, such as a 1 or 2 axis motion controller.][ The overall process includes planning the details of the requirements and project, and then creating a solution. This section describes the technical process that occurs during the operation of the solution. Many of the process steps are the same as with automatic inspection except with a focus on providing position and orientation information as the result.][
==Market==
As recently as 2006, one industry consultant reported that MV represented a $1.5 billion market in North America.][{{cite journal|journal=CIO|page=46|title=Factories of the Future|author=Hapgood, Fred|volume=20|issue=6|date=December 15, 2006 – January 1, 2007|url=https://books.google.com/books?id=nAkAAAAAMBAJ&pg=PA43|issn=0894-9301|access-date=2010-10-28}}] However, the editor-in-chief of an MV trade magazine asserted that "machine vision is not an industry per se" but rather "the integration of technologies and products that provide services or applications that benefit true industries such as automotive or consumer goods manufacturing, agriculture, and defense."[R.A. Schowengerdt. Remote sensing: Models and methods for image processing, Academic Press, 3rd ed., (2007)] to map details of the [[Earth]] related to coastal boundaries, vegetation, and landforms.[{{Cite web|url=https://www.e-education.psu.edu/natureofgeoinfo/node/1897|title=13. Multispectral Image Processing {{!}} The Nature of Geographic Information|website=www.e-education.psu.edu|access-date=2019-11-14}}] Multispectral imaging has also found use in document and painting analysis.[{{cite journal|last1=Hagen|first1=Nathan|last2=Kudenov|first2=Michael W.|title=Review of snapshot spectral imaging technologies|journal=Optical Engineering|volume=52|issue=9|pages=090901|doi=10.1117/1.OE.52.9.090901|year=2013|bibcode=2013OptEn..52i0901H|doi-access=free}}]
==Spectral band usage==
{{further|False-color}}
For different purposes, different combinations of spectral bands can be used. They are usually represented with red, green, and blue channels. Mapping of bands to colors depends on the purpose of the image and the personal preferences of the analysts. Thermal infrared is often omitted from consideration due to poor spatial resolution, except for special purposes.
* '''True-color''' uses only red, green, and blue channels, mapped to their respective colors. As a plain color photograph, it is good for analyzing man-made objects, and is easy to understand for beginner analysts.
* '''Green-red-infrared''', where the blue channel is replaced with near infrared, is used for vegetation, which is highly reflective in near IR; it then shows as blue. This combination is often used to detect vegetation and camouflage.
* '''Blue-NIR-MIR''', where the blue channel uses visible blue, green uses NIR (so vegetation stays green), and MIR is shown as red. Such images allow the water depth, vegetation coverage, soil moisture content, and the presence of fires to be seen, all in a single image.
Many other combinations are in use. NIR is often shown as red, causing vegetation-covered areas to appear red.
===Typical spectral bands===
The wavelengths are approximate; exact values depend on the particular instruments (e.g. characteristics of satellite's sensors for Earth observation, characteristics of illumination and sensors for document analysis):
* '''Blue''', 450–515/520 nm, is used for atmosphere and deep water imaging, and can reach depths up to {{convert|150|ft|m|-1}} in clear water.
* '''Green''', 515/520–590/600 nm, is used for imaging vegetation and deep water structures, up to {{convert|90|ft|m|-1}} in clear water.
* '''Red''', 600/630–680/690 nm, is used for imaging man-made objects, in water up to {{convert|30|ft|m|0}} deep, soil, and vegetation.
* '''Near infrared''' (NIR), 750–900 nm, is used primarily for imaging vegetation.
* '''Mid-infrared''' (MIR), 1550–1750 nm, is used for imaging vegetation, soil moisture content, and some [[forest fire]]s.
* '''Far-infrared''' (FIR), 2080–2350 nm, is used for imaging soil, moisture, geological features, silicates, clays, and fires.
* '''[[thermography|Thermal infrared]]''', 10,400–12,500 nm, uses emitted instead of reflected radiation to image geological structures, thermal differences in water currents, fires, and for night studies.
* '''[[Radar]]''' and related technologies are useful for mapping terrain and for detecting various objects.
== Classification ==
Unlike other [[aerial photographic and satellite image interpretation]] work, these multispectral images do not make it easy to identify directly the feature type by visual inspection. Hence the remote sensing data has to be classified first, followed by processing by various data enhancement techniques so as to help the user to understand the features that are present in the image.
Such classification is a complex task which involves rigorous validation of the training samples depending on the classification algorithm used. The techniques can be grouped mainly into two types.
* Supervised classification techniques
* Unsupervised classification techniques
[[Supervised classification]] makes use of training samples. Training samples are areas on the ground for which there is [[ground truth]], that is, what is there is known. The [[spectral signature]]s of the training areas are used to search for similar signatures in the remaining pixels of the image, and we will classify accordingly. This use of training samples for classification is called supervised classification. Expert knowledge is very important in this method since the selection of the training samples and a biased selection can badly affect the accuracy of classification. Popular techniques include the [[maximum likelihood principle]] and [[convolutional neural network]]. The maximum likelihood principle calculates the probability of a pixel belonging to a class (i.e. feature) and allots the [[pixel]] to its most probable class. Newer [[convolutional neural network]] based methods [{{cite journal | last1=Ran | first1=Lingyan | last2=Zhang | first2=Yanning | last3=Wei | first3=Wei | last4=Zhang | first4=Qilin
| title=A Hyperspectral Image Classification Framework with Spatial Pixel Pair Features
| journal=Sensors | volume=17 | issue=10
| pages=2421 | date=2017-10-23 | doi=10.3390/s17102421
| pmid=29065535 | pmc=5677443 | bibcode=2017Senso..17.2421R | doi-access=free }}] account for both spatial proximity and entire spectra to determine the most likely class.
In case of [[unsupervised classification]] no prior knowledge is required for classifying the features of the image. The natural clustering or grouping of the pixel values (i.e. the gray levels of the pixels) are observed. Then a threshold is defined for adopting the number of classes in the image. The finer the threshold value, the more classes there will be. However, beyond a certain limit the same class will be represented in different classes in the sense that variation in the class is represented. After forming the clusters, [[ground truth]] validation is done to identify the class the image pixel belongs to. Thus in this unsupervised classification a priori information about the classes is not required. One of the popular methods in unsupervised classification is [[k-means clustering]].
=== Data analysis software ===
* MicroMSI is endorsed by the [[National Geospatial-Intelligence Agency|NGA]].
* [[Opticks (Software)|Opticks]] is an open-source remote sensing application.
* Multispec is freeware multispectral analysis software.[{{cite journal|url=https://www.researchgate.net/publication/222985553 |title=MultiSpec: a tool for multispectral—hyperspectral image data analysis |journal=Computers & Geosciences |date=2002-12-01 |access-date=2017-04-28|doi=10.1016/S0098-3004(02)00033-X|bibcode=2002CG.....28.1153B |last1=Biehl |first1=Larry |last2=Landgrebe |first2=David |volume=28 |issue=10 |pages=1153–1159 }}]
* Gerbil is open source multispectral visualization and analysis software.[{{cite book|chapter=Gerbil - A Novel Software Framework for Visualization and Analysis in the Multispectral Domain |editor=Reinhard Koch |title=Vision, Modeling, and Visualization |doi=10.2312/PE/VMV/VMV10/259-266 |isbn=978-3-905673-79-1 |year=2010 |last1=Jordan |first1=Johannes |last2=Angelopoulou |first2=Elli |publisher=The Eurographics Association}}]
== Applications ==
{{see also|Hyperspectral imaging#Applications}}
=== Military target tracking ===
Multispectral imaging measures light emission and is often used in detecting or tracking military targets. In 2003, researchers at the [[United States Army Research Laboratory]] and the Federal Laboratory Collaborative Technology Alliance reported a dual band multispectral imaging [[Focal-plane array testing|focal plane array]] (FPA). This FPA allowed researchers to look at two infrared (IR) planes at the same time.[Goldberg, A.; Stann, B.; Gupta, N. (July 2003). "Multispectral, Hyperspectral, and Three-Dimensional Imaging Research at the U.S. Army Research Laboratory" (PDF). ''Proceedings of the International Conference on International Fusion [6th]''. 1: 499–506.] Because mid-wave infrared (MWIR) and long wave infrared (LWIR) technologies measure radiation inherent to the object and require no external light source, they also are referred to as [[Thermography|thermal imaging]] methods.
The brightness of the image produced by a thermal imager depends on the objects [[emissivity]] and temperature.[{{Cite web |url=https://www.opto-engineering.com/resources/infrared-theory |title=Primer on IR theory |website=Opto Engineering |language=en |access-date=2018-08-15}}] Every material has an [[infrared signature]] that aids in the identification of the object.[{{Cite journal|date=2017-02-01|title=A survey of landmine detection using hyperspectral imaging|journal=ISPRS Journal of Photogrammetry and Remote Sensing|language=en|volume=124|pages=40–53|doi=10.1016/j.isprsjprs.2016.12.009|issn=0924-2716|last1=Makki|first1=Ihab|last2=Younes|first2=Rafic|last3=Francis|first3=Clovis|last4=Bianchi|first4=Tiziano|last5=Zucchetti|first5=Massimo|bibcode=2017JPRS..124...40M|url=http://porto.polito.it/2665194/2/makki_JPRS2017_OA.pdf }}] These signatures are less pronounced in [[Hyperspectral imaging|hyperspectral]] systems (which image in many more bands than multispectral systems) and when exposed to wind and, more dramatically, to rain.[{{Cite journal|last1=Li|first1=Ning|last2=Zhao|first2=Yongqiang|last3=Pan|first3=Quan|last4=Kong|first4=Seong G.|date=2018-06-25|title=Removal of reflections in LWIR image with polarization characteristics|journal=Optics Express|language=EN|volume=26|issue=13|pages=16488–16504|doi=10.1364/OE.26.016488|pmid=30119479|issn=1094-4087|bibcode=2018OExpr..2616488L|doi-access=free}}] Imaging systems that use MWIR technology function better with solar reflections on the target's surface and produce more definitive images of hot objects, such as engines, compared to LWIR technology.[{{Cite book|last1=Nguyen|first1=Chuong|last2=Havlicek|first2=Joseph|last3=Fan|first3=Guoliang|last4=Caulfield|first4=John|last5=Pattichis|first5=Marios|title=2014 48th Asilomar Conference on Signals, Systems and Computers |chapter=Robust dual-band MWIR/LWIR infrared target tracking |date=November 2014|pages=78–83|doi=10.1109/ACSSC.2014.7094401|isbn=978-1-4799-8297-4|s2cid=9071883}}] However, LWIR operates better in hazy environments like smoke or fog because less [[scattering]] occurs in the longer wavelengths.[{{cite web|title=3.1.1. Multispectral and panchromatic images|url=https://www.stars-project.org/en/knowledgeportal/magazine/remote-sensing-technology/introduction/multispectral-and-panchromatic-images/|website=STARS project|access-date=14 May 2018}}] Usually, [[Earth observation satellite]]s have three or more [[radiometer]]s. Each acquires one digital image (in remote sensing, called a 'scene') in a small spectral band. The bands are grouped into wavelength regions based on the origin of the light and the interests of the researchers.
=== Weather forecasting ===
Modern weather satellites produce imagery in a variety of spectra.[{{cite journal|doi=10.1175/1520-0450(2001)040<2115:REFACO>2.0.CO;2|issn=1520-0450 |year=2001 |volume=40 |page=2115 |title=Rainfall Estimation from a Combination of TRMM Precipitation Radar and GOES Multispectral Satellite Imagery through the Use of an Artificial Neural Network |last1=Bellerby |first1=Tim |last2=Todd |first2=Martin |last3=Kniveton |first3=Dom |last4=Kidd |first4=Chris |journal=Journal of Applied Meteorology |issue=12 |s2cid=119747098 |doi-access=free }}]
{{quote|text=Multispectral imaging combines two to five spectral imaging bands of relatively large bandwidth into a single optical system. A multispectral system usually provides a combination of visible (0.4 to 0.7 µm), near infrared (NIR; 0.7 to 1 µm), short-wave infrared (SWIR; 1 to 1.7 µm), mid-wave infrared (MWIR; 3.5 to 5 µm) or long-wave infrared (LWIR; 8 to 12 µm) bands into a single system. — Valerie C. Coffey[{{cite journal|last1=Coffey|first1=Valerie C.|title=Multispectral Imaging Moves into the Mainstream|journal=Optics and Photonics News|date=1 April 2012|volume=23|issue=4|pages=18|doi=10.1364/OPN.23.4.000018|url=https://www.osa-opn.org/home/articles/volume_23/issue_4/features/multispectral_imaging_moves_into_the_mainstream/|access-date=14 May 2018}}]}}
In the case of [[Landsat]] satellites, several different band designations have been used, with as many as 11 bands ([[Landsat 8]]) comprising a multispectral image.[{{cite web|title=What are the band designations for the Landsat satellites?|url=https://landsat.usgs.gov/what-are-band-designations-landsat-satellites|website=U.S. Geological Survey|access-date=April 25, 2018|archive-url=https://web.archive.org/web/20170122043515/https://landsat.usgs.gov/what-are-band-designations-landsat-satellites|archive-date=January 22, 2017|url-status=dead}}][{{cite book|last1=Grolier|first1=Maurice J.|last2=Tibbitts Jr.|first2=G. Chase|last3=Ibrahim|first3=Mohammed Mukred|title=A qualitative appraisal of the hydrology of the Yemen Arab Republic from Landsat images Water Supply Paper 1757-P By|date=1984|publisher=U.S. G.P.O.|page=19|url=https://books.google.com/books?id=EK1gAAAAIAAJ&pg=SL16-PA19|access-date=14 May 2018}}][{{cite journal|last1=Tatem|first1=Andrew J.|last2=Goetz|first2=Scott J.|last3=Hay|first3=Simon I.|title=Fifty Years of Earth-observation Satellites|journal=American Scientist|date=2008|volume=96|issue=5|pages=390–398|doi=10.1511/2008.74.390|pmid=19498953|pmc=2690060}}] [[Spectral imaging]] with a higher radiometric resolution
(involving hundreds or thousands of bands), finer spectral resolution (involving smaller bands), or wider spectral coverage may be called [[hyperspectral]] or ultraspectral.[ Baronti, A. Casini, F. Lotti, and S. Porcinai, Multispectral imaging system for the mapping of pigments in works of art by use of principal-component analysis, Applied Optics Vol. 37, Issue 8, pp. 1299–1309 (1998)] The painting is irradiated by [[ultraviolet]], visible and [[infrared]] rays and the reflected radiation is recorded in a camera sensitive in this region of the spectrum. The image can also be registered using the transmitted instead of reflected radiation. In special cases the painting can be irradiated by [[UV rays|UV]], VIS or IR rays and the [[fluorescence]] of [[pigments]] or [[varnishes]] can be registered.[[http://colourlex.com/project/multispectral-imaging/ Multispectral imaging] at ColourLex]
Multispectral analysis has assisted in the interpretation of [[Herculaneum papyri|ancient papyri]], such as those found at [[Herculaneum]], by imaging the fragments in the infrared range (1000 nm). Often, the text on the documents appears to the naked eye as black ink on black paper. At 1000 nm, the difference in how paper and ink reflect infrared light makes the text clearly readable. It has also been used to image the [[Archimedes palimpsest]] by imaging the parchment leaves in bandwidths from 365–870 nm, and then using advanced digital image processing techniques to reveal the undertext with Archimedes' work.[{{cite web|title=Multi-spectral imaging of the Archimedes Palimpsest|url=http://archimedespalimpsest.org/about/imaging/|website=The Archimedes Palimpsest Project|access-date=17 September 2015}}] Multispectral imaging has been used in a [[Andrew W. Mellon Foundation|Mellon Foundation]] project at [[Yale University]] to compare inks in medieval English manuscripts.[Weiskott, Eric. "Multispectral Imaging and Medieval Manuscripts." In ''The Routledge research companion to digital medieval literature''. Boyle, Jennifer E., and Helen J. Burgess. London: Routledge. Pp. 186–96.]
Multispectral imaging has also been used to examine discolorations and stains on old books and manuscripts. Comparing the "spectral fingerprint" of a stain to the characteristics of known chemical substances can make it possible to identify the stain. This technique has been used to examine medical and [[alchemical]] texts, seeking hints about the activities of early chemists and the possible chemical substances they may have used in their experiments. Like a cook spilling flour or vinegar on a cookbook, an early chemist might have left tangible evidence on the pages of the ingredients used to make medicines.[{{cite news|last1=Avril|first1=Tom|title=Scans reveal secrets of medieval 'Harry Potter' book and medical texts at Penn|url=http://www.philly.com/philly/health/science/482322202.html|access-date=14 May 2018|work=The Philadelphia Inquirer|date=May 14, 2018}}]
==See also==
* [[Hyperspectral imaging]]
* [[Imaging spectrometer]]
* [[Imaging spectroscopy]]
* [[Liquid crystal tunable filter]]
* [[Multispectral pattern recognition]]
* [[Normalized difference vegetation index]] (NDVI)
* [[Pansharpening]]
* [[Reconnaissance satellite]]
* [[Remote sensing]]
* [[Satellite imagery]]
==References==
{{Reflist}}
==Further reading==
* {{cite book|last1=Hough|first1=Harold|title=Satellite surveillance|date=1991|publisher=Loompanics Unlimited|location=Port Townsend, Wash.|isbn=1-55950-077-8|url-access=registration|url=https://archive.org/details/satellitesurveil0000houg}}
==External links==
* [http://www.sc.chula.ac.th/courseware/2309507/Lecture/remote18.htm Sc.chula.ac.th]
* [http://academic.emporia.edu/aberjame/student/banman5/perry3.html Academic.emporia.edu]
* [http://multispettrale.com Multispectral imaging] at Research Institure
{{Portal bar|Astronomy|Stars|Spaceflight|Outer space|Solar System}}
[[Category:Remote sensing]]
[[Category:Spectroscopy]]
[[Category:Imaging]]
[[Category:Articles containing video clips]]
{{Short description|Study of algorithms that improve automatically through experience}}
{{For|the journal|Machine Learning (journal){{!}}''Machine Learning'' (journal)}}
{{Redirect|Statistical learning|statistical learning in linguistics|statistical learning in language acquisition}}
{{Machine learning bar}}
{{Artificial intelligence|Major goals}}
{{Use dmy dates|date=April 2025}}
{{Use British English|date=April 2025}}
'''Machine learning''' ('''ML''') is a [[field of study]] in [[artificial intelligence]] concerned with the development and study of [[Computational statistics|statistical algorithms]] that can learn from [[data]] and [[generalise]] to unseen data, and thus perform [[Task (computing)|tasks]] without explicit [[Machine code|instructions]].{{Refn|The definition "without being explicitly programmed" is often attributed to [[Arthur Samuel (computer scientist)|Arthur Samuel]], who coined the term "machine learning" in 1959, but the phrase is not found verbatim in this publication, and may be a [[paraphrase]] that appeared later. Confer "Paraphrasing Arthur Samuel (1959), the question is: How can computers learn to solve problems without being explicitly programmed?" in {{Cite conference |chapter=Automated Design of Both the Topology and Sizing of Analog Electrical Circuits Using Genetic Programming |conference=Artificial Intelligence in Design '96 |last1=Koza |first1=John R. |last2=Bennett |first2=Forrest H. |last3=Andre |first3=David |last4=Keane |first4=Martin A. |title=Artificial Intelligence in Design '96 |date=1996 |publisher=Springer Netherlands |location=Dordrecht, Netherlands |pages=151–170 |language=en |doi=10.1007/978-94-009-0279-4_9 |isbn=978-94-010-6610-5 }}}} Within a subdiscipline in machine learning, advances in the field of [[deep learning]] have allowed [[Neural network (machine learning)|neural networks]], a class of statistical algorithms, to surpass many previous machine learning approaches in performance.[{{Cite web |title=What is Machine Learning? |url=https://www.ibm.com/topics/machine-learning |access-date=27 June 2023 |website=IBM |date=22 September 2021 |language=en-us |archive-date=27 December 2023 |archive-url=https://web.archive.org/web/20231227153910/https://www.ibm.com/topics/machine-learning |url-status=live }}]
ML finds application in many fields, including [[natural language processing]], [[computer vision]], [[speech recognition]], [[email filtering]], [[agriculture]], and [[medicine]].[{{Cite journal |last1=Hu |first1=Junyan |last2=Niu |first2=Hanlin |last3=Carrasco |first3=Joaquin |last4=Lennox |first4=Barry |last5=Arvin |first5=Farshad |date=2020 |title=Voronoi-Based Multi-Robot Autonomous Exploration in Unknown Environments via Deep Reinforcement Learning |journal=IEEE Transactions on Vehicular Technology |volume=69 |issue=12 |pages=14413–14423 |doi=10.1109/tvt.2020.3034800 |s2cid=228989788 |issn=0018-9545 |doi-access=free |url=https://research.manchester.ac.uk/files/191737243/09244647.pdf }}][{{cite journal |last1=Yoosefzadeh-Najafabadi|first1=Mohsen |last2=Hugh |first2=Earl |last3=Tulpan |first3=Dan |last4=Sulik |first4=John |last5=Eskandari |first5=Milad |title=Application of Machine Learning Algorithms in Plant Breeding: Predicting Yield From Hyperspectral Reflectance in Soybean? |journal=Front. Plant Sci. |volume=11 |year=2021 |pages=624273|doi=10.3389/fpls.2020.624273 |pmid=33510761 |pmc=7835636 |doi-access=free }}] The application of ML to business problems is known as [[predictive analytics]].
[[Statistics]] and [[mathematical optimisation]] (mathematical programming) methods comprise the foundations of machine learning. [[Data mining]] is a related field of study, focusing on [[exploratory data analysis]] (EDA) via [[unsupervised learning]].{{refn|Machine learning and pattern recognition "can be viewed as two facets of the same field".[{{cite journal |last=Friedman |first=Jerome H. |author-link = Jerome H. Friedman|title=Data Mining and Statistics: What's the connection? |journal=Computing Science and Statistics |volume=29 |issue=1 |year=1998 |pages=3–9}}]
From a theoretical viewpoint, [[probably approximately correct learning]] provides a framework for describing machine learning.
{{Toclimit|3}}
== History ==
{{See also|Timeline of machine learning}}
The term ''machine learning'' was coined in 1959 by [[Arthur Samuel (computer scientist)|Arthur Samuel]], an [[IBM]] employee and pioneer in the field of [[computer gaming]] and [[artificial intelligence]].[{{Cite journal|last=Samuel|first=Arthur|date=1959|title=Some Studies in Machine Learning Using the Game of Checkers|journal=IBM Journal of Research and Development|volume=3|issue=3|pages=210–229|doi=10.1147/rd.33.0210|citeseerx=10.1.1.368.2254|s2cid=2126705 }}][R. Kohavi and F. Provost, "Glossary of terms", Machine Learning, vol. 30, no. 2–3, pp. 271–274, 1998.] The synonym ''self-teaching computers'' was also used in this time period.[{{cite news |last1=Gerovitch |first1=Slava |title=How the Computer Got Its Revenge on the Soviet Union |url=https://nautil.us/issue/23/dominoes/how-the-computer-got-its-revenge-on-the-soviet-union |access-date=19 September 2021 |work=Nautilus |date=9 April 2015 |archive-date=22 September 2021 |archive-url=https://web.archive.org/web/20210922175839/https://nautil.us/issue/23/Dominoes/how-the-computer-got-its-revenge-on-the-soviet-union |url-status=dead }}][{{cite journal |last1=Lindsay |first1=Richard P. |title=The Impact of Automation On Public Administration |journal=Western Political Quarterly |date=1 September 1964 |volume=17 |issue=3 |pages=78–81 |doi=10.1177/106591296401700364 |s2cid=154021253 |url=https://journals.sagepub.com/doi/10.1177/106591296401700364 |access-date=6 October 2021 |language=en |issn=0043-4078 |archive-date=6 October 2021 |archive-url=https://web.archive.org/web/20211006190841/https://journals.sagepub.com/doi/10.1177/106591296401700364 |url-status=live |url-access=subscription }}]
Although the earliest machine learning model was introduced in the 1950s when [[Arthur Samuel (computer scientist)|Arthur Samuel]] invented a [[Computer program|program]] that calculated the winning chance in checkers for each side, the history of machine learning roots back to decades of human desire and effort to study human cognitive processes.[{{Cite web |title=History and Evolution of Machine Learning: A Timeline |url=https://www.techtarget.com/whatis/A-Timeline-of-Machine-Learning-History |access-date=8 December 2023 |website=WhatIs |language=en |archive-date=8 December 2023 |archive-url=https://web.archive.org/web/20231208220935/https://www.techtarget.com/whatis/A-Timeline-of-Machine-Learning-History |url-status=live }}] In 1949, [[Canadians|Canadian]] psychologist [[Donald O. Hebb|Donald Hebb]] published the book ''[[Organization of Behavior|The Organization of Behavior]]'', in which he introduced a [[Hebbian theory|theoretical neural structure]] formed by certain interactions among [[nerve cells]].[{{Cite journal |last=Milner |first=Peter M. |date=1993 |title=The Mind and Donald O. Hebb |url=https://www.jstor.org/stable/24941344 |journal=Scientific American |volume=268 |issue=1 |pages=124–129 |doi=10.1038/scientificamerican0193-124 |jstor=24941344 |pmid=8418480 |bibcode=1993SciAm.268a.124M |issn=0036-8733 |access-date=9 December 2023 |archive-date=20 December 2023 |archive-url=https://web.archive.org/web/20231220163326/https://www.jstor.org/stable/24941344 |url-status=live |url-access=subscription }}] Hebb's model of [[neuron]]s interacting with one another set a groundwork for how AIs and machine learning algorithms work under nodes, or [[artificial neuron]]s used by computers to communicate data.["Science: The Goof Button", [[Time (magazine)]], 18 August 1961.
] A representative book on research into machine learning during the 1960s was Nilsson's book on Learning Machines, dealing mostly with machine learning for pattern classification.[Nilsson N. Learning Machines, McGraw Hill, 1965.] Interest related to pattern recognition continued into the 1970s, as described by Duda and Hart in 1973.[Duda, R., Hart P. Pattern Recognition and Scene Analysis, Wiley Interscience, 1973] In 1981 a report was given on using teaching strategies so that an [[artificial neural network]] learns to recognise 40 characters (26 letters, 10 digits, and 4 special symbols) from a computer terminal.[S. Bozinovski "Teaching space: A representation concept for adaptive pattern classification" COINS Technical Report No. 81-28, Computer and Information Science Department, University of Massachusetts at Amherst, MA, 1981. https://web.cs.umass.edu/publication/docs/1981/UM-CS-1981-028.pdf {{Webarchive|url=https://web.archive.org/web/20210225070218/https://web.cs.umass.edu/publication/docs/1981/UM-CS-1981-028.pdf |date=25 February 2021 }}]
[[Tom M. Mitchell]] provided a widely quoted, more formal definition of the algorithms studied in the machine learning field: "A computer program is said to learn from experience ''E'' with respect to some class of tasks ''T'' and performance measure ''P'' if its performance at tasks in ''T'', as measured by ''P'', improves with experience ''E''."[{{cite book
|author=Mitchell, T.
|title=Machine Learning
|publisher=McGraw Hill
|isbn= 978-0-07-042807-2
|pages=2
|year=1997}}] This definition of the tasks in which machine learning is concerned offers a fundamentally [[operational definition]] rather than defining the field in cognitive terms. This follows [[Alan Turing]]'s proposal in his paper "[[Computing Machinery and Intelligence]]", in which the question "Can machines think?" is replaced with the question "Can machines do what we (as thinking entities) can do?".[{{Citation |chapter-url=http://eprints.ecs.soton.ac.uk/12954/ |first=Stevan |last=Harnad |author-link=Stevan Harnad |year=2008 |chapter=The Annotation Game: On Turing (1950) on Computing, Machinery, and Intelligence |editor1-last=Epstein |editor1-first=Robert |editor2-last=Peters |editor2-first=Grace |title=The Turing Test Sourcebook: Philosophical and Methodological Issues in the Quest for the Thinking Computer |pages=23–66 |publisher=Kluwer |isbn=9781402067082 |access-date=11 December 2012 |archive-date=9 March 2012 |archive-url=https://web.archive.org/web/20120309113922/http://eprints.ecs.soton.ac.uk/12954/ }}]
Modern-day machine learning has two objectives. One is to classify data based on models which have been developed; the other purpose is to make predictions for future outcomes based on these models. A hypothetical algorithm specific to classifying data may use computer vision of moles coupled with supervised learning in order to train it to classify the cancerous moles. A machine learning algorithm for stock trading may inform the trader of future potential predictions.[{{Cite web|date=8 December 2020|title=Introduction to AI Part 1|url=https://edzion.com/2020/12/09/introduction-to-ai-part-1/|access-date=9 December 2020|website=Edzion|language=en|archive-date=18 February 2021|archive-url=https://web.archive.org/web/20210218005157/https://edzion.com/2020/12/09/introduction-to-ai-part-1/|url-status=live}}]
== Relationships to other fields ==
=== Artificial intelligence ===
[[File:AI hierarchy.svg|thumb|Machine learning as subfield of AI[{{cite journal |vauthors=Sindhu V, Nivedha S, Prakash M |date=February 2020|title=An Empirical Science Research on Bioinformatics in Machine Learning |journal=Journal of Mechanics of Continua and Mathematical Sciences |issue=7 |doi=10.26782/jmcms.spl.7/2020.02.00006 |doi-access=free}}]]]
As a scientific endeavour, machine learning grew out of the quest for [[artificial intelligence]] (AI). In the early days of AI as an [[Discipline (academia)|academic discipline]], some researchers were interested in having machines learn from data. They attempted to approach the problem with various symbolic methods, as well as what were then termed "[[Artificial neural network|neural network]]s"; these were mostly [[perceptron]]s and [[ADALINE|other models]] that were later found to be reinventions of the [[generalised linear model]]s of statistics.[{{cite book |last1=Sarle |first1=Warren S.|chapter=Neural Networks and statistical models |pages=1538–50 |year=1994 |title=SUGI 19: proceedings of the Nineteenth Annual SAS Users Group International Conference |publisher=SAS Institute |isbn=9781555446116 |oclc=35546178}}] [[Probabilistic reasoning]] was also employed, especially in [[automated medical diagnosis]].[{{cite AIMA|edition=2}}]{{rp|488}}
However, an increasing emphasis on the [[symbolic AI|logical, knowledge-based approach]] caused a rift between AI and machine learning. Probabilistic systems were plagued by theoretical and practical problems of data acquisition and representation.[{{Cite journal | last1 = Langley | first1 = Pat| title = The changing science of machine learning | doi = 10.1007/s10994-011-5242-y | journal = [[Machine Learning (journal)|Machine Learning]]| volume = 82 | issue = 3 | pages = 275–9 | year = 2011 | doi-access = free }}] Work on symbolic/knowledge-based learning did continue within AI, leading to [[inductive logic programming]](ILP), but the more statistical line of research was now outside the field of AI proper, in [[pattern recognition]] and [[information retrieval]].[{{cite encyclopedia |last1=Le Roux |first1=Nicolas |first2=Yoshua |last2=Bengio |first3=Andrew |last3=Fitzgibbon |title=Improving First and Second-Order Methods by Modeling Uncertainty |encyclopedia=Optimization for Machine Learning |year=2012 |page=404 |editor1-last=Sra |editor1-first=Suvrit |editor2-first=Sebastian |editor2-last=Nowozin |editor3-first=Stephen J. |editor3-last=Wright |publisher=MIT Press |url=https://books.google.com/books?id=JPQx7s2L1A8C&q=%22Improving+First+and+Second-Order+Methods+by+Modeling+Uncertainty&pg=PA403 |isbn=9780262016469 |access-date=12 November 2020 |archive-date=17 January 2023 |archive-url=https://web.archive.org/web/20230117053335/https://books.google.com/books?id=JPQx7s2L1A8C&q=%22Improving+First+and+Second-Order+Methods+by+Modeling+Uncertainty&pg=PA403 |url-status=live }}]
=== Generalization ===
Characterizing the generalisation of various learning algorithms is an active topic of current research, especially for [[deep learning]] algorithms.
=== Statistics ===
Machine learning and [[statistics]] are closely related fields in terms of methods, but distinct in their principal goal: statistics draws population [[Statistical inference|inferences]] from a [[Sample (statistics)|sample]], while machine learning finds generalisable predictive patterns.[{{cite journal |first1=Danilo |last1=Bzdok |first2=Naomi |last2=Altman |author-link2=Naomi Altman |first3=Martin |last3=Krzywinski |title=Statistics versus Machine Learning |journal=[[Nature Methods]] |volume=15 |issue=4 |pages=233–234 |year=2018 |doi=10.1038/nmeth.4642 |pmid=30100822 |pmc=6082636 }}] According to [[Michael I. Jordan]], the ideas of machine learning, from methodological principles to theoretical tools, have had a long pre-history in statistics.[{{cite web|url=https://www.reddit.com/r/MachineLearning/comments/2fxi6v/ama_michael_i_jordan/ckelmtt?context=3|title=statistics and machine learning|publisher=reddit|date=10 September 2014|access-date=1 October 2014|author=Michael I. Jordan|author-link=Michael I. Jordan|archive-date=18 October 2017|archive-url=https://web.archive.org/web/20171018192328/https://www.reddit.com/r/MachineLearning/comments/2fxi6v/ama_michael_i_jordan/ckelmtt/?context=3|url-status=live}}] He also suggested the term [[data science]] as a placeholder to call the overall field.[Hung et al. Algorithms to Measure Surgeon Performance and Anticipate Clinical Outcomes in Robotic Surgery. JAMA Surg. 2018]
[[Leo Breiman]] distinguished two statistical modelling paradigms: data model and algorithmic model,[{{cite journal|url=http://projecteuclid.org/download/pdf_1/euclid.ss/1009213726|title=Breiman: Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author)|author=Cornell University Library|journal=Statistical Science|date=August 2001|volume=16|issue=3|doi=10.1214/ss/1009213726|s2cid=62729017|access-date=8 August 2015|archive-date=26 June 2017|archive-url=https://web.archive.org/web/20170626042637/http://projecteuclid.org/download/pdf_1/euclid.ss/1009213726|url-status=live|doi-access=free}}] wherein "algorithmic model" means more or less the machine learning algorithms like [[Random forest|Random Forest]].
Some statisticians have adopted methods from machine learning, leading to a combined field that they call ''statistical learning''.[{{cite book |author1=Gareth James |author2=Daniela Witten |author3=Trevor Hastie |author4=Robert Tibshirani |title=An Introduction to Statistical Learning |publisher=Springer |year=2013 |url=http://www-bcf.usc.edu/~gareth/ISL/ |page=vii |access-date=25 October 2014 |archive-date=23 June 2019 |archive-url=https://web.archive.org/web/20190623150237/http://www-bcf.usc.edu/~gareth/ISL/ |url-status=live }}]
===Statistical physics===
Analytical and computational techniques derived from deep-rooted physics of disordered systems can be extended to large-scale problems, including machine learning, e.g., to analyse the weight space of [[deep neural network]]s.[{{cite journal| author1=Ramezanpour, A.| author2=Beam, A.L.| author3=Chen, J.H.| author4=Mashaghi, A.| title=Statistical Physics for Medical Diagnostics: Learning, Inference, and Optimization Algorithms| journal=Diagnostics| date=17 November 2020| volume=10| issue=11| page=972| doi=10.3390/diagnostics10110972| doi-access=free| pmid=33228143| pmc=7699346}}] Statistical physics is thus finding applications in the area of [[medical diagnostics]].[{{cite journal| title=Statistical physics of medical diagnostics: Study of a probabilistic model| author1=Mashaghi, A.| author2=Ramezanpour, A. | journal=[[Physical Review E]]| volume=97| date=16 March 2018| issue=3–1| page=032118| doi=10.1103/PhysRevE.97.032118| pmid=29776109| arxiv=1803.10019| bibcode=2018PhRvE..97c2118M| s2cid=4955393}}]
== {{anchor|Generalisation}} Theory ==
{{Main|Computational learning theory|Statistical learning theory}}
A core objective of a learner is to generalise from its experience.[{{citation|first= C. M. |last= Bishop |author-link=Christopher M. Bishop |year=2006 |title=Pattern Recognition and Machine Learning |publisher=Springer |isbn=978-0-387-31073-2}}][{{Cite Mehryar Afshin Ameet 2012}}] Generalisation in this context is the ability of a learning machine to perform accurately on new, unseen examples/tasks after having experienced a learning data set. The training examples come from some generally unknown probability distribution (considered representative of the space of occurrences) and the learner has to build a general model about this space that enables it to produce sufficiently accurate predictions in new cases.
The computational analysis of machine learning algorithms and their performance is a branch of [[theoretical computer science]] known as [[computational learning theory]] via the [[probably approximately correct learning]] model. Because training sets are finite and the future is uncertain, learning theory usually does not yield guarantees of the performance of algorithms. Instead, probabilistic bounds on the performance are quite common. The [[bias–variance decomposition]] is one way to quantify generalisation [[Errors and residuals|error]].
For the best performance in the context of generalisation, the complexity of the hypothesis should match the complexity of the function underlying the data. If the hypothesis is less complex than the function, then the model has under fitted the data. If the complexity of the model is increased in response, then the training error decreases. But if the hypothesis is too complex, then the model is subject to [[overfitting]] and generalisation will be poorer.[{{Cite book |author=Alpaydin, Ethem |title=Introduction to Machine Learning |url=https://archive.org/details/introductiontoma00alpa_0 |year=2010 |publisher=The MIT Press |place=London |isbn=978-0-262-01243-0 |access-date=4 February 2017 |url-access=registration }}]
In addition to performance bounds, learning theorists study the time complexity and feasibility of learning. In computational learning theory, a computation is considered feasible if it can be done in [[Time complexity#Polynomial time|polynomial time]]. There are two kinds of [[time complexity]] results: Positive results show that a certain class of functions can be learned in polynomial time. Negative results show that certain classes cannot be learned in polynomial time.
== Approaches ==
{{Anchor|Algorithm types}}
[[File:Supervised_and_unsupervised_learning.png|thumb|upright=1.3|In supervised learning, the training data is labelled with the expected answers, while in [[unsupervised learning]], the model identifies patterns or structures in unlabelled data.]]
Machine learning approaches are traditionally divided into three broad categories, which correspond to learning paradigms, depending on the nature of the "signal" or "feedback" available to the learning system:
* [[Supervised learning]]: The computer is presented with example inputs and their desired outputs, given by a "teacher", and the goal is to learn a general rule that [[Map (mathematics)|maps]] inputs to outputs.
* [[Unsupervised learning]]: No labels are given to the learning algorithm, leaving it on its own to find structure in its input. Unsupervised learning can be a goal in itself (discovering hidden patterns in data) or a means towards an end ([[feature learning]]).
* [[Reinforcement learning]]: A computer program interacts with a dynamic environment in which it must perform a certain goal (such as [[Autonomous car|driving a vehicle]] or playing a game against an opponent). As it navigates its problem space, the program is provided feedback that's analogous to rewards, which it tries to maximise.[{{cite journal |last1=Jordan |first1=M. I. |last2=Mitchell |first2=T. M. |title=Machine learning: Trends, perspectives, and prospects |journal=Science |date=17 July 2015 |volume=349 |issue=6245 |pages=255–260 |doi=10.1126/science.aaa8415|pmid=26185243 |bibcode=2015Sci...349..255J |s2cid=677218 }}][{{cite book |last1=El Naqa |first1=Issam |last2=Murphy |first2=Martin J. |title=Machine Learning in Radiation Oncology |chapter=What is Machine Learning? |date=2015 |pages=3–11 |doi=10.1007/978-3-319-18305-3_1|isbn=978-3-319-18304-6 |s2cid=178586107 }}][{{cite journal |last1=Okolie |first1=Jude A. |last2=Savage |first2=Shauna |last3=Ogbaga |first3=Chukwuma C. |last4=Gunes |first4=Burcu |title=Assessing the potential of machine learning methods to study the removal of pharmaceuticals from wastewater using biochar or activated carbon |journal=Total Environment Research Themes |date=June 2022 |volume=1–2 |pages=100001 |doi=10.1016/j.totert.2022.100001|s2cid=249022386 |doi-access=free |bibcode=2022TERT....100001O }}]
=== Supervised learning ===
{{Main|Supervised learning}}
[[File:Svm max sep hyperplane with margin.png|thumb|A [[support-vector machine]] is a supervised learning model that divides the data into regions separated by a [[linear classifier|linear boundary]]. Here, the linear boundary divides the black circles from the white.]]
Supervised learning algorithms build a mathematical model of a set of data that contains both the inputs and the desired outputs.[{{cite book |last1=Russell |first1=Stuart J. |last2=Norvig |first2=Peter |title=Artificial Intelligence: A Modern Approach |date=2010 |publisher=Prentice Hall |isbn=9780136042594 |edition=Third|title-link=Artificial Intelligence: A Modern Approach }}] The data, known as [[training data]], consists of a set of training examples. Each training example has one or more inputs and the desired output, also known as a supervisory signal. In the mathematical model, each training example is represented by an [[array data structure|array]] or vector, sometimes called a [[feature vector]], and the training data is represented by a [[Matrix (mathematics)|matrix]]. Through [[Mathematical optimization#Computational optimization techniques|iterative optimisation]] of an [[Loss function|objective function]], supervised learning algorithms learn a function that can be used to predict the output associated with new inputs.[{{cite book |last1=Mohri |first1=Mehryar |last2=Rostamizadeh |first2=Afshin |last3=Talwalkar |first3=Ameet |title=Foundations of Machine Learning |date=2012 |publisher=The MIT Press |isbn=9780262018258}}] An optimal function allows the algorithm to correctly determine the output for inputs that were not a part of the training data. An algorithm that improves the accuracy of its outputs or predictions over time is said to have learned to perform that task.[{{cite book|last=Alpaydin|first=Ethem|title=Introduction to Machine Learning|date=2010|publisher=MIT Press|isbn=978-0-262-01243-0|page=9|url=https://books.google.com/books?id=7f5bBAAAQBAJ|access-date=25 November 2018|archive-date=17 January 2023|archive-url=https://web.archive.org/web/20230117053338/https://books.google.com/books?id=7f5bBAAAQBAJ|url-status=live}}] Classification algorithms are used when the outputs are restricted to a limited set of values, while regression algorithms are used when the outputs can take any numerical value within a range. For example, in a classification algorithm that filters emails, the input is an incoming email, and the output is the folder in which to file the email. In contrast, regression is used for tasks such as predicting a person's height based on factors like age and genetics or forecasting future temperatures based on historical data.[{{Cite web |title=Lecture 2 Notes: Supervised Learning |url=https://www.cs.cornell.edu/courses/cs4780/2022sp/notes/LectureNotes02.html |access-date=1 July 2024 |website=www.cs.cornell.edu}}]
[[Similarity learning]] is an area of supervised machine learning closely related to regression and classification, but the goal is to learn from examples using a similarity function that measures how similar or related two objects are. It has applications in [[ranking]], [[recommender system|recommendation systems]], visual identity tracking, face verification, and speaker verification.
=== Unsupervised learning ===
{{Main|Unsupervised learning}}{{See also|Cluster analysis}}
Unsupervised learning algorithms find structures in data that has not been labelled, classified or categorised. Instead of responding to feedback, unsupervised learning algorithms identify commonalities in the data and react based on the presence or absence of such commonalities in each new piece of data. Central applications of unsupervised machine learning include clustering, [[dimensionality reduction]],[{{cite book |first1=Michael I. |last1=Jordan |first2=Christopher M. |last2=Bishop |chapter=Neural Networks |editor=Allen B. Tucker |title=Computer Science Handbook, Second Edition (Section VII: Intelligent Systems) |location=Boca Raton, Florida |publisher=Chapman & Hall/CRC Press LLC |year=2004 |isbn=978-1-58488-360-9 }}]
Cluster analysis is the assignment of a set of observations into subsets (called ''clusters'') so that observations within the same cluster are similar according to one or more predesignated criteria, while observations drawn from different clusters are dissimilar. Different clustering techniques make different assumptions on the structure of the data, often defined by some ''similarity metric'' and evaluated, for example, by ''internal compactness'', or the similarity between members of the same cluster, and ''separation'', the difference between clusters. Other methods are based on ''estimated density'' and ''graph connectivity''.
A special type of unsupervised learning called, [[self-supervised learning]] involves training a model by generating the supervisory signal from the data itself.[{{Cite conference|last1=Misra |first1=Ishan |last2=Maaten |first2=Laurens van der |date=2020 |title=Self-Supervised Learning of Pretext-Invariant Representations |url=https://openaccess.thecvf.com/content_CVPR_2020/html/Misra_Self-Supervised_Learning_of_Pretext-Invariant_Representations_CVPR_2020_paper.html |publisher=[[Institute of Electrical and Electronics Engineers|IEEE]] |pages=6707–6717 |conference=2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) |doi=10.1109/CVPR42600.2020.00674 |location=Seattle, WA, USA |arxiv=1912.01991 }}][{{Cite journal |last1=Jaiswal |first1=Ashish |last2=Babu |first2=Ashwin Ramesh |last3=Zadeh |first3=Mohammad Zaki |last4=Banerjee |first4=Debapriya |last5=Makedon |first5=Fillia |date=March 2021 |title=A Survey on Contrastive Self-Supervised Learning |journal=Technologies |language=en |volume=9 |issue=1 |pages=2 |doi=10.3390/technologies9010002 |doi-access=free |issn=2227-7080|arxiv=2011.00362 }}]
=== Semi-supervised learning ===
{{Main|Semi-supervised learning}}
Semi-supervised learning falls between [[unsupervised learning]] (without any labelled training data) and [[supervised learning]] (with completely labelled training data). Some of the training examples are missing training labels, yet many machine-learning researchers have found that unlabelled data, when used in conjunction with a small amount of labelled data, can produce a considerable improvement in learning accuracy.
In [[Weak supervision|weakly supervised learning]], the training labels are noisy, limited, or imprecise; however, these labels are often cheaper to obtain, resulting in larger effective training sets.[{{Cite web|url=https://hazyresearch.github.io/snorkel/blog/ws_blog_post.html|title=Weak Supervision: The New Programming Paradigm for Machine Learning|author1=Alex Ratner|author2=Stephen Bach|author3=Paroma Varma|author4=Chris|others=referencing work by many other members of Hazy Research|website=hazyresearch.github.io|access-date=6 June 2019|archive-date=6 June 2019|archive-url=https://web.archive.org/web/20190606043931/https://hazyresearch.github.io/snorkel/blog/ws_blog_post.html}}]
=== Reinforcement learning ===
{{Main|Reinforcement learning}}
[[File:Reinforcement learning diagram.svg|right|frameless]]
Reinforcement learning is an area of machine learning concerned with how [[software agent]]s ought to take [[Action selection|actions]] in an environment so as to maximise some notion of cumulative reward. Due to its generality, the field is studied in many other disciplines, such as [[game theory]], [[control theory]], [[operations research]], [[information theory]], [[simulation-based optimisation]], [[multi-agent system]]s, [[swarm intelligence]], [[statistics]] and [[genetic algorithm]]s. In reinforcement learning, the environment is typically represented as a [[Markov decision process]] (MDP). Many reinforcement learning algorithms use [[dynamic programming]] techniques.[{{Cite book|author1=van Otterlo, M.|author2=Wiering, M.|title=Reinforcement Learning |chapter=Reinforcement Learning and Markov Decision Processes |volume=12|pages=3–42 |year=2012 |doi=10.1007/978-3-642-27645-3_1|series=Adaptation, Learning, and Optimization|isbn=978-3-642-27644-6}}] Reinforcement learning algorithms do not assume knowledge of an exact mathematical model of the MDP and are used when exact models are infeasible. Reinforcement learning algorithms are used in autonomous vehicles or in learning to play a game against a human opponent.
=== Dimensionality reduction ===
[[Dimensionality reduction]] is a process of reducing the number of random variables under consideration by obtaining a set of principal variables.[{{cite journal|url=https://science.sciencemag.org/content/290/5500/2323|title=Nonlinear Dimensionality Reduction by Locally Linear Embedding|first1=Sam T.|last1=Roweis|first2=Lawrence K.|last2=Saul|date=22 December 2000|journal=Science|volume=290|issue=5500|pages=2323–2326|doi=10.1126/science.290.5500.2323|pmid=11125150|bibcode=2000Sci...290.2323R|s2cid=5987139|language=en|access-date=17 July 2023|archive-date=15 August 2021|archive-url=https://web.archive.org/web/20210815021528/https://science.sciencemag.org/content/290/5500/2323|url-status=live|url-access=subscription}}] In other words, it is a process of reducing the dimension of the [[Feature (machine learning)|feature]] set, also called the "number of features". Most of the dimensionality reduction techniques can be considered as either feature elimination or [[Feature extraction|extraction]]. One of the popular methods of dimensionality reduction is [[principal component analysis]] (PCA). PCA involves changing higher-dimensional data (e.g., 3D) to a smaller space (e.g., 2D).
The [[manifold hypothesis]] proposes that high-dimensional data sets lie along low-dimensional [[manifold]]s, and many dimensionality reduction techniques make this assumption, leading to the area of [[manifold learning]] and [[manifold regularisation]].
=== Other types ===
Other approaches have been developed which do not fit neatly into this three-fold categorisation, and sometimes more than one is used by the same machine learning system. For example, [[topic model]]ling, [[meta-learning (computer science)|meta-learning]].[{{cite book
|author=Pavel Brazdil |author2=Christophe Giraud Carrier |author3=Carlos Soares |author4=Ricardo Vilalta
| title =Metalearning: Applications to Data Mining
| year = 2009
| edition = Fourth
| pages = 10–14, ''passim''
| publisher = [[Springer Science+Business Media]]
|isbn = 978-3540732624
}}]
==== Self-learning ====
Self-learning, as a machine learning paradigm was introduced in 1982 along with a neural network capable of self-learning, named ''crossbar adaptive array'' (CAA).[Bozinovski, S. (1982). "A self-learning system using secondary reinforcement". In Trappl, Robert (ed.). Cybernetics and Systems Research: Proceedings of the Sixth European Meeting on Cybernetics and Systems Research. North-Holland. pp. 397–402. {{ISBN|978-0-444-86488-8}}.][Bozinovski, S. (1999) "Crossbar Adaptive Array: The first connectionist network that solved the delayed reinforcement learning problem" In A. Dobnikar, N. Steele, D. Pearson, R. Albert (eds.) Artificial Neural Networks and Genetic Algorithms, Springer Verlag, p. 320-325, ISBN 3-211-83364-1 ] It gives a solution to the problem learning without any external reward, by introducing emotion as an internal reward. Emotion is used as state evaluation of a self-learning agent. The CAA self-learning algorithm computes, in a crossbar fashion, both decisions about actions and emotions (feelings) about consequence situations. The system is driven by the interaction between cognition and emotion.[Bozinovski, Stevo (2014) "Modeling mechanisms of cognition-emotion interaction in artificial neural networks, since 1981." Procedia Computer Science p. 255-263]
The self-learning algorithm updates a memory matrix W =||w(a,s)|| such that in each iteration executes the following machine learning routine:
# in situation ''s'' perform action ''a''
# receive a consequence situation ''s'''
# compute emotion of being in the consequence situation ''v(s')''
# update crossbar memory ''w'(a,s) = w(a,s) + v(s')''
It is a system with only one input, situation, and only one output, action (or behaviour) a. There is neither a separate reinforcement input nor an advice input from the environment. The backpropagated value (secondary reinforcement) is the emotion toward the consequence situation. The CAA exists in two environments, one is the behavioural environment where it behaves, and the other is the genetic environment, wherefrom it initially and only once receives initial emotions about situations to be encountered in the behavioural environment. After receiving the genome (species) vector from the genetic environment, the CAA learns a goal-seeking behaviour, in an environment that contains both desirable and undesirable situations.[Bozinovski, S. (2001) "Self-learning agents: A connectionist theory of emotion based on crossbar value judgment." Cybernetics and Systems 32(6) 637–667.]
==== Feature learning ====
{{Main|Feature learning}}
Several learning algorithms aim at discovering better representations of the inputs provided during training.[{{cite journal |author1=Y. Bengio |author2=A. Courville |author3=P. Vincent |title=Representation Learning: A Review and New Perspectives |journal= IEEE Transactions on Pattern Analysis and Machine Intelligence|year=2013|doi=10.1109/tpami.2013.50 |pmid=23787338 |volume=35 |issue=8 |pages=1798–1828|arxiv=1206.5538 |s2cid=393948 }}] Classic examples include [[principal component analysis]] and cluster analysis. Feature learning algorithms, also called representation learning algorithms, often attempt to preserve the information in their input but also transform it in a way that makes it useful, often as a pre-processing step before performing classification or predictions. This technique allows reconstruction of the inputs coming from the unknown data-generating distribution, while not being necessarily faithful to configurations that are implausible under that distribution. This replaces manual [[feature engineering]], and allows a machine to both learn the features and use them to perform a specific task.
Feature learning can be either supervised or unsupervised. In supervised feature learning, features are learned using labelled input data. Examples include [[artificial neural network]]s, [[multilayer perceptron]]s, and supervised [[dictionary learning]]. In unsupervised feature learning, features are learned with unlabelled input data. Examples include dictionary learning, [[independent component analysis]], [[autoencoder]]s, [[matrix decomposition|matrix factorisation]][{{cite conference |author1=Nathan Srebro |author2=Jason D. M. Rennie |author3=Tommi S. Jaakkola |title=Maximum-Margin Matrix Factorization |conference=[[Conference on Neural Information Processing Systems|NIPS]] |year=2004}}] and various forms of [[Cluster analysis|clustering]].[{{cite conference
|last1 = Coates
|first1 = Adam
|last2 = Lee
|first2 = Honglak
|last3 = Ng
|first3 = Andrew Y.
|title = An analysis of single-layer networks in unsupervised feature learning
|conference = Int'l Conf. on AI and Statistics (AISTATS)
|year = 2011
|url = http://machinelearning.wustl.edu/mlpapers/paper_files/AISTATS2011_CoatesNL11.pdf
|access-date = 25 November 2018
|archive-url = https://web.archive.org/web/20170813153615/http://machinelearning.wustl.edu/mlpapers/paper_files/AISTATS2011_CoatesNL11.pdf
|archive-date = 13 August 2017
}}][{{cite conference|last1 = Csurka|first1 = Gabriella|last2 = Dance|first2 = Christopher C.|last3 = Fan|first3 = Lixin|last4 = Willamowski|first4 = Jutta|last5 = Bray|first5 = Cédric|title = Visual categorization with bags of keypoints|conference = ECCV Workshop on Statistical Learning in Computer Vision|year = 2004|url = https://www.cs.cmu.edu/~efros/courses/LBMV07/Papers/csurka-eccv-04.pdf|access-date = 29 August 2019|archive-date = 13 July 2019|archive-url = https://web.archive.org/web/20190713040210/http://www.cs.cmu.edu/~efros/courses/LBMV07/Papers/csurka-eccv-04.pdf|url-status = live}}][{{cite book |title=Speech and Language Processing |author1=Daniel Jurafsky |author2=James H. Martin |publisher=Pearson Education International |year=2009 |pages=145–146}}]
[[Manifold learning]] algorithms attempt to do so under the constraint that the learned representation is low-dimensional. [[Sparse coding]] algorithms attempt to do so under the constraint that the learned representation is sparse, meaning that the mathematical model has many zeros. [[Multilinear subspace learning]] algorithms aim to learn low-dimensional representations directly from [[tensor]] representations for multidimensional data, without reshaping them into higher-dimensional vectors.[{{cite journal |first1=Haiping |last1=Lu |first2=K.N. |last2=Plataniotis |first3=A.N. |last3=Venetsanopoulos |url=http://www.dsp.utoronto.ca/~haiping/Publication/SurveyMSL_PR2011.pdf |title=A Survey of Multilinear Subspace Learning for Tensor Data |journal=Pattern Recognition |volume=44 |number=7 |pages=1540–1551 |year=2011 |doi=10.1016/j.patcog.2011.01.004 |bibcode=2011PatRe..44.1540L |access-date=4 September 2015 |archive-date=10 July 2019 |archive-url=https://web.archive.org/web/20190710225429/http://www.dsp.utoronto.ca/~haiping/Publication/SurveyMSL_PR2011.pdf |url-status=live }}] [[Deep learning]] algorithms discover multiple levels of representation, or a hierarchy of features, with higher-level, more abstract features defined in terms of (or generating) lower-level features. It has been argued that an intelligent machine is one that learns a representation that disentangles the underlying factors of variation that explain the observed data.[{{cite book | title = Learning Deep Architectures for AI | author = Yoshua Bengio | publisher = Now Publishers Inc. | year = 2009 | isbn = 978-1-60198-294-0 | pages = 1–3 | url = https://books.google.com/books?id=cq5ewg7FniMC&pg=PA3 | author-link = Yoshua Bengio | access-date = 15 February 2016 | archive-date = 17 January 2023 | archive-url = https://web.archive.org/web/20230117053339/https://books.google.com/books?id=cq5ewg7FniMC&pg=PA3 | url-status = live }}]
Feature learning is motivated by the fact that machine learning tasks such as classification often require input that is mathematically and computationally convenient to process. However, real-world data such as images, video, and sensory data has not yielded attempts to algorithmically define specific features. An alternative is to discover such features or representations through examination, without relying on explicit algorithms.
==== Sparse dictionary learning ====
{{Main|Sparse dictionary learning}}
Sparse dictionary learning is a feature learning method where a training example is represented as a linear combination of [[basis function]]s and assumed to be a [[sparse matrix]]. The method is [[strongly NP-hard]] and difficult to solve approximately.[{{cite journal |first=A. M. |last=Tillmann |title=On the Computational Intractability of Exact and Approximate Dictionary Learning |journal=IEEE Signal Processing Letters |volume=22 |issue=1 |year=2015 |pages=45–49 |doi=10.1109/LSP.2014.2345761|bibcode=2015ISPL...22...45T |arxiv=1405.6664 |s2cid=13342762 }}] A popular [[heuristic]] method for sparse dictionary learning is the [[k-SVD|''k''-SVD]] algorithm. Sparse dictionary learning has been applied in several contexts. In classification, the problem is to determine the class to which a previously unseen training example belongs. For a dictionary where each class has already been built, a new training example is associated with the class that is best sparsely represented by the corresponding dictionary. Sparse dictionary learning has also been applied in [[image de-noising]]. The key idea is that a clean image patch can be sparsely represented by an image dictionary, but the noise cannot.[[[Michal Aharon|Aharon, M]], M Elad, and A Bruckstein. 2006. "[http://sites.fas.harvard.edu/~cs278/papers/ksvd.pdf K-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation] {{Webarchive|url=https://web.archive.org/web/20181123142158/http://sites.fas.harvard.edu/~cs278/papers/ksvd.pdf |date=2018-11-23 }}." Signal Processing, IEEE Transactions on 54 (11): 4311–4322]
==== Anomaly detection ====
{{Main|Anomaly detection}}
In [[data mining]], anomaly detection, also known as outlier detection, is the identification of rare items, events or observations which raise suspicions by differing significantly from the majority of the data.[{{Citation|last1=Zimek|first1=Arthur|title=Outlier Detection|date=2017|encyclopedia=Encyclopedia of Database Systems|pages=1–5|publisher=Springer New York|language=en|doi=10.1007/978-1-4899-7993-3_80719-1|isbn=9781489979933|last2=Schubert|first2=Erich}}] Typically, the anomalous items represent an issue such as [[bank fraud]], a structural defect, medical problems or errors in a text. Anomalies are referred to as [[outlier]]s, novelties, noise, deviations and exceptions.[{{cite journal | last1 = Hodge | first1 = V. J. | last2 = Austin | first2 = J. | doi = 10.1007/s10462-004-4304-y | title = A Survey of Outlier Detection Methodologies | journal = Artificial Intelligence Review | volume = 22 | issue = 2 | pages = 85–126 | year = 2004 | url = http://eprints.whiterose.ac.uk/767/1/hodgevj4.pdf | citeseerx = 10.1.1.318.4023 | s2cid = 59941878 | access-date = 25 November 2018 | archive-date = 22 June 2015 | archive-url = https://web.archive.org/web/20150622042146/http://eprints.whiterose.ac.uk/767/1/hodgevj4.pdf | url-status = live }}]
In particular, in the context of abuse and network intrusion detection, the interesting objects are often not rare objects, but unexpected bursts of inactivity. This pattern does not adhere to the common statistical definition of an outlier as a rare object. Many outlier detection methods (in particular, unsupervised algorithms) will fail on such data unless aggregated appropriately. Instead, a cluster analysis algorithm may be able to detect the micro-clusters formed by these patterns.[{{cite journal |first1=Paul |last1=Dokas |first2=Levent |last2=Ertoz |first3=Vipin |last3=Kumar |first4=Aleksandar |last4=Lazarevic |first5=Jaideep |last5=Srivastava |first6=Pang-Ning |last6=Tan |title=Data mining for network intrusion detection |year=2002 |journal=Proceedings NSF Workshop on Next Generation Data Mining |url=https://www-users.cse.umn.edu/~lazar027/MINDS/papers/nsf_ngdm_2002.pdf |access-date=26 March 2023 |archive-date=23 September 2015 |archive-url=https://web.archive.org/web/20150923211542/http://www.csee.umbc.edu/~kolari1/Mining/ngdm/dokas.pdf |url-status=live }}]
Three broad categories of anomaly detection techniques exist.[{{cite journal |last1=Chandola |first1=V. |last2=Banerjee |first2=A. |last3=Kumar |first3=V. |s2cid=207172599 |year=2009 |title=Anomaly detection: A survey|journal=[[ACM Computing Surveys]]|volume=41|issue=3|pages=1–58|doi=10.1145/1541880.1541882}}] Unsupervised anomaly detection techniques detect anomalies in an unlabelled test data set under the assumption that the majority of the instances in the data set are normal, by looking for instances that seem to fit the least to the remainder of the data set. Supervised anomaly detection techniques require a data set that has been labelled as "normal" and "abnormal" and involves training a classifier (the key difference from many other statistical classification problems is the inherently unbalanced nature of outlier detection). Semi-supervised anomaly detection techniques construct a model representing normal behaviour from a given normal training data set and then test the likelihood of a test instance to be generated by the model.
==== Robot learning ====
[[Robot learning]] is inspired by a multitude of machine learning methods, starting from supervised learning, reinforcement learning,[{{cite journal|title=Learning efficient haptic shape exploration with a rigid tactile sensor array, S. Fleer, A. Moringen, R. Klatzky, H. Ritter |year=2020 |doi=10.1371/journal.pone.0226880|arxiv=1902.07501 |pmid=31896135 |doi-access=free |last1=Fleer |first1=S. |last2=Moringen |first2=A. |last3=Klatzky |first3=R. L. |last4=Ritter |first4=H. |journal=PLOS ONE |volume=15 |issue=1 |pages=e0226880 |pmc=6940144 }}][{{Citation|last1=Moringen|first1=Alexandra|title=Attention-Based Robot Learning of Haptic Interaction|date=2020|work=Haptics: Science, Technology, Applications|volume=12272|pages=462–470|editor-last=Nisky|editor-first=Ilana|place=Cham|publisher=Springer International Publishing|language=en|doi=10.1007/978-3-030-58147-3_51|isbn=978-3-030-58146-6|last2=Fleer|first2=Sascha|last3=Walck|first3=Guillaume|last4=Ritter|first4=Helge|series=Lecture Notes in Computer Science |s2cid=220069113|editor2-last=Hartcher-O'Brien|editor2-first=Jess|editor3-last=Wiertlewski|editor3-first=Michaël|editor4-last=Smeets|editor4-first=Jeroen|doi-access=free}}] and finally [[meta-learning (computer science)|meta-learning]] (e.g. MAML).
==== Association rules ====
{{Main|Association rule learning}}{{See also|Inductive logic programming}}
Association rule learning is a [[rule-based machine learning]] method for discovering relationships between variables in large databases. It is intended to identify strong rules discovered in databases using some measure of "interestingness".[Piatetsky-Shapiro, Gregory (1991), ''Discovery, analysis, and presentation of strong rules'', in Piatetsky-Shapiro, Gregory; and Frawley, William J.; eds., ''Knowledge Discovery in Databases'', AAAI/MIT Press, Cambridge, MA.]
Rule-based machine learning is a general term for any machine learning method that identifies, learns, or evolves "rules" to store, manipulate or apply knowledge. The defining characteristic of a rule-based machine learning algorithm is the identification and utilisation of a set of relational rules that collectively represent the knowledge captured by the system. This is in contrast to other machine learning algorithms that commonly identify a singular model that can be universally applied to any instance in order to make a prediction.[{{Cite journal|last1=Bassel|first1=George W.|last2=Glaab|first2=Enrico|last3=Marquez|first3=Julietta|last4=Holdsworth|first4=Michael J.|last5=Bacardit|first5=Jaume|date=1 September 2011|title=Functional Network Construction in Arabidopsis Using Rule-Based Machine Learning on Large-Scale Data Sets|journal=The Plant Cell|language=en|volume=23|issue=9|pages=3101–3116|doi=10.1105/tpc.111.088153|issn=1532-298X|pmc=3203449|pmid=21896882|bibcode=2011PlanC..23.3101B }}] Rule-based machine learning approaches include [[learning classifier system]]s, association rule learning, and [[artificial immune system]]s.
Based on the concept of strong rules, [[Rakesh Agrawal (computer scientist)|Rakesh Agrawal]], [[Tomasz Imieliński]] and Arun Swami introduced association rules for discovering regularities between products in large-scale transaction data recorded by [[point-of-sale]] (POS) systems in supermarkets.[{{Cite book | last1 = Agrawal | first1 = R. | last2 = Imieliński | first2 = T. | last3 = Swami | first3 = A. | doi = 10.1145/170035.170072 | chapter = Mining association rules between sets of items in large databases | title = Proceedings of the 1993 ACM SIGMOD international conference on Management of data - SIGMOD '93 | pages = 207 | year = 1993 | isbn = 978-0897915922 | citeseerx = 10.1.1.40.6984 | s2cid = 490415 }}] For example, the rule found in the sales data of a supermarket would indicate that if a customer buys onions and potatoes together, they are likely to also buy hamburger meat. Such information can be used as the basis for decisions about marketing activities such as promotional [[pricing]] or [[product placement]]s. In addition to [[market basket analysis]], association rules are employed today in application areas including [[Web usage mining]], [[intrusion detection]], [[continuous production]], and [[bioinformatics]]. In contrast with [[sequence mining]], association rule learning typically does not consider the order of items either within a transaction or across transactions.
Learning classifier systems (LCS) are a family of rule-based machine learning algorithms that combine a discovery component, typically a [[genetic algorithm]], with a learning component, performing either [[supervised learning]], [[reinforcement learning]], or [[unsupervised learning]]. They seek to identify a set of context-dependent rules that collectively store and apply knowledge in a [[piecewise]] manner in order to make predictions.[{{Cite journal|last1=Urbanowicz|first1=Ryan J.|last2=Moore|first2=Jason H.|date=22 September 2009|title=Learning Classifier Systems: A Complete Introduction, Review, and Roadmap|journal=Journal of Artificial Evolution and Applications|language=en|volume=2009|pages=1–25|doi=10.1155/2009/736398|issn=1687-6229|doi-access=free}}]
[[Inductive logic programming]] (ILP) is an approach to rule learning using [[logic programming]] as a uniform representation for input examples, background knowledge, and hypotheses. Given an encoding of the known background knowledge and a set of examples represented as a logical database of facts, an ILP system will derive a hypothesized logic program that [[Entailment|entails]] all positive and no negative examples. [[Inductive programming]] is a related field that considers any kind of programming language for representing hypotheses (and not only logic programming), such as [[Functional programming|functional programs]].
Inductive logic programming is particularly useful in [[bioinformatics]] and [[natural language processing]]. [[Gordon Plotkin]] and [[Ehud Shapiro]] laid the initial theoretical foundation for inductive machine learning in a logical setting.[Plotkin G.D. [https://www.era.lib.ed.ac.uk/bitstream/handle/1842/6656/Plotkin1972.pdf;sequence=1 Automatic Methods of Inductive Inference] {{Webarchive|url=https://web.archive.org/web/20171222051034/https://www.era.lib.ed.ac.uk/bitstream/handle/1842/6656/Plotkin1972.pdf;sequence=1 |date=22 December 2017 }}, PhD thesis, University of Edinburgh, 1970.][Shapiro, Ehud Y. [http://ftp.cs.yale.edu/publications/techreports/tr192.pdf Inductive inference of theories from facts] {{Webarchive|url=https://web.archive.org/web/20210821071609/http://ftp.cs.yale.edu/publications/techreports/tr192.pdf |date=21 August 2021 }}, Research Report 192, Yale University, Department of Computer Science, 1981. Reprinted in J.-L. Lassez, G. Plotkin (Eds.), Computational Logic, The MIT Press, Cambridge, MA, 1991, pp. 199–254.][Shapiro, Ehud Y. (1983). ''Algorithmic program debugging''. Cambridge, Mass: MIT Press. {{ISBN|0-262-19218-7}}] Shapiro built their first implementation (Model Inference System) in 1981: a Prolog program that inductively inferred logic programs from positive and negative examples.[Shapiro, Ehud Y. "[http://dl.acm.org/citation.cfm?id=1623364 The model inference system] {{Webarchive|url=https://web.archive.org/web/20230406011006/https://dl.acm.org/citation.cfm?id=1623364 |date=2023-04-06 }}." Proceedings of the 7th international joint conference on Artificial intelligence-Volume 2. Morgan Kaufmann Publishers Inc., 1981.] The term ''inductive'' here refers to [[Inductive reasoning|philosophical]] induction, suggesting a theory to explain observed facts, rather than [[mathematical induction]], proving a property for all members of a well-ordered set.
== Models ==
A '''{{vanchor|machine learning model}}''' is a type of [[mathematical model]] that, once "trained" on a given dataset, can be used to make predictions or classifications on new data. During training, a learning algorithm iteratively adjusts the model's internal parameters to minimise errors in its predictions.[{{Cite book |last=Burkov |first=Andriy |title=The hundred-page machine learning book |date=2019 |publisher=Andriy Burkov |isbn=978-1-9995795-0-0 |location=Polen}}] By extension, the term "model" can refer to several levels of specificity, from a general class of models and their associated learning algorithms to a fully trained model with all its internal parameters tuned.[{{Cite book |last1=Russell |first1=Stuart J. |title=Artificial intelligence: a modern approach |last2=Norvig |first2=Peter |date=2021 |publisher=Pearson |isbn=978-0-13-461099-3 |edition=Fourth |series=Pearson series in artificial intelligence |location=Hoboken}}]
Various types of models have been used and researched for machine learning systems, picking the best model for a task is called [[model selection]].
=== Artificial neural networks ===
{{Main|Artificial neural network}}{{See also|Deep learning}}
[[File:Colored neural network.svg|thumb|300px|An artificial neural network is an interconnected group of nodes, akin to the vast network of [[neuron]]s in a [[brain]]. Here, each circular node represents an [[artificial neuron]] and an arrow represents a connection from the output of one artificial neuron to the input of another.]]
Artificial neural networks (ANNs), or [[Connectionism|connectionist]] systems, are computing systems vaguely inspired by the [[biological neural network]]s that constitute animal [[brain]]s. Such systems "learn" to perform tasks by considering examples, generally without being programmed with any task-specific rules.
An ANN is a model based on a collection of connected units or nodes called "[[artificial neuron]]s", which loosely model the [[neuron]]s in a biological brain. Each connection, like the [[synapse]]s in a biological brain, can transmit information, a "signal", from one artificial neuron to another. An artificial neuron that receives a signal can process it and then signal additional artificial neurons connected to it. In common ANN implementations, the signal at a connection between artificial neurons is a [[real number]], and the output of each artificial neuron is computed by some non-linear function of the sum of its inputs. The connections between artificial neurons are called "edges". Artificial neurons and edges typically have a [[weight (mathematics)|weight]] that adjusts as learning proceeds. The weight increases or decreases the strength of the signal at a connection. Artificial neurons may have a threshold such that the signal is only sent if the aggregate signal crosses that threshold. Typically, artificial neurons are aggregated into layers. Different layers may perform different kinds of transformations on their inputs. Signals travel from the first layer (the input layer) to the last layer (the output layer), possibly after traversing the layers multiple times.
The original goal of the ANN approach was to solve problems in the same way that a [[human brain]] would. However, over time, attention moved to performing specific tasks, leading to deviations from [[biology]]. Artificial neural networks have been used on a variety of tasks, including [[computer vision]], [[speech recognition]], [[machine translation]], [[social network]] filtering, [[general game playing|playing board and video games]] and [[medical diagnosis]].
[[Deep learning]] consists of multiple hidden layers in an artificial neural network. This approach tries to model the way the human brain processes light and sound into vision and hearing. Some successful applications of deep learning are computer vision and speech recognition.[Honglak Lee, Roger Grosse, Rajesh Ranganath, Andrew Y. Ng. "[http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.149.802&rep=rep1&type=pdf Convolutional Deep Belief Networks for Scalable Unsupervised Learning of Hierarchical Representations] {{Webarchive|url=https://web.archive.org/web/20171018182235/http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.149.802&rep=rep1&type=pdf |date=2017-10-18 }}" Proceedings of the 26th Annual International Conference on Machine Learning, 2009.]
=== Decision trees ===
{{Main|Decision tree learning}}
[[File:Decision Tree.jpg|thumb|A decision tree showing survival probability of passengers on the [[Titanic]]]]
Decision tree learning uses a [[decision tree]] as a [[Predictive modeling|predictive model]] to go from observations about an item (represented in the branches) to conclusions about the item's target value (represented in the leaves). It is one of the predictive modelling approaches used in statistics, data mining, and machine learning. Tree models where the target variable can take a discrete set of values are called classification trees; in these tree structures, [[leaf node|leaves]] represent class labels, and branches represent [[Logical conjunction|conjunction]]s of features that lead to those class labels. Decision trees where the target variable can take continuous values (typically [[real numbers]]) are called regression trees. In decision analysis, a decision tree can be used to visually and explicitly represent decisions and [[decision making]]. In data mining, a decision tree describes data, but the resulting classification tree can be an input for decision-making.
=== Random forest regression ===
Random forest regression (RFR) falls under umbrella of decision tree-based models. RFR is an ensemble learning method that builds multiple decision trees and averages their predictions to improve accuracy and to avoid overfitting. To build decision trees, RFR uses bootstrapped sampling, for instance each decision tree is trained on random data of from training set. This random selection of RFR for training enables model to reduce bias predictions and achieve accuracy. RFR generates independent decision trees, and it can work on single output data as well multiple regressor task. This makes RFR compatible to be used in various application.[{{Cite web |title=RandomForestRegressor |url=https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestRegressor.html |access-date=12 February 2025 |website=scikit-learn |language=en}}][{{Cite web |date=20 October 2021 |title=What Is Random Forest? {{!}} IBM |url=https://www.ibm.com/think/topics/random-forest |access-date=12 February 2025 |website=www.ibm.com |language=en}}]
=== Support-vector machines ===
{{Main|Support-vector machine}}
Support-vector machines (SVMs), also known as support-vector networks, are a set of related [[supervised learning]] methods used for classification and regression. Given a set of training examples, each marked as belonging to one of two categories, an SVM training algorithm builds a model that predicts whether a new example falls into one category.[{{Cite journal |last1=Cortes |first1=Corinna |author-link1=Corinna Cortes |last2=Vapnik |first2=Vladimir N. |year=1995 |title=Support-vector networks |journal=[[Machine Learning (journal)|Machine Learning]] |volume=20 |issue=3 |pages=273–297 |doi=10.1007/BF00994018 |doi-access=free }}] An SVM training algorithm is a non-[[probabilistic classification|probabilistic]], [[binary classifier|binary]], [[linear classifier]], although methods such as [[Platt scaling]] exist to use SVM in a probabilistic classification setting. In addition to performing linear classification, SVMs can efficiently perform a non-linear classification using what is called the [[kernel trick]], implicitly mapping their inputs into high-dimensional feature spaces.
=== Regression analysis ===
{{Main|Regression analysis}}
[[Image:Linear regression.svg|thumb|upright=1.3|Illustration of linear regression on a data set]]
Regression analysis encompasses a large variety of statistical methods to estimate the relationship between input variables and their associated features. Its most common form is [[linear regression]], where a single line is drawn to best fit the given data according to a mathematical criterion such as [[ordinary least squares]]. The latter is often extended by [[regularization (mathematics)|regularisation]] methods to mitigate overfitting and bias, as in [[ridge regression]]. When dealing with non-linear problems, go-to models include [[polynomial regression]] (for example, used for trendline fitting in Microsoft Excel[{{cite web|last1=Stevenson|first1=Christopher|title=Tutorial: Polynomial Regression in Excel|url=https://facultystaff.richmond.edu/~cstevens/301/Excel4.html|website=facultystaff.richmond.edu|access-date=22 January 2017|archive-date=2 June 2013|archive-url=https://web.archive.org/web/20130602200850/https://facultystaff.richmond.edu/~cstevens/301/Excel4.html|url-status=live}}]), [[logistic regression]] (often used in [[statistical classification]]) or even [[kernel regression]], which introduces non-linearity by taking advantage of the [[kernel trick]] to implicitly map input variables to higher-dimensional space.
[[General linear model|Multivariate linear regression]] extends the concept of linear regression to handle multiple dependent variables simultaneously. This approach estimates the relationships between a set of input variables and several output variables by fitting a [[Multidimensional system|multidimensional]] linear model. It is particularly useful in scenarios where outputs are interdependent or share underlying patterns, such as predicting multiple economic indicators or reconstructing images,[{{cite journal |last1= Wanta |first1= Damian |last2= Smolik |first2= Aleksander |last3= Smolik |first3= Waldemar T. |last4= Midura |first4= Mateusz |last5= Wróblewski |first5= Przemysław |date= 2025 |title= Image reconstruction using machine-learned pseudoinverse in electrical capacitance tomography |journal= Engineering Applications of Artificial Intelligence |volume= 142|page= 109888|doi= 10.1016/j.engappai.2024.109888 |doi-access= free}}] which are inherently multi-dimensional.
=== Bayesian networks ===
{{Main|Bayesian network}}
[[Image:SimpleBayesNetNodes.svg|thumb|right|A simple Bayesian network. Rain influences whether the sprinkler is activated, and both rain and the sprinkler influence whether the grass is wet.]]
A Bayesian network, belief network, or directed acyclic graphical model is a probabilistic [[graphical model]] that represents a set of [[random variables]] and their [[conditional independence]] with a [[directed acyclic graph]] (DAG). For example, a Bayesian network could represent the probabilistic relationships between diseases and symptoms. Given symptoms, the network can be used to compute the probabilities of the presence of various diseases. Efficient algorithms exist that perform [[Bayesian inference|inference]] and learning. Bayesian networks that model sequences of variables, like [[speech recognition|speech signals]] or [[peptide sequence|protein sequences]], are called [[dynamic Bayesian network]]s. Generalisations of Bayesian networks that can represent and solve decision problems under uncertainty are called [[influence diagram]]s.
=== Gaussian processes ===
{{Main|Gaussian processes}}
[[Image:Regressions sine demo.svg|thumbnail|right|An example of Gaussian Process Regression (prediction) compared with other regression models[The documentation for [[scikit-learn]] also has similar [http://scikit-learn.org/stable/auto_examples/gaussian_process/plot_compare_gpr_krr.html examples] {{Webarchive|url=https://web.archive.org/web/20221102184805/https://scikit-learn.org/stable/auto_examples/gaussian_process/plot_compare_gpr_krr.html |date=2 November 2022 }}.]]]
A Gaussian process is a [[stochastic process]] in which every finite collection of the random variables in the process has a [[multivariate normal distribution]], and it relies on a pre-defined [[covariance function]], or kernel, that models how pairs of points relate to each other depending on their locations.
Given a set of observed points, or input–output examples, the distribution of the (unobserved) output of a new point as function of its input data can be directly computed by looking like the observed points and the covariances between those points and the new, unobserved point.
Gaussian processes are popular surrogate models in [[Bayesian optimisation]] used to do [[hyperparameter optimisation]].
=== Genetic algorithms ===
{{Main|Genetic algorithm}}
A genetic algorithm (GA) is a [[search algorithm]] and [[heuristic (computer science)|heuristic]] technique that mimics the process of [[natural selection]], using methods such as [[Mutation (genetic algorithm)|mutation]] and [[Crossover (genetic algorithm)|crossover]] to generate new [[Chromosome (genetic algorithm)|genotype]]s in the hope of finding good solutions to a given problem. In machine learning, genetic algorithms were used in the 1980s and 1990s.[{{cite journal |last1=Goldberg |first1=David E. |first2=John H. |last2=Holland |title=Genetic algorithms and machine learning |journal=[[Machine Learning (journal)|Machine Learning]] |volume=3 |issue=2 |year=1988 |pages=95–99 |doi=10.1007/bf00113892 |s2cid=35506513 |url=https://deepblue.lib.umich.edu/bitstream/2027.42/46947/1/10994_2005_Article_422926.pdf |doi-access=free |access-date=3 September 2019 |archive-date=16 May 2011 |archive-url=https://web.archive.org/web/20110516025803/http://deepblue.lib.umich.edu/bitstream/2027.42/46947/1/10994_2005_Article_422926.pdf |url-status=live }}][{{Cite journal |title=Machine Learning, Neural and Statistical Classification |journal=Ellis Horwood Series in Artificial Intelligence |first1=D. |last1=Michie |first2=D. J. |last2=Spiegelhalter |first3=C. C. |last3=Taylor |year=1994 |bibcode=1994mlns.book.....M }}] Conversely, machine learning techniques have been used to improve the performance of genetic and [[evolutionary algorithm]]s.[{{cite journal |last1=Zhang |first1=Jun |last2=Zhan |first2=Zhi-hui |last3=Lin |first3=Ying |last4=Chen |first4=Ni |last5=Gong |first5=Yue-jiao |last6=Zhong |first6=Jing-hui |last7=Chung |first7=Henry S.H. |last8=Li |first8=Yun |last9=Shi |first9=Yu-hui |title=Evolutionary Computation Meets Machine Learning: A Survey |journal=Computational Intelligence Magazine |year=2011 |volume=6 |issue=4 |pages=68–75 |doi=10.1109/mci.2011.942584|s2cid=6760276 }}]
=== Belief functions ===
{{Main|Dempster–Shafer theory}}
The theory of belief functions, also referred to as evidence theory or Dempster–Shafer theory, is a general framework for reasoning with uncertainty, with understood connections to other frameworks such as [[probability]], [[Possibility theory|possibility]] and [[Imprecise probability|imprecise probability theories]]. These theoretical frameworks can be thought of as a kind of learner and have some analogous properties of how evidence is combined (e.g., Dempster's rule of combination), just like how in a [[Probability mass function|pmf]]-based Bayesian approach{{clarify|date=January 2024}} would combine probabilities. However, there are many caveats to these beliefs functions when compared to Bayesian approaches in order to incorporate ignorance and [[uncertainty quantification]]. These belief function approaches that are implemented within the machine learning domain typically leverage a fusion approach of various [[ensemble methods]] to better handle the learner's [[decision boundary]], low samples, and ambiguous class issues that standard machine learning approach tend to have difficulty resolving.[{{Cite journal |last1=Urbanowicz |first1=Ryan J. |last2=Moore |first2=Jason H. |date=22 September 2009 |title=Learning Classifier Systems: A Complete Introduction, Review, and Roadmap |journal=Journal of Artificial Evolution and Applications |language=en |volume=2009 |pages=1–25 |doi=10.1155/2009/736398 |issn=1687-6229 |doi-access=free }}] [[association rule learning]],[Zhang, C. and Zhang, S., 2002. ''[https://books.google.com/books?id=VqSoCAAAQBAJ Association rule mining: models and algorithms]''. Springer-Verlag.] [[artificial immune system]]s,[De Castro, Leandro Nunes, and Jonathan Timmis. ''[https://books.google.com/books?id=aMFP7p8DtaQC&q=%22rule-based%22 Artificial immune systems: a new computational intelligence approach]''. Springer Science & Business Media, 2002.] and other similar models. These methods extract patterns from data and evolve rules over time.
=== Training models ===
Typically, machine learning models require a high quantity of reliable data to perform accurate predictions. When training a machine learning model, machine learning engineers need to target and collect a large and representative [[Sample (statistics)|sample]] of data. Data from the training set can be as varied as a [[corpus of text]], a collection of images, [[sensor]] data, and data collected from individual users of a service. [[Overfitting]] is something to watch out for when training a machine learning model. Trained models derived from biased or non-evaluated data can result in skewed or undesired predictions. Biased models may result in detrimental outcomes, thereby furthering the negative impacts on society or objectives. [[Algorithmic bias]] is a potential result of data not being fully prepared for training. Machine learning ethics is becoming a field of study and notably, becoming integrated within machine learning engineering teams.
==== Federated learning ====
{{Main|Federated learning}}
Federated learning is an adapted form of [[distributed artificial intelligence]] to training machine learning models that decentralises the training process, allowing for users' privacy to be maintained by not needing to send their data to a centralised server. This also increases efficiency by decentralising the training process to many devices. For example, [[Gboard]] uses federated machine learning to train search query prediction models on users' mobile phones without having to send individual searches back to [[Google]].[{{Cite web|url=http://ai.googleblog.com/2017/04/federated-learning-collaborative.html|title=Federated Learning: Collaborative Machine Learning without Centralized Training Data|website=Google AI Blog|date=6 April 2017 |language=en|access-date=8 June 2019|archive-date=7 June 2019|archive-url=https://web.archive.org/web/20190607054623/https://ai.googleblog.com/2017/04/federated-learning-collaborative.html|url-status=live}}]
== Applications ==
There are many applications for machine learning, including:
{{cols|colwidth=21em}}
* [[Precision agriculture|Agriculture]]
* [[Computational anatomy|Anatomy]]
* [[Adaptive website]]
* [[Affective computing]]
* [[Astroinformatics|Astronomy]]
* [[Automated decision-making]]
* [[Banking]]
* [[Behaviorism]]
* [[Bioinformatics]]
* [[Brain–computer interface|Brain–machine interfaces]]
* [[Cheminformatics]]
* [[Citizen Science]]
* [[Climate Science]]
* [[Network simulation|Computer networks]]
* [[Computer vision]]
* [[Credit-card fraud]] detection
* [[Data quality]]
* [[DNA sequence]] classification
* [[Computational economics|Economics]]
* [[Financial market]] analysis[Machine learning is included in the [[Chartered Financial Analyst (CFA)#Curriculum|CFA Curriculum]] (discussion is top-down); see: [https://www.cfainstitute.org/-/media/documents/study-session/2020-l2-ss3.ashx Kathleen DeRose and Christophe Le Lanno (2020). "Machine Learning"] {{Webarchive|url=https://web.archive.org/web/20200113085425/https://www.cfainstitute.org/-/media/documents/study-session/2020-l2-ss3.ashx |date=13 January 2020 }}.]
* [[General game playing]]
* [[Handwriting recognition]]
* [[Artificial intelligence in healthcare|Healthcare]]
* [[Information retrieval]]
* [[Insurance]]
* [[Internet fraud]] detection
* [[Knowledge graph embedding]]
* [[Computational linguistics|Linguistics]]
* [[Machine learning control]]
* [[Machine perception]]
* [[Machine translation]]
* [[Material Engineering]]
* [[Marketing]]
* [[Automated medical diagnosis|Medical diagnosis]]
* [[Natural language processing]]
* [[Natural-language understanding|Natural language understanding]]
* [[Online advertising]]
* [[Optimisation]]
* [[Recommender system]]s
* [[Robot locomotion]]
* [[Search engines]]
* [[Sentiment analysis]]
* [[Sequence mining]]
* [[Software engineering]]
* [[Speech recognition]]
* [[Structural health monitoring]]
* [[Syntactic pattern recognition]]
* [[Telecommunications]]
* [[Automated theorem proving|Theorem proving]]
* [[Time series|Time-series forecasting]]
* [[Tomographic reconstruction]][{{cite journal |last1= Ivanenko |first1= Mikhail |last2= Smolik |first2= Waldemar T. |last3= Wanta |first3= Damian |last4= Midura |first4= Mateusz |last5= Wróblewski |first5= Przemysław |last6= Hou |first6= Xiaohan |last7= Yan |first7= Xiaoheng |date= 2023 |title= Image Reconstruction Using Supervised Learning in Wearable Electrical Impedance Tomography of the Thorax |journal= Sensors |volume= 23|issue= 18|page= 7774|doi= 10.3390/s23187774|pmid= 37765831 |pmc= 10538128 |bibcode= 2023Senso..23.7774I |doi-access= free}}]
* [[User behaviour analytics]]
{{colend}}
In 2006, the media-services provider [[Netflix]] held the first "[[Netflix Prize]]" competition to find a program to better predict user preferences and improve the accuracy of its existing Cinematch movie recommendation algorithm by at least 10%. A joint team made up of researchers from [[AT&T Labs]]-Research in collaboration with the teams Big Chaos and Pragmatic Theory built an [[Ensemble Averaging|ensemble model]] to win the Grand Prize in 2009 for $1 million.[[https://web.archive.org/web/20151110062742/http://www2.research.att.com/~volinsky/netflix/ "BelKor Home Page"] research.att.com] Shortly after the prize was awarded, Netflix realised that viewers' ratings were not the best indicators of their viewing patterns ("everything is a recommendation") and they changed their recommendation engine accordingly.[{{cite web|url=http://techblog.netflix.com/2012/04/netflix-recommendations-beyond-5-stars.html|title=The Netflix Tech Blog: Netflix Recommendations: Beyond the 5 stars (Part 1)|access-date=8 August 2015|date=6 April 2012|archive-url=https://web.archive.org/web/20160531002916/http://techblog.netflix.com/2012/04/netflix-recommendations-beyond-5-stars.html|archive-date=31 May 2016}}] In 2010 The Wall Street Journal wrote about the firm Rebellion Research and their use of machine learning to predict the financial crisis.[{{cite web|url=https://www.wsj.com/articles/SB10001424052748703834604575365310813948080|title=Letting the Machines Decide|author=Scott Patterson|date=13 July 2010|publisher=[[The Wall Street Journal]]|access-date=24 June 2018|archive-date=24 June 2018|archive-url=https://web.archive.org/web/20180624151019/https://www.wsj.com/articles/SB10001424052748703834604575365310813948080|url-status=live}}] In 2012, co-founder of [[Sun Microsystems]], [[Vinod Khosla]], predicted that 80% of medical doctors jobs would be lost in the next two decades to automated machine learning medical diagnostic software.[{{cite web|url=https://techcrunch.com/2012/01/10/doctors-or-algorithms/|author=Vinod Khosla|publisher=Tech Crunch|title=Do We Need Doctors or Algorithms?|date=10 January 2012|access-date=20 October 2016|archive-date=18 June 2018|archive-url=https://web.archive.org/web/20180618175811/https://techcrunch.com/2012/01/10/doctors-or-algorithms/|url-status=live}}] In 2014, it was reported that a machine learning algorithm had been applied in the field of art history to study fine art paintings and that it may have revealed previously unrecognised influences among artists.[[https://medium.com/the-physics-arxiv-blog/when-a-machine-learning-algorithm-studied-fine-art-paintings-it-saw-things-art-historians-had-never-b8e4e7bf7d3e When A Machine Learning Algorithm Studied Fine Art Paintings, It Saw Things Art Historians Had Never Noticed] {{Webarchive|url=https://web.archive.org/web/20160604072143/https://medium.com/the-physics-arxiv-blog/when-a-machine-learning-algorithm-studied-fine-art-paintings-it-saw-things-art-historians-had-never-b8e4e7bf7d3e |date=4 June 2016 }}, ''The Physics at [[ArXiv]] blog''] In 2019 [[Springer Nature]] published the first research book created using machine learning.[{{Cite web|url=https://www.theverge.com/2019/4/10/18304558/ai-writing-academic-research-book-springer-nature-artificial-intelligence|title=The first AI-generated textbook shows what robot writers are actually good at|last=Vincent|first=James|date=10 April 2019|website=The Verge|access-date=5 May 2019|archive-date=5 May 2019|archive-url=https://web.archive.org/web/20190505200409/https://www.theverge.com/2019/4/10/18304558/ai-writing-academic-research-book-springer-nature-artificial-intelligence|url-status=live}}] In 2020, machine learning technology was used to help make diagnoses and aid researchers in developing a cure for COVID-19.[{{Cite journal|title=Artificial Intelligence (AI) applications for COVID-19 pandemic|date=1 July 2020|journal=Diabetes & Metabolic Syndrome: Clinical Research & Reviews|volume=14|issue=4|pages=337–339|doi=10.1016/j.dsx.2020.04.012|doi-access=free|last1=Vaishya|first1=Raju|last2=Javaid|first2=Mohd|last3=Khan|first3=Ibrahim Haleem|last4=Haleem|first4=Abid|pmid=32305024|pmc=7195043}}] Machine learning was recently applied to predict the pro-environmental behaviour of travellers.[{{Cite journal|title=Application of machine learning to predict visitors' green behavior in marine protected areas: evidence from Cyprus|first1=Hamed|last1=Rezapouraghdam|first2=Arash|last2=Akhshik|first3=Haywantee|last3=Ramkissoon|date=10 March 2021|journal=Journal of Sustainable Tourism|volume=31 |issue=11 |pages=2479–2505|doi=10.1080/09669582.2021.1887878|doi-access=free|hdl=10037/24073|hdl-access=free}}] Recently, machine learning technology was also applied to optimise smartphone's performance and thermal behaviour based on the user's interaction with the phone.[{{Cite book|last1=Dey|first1=Somdip|last2=Singh|first2=Amit Kumar|last3=Wang|first3=Xiaohang|last4=McDonald-Maier|first4=Klaus|title=2020 Design, Automation & Test in Europe Conference & Exhibition (DATE) |chapter=User Interaction Aware Reinforcement Learning for Power and Thermal Efficiency of CPU-GPU Mobile MPSoCs |date=15 June 2020|chapter-url=https://ieeexplore.ieee.org/document/9116294|pages=1728–1733|doi=10.23919/DATE48585.2020.9116294|isbn=978-3-9819263-4-7|s2cid=219858480|url=http://repository.essex.ac.uk/27546/1/User%20Interaction%20Aware%20Reinforcement%20Learning.pdf |access-date=20 January 2022|archive-date=13 December 2021|archive-url=https://web.archive.org/web/20211213192526/https://ieeexplore.ieee.org/document/9116294/|url-status=live}}][{{Cite news|last=Quested|first=Tony|title=Smartphones get smarter with Essex innovation|work=Business Weekly|url=https://www.businessweekly.co.uk/news/academia-research/smartphones-get-smarter-essex-innovation|access-date=17 June 2021|archive-date=24 June 2021|archive-url=https://web.archive.org/web/20210624200126/https://www.businessweekly.co.uk/news/academia-research/smartphones-get-smarter-essex-innovation|url-status=live}}][{{Cite news|last=Williams|first=Rhiannon|date=21 July 2020|title=Future smartphones 'will prolong their own battery life by monitoring owners' behaviour'|url=https://inews.co.uk/news/technology/future-smartphones-prolong-battery-life-monitoring-behaviour-558689|access-date=17 June 2021|newspaper=[[i (British newspaper)|i]]|language=en|archive-date=24 June 2021|archive-url=https://web.archive.org/web/20210624201153/https://inews.co.uk/news/technology/future-smartphones-prolong-battery-life-monitoring-behaviour-558689|url-status=live}}] When applied correctly, machine learning algorithms (MLAs) can utilise a wide range of company characteristics to predict stock returns without [[overfitting]]. By employing effective feature engineering and combining forecasts, MLAs can generate results that far surpass those obtained from basic linear techniques like [[Ordinary least squares|OLS]].[{{Cite journal |last1=Rasekhschaffe |first1=Keywan Christian |last2=Jones |first2=Robert C. |date=1 July 2019 |title=Machine Learning for Stock Selection |url=https://www.tandfonline.com/doi/full/10.1080/0015198X.2019.1596678 |journal=Financial Analysts Journal |language=en |volume=75 |issue=3 |pages=70–88 |doi=10.1080/0015198X.2019.1596678 |s2cid=108312507 |issn=0015-198X |access-date=26 November 2023 |archive-date=26 November 2023 |archive-url=https://web.archive.org/web/20231126160605/https://www.tandfonline.com/doi/full/10.1080/0015198X.2019.1596678 |url-status=live |url-access=subscription }}]
Recent advancements in machine learning have extended into the field of quantum chemistry, where novel algorithms now enable the prediction of solvent effects on chemical reactions, thereby offering new tools for chemists to tailor experimental conditions for optimal outcomes.[{{Cite journal |last1=Chung |first1=Yunsie |last2=Green |first2=William H. |date=2024 |title=Machine learning from quantum chemistry to predict experimental solvent effects on reaction rates |journal=Chemical Science |language=en |volume=15 |issue=7 |pages=2410–2424 |doi=10.1039/D3SC05353A |issn=2041-6520 |pmc=10866337 |pmid=38362410 }}]
Machine Learning is becoming a useful tool to investigate and predict evacuation decision making in large scale and small scale disasters. Different solutions have been tested to predict if and when householders decide to evacuate during wildfires and hurricanes.[{{Cite journal |last1=Sun |first1=Yuran |last2=Huang |first2=Shih-Kai |last3=Zhao |first3=Xilei |date=1 February 2024 |title=Predicting Hurricane Evacuation Decisions with Interpretable Machine Learning Methods |journal=International Journal of Disaster Risk Science |language=en |volume=15 |issue=1 |pages=134–148 |doi=10.1007/s13753-024-00541-1 |issn=2192-6395 |doi-access=free |arxiv=2303.06557 |bibcode=2024IJDRS..15..134S }}][{{Citation |last1=Sun |first1=Yuran |title=8 - AI for large-scale evacuation modeling: promises and challenges |date=1 January 2024 |work=Interpretable Machine Learning for the Analysis, Design, Assessment, and Informed Decision Making for Civil Infrastructure |pages=185–204 |editor-last=Naser |editor-first=M. Z. |url=https://www.sciencedirect.com/science/article/pii/B9780128240731000149 |access-date=19 May 2024 |series=Woodhead Publishing Series in Civil and Structural Engineering |publisher=Woodhead Publishing |isbn=978-0-12-824073-1 |last2=Zhao |first2=Xilei |last3=Lovreglio |first3=Ruggiero |last4=Kuligowski |first4=Erica |archive-date=19 May 2024 |archive-url=https://web.archive.org/web/20240519121547/https://www.sciencedirect.com/science/article/abs/pii/B9780128240731000149 |url-status=live }}][{{Cite journal |last1=Xu |first1=Ningzhe |last2=Lovreglio |first2=Ruggiero |last3=Kuligowski |first3=Erica D. |last4=Cova |first4=Thomas J. |last5=Nilsson |first5=Daniel |last6=Zhao |first6=Xilei |date=1 March 2023 |title=Predicting and Assessing Wildfire Evacuation Decision-Making Using Machine Learning: Findings from the 2019 Kincade Fire |url=https://doi.org/10.1007/s10694-023-01363-1 |journal=Fire Technology |language=en |volume=59 |issue=2 |pages=793–825 |doi=10.1007/s10694-023-01363-1 |issn=1572-8099 |access-date=19 May 2024 |archive-date=19 May 2024 |archive-url=https://web.archive.org/web/20240519121534/https://link.springer.com/article/10.1007/s10694-023-01363-1 |url-status=live |url-access=subscription }}] Other applications have been focusing on pre evacuation decisions in building fires.[{{Cite journal |last1=Wang |first1=Ke |last2=Shi |first2=Xiupeng |last3=Goh |first3=Algena Pei Xuan |last4=Qian |first4=Shunzhi |date=1 June 2019 |title=A machine learning based study on pedestrian movement dynamics under emergency evacuation |url=https://www.sciencedirect.com/science/article/pii/S037971121830376X |journal=Fire Safety Journal |volume=106 |pages=163–176 |doi=10.1016/j.firesaf.2019.04.008 |bibcode=2019FirSJ.106..163W |issn=0379-7112 |access-date=19 May 2024 |archive-date=19 May 2024 |archive-url=https://web.archive.org/web/20240519121539/https://www.sciencedirect.com/science/article/abs/pii/S037971121830376X |url-status=live |hdl=10356/143390 |hdl-access=free }}][{{Cite journal |last1=Zhao |first1=Xilei |last2=Lovreglio |first2=Ruggiero |last3=Nilsson |first3=Daniel |date=1 May 2020 |title=Modelling and interpreting pre-evacuation decision-making using machine learning |url=https://www.sciencedirect.com/science/article/pii/S0926580519313184 |journal=Automation in Construction |volume=113 |pages=103140 |doi=10.1016/j.autcon.2020.103140 |hdl=10179/17315 |issn=0926-5805 |access-date=19 May 2024 |archive-date=19 May 2024 |archive-url=https://web.archive.org/web/20240519121548/https://www.sciencedirect.com/science/article/abs/pii/S0926580519313184 |url-status=live |hdl-access=free }}]
Machine learning is also emerging as a promising tool in geotechnical engineering, where it is used to support tasks such as ground classification, hazard prediction, and site characterization. Recent research emphasizes a move toward data-centric methods in this field, where machine learning is not a replacement for engineering judgment, but a way to enhance it using site-specific data and patterns.[{{Cite journal |last=Phoon |first=Kok-Kwang |last2=Zhang |first2=Wengang |date=2023-01-02 |title=Future of machine learning in geotechnics |url=https://www.tandfonline.com/doi/full/10.1080/17499518.2022.2087884 |journal=Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards |language=en |volume=17 |issue=1 |pages=7–22 |doi=10.1080/17499518.2022.2087884 |issn=1749-9518}}]
== Limitations ==
Although machine learning has been transformative in some fields, machine-learning programs often fail to deliver expected results.[{{Cite news|url=https://www.bloomberg.com/news/articles/2016-11-10/why-machine-learning-models-often-fail-to-learn-quicktake-q-a|title=Why Machine Learning Models Often Fail to Learn: QuickTake Q&A|date=10 November 2016|work=Bloomberg.com|access-date=10 April 2017|archive-url=https://web.archive.org/web/20170320225010/https://www.bloomberg.com/news/articles/2016-11-10/why-machine-learning-models-often-fail-to-learn-quicktake-q-a|archive-date=20 March 2017}}][{{Cite news|url=https://hbr.org/2017/04/the-first-wave-of-corporate-ai-is-doomed-to-fail|title=The First Wave of Corporate AI Is Doomed to Fail|date=18 April 2017|work=Harvard Business Review|access-date=20 August 2018|archive-date=21 August 2018|archive-url=https://web.archive.org/web/20180821032004/https://hbr.org/2017/04/the-first-wave-of-corporate-ai-is-doomed-to-fail|url-status=live}}][{{Cite news|url=https://venturebeat.com/2016/09/17/why-the-a-i-euphoria-is-doomed-to-fail/|title=Why the A.I. euphoria is doomed to fail|date=18 September 2016|work=VentureBeat|access-date=20 August 2018|language=en-US|archive-date=19 August 2018|archive-url=https://web.archive.org/web/20180819124138/https://venturebeat.com/2016/09/17/why-the-a-i-euphoria-is-doomed-to-fail/|url-status=live}}] Reasons for this are numerous: lack of (suitable) data, lack of access to the data, data bias, privacy problems, badly chosen tasks and algorithms, wrong tools and people, lack of resources, and evaluation problems.[{{Cite web|url=https://www.kdnuggets.com/2018/07/why-machine-learning-project-fail.html|title=9 Reasons why your machine learning project will fail|website=www.kdnuggets.com|language=en-US|access-date=20 August 2018|archive-date=21 August 2018|archive-url=https://web.archive.org/web/20180821031802/https://www.kdnuggets.com/2018/07/why-machine-learning-project-fail.html|url-status=live}}]
The "[[Black box|black box theory]]" poses another yet significant challenge. Black box refers to a situation where the algorithm or the process of producing an output is entirely opaque, meaning that even the coders of the algorithm cannot audit the pattern that the machine extracted out of the data.[{{Cite report |url=https://www.jstor.org/stable/resrep37375.8 |title=Transparency and Intelligibility |last1=Babuta |first1=Alexander |last2=Oswald |first2=Marion |date=2018 |publisher=Royal United Services Institute (RUSI) |pages=17–22 |last3=Rinik |first3=Christine |access-date=9 December 2023 |archive-date=9 December 2023 |archive-url=https://web.archive.org/web/20231209002929/https://www.jstor.org/stable/resrep37375.8 |url-status=live }}] The House of Lords Select Committee, which claimed that such an "intelligence system" that could have a "substantial impact on an individual's life" would not be considered acceptable unless it provided "a full and satisfactory explanation for the decisions" it makes.[{{Cite news|url=https://www.economist.com/the-economist-explains/2018/05/29/why-ubers-self-driving-car-killed-a-pedestrian|title=Why Uber's self-driving car killed a pedestrian|newspaper=The Economist|access-date=20 August 2018|language=en|archive-date=21 August 2018|archive-url=https://web.archive.org/web/20180821031818/https://www.economist.com/the-economist-explains/2018/05/29/why-ubers-self-driving-car-killed-a-pedestrian|url-status=live}}] Attempts to use machine learning in healthcare with the [[Watson (computer)|IBM Watson]] system failed to deliver even after years of time and billions of dollars invested.[{{Cite news|url=https://www.statnews.com/2018/07/25/ibm-watson-recommended-unsafe-incorrect-treatments/|title=IBM's Watson recommended 'unsafe and incorrect' cancer treatments – STAT|date=25 July 2018|work=STAT|access-date=21 August 2018|language=en-US|archive-date=21 August 2018|archive-url=https://web.archive.org/web/20180821062616/https://www.statnews.com/2018/07/25/ibm-watson-recommended-unsafe-incorrect-treatments/|url-status=live}}][{{Cite news|url=https://www.wsj.com/articles/ibm-bet-billions-that-watson-could-improve-cancer-treatment-it-hasnt-worked-1533961147|title=IBM Has a Watson Dilemma|last1=Hernandez|first1=Daniela|date=11 August 2018|work=[[The Wall Street Journal]]|access-date=21 August 2018|last2=Greenwald|first2=Ted|language=en-US|issn=0099-9660|archive-date=21 August 2018|archive-url=https://web.archive.org/web/20180821031906/https://www.wsj.com/articles/ibm-bet-billions-that-watson-could-improve-cancer-treatment-it-hasnt-worked-1533961147|url-status=live}}] Microsoft's [[Bing Chat]] chatbot has been reported to produce hostile and offensive response against its users.[{{Cite web |last=Allyn |first=Bobby |date=27 February 2023 |title=How Microsoft's experiment in artificial intelligence tech backfired |url=https://www.npr.org/2023/02/27/1159630243/how-microsofts-experiment-in-artificial-intelligence-tech-backfired |access-date=8 December 2023 |website=National Public Radio |archive-date=8 December 2023 |archive-url=https://web.archive.org/web/20231208234056/https://www.npr.org/2023/02/27/1159630243/how-microsofts-experiment-in-artificial-intelligence-tech-backfired |url-status=live }}]
Machine learning has been used as a strategy to update the evidence related to a systematic review and increased reviewer burden related to the growth of biomedical literature. While it has improved with training sets, it has not yet developed sufficiently to reduce the workload burden without limiting the necessary sensitivity for the findings research themselves.[{{Cite journal|last1=Reddy|first1=Shivani M.|last2=Patel|first2=Sheila|last3=Weyrich|first3=Meghan|last4=Fenton|first4=Joshua|last5=Viswanathan|first5=Meera|date=2020|title=Comparison of a traditional systematic review approach with review-of-reviews and semi-automation as strategies to update the evidence|url= |journal=Systematic Reviews|language=en|volume=9|issue=1|pages=243|doi=10.1186/s13643-020-01450-2|issn=2046-4053|pmc=7574591|pmid=33076975 |doi-access=free }}]
=== Explainability ===
{{Main|Explainable artificial intelligence}}
Explainable AI (XAI), or Interpretable AI, or Explainable Machine Learning (XML), is artificial intelligence (AI) in which humans can understand the decisions or predictions made by the AI.[{{cite journal |last1=Rudin |first1=Cynthia |title=Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead |journal=Nature Machine Intelligence |date=2019 |volume=1 |issue=5 |pages=206–215 |doi=10.1038/s42256-019-0048-x |pmid=35603010 |pmc=9122117 }}] It contrasts with the "black box" concept in machine learning where even its designers cannot explain why an AI arrived at a specific decision.[{{cite journal |last1=Hu |first1=Tongxi |last2=Zhang |first2=Xuesong |last3=Bohrer |first3=Gil |last4=Liu |first4=Yanlan |last5=Zhou |first5=Yuyu |last6=Martin |first6=Jay |last7=LI |first7=Yang |last8=Zhao |first8=Kaiguang |title=Crop yield prediction via explainable AI and interpretable machine learning: Dangers of black box models for evaluating climate change impacts on crop yield|journal=Agricultural and Forest Meteorology |date=2023 |volume=336 |page=109458 |doi=10.1016/j.agrformet.2023.109458 |s2cid=258552400 |doi-access=free }}] By refining the mental models of users of AI-powered systems and dismantling their misconceptions, XAI promises to help users perform more effectively. XAI may be an implementation of the social right to explanation.
=== Overfitting ===
{{Main|Overfitting}}
[[File: Overfitted Data.png|thumb|The blue line could be an example of overfitting a linear function due to random noise.]]
Settling on a bad, overly complex theory gerrymandered to fit all the past training data is known as overfitting. Many systems attempt to reduce overfitting by rewarding a theory in accordance with how well it fits the data but penalising the theory in accordance with how complex the theory is.{{sfn|Domingos|2015|loc=Chapter 6, Chapter 7}}
=== Other limitations and vulnerabilities ===
Learners can also disappoint by "learning the wrong lesson". A toy example is that an image classifier trained only on pictures of brown horses and black cats might conclude that all brown patches are likely to be horses.{{sfn|Domingos|2015|p=286}} A real-world example is that, unlike humans, current image classifiers often do not primarily make judgements from the spatial relationship between components of the picture, and they learn relationships between pixels that humans are oblivious to, but that still correlate with images of certain types of real objects. Modifying these patterns on a legitimate image can result in "adversarial" images that the system misclassifies.[{{cite news|title=Single pixel change fools AI programs|url=https://www.bbc.com/news/technology-41845878|access-date=12 March 2018|work=BBC News|date=3 November 2017|archive-date=22 March 2018|archive-url=https://web.archive.org/web/20180322011306/http://www.bbc.com/news/technology-41845878|url-status=live}}][{{cite news|title=AI Has a Hallucination Problem That's Proving Tough to Fix|url=https://www.wired.com/story/ai-has-a-hallucination-problem-thats-proving-tough-to-fix/|access-date=12 March 2018|magazine=WIRED|date=2018|archive-date=12 March 2018|archive-url=https://web.archive.org/web/20180312024533/https://www.wired.com/story/ai-has-a-hallucination-problem-thats-proving-tough-to-fix/|url-status=live}}]
Adversarial vulnerabilities can also result in nonlinear systems, or from non-pattern perturbations. For some systems, it is possible to change the output by only changing a single adversarially chosen pixel.[{{cite arXiv | title=Towards deep learning models resistant to adversarial attacks| author1=Madry, A.| author2=Makelov, A.| author3=Schmidt, L.| author4=Tsipras, D.| author5=Vladu, A. | date=4 September 2019| class=stat.ML| eprint=1706.06083}}] Machine learning models are often vulnerable to manipulation or evasion via [[adversarial machine learning]].[{{cite web |title=Adversarial Machine Learning – CLTC UC Berkeley Center for Long-Term Cybersecurity |url=https://cltc.berkeley.edu/aml/ |website=CLTC |access-date=25 May 2022 |archive-date=17 May 2022 |archive-url=https://web.archive.org/web/20220517045352/https://cltc.berkeley.edu/aml/ |url-status=live }}]
Researchers have demonstrated how [[Backdoor (computing)|backdoors]] can be placed undetectably into classifying (e.g., for categories "spam" and well-visible "not spam" of posts) machine learning models that are often developed or trained by third parties. Parties can change the classification of any input, including in cases for which a type of [[algorithmic transparency|data/software transparency]] is provided, possibly including [[white-box testing|white-box access]].[{{cite news |title=Machine-learning models vulnerable to undetectable backdoors |url=https://www.theregister.com/2022/04/21/machine_learning_models_backdoors/ |access-date=13 May 2022 |work=[[The Register]] |language=en |archive-date=13 May 2022 |archive-url=https://web.archive.org/web/20220513171215/https://www.theregister.com/2022/04/21/machine_learning_models_backdoors/ |url-status=live }}][{{cite news |title=Undetectable Backdoors Plantable In Any Machine-Learning Algorithm |url=https://spectrum.ieee.org/machine-learningbackdoor |access-date=13 May 2022 |work=[[IEEE Spectrum]] |date=10 May 2022 |language=en |archive-date=11 May 2022 |archive-url=https://web.archive.org/web/20220511152052/https://spectrum.ieee.org/machine-learningbackdoor |url-status=live }}][{{Cite arXiv|last1=Goldwasser |first1=Shafi |last2=Kim |first2=Michael P. |last3=Vaikuntanathan |first3=Vinod |last4=Zamir |first4=Or |title=Planting Undetectable Backdoors in Machine Learning Models |date=14 April 2022|class=cs.LG |eprint=2204.06974 }}]
== Model assessments ==
Classification of machine learning models can be validated by accuracy estimation techniques like the [[Test set|holdout]] method, which splits the data in a training and test set (conventionally 2/3 training set and 1/3 test set designation) and evaluates the performance of the training model on the test set. In comparison, the K-fold-[[Cross-validation (statistics)|cross-validation]] method randomly partitions the data into K subsets and then K experiments are performed each respectively considering 1 subset for evaluation and the remaining K-1 subsets for training the model. In addition to the holdout and cross-validation methods, [[Bootstrapping (statistics)|bootstrap]], which samples n instances with replacement from the dataset, can be used to assess model accuracy.[{{cite journal|last1=Kohavi|first1=Ron|title=A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection|journal=International Joint Conference on Artificial Intelligence|date=1995|url=https://ai.stanford.edu/~ronnyk/accEst.pdf|access-date=26 March 2023|archive-date=12 July 2018|archive-url=https://web.archive.org/web/20180712102706/http://web.cs.iastate.edu/~jtian/cs573/Papers/Kohavi-IJCAI-95.pdf|url-status=live}}]
In addition to overall accuracy, investigators frequently report [[sensitivity and specificity]] meaning true positive rate (TPR) and true negative rate (TNR) respectively. Similarly, investigators sometimes report the [[false positive rate]] (FPR) as well as the [[false negative rate]] (FNR). However, these rates are ratios that fail to reveal their numerators and denominators. [[Receiver operating characteristic]] (ROC) along with the accompanying Area Under the ROC Curve (AUC) offer additional tools for classification model assessment. Higher AUC is associated with a better performing model.[{{cite journal|last1=Catal|first1=Cagatay|title=Performance Evaluation Metrics for Software Fault Prediction Studies|journal=Acta Polytechnica Hungarica|date=2012|volume=9|issue=4|url=http://www.uni-obuda.hu/journal/Catal_36.pdf|accessdate=2 October 2016}}]
== Ethics ==
{{Excerpt|Ethics of artificial intelligence|templates=-Artificial intelligence}}
=== Bias ===
{{Main|Algorithmic bias}}
Different machine learning approaches can suffer from different data biases. A machine learning system trained specifically on current customers may not be able to predict the needs of new customer groups that are not represented in the training data. When trained on human-made data, machine learning is likely to pick up the constitutional and unconscious biases already present in society.[{{Cite journal |last=Garcia |first=Megan |date=2016 |title=Racist in the Machine |journal=World Policy Journal |language=en |volume=33 |issue=4 |pages=111–117 |doi=10.1215/07402775-3813015 |issn=0740-2775 |s2cid=151595343}}]
Systems that are trained on datasets collected with biases may exhibit these biases upon use (algorithmic bias), thus digitising cultural prejudices.[{{Cite web |last=Bostrom |first=Nick |date=2011 |title=The Ethics of Artificial Intelligence |url=http://www.nickbostrom.com/ethics/artificial-intelligence.pdf |archive-url=https://web.archive.org/web/20160304015020/http://www.nickbostrom.com/ethics/artificial-intelligence.pdf |archive-date=4 March 2016 |access-date=11 April 2016}}] For example, in 1988, the UK's [[Commission for Racial Equality]] found that [[St George's, University of London|St. George's Medical School]] had been using a computer program trained from data of previous admissions staff and that this program had denied nearly 60 candidates who were found to either be women or have non-European sounding names.[{{cite web |last1=Edionwe |first1=Tolulope |title=The fight against racist algorithms |url=https://theoutline.com/post/1571/the-fight-against-racist-algorithms |url-status=live |archive-url=https://web.archive.org/web/20171117174504/https://theoutline.com/post/1571/the-fight-against-racist-algorithms |archive-date=17 November 2017 |access-date=17 November 2017 |website=The Outline}}][{{cite web |last1=Jeffries |first1=Adrianne |title=Machine learning is racist because the internet is racist |url=https://theoutline.com/post/1439/machine-learning-is-racist-because-the-internet-is-racist |url-status=live |archive-url=https://web.archive.org/web/20171117174503/https://theoutline.com/post/1439/machine-learning-is-racist-because-the-internet-is-racist |archive-date=17 November 2017 |access-date=17 November 2017 |website=The Outline}}] Another example includes predictive policing company [[Geolitica]]'s predictive algorithm that resulted in "disproportionately high levels of over-policing in low-income and minority communities" after being trained with historical crime data.[{{Cite journal |last1=Silva |first1=Selena |last2=Kenney |first2=Martin |date=2018 |title=Algorithms, Platforms, and Ethnic Bias: An Integrative Essay |url=https://brie.berkeley.edu/sites/default/files/brie_wp_2018-3.pdf |url-status=live |journal=Phylon |volume=55 |issue=1 & 2 |pages=9–37 |issn=0031-8906 |jstor=26545017 |archive-url=https://web.archive.org/web/20240127200319/https://brie.berkeley.edu/sites/default/files/brie_wp_2018-3.pdf |archive-date=27 January 2024}}]
While responsible [[Data collection|collection of data]] and documentation of algorithmic rules used by a system is considered a critical part of machine learning, some researchers blame lack of participation and representation of minority population in the field of AI for machine learning's vulnerability to biases.[{{Cite journal |last=Wong |first=Carissa |date=30 March 2023 |title=AI 'fairness' research held back by lack of diversity |url=https://www.nature.com/articles/d41586-023-00935-z |url-status=live |journal=Nature |language=en |doi=10.1038/d41586-023-00935-z |pmid=36997714 |s2cid=257857012 |archive-url=https://web.archive.org/web/20230412120505/https://www.nature.com/articles/d41586-023-00935-z |archive-date=12 April 2023 |access-date=9 December 2023|url-access=subscription }}] In fact, according to research carried out by the Computing Research Association (CRA) in 2021, "female faculty merely make up 16.1%" of all faculty members who focus on AI among several universities around the world.[{{Cite journal |last=Zhang |first=Jack Clark |title=Artificial Intelligence Index Report 2021 |url=https://aiindex.stanford.edu/wp-content/uploads/2021/11/2021-AI-Index-Report_Master.pdf |url-status=live |journal=Stanford Institute for Human-Centered Artificial Intelligence |archive-url=https://web.archive.org/web/20240519121545/https://aiindex.stanford.edu/wp-content/uploads/2021/11/2021-AI-Index-Report_Master.pdf |archive-date=19 May 2024 |access-date=9 December 2023}}] Furthermore, among the group of "new U.S. resident AI PhD graduates," 45% identified as white, 22.4% as Asian, 3.2% as Hispanic, and 2.4% as African American, which further demonstrates a lack of diversity in the field of AI.[{{Cite journal |last1=Caliskan |first1=Aylin |last2=Bryson |first2=Joanna J. |last3=Narayanan |first3=Arvind |date=14 April 2017 |title=Semantics derived automatically from language corpora contain human-like biases |journal=Science |language=en |volume=356 |issue=6334 |pages=183–186 |arxiv=1608.07187 |bibcode=2017Sci...356..183C |doi=10.1126/science.aal4230 |issn=0036-8075 |pmid=28408601 |s2cid=23163324}}][{{Citation |last1=Wang |first1=Xinan |title=An algorithm for L1 nearest neighbor search via monotonic embedding |date=2016 |work=Advances in Neural Information Processing Systems 29 |pages=983–991 |editor-last=Lee |editor-first=D. D. |url=http://papers.nips.cc/paper/6227-an-algorithm-for-l1-nearest-neighbor-search-via-monotonic-embedding.pdf |access-date=20 August 2018 |archive-url=https://web.archive.org/web/20170407051313/http://papers.nips.cc/paper/6227-an-algorithm-for-l1-nearest-neighbor-search-via-monotonic-embedding.pdf |archive-date=7 April 2017 |url-status=live |publisher=Curran Associates, Inc. |last2=Dasgupta |first2=Sanjoy |editor2-last=Sugiyama |editor2-first=M. |editor3-last=Luxburg |editor3-first=U. V. |editor4-last=Guyon |editor4-first=I.}}] Because human languages contain biases, machines trained on language ''[[Text corpus|corpora]]'' will necessarily also learn these biases.[{{cite arXiv |eprint=1809.02208 |class=cs.CY |author=M.O.R. Prates |author2=P.H.C. Avelar |title=Assessing Gender Bias in Machine Translation – A Case Study with Google Translate |date=11 March 2019 |author3=L.C. Lamb}}][{{cite web |last=Narayanan |first=Arvind |date=24 August 2016 |title=Language necessarily contains human biases, and so will machines trained on language corpora |url=https://freedom-to-tinker.com/2016/08/24/language-necessarily-contains-human-biases-and-so-will-machines-trained-on-language-corpora/ |url-status=live |archive-url=https://web.archive.org/web/20180625021555/https://freedom-to-tinker.com/2016/08/24/language-necessarily-contains-human-biases-and-so-will-machines-trained-on-language-corpora/ |archive-date=25 June 2018 |access-date=19 November 2016 |website=Freedom to Tinker}}] In 2016, Microsoft tested [[Tay (chatbot)|Tay]], a [[chatbot]] that learned from Twitter, and it quickly picked up racist and sexist language.[{{Cite news |last=Metz |first=Rachel |date=24 March 2016 |title=Why Microsoft Accidentally Unleashed a Neo-Nazi Sexbot |url=https://www.technologyreview.com/s/601111/why-microsoft-accidentally-unleashed-a-neo-nazi-sexbot/ |url-access=limited |url-status=live |archive-url=https://web.archive.org/web/20181109023754/https://www.technologyreview.com/s/601111/why-microsoft-accidentally-unleashed-a-neo-nazi-sexbot/ |archive-date=9 November 2018 |access-date=20 August 2018 |work=MIT Technology Review |language=en}}]
In an experiment carried out by [[ProPublica]], an [[investigative journalism]] organisation, a machine learning algorithm's insight into the recidivism rates among prisoners falsely flagged "black defendants high risk twice as often as white defendants".[{{Cite news |last1=Vincent |first1=James |date=12 January 2018 |title=Google 'fixed' its racist algorithm by removing gorillas from its image-labeling tech |url=https://www.theverge.com/2018/1/12/16882408/google-racist-gorillas-photo-recognition-algorithm-ai |url-status=live |archive-url=https://web.archive.org/web/20180821031830/https://www.theverge.com/2018/1/12/16882408/google-racist-gorillas-photo-recognition-algorithm-ai |archive-date=21 August 2018 |access-date=20 August 2018 |work=The Verge}}] Similar issues with recognising non-white people have been found in many other systems.[{{Cite news |last1=Crawford |first1=Kate |date=25 June 2016 |title=Opinion {{!}} Artificial Intelligence's White Guy Problem |url=https://www.nytimes.com/2016/06/26/opinion/sunday/artificial-intelligences-white-guy-problem.html |url-access=subscription |url-status=live |archive-url=https://web.archive.org/web/20210114220619/https://www.nytimes.com/2016/06/26/opinion/sunday/artificial-intelligences-white-guy-problem.html |archive-date=14 January 2021 |access-date=20 August 2018 |work=[[New York Times]] |language=en}}]
Because of such challenges, the effective use of machine learning may take longer to be adopted in other domains.[{{Cite news |last=Simonite |first=Tom |date=30 March 2017 |title=Microsoft: AI Isn't Yet Adaptable Enough to Help Businesses |url=https://www.technologyreview.com/s/603944/microsoft-ai-isnt-yet-adaptable-enough-to-help-businesses/ |url-status=live |archive-url=https://web.archive.org/web/20181109022820/https://www.technologyreview.com/s/603944/microsoft-ai-isnt-yet-adaptable-enough-to-help-businesses/ |archive-date=9 November 2018 |access-date=20 August 2018 |work=MIT Technology Review |language=en}}] Concern for [[Fairness (machine learning)|fairness]] in machine learning, that is, reducing bias in machine learning and propelling its use for human good, is increasingly expressed by artificial intelligence scientists, including [[Fei-Fei Li]], who said that "[t]here's nothing artificial about AI. It's inspired by people, it's created by people, and—most importantly—it impacts people. It is a powerful tool we are only just beginning to understand, and that is a profound responsibility."[{{Cite news |last=Hempel |first=Jessi |date=13 November 2018 |title=Fei-Fei Li's Quest to Make Machines Better for Humanity |url=https://www.wired.com/story/fei-fei-li-artificial-intelligence-humanity/ |url-status=live |archive-url=https://web.archive.org/web/20201214095220/https://www.wired.com/story/fei-fei-li-artificial-intelligence-humanity/ |archive-date=14 December 2020 |access-date=17 February 2019 |magazine=Wired |issn=1059-1028}}]
=== Financial incentives ===
There are concerns among health care professionals that these systems might not be designed in the public's interest but as income-generating machines. This is especially true in the United States where there is a long-standing ethical dilemma of improving health care, but also increasing profits. For example, the algorithms could be designed to provide patients with unnecessary tests or medication in which the algorithm's proprietary owners hold stakes. There is potential for machine learning in health care to provide professionals an additional tool to diagnose, medicate, and plan recovery paths for patients, but this requires these biases to be mitigated.[{{cite journal |last1=Char |first1=D. S. |last2=Shah |first2=N. H. |last3=Magnus |first3=D. |year=2018 |title=Implementing Machine Learning in Health Care—Addressing Ethical Challenges |journal=[[New England Journal of Medicine]] |volume=378 |issue=11 |pages=981–983 |doi=10.1056/nejmp1714229 |pmid=29539284 |pmc=5962261 }}]
== Hardware ==
Since the 2010s, advances in both machine learning algorithms and computer hardware have led to more efficient methods for training [[deep neural network]]s (a particular narrow subdomain of machine learning) that contain many layers of nonlinear hidden units.[{{cite web|last1=Research|first1=AI|title=Deep Neural Networks for Acoustic Modeling in Speech Recognition|url=http://airesearch.com/ai-research-papers/deep-neural-networks-for-acoustic-modeling-in-speech-recognition/|website=airesearch.com|access-date=23 October 2015|date=23 October 2015|archive-date=1 February 2016|archive-url=https://web.archive.org/web/20160201033801/http://airesearch.com/ai-research-papers/deep-neural-networks-for-acoustic-modeling-in-speech-recognition/|url-status=live}}] By 2019, graphics processing units ([[GPU]]s), often with AI-specific enhancements, had displaced CPUs as the dominant method of training large-scale commercial cloud AI.[{{cite news |title=GPUs Continue to Dominate the AI Accelerator Market for Now |url=https://www.informationweek.com/big-data/ai-machine-learning/gpus-continue-to-dominate-the-ai-accelerator-market-for-now/a/d-id/1336475 |access-date=11 June 2020 |work=InformationWeek |date=December 2019 |language=en |archive-date=10 June 2020 |archive-url=https://web.archive.org/web/20200610094310/https://www.informationweek.com/big-data/ai-machine-learning/gpus-continue-to-dominate-the-ai-accelerator-market-for-now/a/d-id/1336475 |url-status=live }}] [[OpenAI]] estimated the hardware compute used in the largest deep learning projects from [[AlexNet]] (2012) to [[AlphaZero]] (2017), and found a 300,000-fold increase in the amount of compute required, with a doubling-time trendline of 3.4 months.[{{cite news |last1=Ray |first1=Tiernan |title=AI is changing the entire nature of compute |url=https://www.zdnet.com/article/ai-is-changing-the-entire-nature-of-compute/ |access-date=11 June 2020 |work=ZDNet |date=2019 |language=en |archive-date=25 May 2020 |archive-url=https://web.archive.org/web/20200525144635/https://www.zdnet.com/article/ai-is-changing-the-entire-nature-of-compute/ |url-status=live }}][{{cite web |title=AI and Compute |url=https://openai.com/blog/ai-and-compute/ |website=OpenAI |access-date=11 June 2020 |language=en |date=16 May 2018 |archive-date=17 June 2020 |archive-url=https://web.archive.org/web/20200617200602/https://openai.com/blog/ai-and-compute/ |url-status=live }}]
=== Tensor Processing Units (TPUs) ===
[[Tensor Processing Unit|Tensor Processing Units (TPUs)]] are specialised hardware accelerators developed by [[Google]] specifically for machine learning workloads. Unlike general-purpose [[Graphics processing unit|GPUs]] and [[Field-programmable gate array|FPGAs]], TPUs are optimised for tensor computations, making them particularly efficient for deep learning tasks such as training and inference. They are widely used in Google Cloud AI services and large-scale machine learning models like Google's DeepMind AlphaFold and large language models. TPUs leverage matrix multiplication units and high-bandwidth memory to accelerate computations while maintaining energy efficiency.[{{Cite book |last1=Jouppi |first1=Norman P. |last2=Young |first2=Cliff |last3=Patil |first3=Nishant |last4=Patterson |first4=David |last5=Agrawal |first5=Gaurav |last6=Bajwa |first6=Raminder |last7=Bates |first7=Sarah |last8=Bhatia |first8=Suresh |last9=Boden |first9=Nan |last10=Borchers |first10=Al |last11=Boyle |first11=Rick |last12=Cantin |first12=Pierre-luc |last13=Chao |first13=Clifford |last14=Clark |first14=Chris |last15=Coriell |first15=Jeremy |chapter=In-Datacenter Performance Analysis of a Tensor Processing Unit |date=24 June 2017 |title=Proceedings of the 44th Annual International Symposium on Computer Architecture |chapter-url=https://dl.acm.org/doi/10.1145/3079856.3080246 |series=ISCA '17 |location=New York, NY, USA |publisher=Association for Computing Machinery |pages=1–12 |doi=10.1145/3079856.3080246 |isbn=978-1-4503-4892-8|arxiv=1704.04760 }}] Since their introduction in 2016, TPUs have become a key component of AI infrastructure, especially in cloud-based environments.
===Neuromorphic computing===
[[Neuromorphic computing]] refers to a class of computing systems designed to emulate the structure and functionality of biological neural networks. These systems may be implemented through software-based simulations on conventional hardware or through specialised hardware architectures.[{{Cite web |date=8 December 2020 |title=What is neuromorphic computing? Everything you need to know about how it is changing the future of computing |url=https://www.zdnet.com/article/what-is-neuromorphic-computing-everything-you-need-to-know-about-how-it-will-change-the-future-of-computing/ |access-date=21 November 2024 |website=ZDNET |language=en}}]
==== physical neural networks ====
A [[physical neural network]] is a specific type of neuromorphic hardware that relies on electrically adjustable materials, such as memristors, to emulate the function of [[chemical synapse|neural synapses]]. The term "physical neural network" highlights the use of physical hardware for computation, as opposed to software-based implementations. It broadly refers to artificial neural networks that use materials with adjustable resistance to replicate neural synapses.[{{Cite web |date=27 May 2021 |title=Cornell & NTT's Physical Neural Networks: A "Radical Alternative for Implementing Deep Neural Networks" That Enables Arbitrary Physical Systems Training |url=https://syncedreview.com/2021/05/27/deepmind-podracer-tpu-based-rl-frameworks-deliver-exceptional-performance-at-low-cost-28/ |url-status=live |archive-url=https://web.archive.org/web/20211027183428/https://syncedreview.com/2021/05/27/deepmind-podracer-tpu-based-rl-frameworks-deliver-exceptional-performance-at-low-cost-28/ |archive-date=27 October 2021 |access-date=12 October 2021 |website=Synced}}][{{Cite news |date=5 October 2021 |title=Nano-spaghetti to solve neural network power consumption |url=https://www.theregister.com/2021/10/05/analogue_neural_network_research/ |url-status=live |archive-url=https://web.archive.org/web/20211006150057/https://www.theregister.com/2021/10/05/analogue_neural_network_research/ |archive-date=6 October 2021 |access-date=12 October 2021 |work=The Register}}]
===Embedded machine learning===
Embedded machine learning is a sub-field of machine learning where models are deployed on [[embedded systems]] with limited computing resources, such as [[wearable computer]]s, [[edge device]]s and [[microcontrollers]].[{{Cite book|last1=Fafoutis|first1=Xenofon|last2=Marchegiani|first2=Letizia|last3=Elsts|first3=Atis|last4=Pope|first4=James|last5=Piechocki|first5=Robert|last6=Craddock|first6=Ian|title=2018 IEEE 4th World Forum on Internet of Things (WF-IoT) |chapter=Extending the battery lifetime of wearable sensors with embedded machine learning |date=7 May 2018|chapter-url=https://ieeexplore.ieee.org/document/8355116|pages=269–274|doi=10.1109/WF-IoT.2018.8355116|hdl=1983/b8fdb58b-7114-45c6-82e4-4ab239c1327f|isbn=978-1-4673-9944-9|s2cid=19192912|url=https://research-information.bris.ac.uk/en/publications/b8fdb58b-7114-45c6-82e4-4ab239c1327f |access-date=17 January 2022|archive-date=18 January 2022|archive-url=https://web.archive.org/web/20220118182543/https://ieeexplore.ieee.org/abstract/document/8355116?casa_token=LCpUeGLS1e8AAAAA:2OjuJfNwZBnV2pgDxfnEAC-jbrETv_BpTcX35_aFqN6IULFxu1xbYbVSRpD-zMd4GCUMELyG|url-status=live}}][{{Cite web|date=2 June 2021|title=A Beginner's Guide To Machine learning For Embedded Systems|url=https://analyticsindiamag.com/a-beginners-guide-to-machine-learning-for-embedded-systems/|access-date=17 January 2022|website=Analytics India Magazine|language=en-US|archive-date=18 January 2022|archive-url=https://web.archive.org/web/20220118182754/https://analyticsindiamag.com/a-beginners-guide-to-machine-learning-for-embedded-systems/|url-status=live}}][{{Cite web|last=Synced|date=12 January 2022|title=Google, Purdue & Harvard U's Open-Source Framework for TinyML Achieves up to 75x Speedups on FPGAs {{!}} Synced|url=https://syncedreview.com/2022/01/12/deepmind-podracer-tpu-based-rl-frameworks-deliver-exceptional-performance-at-low-cost-183/|access-date=17 January 2022|website=syncedreview.com|language=en-US|archive-date=18 January 2022|archive-url=https://web.archive.org/web/20220118182404/https://syncedreview.com/2022/01/12/deepmind-podracer-tpu-based-rl-frameworks-deliver-exceptional-performance-at-low-cost-183/|url-status=live}}][{{Cite journal
| last1 = AlSelek
| first1 = Mohammad
| last2 = Alcaraz-Calero
| first2 = Jose M.
| last3 = Wang
| first3 = Qi
| year = 2024
| title = Dynamic AI-IoT: Enabling Updatable AI Models in Ultralow-Power 5G IoT Devices
| journal = IEEE Internet of Things Journal
| volume = 11
| issue = 8
| pages = 14192–14205
| doi = 10.1109/JIOT.2023.3340858
}}] Running models directly on these devices eliminates the need to transfer and store data on cloud servers for further processing, thereby reducing the risk of data breaches, privacy leaks and theft of intellectual property, personal data and business secrets. Embedded machine learning can be achieved through various techniques, such as [[hardware acceleration]],[{{Cite book|last1=Giri|first1=Davide|last2=Chiu|first2=Kuan-Lin|last3=Di Guglielmo|first3=Giuseppe|last4=Mantovani|first4=Paolo|last5=Carloni|first5=Luca P.|title=2020 Design, Automation & Test in Europe Conference & Exhibition (DATE) |chapter=ESP4ML: Platform-Based Design of Systems-on-Chip for Embedded Machine Learning |date=15 June 2020|chapter-url=https://ieeexplore.ieee.org/document/9116317|pages=1049–1054|doi=10.23919/DATE48585.2020.9116317|arxiv=2004.03640|isbn=978-3-9819263-4-7|s2cid=210928161|access-date=17 January 2022|archive-date=18 January 2022|archive-url=https://web.archive.org/web/20220118182342/https://ieeexplore.ieee.org/abstract/document/9116317?casa_token=5I_Tmgrrbu4AAAAA:v7pDHPEWlRuo2Vk3pU06194PO0-W21UOdyZqADrZxrRdPBZDMLwQrjJSAHUhHtzJmLu_VdgW|url-status=live}}][{{Cite web|last1=Louis|first1=Marcia Sahaya|last2=Azad|first2=Zahra|last3=Delshadtehrani|first3=Leila|last4=Gupta|first4=Suyog|last5=Warden|first5=Pete|last6=Reddi|first6=Vijay Janapa|last7=Joshi|first7=Ajay|date=2019|title=Towards Deep Learning using TensorFlow Lite on RISC-V|url=https://edge.seas.harvard.edu/publications/towards-deep-learning-using-tensorflow-lite-risc-v|access-date=17 January 2022|website=[[Harvard University]]|archive-date=17 January 2022|archive-url=https://web.archive.org/web/20220117031909/https://edge.seas.harvard.edu/publications/towards-deep-learning-using-tensorflow-lite-risc-v|url-status=live}}] [[approximate computing]],[{{Cite book|last1=Ibrahim|first1=Ali|last2=Osta|first2=Mario|last3=Alameh|first3=Mohamad|last4=Saleh|first4=Moustafa|last5=Chible|first5=Hussein|last6=Valle|first6=Maurizio|title=2018 25th IEEE International Conference on Electronics, Circuits and Systems (ICECS) |chapter=Approximate Computing Methods for Embedded Machine Learning |date=21 January 2019|chapter-url=https://ieeexplore.ieee.org/document/8617877|pages=845–848|doi=10.1109/ICECS.2018.8617877|isbn=978-1-5386-9562-3|s2cid=58670712|access-date=17 January 2022|archive-date=17 January 2022|archive-url=https://web.archive.org/web/20220117031855/https://ieeexplore.ieee.org/abstract/document/8617877?casa_token=arUW5Oy-tzwAAAAA:I9x6edlfskM6kGNFUN9zAFrjEBv_8kYTz7ERTxtXu9jAqdrYCcDbbwjBdgwXvb6QAH_-0VJJ|url-status=live}}] and model optimisation.[{{Cite web|title=dblp: TensorFlow Eager: A Multi-Stage, Python-Embedded DSL for Machine Learning.|url=https://dblp.org/rec/journals/corr/abs-1903-01855.html|access-date=17 January 2022|website=dblp.org|language=en|archive-date=18 January 2022|archive-url=https://web.archive.org/web/20220118182335/https://dblp.org/rec/journals/corr/abs-1903-01855.html|url-status=live}}][{{Cite journal|last1=Branco|first1=Sérgio|last2=Ferreira|first2=André G.|last3=Cabral|first3=Jorge|date=5 November 2019|title=Machine Learning in Resource-Scarce Embedded Systems, FPGAs, and End-Devices: A Survey|journal=Electronics|volume=8|issue=11|pages=1289|doi=10.3390/electronics8111289|issn=2079-9292|doi-access=free|hdl=1822/62521|hdl-access=free}}] Common optimisation techniques include [[Pruning (artificial neural network)|pruning]], [[Quantization (Embedded Machine Learning)|quantisation]], [[knowledge distillation]], low-rank factorisation, network architecture search, and parameter sharing.
== Software ==
[[Software suite]]s containing a variety of machine learning algorithms include the following:
=== Free and open-source software{{anchor|Open-source_software}} ===
{{Div col|colwidth=18em}}
* [[Caffe (software)|Caffe]]
* [[Deeplearning4j]]
* [[DeepSpeed]]
* [[ELKI]]
* [[Google JAX]]
* [[Infer.NET]]
* [[Keras]]
* [[Kubeflow]]
* [[LightGBM]]
* [[Apache Mahout|Mahout]]
* [[Mallet (software project)|Mallet]]
* [[Microsoft Cognitive Toolkit]]
* [[ML.NET]]
* [[mlpack]]
* [[MXNet]]
* [[OpenNN]]
* [[Orange (software)|Orange]]
* [[pandas (software)]]
* [[ROOT]] (TMVA with ROOT)
* [[scikit-learn]]
* [[Shogun (toolbox)|Shogun]]
* [[Apache Spark#MLlib Machine Learning Library|Spark MLlib]]
* [[Apache SystemML|SystemML]]
* [[TensorFlow]]
* [[Torch (machine learning)|Torch]] / [[PyTorch]]
* [[Weka (machine learning)|Weka]] / [[MOA (Massive Online Analysis)|MOA]]
* [[XGBoost]]
* [[Yooreeka]]
{{Div col end}}
=== Proprietary software with free and open-source editions ===
* [[KNIME]]
* [[RapidMiner]]
=== Proprietary software ===
{{Div col|colwidth=18em}}
* [[Amazon Machine Learning]]
* [[Angoss]] KnowledgeSTUDIO
* [[Azure Machine Learning]]
* [[IBM Watson Studio]]
* [[Google Cloud Platform#Cloud AI|Google Cloud Vertex AI]]
* [[Google APIs|Google Prediction API]]
* [[SPSS Modeler|IBM SPSS Modeller]]
* [[KXEN Inc.|KXEN Modeller]]
* [[LIONsolver]]
* [[Mathematica]]
* [[MATLAB]]
* [[Neural Designer]]
* [[NeuroSolutions]]
* [[Oracle Data Mining]]
* [[Oracle Cloud#Platform as a Service (PaaS)|Oracle AI Platform Cloud Service]]
* [[PolyAnalyst]]
* [[RCASE]]
* [[SAS (software)#Components|SAS Enterprise Miner]]
* [[SequenceL]]
* [[Splunk]]
* [[STATISTICA]] Data Miner
{{Div col end}}
== Journals ==
* [[Journal of Machine Learning Research]]
* [[Machine Learning (journal)|Machine Learning]]
* [[Nature Machine Intelligence]]
* [[Neural Computation (journal)|Neural Computation]]
* [[IEEE Transactions on Pattern Analysis and Machine Intelligence]]
== Conferences ==
* [[AAAI Conference on Artificial Intelligence]]
* [[Association for Computational Linguistics|Association for Computational Linguistics ('''ACL''')]]
* [[European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases|European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases ('''ECML PKDD''')]]
* [[International Conference on Computational Intelligence Methods for Bioinformatics and Biostatistics|International Conference on Computational Intelligence Methods for Bioinformatics and Biostatistics ('''CIBB''')]]
* [[International Conference on Machine Learning|International Conference on Machine Learning ('''ICML''')]]
* [[International Conference on Learning Representations|International Conference on Learning Representations ('''ICLR''')]]
* [[International Conference on Intelligent Robots and Systems|International Conference on Intelligent Robots and Systems ('''IROS''')]]
* [[Conference on Knowledge Discovery and Data Mining|Conference on Knowledge Discovery and Data Mining ('''KDD''')]]
* [[Conference on Neural Information Processing Systems|Conference on Neural Information Processing Systems ('''NeurIPS''')]]
== See also ==
* {{annotated link|Automated machine learning}}
* {{annotated link|Big data}}
* [[Deep learning]] — branch of ML concerned with [[artificial neural network]]s
* {{annotated link|Differentiable programming}}
* {{annotated link|List of datasets for machine-learning research}}
* [[M-theory (learning framework)]]
*[[Machine unlearning]]
* {{annotated link|Solomonoff's theory of inductive inference}}
== References ==
{{Reflist|30em}}
== Sources ==
* {{Cite book
| last = Domingos | first = Pedro | author-link = Pedro Domingos
| title = The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World
| date = 22 September 2015
| publisher = Basic Books
| isbn = 978-0465065707
}}
* {{Cite book|last=Nilsson|first=Nils|author-link=Nils Nilsson (researcher)|year=1998|title=Artificial Intelligence: A New Synthesis|url=https://archive.org/details/artificialintell0000nils|url-access=registration|publisher=Morgan Kaufmann|isbn=978-1-55860-467-4|access-date=18 November 2019|archive-date=26 July 2020|archive-url=https://web.archive.org/web/20200726131654/https://archive.org/details/artificialintell0000nils|url-status=live}}
* {{Cite book|first1=David|last1=Poole|first2=Alan|last2=Mackworth|author2-link=Alan Mackworth|first3=Randy|last3=Goebel|year=1998|title=Computational Intelligence: A Logical Approach|publisher=Oxford University Press|location=New York|isbn=978-0-19-510270-3|url=https://archive.org/details/computationalint00pool|access-date=22 August 2020|archive-date=26 July 2020|archive-url=https://web.archive.org/web/20200726131436/https://archive.org/details/computationalint00pool|url-status=live}}
* {{Russell Norvig 2003}}.
== Further reading ==
{{refbegin|30em}}
* Alpaydin, Ethem (2020). ''Introduction to Machine Learning'', (4th edition) MIT Press, {{ISBN|9780262043793}}.
* [[Christopher Bishop|Bishop, Christopher]] (1995). ''Neural Networks for Pattern Recognition'', Oxford University Press. {{ISBN|0-19-853864-2}}.
* Bishop, Christopher (2006) ''Pattern Recognition and Machine Learning'', Springer. {{ISBN|978-0-387-31073-2}}
* [[Pedro Domingos|Domingos, Pedro]] (September 2015), ''[[The Master Algorithm]]'', Basic Books, {{ISBN|978-0-465-06570-7}}
* [[Richard O. Duda|Duda, Richard O.]]; [[Peter E. Hart|Hart, Peter E.]]; Stork, David G. (2001) ''Pattern classification'' (2nd edition), Wiley, New York, {{ISBN|0-471-05669-3}}.
* [[Trevor Hastie|Hastie, Trevor]]; [[Robert Tibshirani|Tibshirani, Robert]] & [[Jerome H. Friedman|Friedman, Jerome H.]] (2009) ''The Elements of Statistical Learning'', Springer. {{doi|10.1007/978-0-387-84858-7}} {{ISBN|0-387-95284-5}}.
* [[David J. C. MacKay|MacKay, David J. C.]] ''Information Theory, Inference, and Learning Algorithms'' Cambridge: Cambridge University Press, 2003. {{ISBN|0-521-64298-1}}
* Murphy, Kevin P. (2021). ''[https://probml.github.io/pml-book/book1.html Probabilistic Machine Learning: An Introduction] {{Webarchive|url=https://web.archive.org/web/20210411153246/https://probml.github.io/pml-book/book1.html |date=11 April 2021 }}'', MIT Press.
* Nilsson, Nils J. (2015) ''[https://ai.stanford.edu/people/nilsson/mlbook.html Introduction to Machine Learning] {{Webarchive|url=https://web.archive.org/web/20190816182600/http://ai.stanford.edu/people/nilsson/mlbook.html |date=16 August 2019 }}''.
* Russell, Stuart & Norvig, Peter (2020). ''Artificial Intelligence – A Modern Approach''. (4th edition) Pearson, {{ISBN|978-0134610993}}.
* [[Ray Solomonoff|Solomonoff, Ray]], (1956) ''[http://world.std.com/~rjs/indinf56.pdf An Inductive Inference Machine] {{Webarchive|url=https://web.archive.org/web/20110426161749/http://world.std.com/~rjs/indinf56.pdf |date=26 April 2011 }}'' A privately circulated report from the 1956 [[Dartmouth workshop|Dartmouth Summer Research Conference on AI]].
* Witten, Ian H. & Frank, Eibe (2011). ''[https://www.sciencedirect.com/book/9780123748560 Data Mining: Practical machine learning tools and techniques]'' Morgan Kaufmann, 664pp., {{ISBN|978-0-12-374856-0}}.
{{Refend}}
== External links ==
* [https://web.archive.org/web/20171230081341/http://machinelearning.org/ International Machine Learning Society]
* [https://mloss.org/ mloss] is an academic database of open-source machine learning software.
{{Artificial intelligence navbox}}
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[[Category:Machine learning| ]]
[[Category:Cybernetics]]
[[Category:Learning]]
[[Category:Definition]]
{{short description|None}}
{{Update|date=August 2021}}
This page is a '''timeline of machine learning'''. Major discoveries, achievements, milestones and other major events in [[machine learning]] are included.
==Overview==
{| class="wikitable sortable"
|-
! Decade !! Summary
|-
| pre-
1950|| Statistical methods are discovered and refined.
|-
| 1950s || Pioneering [[machine learning]] research is conducted using simple algorithms.
|-
| 1960s || [[Bayesian method]]s are introduced for [[Bayesian inference|probabilistic inference]] in machine learning.[{{cite journal |last1=Solomonoff |first1=R.J. |title=A formal theory of inductive inference. Part II |journal=Information and Control |date=June 1964 |volume=7 |issue=2 |pages=224–254 |doi=10.1016/S0019-9958(64)90131-7 |doi-access= }}]
|-
| 1970s || '[[AI winter]]' caused by pessimism about machine learning effectiveness.
|-
| 1980s || Rediscovery of [[backpropagation]] causes a resurgence in machine learning research.
|-
| 1990s || Work on Machine learning shifts from a knowledge-driven approach to a data-driven approach. Scientists begin creating programs for computers to analyze large amounts of data and draw conclusions{{snd}} or "learn"{{snd}} from the results.[{{harvnb|Marr|2016}}.] [[Support-vector machine]]s (SVMs) and [[recurrent neural network]]s (RNNs) become popular.[{{cite journal |last1=Siegelmann |first1=H.T. |last2=Sontag |first2=E.D. |title=On the Computational Power of Neural Nets |journal=Journal of Computer and System Sciences |date=February 1995 |volume=50 |issue=1 |pages=132–150 |doi=10.1006/jcss.1995.1013 |doi-access=free }}] The fields of computational complexity via neural networks and [[super-Turing computation]] started.[{{cite journal |last1=Siegelmann |first1=Hava |title=Computation Beyond the Turing Limit |journal=Journal of Computer and System Sciences |volume=238 |issue=28 |year=1995 |pages=632–637 |doi=10.1126/science.268.5210.545 |pmid=17756722 |bibcode=1995Sci...268..545S |s2cid=17495161 }}]
|-
| 2000s || Support-Vector Clustering[{{cite journal |first1=Asa |last1=Ben-Hur |first2=David |last2=Horn |first3=Hava |last3=Siegelmann |first4=Vladimir|last4=Vapnik |title=Support vector clustering |journal=Journal of Machine Learning Research|volume=2 |year=2001 |pages=51–86}}] and other [[kernel method]]s[{{cite journal |last1=Hofmann |first1=Thomas |first2=Bernhard |last2=Schölkopf |first3=Alexander J. |last3=Smola |title=Kernel methods in machine learning |journal=The Annals of Statistics |volume=36 |issue=3 |year=2008 |pages=1171–1220 |jstor=25464664 |arxiv=math/0701907| doi=10.1214/009053607000000677 |doi-access=free }}] and [[unsupervised machine learning]] methods become widespread.[{{cite journal |first1=James |last1=Bennett |first2=Stan |last2=Lanning |title=The netflix prize |journal=Proceedings of KDD Cup and Workshop 2007 |date=2007 |url=https://www.cs.uic.edu/~liub/KDD-cup-2007/NetflixPrize-description.pdf }}]
|-
| 2010s || [[Deep learning]] becomes feasible, which leads to machine learning becoming integral to many widely used software services and applications. Deep learning spurs huge advances in vision and text processing.
|-
|2020s
|[[Generative AI]] leads to revolutionary models, creating a proliferation of [[foundation models]] both proprietary and open source, notably enabling products such as [[ChatGPT]] (text-based) and [[Stable Diffusion]] (image based). Machine learning and AI enter the wider public consciousness. The commercial potential of AI based on machine learning causes large increases in valuations of companies linked to AI.
|}
==Timeline==
{{Incomplete list|date=December 2022}}
{| class="wikitable sortable"
|-
! Year !! Event type !! Caption !! Event
|-
| 1763 || Discovery || The Underpinnings of [[Bayes' theorem|Bayes' Theorem]] || [[Thomas Bayes]]'s work ''[[An Essay Towards Solving a Problem in the Doctrine of Chances]]'' is published two years after his death, having been amended and edited by a friend of Bayes, [[Richard Price]].[{{cite journal|last1=Bayes|first1=Thomas|title=An Essay Towards Solving a Problem in the Doctrine of Chance|journal=Philosophical Transactions|date=1 January 1763|volume=53|pages=370–418|doi=10.1098/rstl.1763.0053|jstor=105741|doi-access=free}}] The essay presents work which underpins [[Bayes' theorem]].
|-
| 1805 || Discovery || Least Square || [[Adrien-Marie Legendre]] describes the "méthode des moindres carrés", known in English as the [[least squares]] method.[{{cite book|last1=Legendre|first1=Adrien-Marie|title=Nouvelles méthodes pour la détermination des orbites des comètes|date=1805|publisher=Firmin Didot|location=Paris|page=viii|url=https://archive.org/details/bub_gb_FRcOAAAAQAAJ|accessdate=13 June 2016|language=French}}] The least squares method is used widely in [[data fitting]].
|-
| 1812 || || [[Bayes' theorem|Bayes' Theorem]] || [[Pierre-Simon Laplace]] publishes ''Théorie Analytique des Probabilités'', in which he expands upon the work of Bayes and defines what is now known as [[Bayes' Theorem]].[{{cite web|last1=O'Connor|first1=J J|last2=Robertson|first2=E F|title=Pierre-Simon Laplace|url=http://www-history.mcs.st-and.ac.uk/Biographies/Laplace.html|publisher=School of Mathematics and Statistics, University of St Andrews, Scotland|accessdate=15 June 2016}}]
|-
| 1843 || Visionary || Visionary Pioneer || [[Ada Lovelace]] Lovelace's most significant relationship was with Charles Babbage, the inventor of the Analytical Engine, which is considered the first conceptual blueprint for a modern computer. [{{cite web|title=Ada Lovelace|date=11 September 2024 |url=https://aivips.org/ada-lovelace/|publisher=AI VIPs}}] Lovelace's vision extended beyond Babbage's own understanding of his machine. She saw the Analytical Engine as more than a calculator; she believed it could process and manipulate any form of symbolic data, such as music or text. This early vision of machines processing more than just numbers laid the groundwork for the development of symbolic AI and machine learning. [{{cite web|last1=Zwolak|first1=Justyna|title=Ada Lovelace: The World's First Computer Programmer Who Predicted Artificial Intelligence|work=NIST |date=22 March 2023 |url=https://www.nist.gov/blogs/taking-measure/ada-lovelace-worlds-first-computer-programmer-who-predicted-artificial|publisher=National Institute of Standards and Technology}}] Her contributions included what is now considered the first algorithm designed to be executed by a machine, making her the world's first computer programmer. Lovelace's understanding of the computational potential of machines continues to influence modern technologies like artificial intelligence.
[{{cite web|last1=Gregersen|first1=Erik|title=Ada Lovelace: The First Computer Programmer|url=https://www.britannica.com/story/ada-lovelace-the-first-computer-programmer|publisher=Encyclopaedia Britannica}}]
|-
| 1913 || Discovery || Markov Chains || [[Andrey Markov]] first describes techniques he used to analyse a poem. The techniques later become known as [[Markov chains]].[{{cite journal |last1=Langston |first1=Nancy |title=Mining the Boreal North |journal=American Scientist |date=2013 |volume=101 |issue=2 |page=1 |doi=10.1511/2013.101.1 |quote=Delving into the text of Alexander Pushkin's novel in verse Eugene Onegin, Markov spent hours sifting through patterns of vowels and consonants. On January 23, 1913, he summarized his findings in an address to the Imperial Academy of Sciences in St. Petersburg. His analysis did not alter the understanding or appreciation of Pushkin's poem, but the technique he developed—now known as a Markov chain—extended the theory of probability in a new direction. }}]
|-
|1943
|Discovery
|[[Artificial neuron|Artificial Neuron]]
|[[Warren Sturgis McCulloch|Warren McCulloch]] and [[Walter Pitts]] develop a mathematical model that imitates the functioning of a biological neuron, the [[artificial neuron]] which is considered to be the first neural model invented.[{{cite journal |last1=McCulloch |first1=Warren S. |last2=Pitts |first2=Walter |title=A logical calculus of the ideas immanent in nervous activity |journal=The Bulletin of Mathematical Biophysics |date=December 1943 |volume=5 |issue=4 |pages=115–133 |doi=10.1007/BF02478259 }}]
|-
| 1950 || || Turing's Learning Machine || [[Alan Turing]] proposes a 'learning machine' that could learn and become artificially intelligent. Turing's specific proposal foreshadows [[genetic algorithms]].[{{cite journal |last1=Turing |first1=A. M. |title=I.—COMPUTING MACHINERY AND INTELLIGENCE |journal=Mind |date=1 October 1950 |volume=LIX |issue=236 |pages=433–460 |doi=10.1093/mind/LIX.236.433 }}]
|-
| 1951 || || First Neural Network Machine || [[Marvin Minsky]] and Dean Edmonds build the first neural network machine, able to learn, the [[Stochastic Neural Analog Reinforcement Calculator|SNARC]].[{{Harvnb|Crevier|1993|pp=34–35}} and {{Harvnb|Russell|Norvig|2003|p=17}}.]
|-
| 1952 || || Machines Playing Checkers || [[Arthur Samuel (computer scientist)|Arthur Samuel]] joins IBM's Poughkeepsie Laboratory and begins working on some of the first machine learning programs, first creating programs that play [[checkers]].[{{cite journal |last1=McCarthy |first1=J. |last2=Feigenbaum |first2=E. |title=In memoriam—Arthur Samuel (1901–1990) |journal=AI Magazine |date=1 September 1990 |volume=11 |issue=3 |pages=10–11 |url=https://dl.acm.org/doi/10.5555/95618.95622 }}]
|-
| 1957 || Discovery || Perceptron || [[Frank Rosenblatt]] invents the [[perceptron]] while working at the [[Cornell Aeronautical Laboratory]].[{{cite journal |last1=Rosenblatt |first1=F. |title=The perceptron: A probabilistic model for information storage and organization in the brain. |journal=Psychological Review |date=1958 |volume=65 |issue=6 |pages=386–408 |doi=10.1037/h0042519 |pmid=13602029 |citeseerx=10.1.1.588.3775 |s2cid=12781225 }}] The invention of the perceptron generated a great deal of excitement and was widely covered in the media.[{{cite magazine|last1=Mason|first1=Harding|last2=Stewart|first2=D|last3=Gill|first3=Brendan|title=Rival|url=http://www.newyorker.com/magazine/1958/12/06/rival-2|accessdate=5 June 2016|magazine=The New Yorker|date=6 December 1958}}]
|-
| 1963 || Achievement || Machines Playing Tic-Tac-Toe || [[Donald Michie]] creates a [[Matchbox Educable Noughts and Crosses Engine|'machine']] consisting of 304 match boxes and beads, which uses [[reinforcement learning]] to play [[Tic-tac-toe]] (also known as noughts and crosses).[{{cite web|last1=Child|first1=Oliver|title=Menace: the Machine Educable Noughts And Crosses Engine Read|url=http://chalkdustmagazine.com/features/menace-machine-educable-noughts-crosses-engine/#more-3326|website=Chalkdust Magazine |date=13 March 2016|accessdate=16 Jan 2018}}]
|-
| 1967 || || Nearest Neighbor || The [[nearest neighbour algorithm]] was created, which is the start of basic pattern recognition. The algorithm was used to map routes.[{{cite web|last1=Cohen|first1=Harvey|title=The Perceptron|url=http://harveycohen.net/image/perceptron.html|accessdate=5 June 2016}}]
|-
| 1970 || || Automatic Differentiation (Backpropagation) || [[Seppo Linnainmaa]] publishes the general method for automatic differentiation (AD) of discrete connected networks of nested differentiable functions.[{{cite thesis |authorlink1=Seppo Linnainmaa |first1=Seppo |last1=Linnainmaa |year=1970 |title=Algoritmin kumulatiivinen pyoristysvirhe yksittaisten pyoristysvirheiden taylor-kehitelmana |trans-title=The representation of the cumulative rounding error of an algorithm as a Taylor expansion of the local rounding errors |language=Finnish |pages=6–7 |url=https://people.idsia.ch/~juergen/linnainmaa1970thesis.pdf }}][{{cite journal |first=Seppo |last=Linnainmaa |authorlink=Seppo Linnainmaa |year=1976 |title=Taylor expansion of the accumulated rounding error |journal=BIT Numerical Mathematics |volume=16 |issue=2 |pages=146–160 |doi=10.1007/BF01931367 |s2cid=122357351 }}] This corresponds to the modern version of backpropagation, but is not yet named as such.[{{cite journal |last=Griewank |first=Andreas |year=2012 |title=Who Invented the Reverse Mode of Differentiation? |journal=Documenta Mathematica, Extra Volume ISMP |series=Documenta Mathematica Series |volume=6 |pages=389–400|doi=10.4171/dms/6/38 |doi-access=free |isbn=978-3-936609-58-5 }}][{{cite book|last1=Griewank|first1=Andreas|last2=Walther|first2=A.|title=Principles and Techniques of Algorithmic Differentiation|url=https://books.google.com/books?id=qMLUIsgCwvUC|language=en|edition=Second|publisher=SIAM|year=2008|isbn=978-0898716597}}][{{cite journal |authorlink=Jürgen Schmidhuber |last=Schmidhuber |first=Jürgen |year=2015 |title=Deep learning in neural networks: An overview |journal=Neural Networks |volume=61 |pages=85–117 |arxiv=1404.7828|bibcode=2014arXiv1404.7828S |doi=10.1016/j.neunet.2014.09.003 |pmid=25462637|s2cid=11715509 }}][{{cite journal | last1 = Schmidhuber | first1 = Jürgen | authorlink = Jürgen Schmidhuber | year = 2015 | title = Deep Learning (Section on Backpropagation) | journal = Scholarpedia | volume = 10 | issue = 11| page = 32832 | doi = 10.4249/scholarpedia.32832 | bibcode = 2015SchpJ..1032832S | doi-access = free }}]
|-
| 1976 || Discovery || Transfer Learning || Stevo Bozinovski and Ante Fulgosi introduced transfer learning method in neural networks training. [ Stevo Bozinovski and Ante Fulgosi (1976) "The influence of pattern similarity and transfer learning upon training of a base perceptron" (original in Croatian) Proceedings of Symposium Informatica 3-121-5, Bled. ] [ Stevo Bozinovski (2020) "Reminder of the first paper on transfer learning in neural networks, 1976". Informatica 44: 291–302. ]
|-
| 1979 || || Stanford Cart || Students at Stanford University develop a cart that can navigate and avoid obstacles in a room.[{{cite journal
| last = Fukushima
| first = Kunihiko
| date = October 1979
| title = 位置ずれに影響されないパターン認識機構の神経回路のモデル --- ネオコグニトロン ---
| trans-title = Neural network model for a mechanism of pattern recognition unaffected by shift in position — Neocognitron —
| language = Japanese
| journal = Trans. IECE
| volume = J62-A
| issue = 10
| pages = 658–665
| url = https://search.ieice.org/bin/summary.php?id=j62-a_10_658
}}][{{cite journal |last1=Fukushima |first1=Kunihiko |title=Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position |journal=Biological Cybernetics |date=April 1980 |volume=36 |issue=4 |pages=193–202 |doi=10.1007/BF00344251 |pmid=7370364 |s2cid=206775608 }}] [[Neocognitron|Neocognition]] later inspires [[convolutional neural network]]s (CNNs).[{{cite journal|last1=Le Cun|first1=Yann|title=Deep Learning|citeseerx=10.1.1.297.6176}}]
|-
|1981||Achievement||Learning to recognize 40 patterns||Stevo Bozinovski showed an experiment of neural network supervised learning for recognition of 40 linearly dependent patters: 26 letters, 10 numbers, and 4 special symbols from a computer terminal. [ S. Bozinovski (1981) "Teaching space: A representation concept for adaptive pattern classification" COINS Technical Report No. 81-28, Computer and Information Science Department, University of Massachusetts at Amherst, MA, 1981. UM-CS-1981-028.pdf ]
|-
| 1981 || || Explanation Based Learning || Gerald Dejong introduces Explanation Based Learning, where a computer algorithm analyses data and creates a general rule it can follow and discard unimportant data.[{{cite journal |last1=Hopfield |first1=J J |title=Neural networks and physical systems with emergent collective computational abilities. |journal=Proceedings of the National Academy of Sciences |date=April 1982 |volume=79 |issue=8 |pages=2554–2558 |doi=10.1073/pnas.79.8.2554 |pmid=6953413 |pmc=346238 |bibcode=1982PNAS...79.2554H |doi-access=free }}]
|-
|1982||Discovery||Self Learning||Stevo Bozinovski develops a self-learning paradigm in which an agent does not use an external reinforcement. Instead, the agent learns using internal state evaluations, represented by emotions. He introduces the Crossbar Adaptive Array (CAA) architecture capable of self-learning. [ Bozinovski, S. (1982). "A self-learning system using secondary reinforcement". In Trappl, Robert (ed.). Cybernetics and Systems Research: Proceedings of the Sixth European Meeting on Cybernetics and Systems Research. North-Holland. pp. 397–402. ISBN 978-0-444-86488-8 ][ Bozinovski S. (1995) "Adaptive parallel distributed processing, neural and genetic agents. Part I: Neuro-genetic agents and structural theory of self-reinforcement learning systems". CMPSCI Technical Report 95-107, University of Massachusetts at Amherst, UM-CS-1995-107]
|-
|1982||Achievement||Delayed reinforcement learning||Stevo Bozinovski solved the challenge of reinforcement learning with delayed rewards. Using the Crossbar Adaptive Array (CAA) he presented solutions of two tasks: 1) learning path in a graph 2) balancing an inverted pendulum.[Bozinovski, S. (1999) "Crossbar Adaptive Array: The first connectionist network that solved the delayed reinforcement learning problem" In A. Dobnikar, N. Steele, D. Pearson, R. Albert (Eds.) Artificial Neural Networks and Genetic Algorithms, Springer Verlag, p. 320-325, 1999, ISBN 3-211-83364-1 ]
|-
| 1985 || || [[NETtalk (artificial neural network)|NETtalk]] || A program that learns to pronounce words the same way a baby does, is developed by [[Terry Sejnowski]].[{{cite journal |last1=Rumelhart |first1=David E. |last2=Hinton |first2=Geoffrey E. |last3=Williams |first3=Ronald J. |title=Learning representations by back-propagating errors |journal=Nature |date=October 1986 |volume=323 |issue=6088 |pages=533–536 |doi=10.1038/323533a0 |bibcode=1986Natur.323..533R |s2cid=205001834 }}]
|-
| 1988 || Discovery|| [[Universal approximation theorem]] || {{ill|Kurt Hornik|de}} proves that standard multilayer feedforward networks are capable of approximating any Borel measurable function from one finite dimensional space to another to any desired degree of accuracy, provided sufficiently many hidden units are available.
|-
| 1989 || Discovery || Reinforcement Learning || Christopher Watkins develops [[Q-learning]], which greatly improves the practicality and feasibility of [[reinforcement learning]].[{{cite journal|last1=Watksin|first1=Christopher|title=Learning from Delayed Rewards|date=1 May 1989|url=http://www.cs.rhul.ac.uk/~chrisw/new_thesis.pdf}}]
|-
| 1989 || Commercialization || Commercialization of Machine Learning on Personal Computers || Axcelis, Inc. releases [[Evolver (software)|Evolver]], the first software package to commercialize the use of genetic algorithms on personal computers.[{{cite news|last1=Markoff|first1=John|title=BUSINESS TECHNOLOGY; What's the Best Answer? It's Survival of the Fittest|url=https://www.nytimes.com/1990/08/29/business/business-technology-what-s-the-best-answer-it-s-survival-of-the-fittest.html|accessdate=8 June 2016|work=New York Times|date=29 August 1990}}]
|-
| 1992 || Achievement || Machines Playing Backgammon || Gerald Tesauro develops [[TD-Gammon]], a computer [[backgammon]] program that uses an [[artificial neural network]] trained using [[temporal-difference learning]] (hence the 'TD' in the name). TD-Gammon is able to rival, but not consistently surpass, the abilities of top human backgammon players.[{{cite journal |last1=Tesauro |first1=Gerald |title=Temporal difference learning and TD-Gammon |journal=Communications of the ACM |date=March 1995 |volume=38 |issue=3 |pages=58–68 |doi=10.1145/203330.203343 |s2cid=8763243 }}]
|-
| 1995 || Discovery || Random Forest Algorithm || Tin Kam Ho publishes a paper describing [[random forest|random decision forests]].[{{cite book |doi=10.1109/ICDAR.1995.598994 |chapter=Random decision forests |title=Proceedings of 3rd International Conference on Document Analysis and Recognition |year=1995 |last1=Tin Kam Ho |volume=1 |pages=278–282 |isbn=0-8186-7128-9 }}]
|-
| 1995 || Discovery || Support-Vector Machines || [[Corinna Cortes]] and [[Vladimir Vapnik]] publish their work on [[support-vector machine]]s.[{{cite journal |last1=Cortes |first1=Corinna |last2=Vapnik |first2=Vladimir |title=Support-vector networks |journal=Machine Learning |date=September 1995 |volume=20 |issue=3 |pages=273–297 |doi=10.1007/BF00994018 |doi-access=free }}]
|-
| 1997 || Achievement || IBM Deep Blue Beats Kasparov || IBM's [[Deep Blue (chess computer)|Deep Blue]] beats the world champion at chess.[{{cite journal |last1=Hochreiter |first1=Sepp |last2=Schmidhuber |first2=Jürgen |title=Long Short-Term Memory |journal=Neural Computation |date=1 November 1997 |volume=9 |issue=8 |pages=1735–1780 |doi=10.1162/neco.1997.9.8.1735 |pmid=9377276 |s2cid=1915014 }}] greatly improving the efficiency and practicality of recurrent neural networks.
|-
| 1998 || || MNIST database || A team led by [[Yann LeCun]] releases the [[MNIST database]], a dataset comprising a mix of handwritten digits from [[American Census Bureau]] employees and American high school students.[{{cite web|last1=LeCun|first1=Yann|last2=Cortes|first2=Corinna|last3=Burges|first3=Christopher|title=THE MNIST DATABASE of handwritten digits|url=http://yann.lecun.com/exdb/mnist/|accessdate=16 June 2016}}] The MNIST database has since become a benchmark for evaluating [[handwriting recognition]].
|-
| 2002 || Project|| Torch Machine Learning Library || [[Torch (machine learning)|Torch]], a software library for machine learning, is first released.[{{cite journal|last1=Collobert|first1=Ronan|last2=Benigo|first2=Samy|last3=Mariethoz|first3=Johnny|title=Torch: a modular machine learning software library|date=30 October 2002|url=http://www.idiap.ch/ftp/reports/2002/rr02-46.pdf|accessdate=5 June 2016|archive-date=6 August 2016|archive-url=https://web.archive.org/web/20160806084735/http://www.idiap.ch/ftp/reports/2002/rr02-46.pdf|url-status=dead}}]
|-
| 2006 || || The Netflix Prize || The [[Netflix Prize]] competition is launched by [[Netflix]]. The aim of the competition was to use machine learning to beat Netflix's own recommendation software's accuracy in predicting a user's rating for a film given their ratings for previous films by at least 10%.[{{cite web|title=The Netflix Prize Rules|url=http://www.netflixprize.com/rules|website=Netflix Prize|publisher=Netflix|accessdate=16 June 2016|url-status=dead|archiveurl=https://web.archive.org/web/20120303162455/http://www.netflixprize.com/rules|archivedate=3 March 2012}}] The prize was won in 2009.
|-
|2009
|Achievement
|ImageNet
|[[ImageNet]] is created. ImageNet is a large visual database envisioned by [[Fei-Fei Li]] from Stanford University, who realized that the best machine learning algorithms wouldn't work well if the data didn't reflect the real world.[{{Cite web|url=https://qz.com/1034972/the-data-that-changed-the-direction-of-ai-research-and-possibly-the-world/|title=ImageNet: the data that spawned the current AI boom — Quartz|last=Gershgorn|first=Dave|website=qz.com|date=26 July 2017 |language=en-US|access-date=2018-03-30}}] For many, ImageNet was the catalyst for the AI boom[{{cite news |last1=Hardy |first1=Quentin |title=Reasons to Believe the A.I. Boom Is Real |url=https://www.nytimes.com/2016/07/19/technology/reasons-to-believe-the-ai-boom-is-real.html |work=The New York Times |date=18 July 2016 }}] of the 21st century.
|-
| 2010 || Project|| Kaggle Competition || [[Kaggle]], a website that serves as a platform for machine learning competitions, is launched.[{{cite web|title=About|url=https://www.kaggle.com/about|website=Kaggle|publisher=Kaggle Inc|accessdate=16 June 2016|archive-date=18 March 2016|archive-url=https://web.archive.org/web/20160318210802/https://www.kaggle.com/about|url-status=dead}}]
|-
| 2011 || Achievement || Beating Humans in Jeopardy || Using a combination of machine learning, [[natural language processing]] and information retrieval techniques, [[IBM]]'s [[Watson (computer)|Watson]] beats two human champions in a [[Jeopardy!]] competition.[{{cite news |last1=Markoff |first1=John |title=Computer Wins on 'Jeopardy!': Trivial, It's Not |url=https://www.nytimes.com/2011/02/17/science/17jeopardy-watson.html |work=The New York Times |date=16 February 2011 |page=A1 }}]
|-
| 2012 || Achievement || Recognizing Cats on YouTube || The [[Google Brain]] team, led by [[Andrew Ng]] and [[Jeff Dean (computer scientist)|Jeff Dean]], create a neural network that learns to recognize cats by watching unlabeled images taken from frames of [[YouTube]] videos.[{{cite book |doi=10.1109/ICASSP.2013.6639343 |chapter=Building high-level features using large scale unsupervised learning |title=2013 IEEE International Conference on Acoustics, Speech and Signal Processing |year=2013 |last1=Le |first1=Quoc V. |pages=8595–8598 |isbn=978-1-4799-0356-6 |s2cid=206741597 }}][{{cite news|last1=Markoff|first1=John|title=How Many Computers to Identify a Cat? 16,000|url=https://www.nytimes.com/2012/06/26/technology/in-a-big-network-of-computers-evidence-of-machine-learning.html|accessdate=5 June 2016|work=New York Times|date=26 June 2012|page=B1}}]
|-
|2012
|Discovery
|Visual Recognition
|The [[AlexNet]] paper and algorithm achieves breakthrough results in image recognition in the ImageNet benchmark. This popularizes deep neural networks.[{{Cite web |date=2017-07-26 |title=The data that transformed AI research—and possibly the world |url=https://qz.com/1034972/the-data-that-changed-the-direction-of-ai-research-and-possibly-the-world |access-date=2023-09-12 |website=Quartz |language=en}}]
|-
|2013
|Discovery
|Word Embeddings
|A widely cited paper nicknamed [[word2vec]] revolutionizes the processing of text in machine learnings. It shows how each word can be converted into a sequence of numbers ([[Word embedding|word embeddings]]), the use of these vectors revolutionized text processing in machine learning.
|-
| 2014 || Achievement|| Leap in Face Recognition || [[Facebook]] researchers publish their work on [[DeepFace]], a system that uses neural networks that identifies faces with 97.35% accuracy. The results are an improvement of more than 27% over previous systems and rivals human performance.[{{cite journal|last1=Taigman|first1=Yaniv|last2=Yang|first2=Ming|last3=Ranzato|first3=Marc'Aurelio|last4=Wolf|first4=Lior|title=DeepFace: Closing the Gap to Human-Level Performance in Face Verification|journal=Conference on Computer Vision and Pattern Recognition|date=24 June 2014|url=https://research.facebook.com/publications/deepface-closing-the-gap-to-human-level-performance-in-face-verification/|accessdate=8 June 2016}}]
|-
| 2014 || || Sibyl || Researchers from [[Google]] detail their work on Sibyl,[{{cite web|last1=Canini|first1=Kevin|last2=Chandra|first2=Tushar|last3=Ie|first3=Eugene|last4=McFadden|first4=Jim|last5=Goldman|first5=Ken|last6=Gunter|first6=Mike|last7=Harmsen|first7=Jeremiah|last8=LeFevre|first8=Kristen|last9=Lepikhin|first9=Dmitry|last10=Llinares|first10=Tomas Lloret|last11=Mukherjee|first11=Indraneel|last12=Pereira|first12=Fernando|last13=Redstone|first13=Josh|last14=Shaked|first14=Tal|last15=Singer|first15=Yoram|title=Sibyl: A system for large scale supervised machine learning|url=https://users.soe.ucsc.edu/~niejiazhong/slides/chandra.pdf|website=Jack Baskin School of Engineering|publisher=UC Santa Cruz|accessdate=8 June 2016|archive-date=15 August 2017|archive-url=https://web.archive.org/web/20170815072141/https://users.soe.ucsc.edu/~niejiazhong/slides/chandra.pdf|url-status=dead}}] a proprietary platform for massively parallel machine learning used internally by Google to make predictions about user behavior and provide recommendations.[{{cite news|last1=Woodie|first1=Alex|title=Inside Sibyl, Google's Massively Parallel Machine Learning Platform|url=http://www.datanami.com/2014/07/17/inside-sibyl-googles-massively-parallel-machine-learning-platform/|accessdate=8 June 2016|work=Datanami|publisher=Tabor Communications|date=17 July 2014}}]
|-
| 2016 || Achievement || Beating Humans in Go ||Google's [[AlphaGo]] program becomes the first [[Computer Go]] program to beat an unhandicapped professional human player[{{cite web|title=Google achieves AI 'breakthrough' by beating Go champion|url=https://www.bbc.com/news/technology-35420579|website=BBC News|publisher=BBC|accessdate=5 June 2016|date=27 January 2016}}] using a combination of machine learning and tree search techniques.[{{cite web|title=AlphaGo|url=https://www.deepmind.com/alpha-go.html|website=Google DeepMind|publisher=Google Inc|accessdate=5 June 2016|archive-date=30 January 2016|archive-url=https://web.archive.org/web/20160130230207/http://www.deepmind.com/alpha-go.html|url-status=dead}}] Later improved as [[AlphaGo Zero]] and then in 2017 generalized to Chess and more two-player games with [[AlphaZero]].
|-
|2017
|Discovery
|Transformer
|A team at [[Google Brain]] invent the [[Transformer (machine learning model)|transformer]] architecture,[{{Cite journal |last1=Vaswani |first1=Ashish |last2=Shazeer |first2=Noam |last3=Parmar |first3=Niki |last4=Uszkoreit |first4=Jakob |last5=Jones |first5=Llion |last6=Gomez |first6=Aidan N. |last7=Kaiser |first7=Lukasz |last8=Polosukhin |first8=Illia |date=2017 |title=Attention Is All You Need |arxiv=1706.03762}}] which allows for faster parallel training of neural networks on sequential data like text.
|-
| 2018 || Achievement || Protein Structure Prediction || AlphaFold 1 (2018) placed first in the overall rankings of the 13th [[CASP|Critical Assessment of Techniques for Protein Structure Prediction]] (CASP) in December 2018.[{{cite news |last1=Sample |first1=Ian |title=Google's DeepMind predicts 3D shapes of proteins |url=https://www.theguardian.com/science/2018/dec/02/google-deepminds-ai-program-alphafold-predicts-3d-shapes-of-proteins |work=The Guardian |date=2 December 2018 }}]
|-
|2021 || Achievement || Protein Structure Prediction || AlphaFold 2 (2021), A team that used AlphaFold 2 (2020) repeated the placement in the CASP competition in November 2020. The team achieved a level of accuracy much higher than any other group. It scored above 90 for around two-thirds of the proteins in CASP's global distance test (GDT), a test that measures the degree to which a computational program predicted structure is similar to the lab experiment determined structure, with 100 being a complete match, within the distance cutoff used for calculating GDT.[{{cite journal |last1=Eisenstein |first1=Michael |title=Artificial intelligence powers protein-folding predictions |journal=Nature |date=23 November 2021 |volume=599 |issue=7886 |pages=706–708 |doi=10.1038/d41586-021-03499-y |s2cid=244528561 }}]
|-
|}
==See also==
* [[History of artificial intelligence]]
* [[Timeline of artificial intelligence]]
* [[Timeline of machine translation]]
==References==
=== Citations ===
{{Reflist}}
=== Works cited ===
*{{Cite book |first=Daniel |last=Crevier |year=1993 |title=AI: The Tumultuous Search for Artificial Intelligence |publisher=BasicBooks |isbn=0-465-02997-3 |location=New York |author-link=Daniel Crevier}}
*{{cite news |last1=Marr |first1=Bernard |title=A Short History of Machine Learning -- Every Manager Should Read |url=https://www.forbes.com/sites/bernardmarr/2016/02/19/a-short-history-of-machine-learning-every-manager-should-read/ |work=Forbes |date=19 February 2016 |access-date=2022-12-25 |archive-url=https://web.archive.org/web/20221205135114/https://www.forbes.com/sites/bernardmarr/2016/02/19/a-short-history-of-machine-learning-every-manager-should-read/ |archive-date=2022-12-05 |url-status=live}}
* {{Cite book |first1=Stuart |last1=Russell |first2=Peter |last2=Norvig |year=2003 |title=Artificial Intelligence: A Modern Approach |publisher=Pearson Education |isbn=0-137-90395-2 |location=London |author-link1=Stuart J. Russell |author-link2=Peter Norvig}}
{{Timelines of computing}}
[[Category:Machine learning]]
[[Category:Computing timelines|Machine learning]]
{{Short description|Animals in mammal order Chiroptera}}
File:Wikipedia-Bats-001-v01.jpg|300px|thumb|right|Clockwise from top-right: [[Egyptian fruit bat]] (''Rousettus aegyptiacus''), [[Mexican free-tailed bat]] (''Tadarida brasiliensis''), [[greater mouse-eared bat]]s (''Myotis myotis''), [[greater short-nosed fruit bat]] (''Cynopterus sphinx''), [[greater horseshoe bat]] (''Rhinolophus ferrumequinum''), [[common vampire bat]] (''Desmodus rotundus'')|alt=six bat images
rect 0 0 820 510 [[Common vampire bat]]
rect 0 510 820 950 [[Greater horseshoe bat]]
rect 0 950 820 1560 [[Greater short-nosed fruit bat]]
rect 1520 0 820 510 [[Egyptian fruit bat]]
rect 1520 510 820 950 [[Mexican free-tailed bat]]
rect 1520 950 820 1560 [[Greater mouse-eared bat]]
[[File:Bat range.png|thumb|right|Worldwide distribution of bat species|alt=Map of the world, with most of the world outside of the arctic and antarctic regions shaded red]]
[[Chiroptera]] is an [[order (biology)|order]] of flying [[placentalia|placental]] [[mammal]]s. Members of this order are called chiropterans, or bats. The order comprises 1318 [[extant taxa|extant]] species, which are grouped into 226 [[genus|genera]]. The second largest order of mammals after [[rodent]]s, bats comprise about 20% of all mammal species worldwide. The majority of bats live in South and Central America, Africa, and southern and Southeast Asia, but the order as a whole can be found in most of the world outside of Antarctica and the arctic. They live in a variety of habitats, particularly forests and caves but also grasslands, savannas, shrublands, wetlands, deserts, and rocky areas. With their forelimbs adapted as [[bat wing development|wing]]s, they are the only mammals capable of true and sustained [[bat flight|flight]]. They range in length from [[Kitti's hog-nosed bat]], at {{convert|2|cm|in|0|abbr=on}}, to the [[great flying fox]], at {{convert|37|cm|in|0|abbr=on}}, both with no tail. Bat wings are relatively proportionate to their size, with the [[large flying fox]] having the largest overall wingspan, up to {{convert|1.7|m|ft|abbr=on}}.[[[#CITEREF_MSW|Wilson, Reeder]], pp. 312–529]
[{{cite web |url=https://www.mammaldiversity.org/explore/ |title=Explore Taxonomy |work=The Mammal Diversity Database |publisher=[[American Society of Mammalogists]] |access-date=April 22, 2025 |archive-url=https://web.archive.org/web/20250331101159/https://www.mammaldiversity.org/explore/ |archive-date=March 31, 2025 |url-status=live}}]
[{{cite journal |last1=Hao |first1=X. |last2=Zhao |first2=H. |title=A molecular phylogeny for all 21 families within Chiroptera (bats) |journal=[[Integrative Zoology]] |date=2023 |volume=19 |issue=5 |pages=989–998 |doi=10.1111/1749-4877.12772 |pmid=37853557}}]
[[[#CITEREF_BATWORLD|Nowak]], pp. [https://archive.org/details/walkersbatsofwor00rona/page/47 48–49]]
[[[#CITEREF_BATWORLD|Nowak]], p. [https://archive.org/details/walkersbatsofwor00rona/page/85 86]]
[[[#CITEREF_BATWORLD|Nowak]], pp. [https://archive.org/details/walkersbatsofwor00rona/page/87 87–88]]
[[[#CITEREF_BATWORLD|Nowak]], p. [https://archive.org/details/walkersbatsofwor00rona/page/99 100]]
[[[#CITEREF_BATWORLD|Nowak]], pp. [https://archive.org/details/walkersbatsofwor00rona/page/101 101–102]]
[[[#CITEREF_BATWORLD|Nowak]], p. [https://archive.org/details/walkersbatsofwor00rona/page/107 107]]
[[[#CITEREF_BATWORLD|Nowak]], p. [https://archive.org/details/walkersbatsofwor00rona/page/109 110]]
[[[#CITEREF_BATWORLD|Nowak]], p. [https://archive.org/details/walkersbatsofwor00rona/page/119 119]]
[[[#CITEREF_BATWORLD|Nowak]], p. [https://archive.org/details/walkersbatsofwor00rona/page/123 123]]
[[[#CITEREF_BATWORLD|Nowak]], p. [https://archive.org/details/walkersbatsofwor00rona/page/127 127]]
[[[#CITEREF_BATWORLD|Nowak]], p. [https://archive.org/details/walkersbatsofwor00rona/page/175 176]]
[[[#CITEREF_BATWORLD|Nowak]], p. [https://archive.org/details/walkersbatsofwor00rona/page/177 178]]
[[[#CITEREF_BATWORLD|Nowak]], p. [https://archive.org/details/walkersbatsofwor00rona/page/179 179]]
[[[#CITEREF_BATWORLD|Nowak]], p. [https://archive.org/details/walkersbatsofwor00rona/page/181 181]]
[[[#CITEREF_BATWORLD|Nowak]], p. [https://archive.org/details/walkersbatsofwor00rona/page/181 182]]
[[[#CITEREF_BATWORLD|Nowak]], p. [https://archive.org/details/walkersbatsofwor00rona/page/183 184]]
[[[#CITEREF_BATWORLD|Nowak]], p. [https://archive.org/details/walkersbatsofwor00rona/page/221 221]]
[[[#CITEREF_BATWORLD|Nowak]], p. [https://archive.org/details/walkersbatsofwor00rona/page/229 230–232]]
[[[#CITEREF_ALLMAM|Chernasky; Motis; Burgin]], pp. 484–488]
[''Balantiopteryx'' habitats:
* ''Ecuadorian sac-winged bat'': Tirira, D. (2016) [errata version of 2015 assessment]. [https://www.iucnredlist.org/species/2531/97206692 "''Balantiopteryx infusca''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T2531A97206692. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T2531A22029804.en 10.2305/IUCN.UK.2015-4.RLTS.T2531A22029804.en].
* ''Gray sac-winged bat'': Lim, B.; et al. (2016). [https://www.iucnredlist.org/species/2533/22029659 "''Balantiopteryx plicata''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T2533A22029659. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T2533A22029659.en 10.2305/IUCN.UK.2016-2.RLTS.T2533A22029659.en].
* ''Thomas's sac-winged bat'': Lim, B. (2015). [https://www.iucnredlist.org/species/2532/22030080 "''Balantiopteryx io''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T2532A22030080. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T2532A22030080.en 10.2305/IUCN.UK.2015-4.RLTS.T2532A22030080.en].
]
[''Centronycteris'' habitats:
* ''Shaggy bat'': Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/4112/22002444 "''Centronycteris maximiliani''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T4112A22002444. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T4112A22002444.en 10.2305/IUCN.UK.2016-2.RLTS.T4112A22002444.en].
* ''Thomas's shaggy bat'': Arroyo-Cabrales, J.; et al. (2015). [https://www.iucnredlist.org/species/136350/22023809 "''Centronycteris centralis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T136350A22023809. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T136350A22023809.en 10.2305/IUCN.UK.2015-4.RLTS.T136350A22023809.en].
]
[''Coleura'' habitats:
* ''African sheath-tailed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/5113/22089365 "''Coleura afra''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T5113A22089365. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T5113A22089365.en 10.2305/IUCN.UK.2017-2.RLTS.T5113A22089365.en].
* ''Madagascar sheath-tailed bat'': Goodman, S. (2017). [https://www.iucnredlist.org/species/80221085/95642170 "''Coleura kibomalandy''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T80221085A95642170. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T80221085A95642170.en 10.2305/IUCN.UK.2017-2.RLTS.T80221085A95642170.en].
* ''Seychelles sheath-tailed bat'': Mondajem, A.; et al. (2017). [https://www.iucnredlist.org/species/5112/22089794 "''Coleura seychellensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T5112A22089794. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T5112A22089794.en 10.2305/IUCN.UK.2017-2.RLTS.T5112A22089794.en].
]
[Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/41527/22006450 "''Cormura brevirostris''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T41527A22006450. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T41527A22006450.en 10.2305/IUCN.UK.2016-2.RLTS.T41527A22006450.en].]
[Lim, B.; et al. (2016). [https://www.iucnredlist.org/species/6206/22022820 "''Cyttarops alecto''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T6206A22022820. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T6206A22022820.en 10.2305/IUCN.UK.2016-2.RLTS.T6206A22022820.en].]
[''Diclidurus'' habitats:
* ''Greater ghost bat'': Lim, B.; et al. (2016). [https://www.iucnredlist.org/species/6562/21986793 "''Diclidurus ingens''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T6562A21986793. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T6562A21986793.en 10.2305/IUCN.UK.2016-2.RLTS.T6562A21986793.en].
* ''Isabelle's ghost bat'': Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/6563/21986404 "''Diclidurus isabella''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T6563A21986404. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T6563A21986404.en 10.2305/IUCN.UK.2016-3.RLTS.T6563A21986404.en].
* ''Lesser ghost bat'': Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/6564/21986499 "''Diclidurus scutatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T6564A21986499. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T6564A21986499.en 10.2305/IUCN.UK.2016-2.RLTS.T6564A21986499.en].
* ''Northern ghost bat'': Lim, B.; et al. (2016). [https://www.iucnredlist.org/species/6561/21986615 "''Diclidurus albus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T6561A21986615. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T6561A21986615.en 10.2305/IUCN.UK.2016-2.RLTS.T6561A21986615.en].
]
[''Emballonura'' habitats:
* ''Beccari's sheath-tailed bat'': Armstrong, K. N. (2021) [amended version of 2019 assessment]. [https://www.iucnredlist.org/species/7672/209521847 "''Emballonura beccarii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T7672A209521847. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T7672A209521847.en 10.2305/IUCN.UK.2021-3.RLTS.T7672A209521847.en].
* ''Greater sheath-tailed bat'': Armstrong, K. N.; et al. (2021) [amended version of 2017 assessment]. [https://www.iucnredlist.org/species/7667/209536771 "''Emballonura furax''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T7667A209536771. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T7667A209536771.en 10.2305/IUCN.UK.2021-3.RLTS.T7667A209536771.en].
* ''Large-eared sheath-tailed bat'': Armstrong, K. N. (2021) [amended version of 2019 assessment]. [https://www.iucnredlist.org/species/7673/209522232 "''Emballonura dianae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T7673A209522232. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T7673A209522232.en 10.2305/IUCN.UK.2021-3.RLTS.T7673A209522232.en].
* ''Lesser sheath-tailed bat'': Bates, P. J. J.; et al. (2021). [https://www.iucnredlist.org/species/7674/22134864 "''Emballonura monticola''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T7674A22134864. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T7674A22134864.en 10.2305/IUCN.UK.2021-1.RLTS.T7674A22134864.en].
* ''Pacific sheath-tailed bat'': Waldien, D. L.; et al. (2021). [https://www.iucnredlist.org/species/7669/22135085 "''Emballonura semicaudata''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T7669A22135085. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T7669A22135085.en 10.2305/IUCN.UK.2021-1.RLTS.T7669A22135085.en].
* ''Raffray's sheath-tailed bat'': Armstrong, K. N. (2021) [amended version of 2019 assessment]. [https://www.iucnredlist.org/species/7668/209522673 "''Emballonura raffrayana''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T7668A209522673. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T7668A209522673.en 10.2305/IUCN.UK.2021-3.RLTS.T7668A209522673.en].
* ''Seri's sheath-tailed bat'': Armstrong, K. N. (2021) [amended version of 2019 assessment]. [https://www.iucnredlist.org/species/41528/209523175 "''Emballonura serii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T41528A209523175. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T41528A209523175.en 10.2305/IUCN.UK.2021-3.RLTS.T41528A209523175.en].
* ''Small Asian sheath-tailed bat'': Armstrong, K. N.; et al. (2021) [amended version of 2019 assessment]. [https://www.iucnredlist.org/species/7670/209548087 "''Emballonura alecto''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T7670A209548087. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T7670A209548087.en 10.2305/IUCN.UK.2021-3.RLTS.T7670A209548087.en].
]
[Armstrong, K. N. (2021) [amended version of 2020 assessment]. [https://www.iucnredlist.org/species/13904/209523725 "''Mosia nigrescens''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T13904A209523725. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T13904A209523725.en 10.2305/IUCN.UK.2021-3.RLTS.T13904A209523725.en].]
[''Paremballonura'' habitats:
* ''Peters's sheath-tailed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/7671/22135427 "''Paremballonura atrata''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T7671A22135427. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T7671A22135427.en 10.2305/IUCN.UK.2017-2.RLTS.T7671A22135427.en].
* ''Western sheath-tailed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/136835/22040708 "''Paremballonura tiavato''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T136835A22040708. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T136835A22040708.en 10.2305/IUCN.UK.2017-2.RLTS.T136835A22040708.en].
]
[''Peropteryx'' habitats:
* ''Greater dog-like bat'': Davalos, L.; et al. (2018). [https://www.iucnredlist.org/species/16707/22100544 "''Peropteryx kappleri''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T16707A22100544. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T16707A22100544.en 10.2305/IUCN.UK.2018-2.RLTS.T16707A22100544.en].
* ''Lesser dog-like bat'': Barquez, R.; et al. (2015). [https://www.iucnredlist.org/species/16709/22101100 "''Peropteryx macrotis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T16709A22101100. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T16709A22101100.en 10.2305/IUCN.UK.2015-4.RLTS.T16709A22101100.en].
* ''Pale-winged dog-like bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/85822291/85822446 "''Peropteryx pallidoptera''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T85822291A85822446. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T85822291A85822446.en 10.2305/IUCN.UK.2016-3.RLTS.T85822291A85822446.en].
* ''Trinidad dog-like bat'': Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/136790/22035534 "''Peropteryx trinitatis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136790A22035534. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T136790A22035534.en 10.2305/IUCN.UK.2016-2.RLTS.T136790A22035534.en].
* ''White-winged dog-like bat'': Solari, S. (2015). [https://www.iucnredlist.org/species/16708/22100830 "''Peropteryx leucoptera''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T16708A22100830. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T16708A22100830.en 10.2305/IUCN.UK.2015-4.RLTS.T16708A22100830.en].
]
[Lim, B.; et al. (2016). [https://www.iucnredlist.org/species/19714/22010818 "''Rhynchonycteris naso''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T19714A22010818. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T19714A22010818.en 10.2305/IUCN.UK.2016-2.RLTS.T19714A22010818.en].]
[''Saccopteryx'' habitats:
* ''Amazonian sac-winged bat'': Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/19806/22005356 "''Saccopteryx gymnura''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T19806A22005356. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T19806A22005356.en 10.2305/IUCN.UK.2016-2.RLTS.T19806A22005356.en].
* ''Antioquian sac-winged bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/136420/21985022 "''Saccopteryx antioquensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136420A21985022. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T136420A21985022.en 10.2305/IUCN.UK.2016-1.RLTS.T136420A21985022.en].
* ''Frosted sac-winged bat'': Solari, S. (2015). [https://www.iucnredlist.org/species/19805/22005456 "''Saccopteryx canescens''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T19805A22005456. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T19805A22005456.en 10.2305/IUCN.UK.2015-4.RLTS.T19805A22005456.en].
* ''Greater sac-winged bat'': Solari, S. (2015). [https://www.iucnredlist.org/species/19804/22004716 "''Saccopteryx bilineata''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T19804A22004716. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T19804A22004716.en 10.2305/IUCN.UK.2015-4.RLTS.T19804A22004716.en].
* ''Lesser sac-winged bat'': Solari, S. (2015). [https://www.iucnredlist.org/species/19807/22005807 "''Saccopteryx leptura''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T19807A22005807. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T19807A22005807.en 10.2305/IUCN.UK.2015-4.RLTS.T19807A22005807.en].
]
[''Saccolaimus'' habitats:
* ''Naked-rumped pouched bat'': Lumsden, L. F. (2021) [errata version of 2017 assessment]. [https://www.iucnredlist.org/species/19802/209550074 "''Saccolaimus saccolaimus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T19802A209550074. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T19802A209550074.en 10.2305/IUCN.UK.2017-2.RLTS.T19802A209550074.en].
* ''Papuan sheath-tailed bat'': Armstrong, K. N.; et al. (2021) [amended version of 2020 assessment]. [https://www.iucnredlist.org/species/19800/209535232 "''Saccolaimus mixtus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T19800A209535232. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T19800A209535232.en 10.2305/IUCN.UK.2021-3.RLTS.T19800A209535232.en].
* ''Pel's pouched bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/19801/22004557 "''Saccolaimus peli''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T19801A22004557. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T19801A22004557.en 10.2305/IUCN.UK.2017-2.RLTS.T19801A22004557.en].
* ''Yellow-bellied sheath-tailed bat'': Armstrong, K. N.; et al. (2021) [amended version of 2017 assessment]. [https://www.iucnredlist.org/species/19799/209538418 "''Saccolaimus flaviventris''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T19799A209538418. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T19799A209538418.en 10.2305/IUCN.UK.2021-3.RLTS.T19799A209538418.en].
]
[''Taphozous'' habitats:
* ''Arnhem sheath-tailed bat'': Armstrong, K. N.; et al. (2021) [amended version of 2017 assessment]. [https://www.iucnredlist.org/species/21458/209539248 "''Taphozous kapalgensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T21458A209539248. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T21458A209539248.en 10.2305/IUCN.UK.2021-3.RLTS.T21458A209539248.en].
* ''Black-bearded tomb bat'': Phelps, K.; et al. (2019). [https://www.iucnredlist.org/species/21461/22110277 "''Taphozous melanopogon''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T21461A22110277. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T21461A22110277.en 10.2305/IUCN.UK.2019-3.RLTS.T21461A22110277.en].
* ''Coastal sheath-tailed bat'': Armstrong, K. N. (2021). [https://www.iucnredlist.org/species/21452/22112046 "''Taphozous australis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T21452A22112046. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T21452A22112046.en 10.2305/IUCN.UK.2021-1.RLTS.T21452A22112046.en].
* ''Common sheath-tailed bat'': Armstrong, K. N.; et al. (2021) [amended version of 2017 assessment]. [https://www.iucnredlist.org/species/21454/209538623 "''Taphozous georgianus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T21454A209538623. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T21454A209538623.en 10.2305/IUCN.UK.2021-3.RLTS.T21454A209538623.en].
* ''Egyptian tomb bat'': Monadjem, A.; et al. (2020) [amended version of 2017 assessment]. [https://www.iucnredlist.org/species/21463/166505490 "''Taphozous perforatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T21463A166505490. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-1.RLTS.T21463A166505490.en 10.2305/IUCN.UK.2020-1.RLTS.T21463A166505490.en].
* ''Hamilton's tomb bat'': Mickleburgh, S.; et al. (2019). [https://www.iucnredlist.org/species/21455/22111838 "''Taphozous hamiltoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T21455A22111838. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-2.RLTS.T21455A22111838.en 10.2305/IUCN.UK.2019-2.RLTS.T21455A22111838.en].
* ''Hildegarde's tomb bat'': Webala, P.; et al. (2020). [https://www.iucnredlist.org/species/21456/22111960 "''Taphozous hildegardeae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T21456A22111960. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T21456A22111960.en 10.2305/IUCN.UK.2020-2.RLTS.T21456A22111960.en].
* ''Hill's sheath-tailed bat'': Armstrong, K. N. (2021) [amended version of 2020 assessment]. [https://www.iucnredlist.org/species/21457/209524440 "''Taphozous hilli''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T21457A209524440. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T21457A209524440.en 10.2305/IUCN.UK.2021-3.RLTS.T21457A209524440.en].
* ''Indonesian tomb bat'': Hutson, A. M.; et al. (2016). [https://www.iucnredlist.org/species/21453/22111549 "''Taphozous achates''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T21453A22111549. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T21453A22111549.en 10.2305/IUCN.UK.2016-3.RLTS.T21453A22111549.en].
* ''Long-winged tomb bat'': Srinivasulu, B.; et al. (2019). [https://www.iucnredlist.org/species/21459/22111355 "''Taphozous longimanus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T21459A22111355. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-2.RLTS.T21459A22111355.en 10.2305/IUCN.UK.2019-2.RLTS.T21459A22111355.en].
* ''Mauritian tomb bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/21460/22111004 "''Taphozous mauritianus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T21460A22111004. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T21460A22111004.en 10.2305/IUCN.UK.2017-2.RLTS.T21460A22111004.en].
* ''Naked-rumped tomb bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/21462/22109884 "''Taphozous nudiventris''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T21462A22109884. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T21462A22109884.en 10.2305/IUCN.UK.2017-2.RLTS.T21462A22109884.en].
* ''Theobald's tomb bat'': Bates, P.; et al. (2019). [https://www.iucnredlist.org/species/21465/22109663 "''Taphozous theobaldi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T21465A22109663. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T21465A22109663.en 10.2305/IUCN.UK.2019-3.RLTS.T21465A22109663.en].
* ''Troughton's sheath-tailed bat'': Armstrong, K. N.; et al. (2021) [amended version of 2017 assessment]. [https://www.iucnredlist.org/species/21466/209539933 "''Taphozous troughtoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T21466A209539933. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T21466A209539933.en 10.2305/IUCN.UK.2021-3.RLTS.T21466A209539933.en].
]
[[[#CITEREF_ALLMAM|Chernasky; Motis; Burgin]], p. 465]
[Bates, P.; et al. (2019). [https://www.iucnredlist.org/species/5481/22072935 "''Craseonycteris thonglongyai''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T5481A22072935. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T5481A22072935.en 10.2305/IUCN.UK.2019-3.RLTS.T5481A22072935.en].]
[[[#CITEREF_ALLMAM|Chernasky; Motis; Burgin]], pp. 467–475]
[Leary, T.; et al. (2020). [https://www.iucnredlist.org/species/1620/22103184 "''Anthops ornatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T1620A22103184. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T1620A22103184.en 10.2305/IUCN.UK.2020-3.RLTS.T1620A22103184.en].]
[''Asellia'' habitats:
* ''Arabian trident bat'': Benda, P. (2017). [https://www.iucnredlist.org/species/80222726/95642180 "''Asellia arabica''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T80222726A95642180. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T80222726A95642180.en 10.2305/IUCN.UK.2017-2.RLTS.T80222726A95642180.en].
* ''Patrizi's trident leaf-nosed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/2153/21975955 "''Asellia patrizii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T2153A21975955. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T2153A21975955.en 10.2305/IUCN.UK.2017-2.RLTS.T2153A21975955.en].
* ''Somalian trident bat'': Benda, P. (2017). [https://www.iucnredlist.org/species/80221456/95642175 "''Asellia italosomalica''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T80221456A95642175. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T80221456A95642175.en 10.2305/IUCN.UK.2017-2.RLTS.T80221456A95642175.en].
* ''Trident bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/80221529/21975715 "''Asellia tridens''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T80221529A21975715. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T80221529A21975715.en 10.2305/IUCN.UK.2017-2.RLTS.T80221529A21975715.en].
]
[''Aselliscus'' habitats:
* ''Dong Bac's trident bat'': Tu, V.; et al. (2023). [https://www.iucnredlist.org/species/214508825/214518540 "''Aselliscus dongbacanus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2023''': e.T214508825A214518540. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2023-1.RLTS.T214508825A214518540.en 10.2305/IUCN.UK.2023-1.RLTS.T214508825A214518540.en].
* ''Stoliczka's trident bat'': Tu, V.; et al. (2022). [https://www.iucnredlist.org/species/214518902/21976509 "''Aselliscus stoliczkanus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2022''': e.T214518902A21976509. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2022-2.RLTS.T214518902A21976509.en 10.2305/IUCN.UK.2022-2.RLTS.T214518902A21976509.en].
* ''Temminck's trident bat'': Armstrong, K. N. (2021). [https://www.iucnredlist.org/species/2156/21976047 "''Aselliscus tricuspidatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T2156A21976047. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T2156A21976047.en 10.2305/IUCN.UK.2021-2.RLTS.T2156A21976047.en].
]
[''Coelops'' habitats:
* ''East Asian tailless leaf-nosed bat'': Huang, J. C. -C.; et al. (2019). [https://www.iucnredlist.org/species/5074/22030377 "''Coelops frithii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T5074A22030377. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T5074A22030377.en 10.2305/IUCN.UK.2019-3.RLTS.T5074A22030377.en].
* ''Malayan tailless leaf-nosed bat'': Heaney, L. (2008). [https://www.iucnredlist.org/species/5076/11112095 "''Coelops robinsoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2008''': e.T5076A11112095. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2008.RLTS.T5076A11112095.en 10.2305/IUCN.UK.2008.RLTS.T5076A11112095.en].
]
[''Doryrhina'' habitats:
* ''Greater roundleaf bat'': Mickleburgh, S.; et al. (2019). [https://www.iucnredlist.org/species/10117/22093985 "''Doryrhina camerunensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T10117A22093985. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-2.RLTS.T10117A22093985.en 10.2305/IUCN.UK.2019-2.RLTS.T10117A22093985.en].
* ''Cyclops roundleaf bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/10126/22095945 "''Doryrhina cyclops''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T10126A22095945. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T10126A22095945.en 10.2305/IUCN.UK.2017-2.RLTS.T10126A22095945.en].
]
[''Hipposideros'' habitats:
* ''Aba roundleaf bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/10109/22097582 "''Hipposideros abae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T10109A22097582. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T10109A22097582.en 10.2305/IUCN.UK.2017-2.RLTS.T10109A22097582.en].
* ''Aellen's roundleaf bat'': Cooper-Bohannon, R.; et al. (2020). [https://www.iucnredlist.org/species/10149/22101390 "''Hipposideros marisae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T10149A22101390. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T10149A22101390.en 10.2305/IUCN.UK.2020-2.RLTS.T10149A22101390.en].
* ''Andersen's leaf-nosed bat'': Srinivasulu, C.; et al. (2020). [https://www.iucnredlist.org/species/180991219/180991293 "''Hipposideros gentilis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T180991219A180991293. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T180991219A180991293.en 10.2305/IUCN.UK.2020-3.RLTS.T180991219A180991293.en].
* ''Arnhem leaf-nosed bat'': Milne, D. J. (2020). [https://www.iucnredlist.org/species/136739/22035711 "''Hipposideros inornatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T136739A22035711. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T136739A22035711.en 10.2305/IUCN.UK.2020-2.RLTS.T136739A22035711.en].
* ''Ashy roundleaf bat'': Douangboubpha , B.; et al. (2019). [https://www.iucnredlist.org/species/10119/22093106 "''Hipposideros cineraceus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T10119A22093106. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-2.RLTS.T10119A22093106.en 10.2305/IUCN.UK.2019-2.RLTS.T10119A22093106.en].
* ''Benito roundleaf bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/10112/22098184 "''Hipposideros beatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T10112A22098184. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T10112A22098184.en 10.2305/IUCN.UK.2017-2.RLTS.T10112A22098184.en].
* ''Biak roundleaf bat'': Armstrong, K. N.; et al. (2021). [https://www.iucnredlist.org/species/10107/22098360 "''Hipposideros papua''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T10107A22098360. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T10107A22098360.en 10.2305/IUCN.UK.2021-3.RLTS.T10107A22098360.en].
* ''Bicolored roundleaf bat'': Khan, F. A. A.; et al. (2020). [https://www.iucnredlist.org/species/80258800/22095301 "''Hipposideros bicolor''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T80258800A22095301. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T80258800A22095301.en 10.2305/IUCN.UK.2020-2.RLTS.T80258800A22095301.en].
* ''Big-eared roundleaf bat'': Hutson, A. M.; et al. (2016). [https://www.iucnredlist.org/species/10146/22100268 "''Hipposideros macrobullatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T10146A22100268. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T10146A22100268.en 10.2305/IUCN.UK.2016-2.RLTS.T10146A22100268.en].
* ''Boeadi's roundleaf bat'': Chiozza, F.; et al. (2016). [https://www.iucnredlist.org/species/136566/21991596 "''Hipposideros boeadii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136566A21991596. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T136566A21991596.en 10.2305/IUCN.UK.2016-2.RLTS.T136566A21991596.en].
* ''Borneo roundleaf bat'': Khan, F. A. A.; et al. (2020). [https://www.iucnredlist.org/species/10130/22091121 "''Hipposideros doriae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T10130A22091121. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T10130A22091121.en 10.2305/IUCN.UK.2020-2.RLTS.T10130A22091121.en].
* ''Cantor's roundleaf bat'': Srinivasulu, B.; et al. (2019). [https://www.iucnredlist.org/species/10136/22090092 "''Hipposideros galeritus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T10136A22090092. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T10136A22090092.en 10.2305/IUCN.UK.2019-3.RLTS.T10136A22090092.en].
* ''Cox's roundleaf bat'': MacArthur, E. (2016). [https://www.iucnredlist.org/species/10123/22096963 "''Hipposideros coxi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T10123A22096963. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T10123A22096963.en 10.2305/IUCN.UK.2016-2.RLTS.T10123A22096963.en].
* ''Crested roundleaf bat'': Kingston, T. (2016). [https://www.iucnredlist.org/species/10139/22092281 "''Hipposideros inexpectatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T10139A22092281. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T10139A22092281.en 10.2305/IUCN.UK.2016-2.RLTS.T10139A22092281.en].
* ''Dayak roundleaf bat'': Khan, F. A. A.; et al. (2020). [https://www.iucnredlist.org/species/10132/22090760 "''Hipposideros dyacorum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T10132A22090760. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T10132A22090760.en 10.2305/IUCN.UK.2020-2.RLTS.T10132A22090760.en].
* ''Diadem leaf-nosed bat'': Aguilar, J.; et al. (2021). [https://www.iucnredlist.org/species/10128/22095445 "''Hipposideros diadema''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T10128A22095445. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T10128A22095445.en 10.2305/IUCN.UK.2021-2.RLTS.T10128A22095445.en].
* ''Dusky leaf-nosed bat'': Armstrong, K. N. (2021). [https://www.iucnredlist.org/species/80457009/22097974 "''Hipposideros ater''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T80457009A22097974. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T80457009A22097974.en 10.2305/IUCN.UK.2021-3.RLTS.T80457009A22097974.en].
* ''Ethiopian large-eared roundleaf bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/10150/22101286 "''Hipposideros megalotis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T10150A22101286. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T10150A22101286.en 10.2305/IUCN.UK.2017-2.RLTS.T10150A22101286.en].
* ''Fawn leaf-nosed bat'': Armstrong, K. N. (2021). [https://www.iucnredlist.org/species/10118/22093732 "''Hipposideros cervinus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T10118A22093732. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T10118A22093732.en 10.2305/IUCN.UK.2021-3.RLTS.T10118A22093732.en].
* ''Fierce roundleaf bat'': Pennay, M.; et al. (2021). [https://www.iucnredlist.org/species/10129/22091011 "''Hipposideros dinops''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T10129A22091011. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T10129A22091011.en 10.2305/IUCN.UK.2021-3.RLTS.T10129A22091011.en].
* ''Fly River roundleaf bat'': Armstrong, K. N.; et al. (2021) [amended version of 2017 assessment]. [https://www.iucnredlist.org/species/10151/209537407 "''Hipposideros muscinus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T10151A209537407. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T10151A209537407.en 10.2305/IUCN.UK.2021-3.RLTS.T10151A209537407.en].
* ''Fulvus roundleaf bat'': Srinivasulu, B.; et al. (2019). [https://www.iucnredlist.org/species/10135/22089934 "''Hipposideros fulvus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T10135A22089934. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-2.RLTS.T10135A22089934.en 10.2305/IUCN.UK.2019-2.RLTS.T10135A22089934.en].
* ''Grand roundleaf bat'': Bates, P.; et al. (2016). [https://www.iucnredlist.org/species/136478/21986047 "''Hipposideros grandis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136478A21986047. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T136478A21986047.en 10.2305/IUCN.UK.2016-3.RLTS.T136478A21986047.en].
* ''Great roundleaf bat'': Bates, P. J. J.; et al. (2020). [https://www.iucnredlist.org/species/10110/22097743 "''Hipposideros armiger''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T10110A22097743. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T10110A22097743.en 10.2305/IUCN.UK.2020-2.RLTS.T10110A22097743.en].
* ''Griffin's leaf-nosed bat'': Thong, V. D.; et al. (2019). [https://www.iucnredlist.org/species/80222915/95642190 "''Hipposideros griffini''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T80222915A95642190. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T80222915A95642190.en 10.2305/IUCN.UK.2019-3.RLTS.T80222915A95642190.en].
* ''Ha Long leaf-nosed bat'': Thong, V. D.; et al. (2019). [https://www.iucnredlist.org/species/80224880/95642200 "''Hipposideros alongensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T80224880A95642200. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T80224880A95642200.en 10.2305/IUCN.UK.2019-3.RLTS.T80224880A95642200.en].
* ''Hill's roundleaf bat'': Armstrong, K. N.; et al. (2021) [amended version of 2017 assessment]. [https://www.iucnredlist.org/species/10133/209537105 "''Hipposideros edwardshilli''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T10133A209537105. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T10133A209537105.en 10.2305/IUCN.UK.2021-3.RLTS.T10133A209537105.en].
* ''House-dwelling leaf-nosed bat'': Douangboubpha , B. (2019). [https://www.iucnredlist.org/species/80222798/95642185 "''Hipposideros einnaythu''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T80222798A95642185. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-2.RLTS.T80222798A95642185.en 10.2305/IUCN.UK.2019-2.RLTS.T80222798A95642185.en].
* ''Indian roundleaf bat'': Srinivasulu, B.; et al. (2019). [https://www.iucnredlist.org/species/10142/22092089 "''Hipposideros lankadiva''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T10142A22092089. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-2.RLTS.T10142A22092089.en 10.2305/IUCN.UK.2019-2.RLTS.T10142A22092089.en].
* ''Intermediate roundleaf bat'': Srinivasulu, C.; et al. (2020). [https://www.iucnredlist.org/species/85646564/22091287 "''Hipposideros larvatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T85646564A22091287. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T85646564A22091287.en 10.2305/IUCN.UK.2020-3.RLTS.T85646564A22091287.en].
* ''Jones's roundleaf bat'': Cooper-Bohannon, R.; et al. (2020). [https://www.iucnredlist.org/species/10140/22092411 "''Hipposideros jonesi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T10140A22092411. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T10140A22092411.en 10.2305/IUCN.UK.2020-2.RLTS.T10140A22092411.en].
* ''Khajuria's leaf-nosed bat'': Mishra, R.; et al. (2016). [https://www.iucnredlist.org/species/10131/22090631 "''Hipposideros durgadasi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T10131A22090631. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T10131A22090631.en 10.2305/IUCN.UK.2016-2.RLTS.T10131A22090631.en].
* ''Kolar leaf-nosed bat'': Chakravarty, R.; et al. (2016). [https://www.iucnredlist.org/species/10138/22092730 "''Hipposideros hypophyllus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T10138A22092730. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T10138A22092730.en 10.2305/IUCN.UK.2016-2.RLTS.T10138A22092730.en].
* ''Lamotte's roundleaf bat'': Monadjem, A.; et al. (2020). [https://www.iucnredlist.org/species/10141/22091938 "''Hipposideros lamottei''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T10141A22091938. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T10141A22091938.en 10.2305/IUCN.UK.2020-2.RLTS.T10141A22091938.en].
* ''Laotian leaf-nosed bat'': Francis, C. M. (2019). [https://www.iucnredlist.org/species/136477/21985931 "''Hipposideros rotalis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136477A21985931. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-2.RLTS.T136477A21985931.en 10.2305/IUCN.UK.2019-2.RLTS.T136477A21985931.en].
* ''Large Asian roundleaf bat'': Csorba, G.; et al. (2019). [https://www.iucnredlist.org/species/10144/22091565 "''Hipposideros lekaguli''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T10144A22091565. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T10144A22091565.en 10.2305/IUCN.UK.2019-3.RLTS.T10144A22091565.en].
* ''Large Mindanao roundleaf bat'': Phelps, K.; et al. (2016). [https://www.iucnredlist.org/species/10121/22097259 "''Hipposideros coronatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T10121A22097259. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T10121A22097259.en 10.2305/IUCN.UK.2016-3.RLTS.T10121A22097259.en].
* ''Lesser great leaf-nosed bat'': Fukui, D.; et al. (2019). [https://www.iucnredlist.org/species/80224148/22099660 "''Hipposideros turpis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T80224148A22099660. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T80224148A22099660.en 10.2305/IUCN.UK.2019-3.RLTS.T80224148A22099660.en].
* ''Maduran leaf-nosed bat'': Santiago, K.; et al. (2021). [https://www.iucnredlist.org/species/10147/22100964 "''Hipposideros madurae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T10147A22100964. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T10147A22100964.en 10.2305/IUCN.UK.2021-2.RLTS.T10147A22100964.en].
* ''Maggie Taylor's roundleaf bat'': Armstrong, K. N.; et al. (2021). [https://www.iucnredlist.org/species/10148/22100717 "''Hipposideros maggietaylorae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T10148A22100717. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T10148A22100717.en 10.2305/IUCN.UK.2021-3.RLTS.T10148A22100717.en].
* ''Maghreb Leaf-nosed Bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/85646524/85646528 "''Hipposideros tephrus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T85646524A85646528. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T85646524A85646528.en 10.2305/IUCN.UK.2017-2.RLTS.T85646524A85646528.en].
* ''Makira roundleaf bat'': Pennay, M.; et al. (2020). [https://www.iucnredlist.org/species/10127/22095744 "''Hipposideros demissus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T10127A22095744. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T10127A22095744.en 10.2305/IUCN.UK.2020-2.RLTS.T10127A22095744.en].
* ''Malayan roundleaf bat'': Senawi, J.; et al. (2016). [https://www.iucnredlist.org/species/10152/22101545 "''Hipposideros nequam''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T10152A22101545. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T10152A22101545.en 10.2305/IUCN.UK.2016-2.RLTS.T10152A22101545.en].
* ''Nicobar leaf-nosed bat'': Srinivasulu, B.; et al. (2020). [https://www.iucnredlist.org/species/80458824/95642215 "''Hipposideros nicobarulae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T80458824A95642215. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T80458824A95642215.en 10.2305/IUCN.UK.2020-3.RLTS.T80458824A95642215.en].
* ''Noack's roundleaf bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/10157/22102440 "''Hipposideros ruber''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T10157A22102440. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T10157A22102440.en 10.2305/IUCN.UK.2017-2.RLTS.T10157A22102440.en].
* ''Northern leaf-nosed bat'': Armstrong, K. N.; et al. (2021). [https://www.iucnredlist.org/species/10163/22099463 "''Hipposideros stenotis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T10163A22099463. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T10163A22099463.en 10.2305/IUCN.UK.2021-1.RLTS.T10163A22099463.en].
* ''Orbiculus leaf-nosed bat'': Francis, C; et al. (2016). [https://www.iucnredlist.org/species/136192/22008477 "''Hipposideros orbiculus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136192A22008477. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T136192A22008477.en 10.2305/IUCN.UK.2016-2.RLTS.T136192A22008477.en].
* ''Peleng leaf-nosed bat'': Wiantoro, S.; et al. (2021). [https://www.iucnredlist.org/species/136600/21996457 "''Hipposideros pelingensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T136600A21996457. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T136600A21996457.en 10.2305/IUCN.UK.2021-2.RLTS.T136600A21996457.en].
* ''Pendlebury's roundleaf bat'': Soisook, P. (2019). [https://www.iucnredlist.org/species/80224655/95642195 "''Hipposideros pendlebury''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T80224655A95642195. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T80224655A95642195.en 10.2305/IUCN.UK.2019-3.RLTS.T80224655A95642195.en].
* ''Philippine forest roundleaf bat'': Alviola, P. A.; et al. (2019). [https://www.iucnredlist.org/species/10153/22101961 "''Hipposideros obscurus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T10153A22101961. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T10153A22101961.en 10.2305/IUCN.UK.2019-3.RLTS.T10153A22101961.en].
* ''Philippine pygmy roundleaf bat'': Sedlock, J.; et al. (2019). [https://www.iucnredlist.org/species/10156/22102078 "''Hipposideros pygmaeus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T10156A22102078. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T10156A22102078.en 10.2305/IUCN.UK.2019-3.RLTS.T10156A22102078.en].
* ''Phou Khao Khouay leaf-nosed bat'': Douangboubpha , B. (2020) [amended version of 2019 assessment]. [https://www.iucnredlist.org/species/136819/166602959 "''Hipposideros khaokhouayensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T136819A166602959. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-1.RLTS.T136819A166602959.en 10.2305/IUCN.UK.2020-1.RLTS.T136819A166602959.en].
* ''Pomona roundleaf bat'': Srinivasulu, C.; et al. (2020). [https://www.iucnredlist.org/species/180990825/180990948 "''Hipposideros pomona''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T180990825A180990948. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T180990825A180990948.en 10.2305/IUCN.UK.2020-3.RLTS.T180990825A180990948.en].
* ''Pratt's roundleaf bat'': Jiang, T. L.; et al. (2019). [https://www.iucnredlist.org/species/10155/22102257 "''Hipposideros pratti''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T10155A22102257. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T10155A22102257.en 10.2305/IUCN.UK.2019-3.RLTS.T10155A22102257.en].
* ''Ridley's leaf-nosed bat'': Khan, F. A. A.; et al. (2020). [https://www.iucnredlist.org/species/10108/22098446 "''Hipposideros ridleyi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T10108A22098446. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T10108A22098446.en 10.2305/IUCN.UK.2020-2.RLTS.T10108A22098446.en].
* ''Schneider's leaf-nosed bat'': Srinivasulu, B.; et al. (2019). [https://www.iucnredlist.org/species/10162/22099260 "''Hipposideros speoris''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T10162A22099260. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-2.RLTS.T10162A22099260.en 10.2305/IUCN.UK.2019-2.RLTS.T10162A22099260.en].
* ''Semon's leaf-nosed bat'': Armstrong, K. N.; et al. (2021) [amended version of 2017 assessment]. [https://www.iucnredlist.org/species/10160/209537564 "''Hipposideros semoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T10160A209537564. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T10160A209537564.en 10.2305/IUCN.UK.2021-3.RLTS.T10160A209537564.en].
* ''Shield-faced roundleaf bat'': Senawi, J.; et al. (2019). [https://www.iucnredlist.org/species/10145/22100391 "''Hipposideros lylei''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T10145A22100391. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-2.RLTS.T10145A22100391.en 10.2305/IUCN.UK.2019-2.RLTS.T10145A22100391.en].
* ''Shield-nosed leaf-nosed bat'': Furey, N.; et al. (2019). [https://www.iucnredlist.org/species/136586/22000133 "''Hipposideros scutinares''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136586A22000133. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T136586A22000133.en 10.2305/IUCN.UK.2019-3.RLTS.T136586A22000133.en].
* ''Short-headed roundleaf bat'': Huang, J. C.-C.; et al. (2016). [https://www.iucnredlist.org/species/10114/22094935 "''Hipposideros breviceps''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T10114A22094935. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T10114A22094935.en 10.2305/IUCN.UK.2016-2.RLTS.T10114A22094935.en].
* ''Short-tailed roundleaf bat'': Tanshi, I. (2020). [https://www.iucnredlist.org/species/10125/22096364 "''Hipposideros curtus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T10125A22096364. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T10125A22096364.en 10.2305/IUCN.UK.2020-2.RLTS.T10125A22096364.en].
* ''Sooty roundleaf bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/10134/22090466 "''Hipposideros fuliginosus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T10134A22090466. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T10134A22090466.en 10.2305/IUCN.UK.2017-2.RLTS.T10134A22090466.en].
* ''Sorensen's leaf-nosed bat'': Waldien, D. L.; et al. (2021). [https://www.iucnredlist.org/species/10161/22099115 "''Hipposideros sorenseni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T10161A22099115. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T10161A22099115.en 10.2305/IUCN.UK.2021-2.RLTS.T10161A22099115.en].
* ''Spurred roundleaf bat'': Armstrong, K. N.; et al. (2021). [https://www.iucnredlist.org/species/10116/22094185 "''Hipposideros calcaratus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T10116A22094185. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T10116A22094185.en 10.2305/IUCN.UK.2021-2.RLTS.T10116A22094185.en].
* ''Sumba roundleaf bat'': Santiago, K.; et al. (2021). [https://www.iucnredlist.org/species/10164/22099540 "''Hipposideros sumbae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T10164A22099540. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T10164A22099540.en 10.2305/IUCN.UK.2021-3.RLTS.T10164A22099540.en].
* ''Sundevall's roundleaf bat'': Richards, L. R.; et al. (2020). [https://www.iucnredlist.org/species/80459007/22094271 "''Hipposideros caffer''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T80459007A22094271. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T80459007A22094271.en 10.2305/IUCN.UK.2020-2.RLTS.T80459007A22094271.en].
* ''Telefomin roundleaf bat'': Armstrong, K. N.; et al. (2021) [amended version of 2017 assessment]. [https://www.iucnredlist.org/species/10122/209536979 "''Hipposideros corynophyllus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T10122A209536979. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T10122A209536979.en 10.2305/IUCN.UK.2021-3.RLTS.T10122A209536979.en].
* ''Thailand roundleaf bat'': Douangboubpha , B.; et al. (2016). [https://www.iucnredlist.org/species/10137/22092544 "''Hipposideros halophyllus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T10137A22092544. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T10137A22092544.en 10.2305/IUCN.UK.2016-2.RLTS.T10137A22092544.en].
* ''Timor roundleaf bat'': Hutson, A. M.; et al. (2016). [https://www.iucnredlist.org/species/10124/22096519 "''Hipposideros crumeniferus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T10124A22096519. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T10124A22096519.en 10.2305/IUCN.UK.2016-2.RLTS.T10124A22096519.en].
* ''Wollaston's roundleaf bat'': Armstrong, K. N.; et al. (2021) [amended version of 2017 assessment]. [https://www.iucnredlist.org/species/10166/209537699 "''Hipposideros wollastoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T10166A209537699. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T10166A209537699.en 10.2305/IUCN.UK.2021-3.RLTS.T10166A209537699.en].
]
[''Macronycteris'' habitats:
* ''Commerson's roundleaf bat'': Monadjem, A.; et al. (2019). [https://www.iucnredlist.org/species/10120/22092860 "''Hipposideros commersoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T10120A22092860. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T10120A22092860.en 10.2305/IUCN.UK.2019-3.RLTS.T10120A22092860.en].
* ''Giant roundleaf bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/44687/22075133 "''Hipposideros gigas''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T44687A22075133. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T44687A22075133.en 10.2305/IUCN.UK.2017-2.RLTS.T44687A22075133.en].
* ''São Tomé leaf-nosed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/44689/22074748 "''Hipposideros thomensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T44689A22074748. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T44689A22074748.en 10.2305/IUCN.UK.2017-2.RLTS.T44689A22074748.en].
* ''Striped leaf-nosed bat'': Mickleburgh, S.; et al. (2020). [https://www.iucnredlist.org/species/135485/22050985 "''Macronycteris vittatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T135485A22050985. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T135485A22050985.en 10.2305/IUCN.UK.2020-2.RLTS.T135485A22050985.en].
]
[[[#CITEREF_ALLMAM|Chernasky; Motis; Burgin]], p. 466]
[Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/3859/22136371 "''Cardioderma cor''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T3859A22136371. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T3859A22136371.en 10.2305/IUCN.UK.2017-2.RLTS.T3859A22136371.en].]
[Soisook, P. (2017). [https://www.iucnredlist.org/species/80263386/95642210 "''Eudiscoderma thongareeae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T80263386A95642210. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T80263386A95642210.en 10.2305/IUCN.UK.2017-2.RLTS.T80263386A95642210.en].]
[Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/11378/22102877 "''Lavia frons''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T11378A22102877. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T11378A22102877.en 10.2305/IUCN.UK.2017-2.RLTS.T11378A22102877.en].]
[Srinivasulu, C.; et al. (2020). [https://www.iucnredlist.org/species/12938/22021835 "''Megaderma lyra''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T12938A22021835. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T12938A22021835.en 10.2305/IUCN.UK.2020-2.RLTS.T12938A22021835.en].]
[Armstrong, K. N.; et al. (2021) [amended version of 2019 assessment]. [https://www.iucnredlist.org/species/12590/209530568 "''Macroderma gigas''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T12590A209530568. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T12590A209530568.en 10.2305/IUCN.UK.2021-3.RLTS.T12590A209530568.en].]
[Srinivasulu, B.; et al. (2019). [https://www.iucnredlist.org/species/12939/22022345 "''Megaderma spasma''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T12939A22022345. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-2.RLTS.T12939A22022345.en 10.2305/IUCN.UK.2019-2.RLTS.T12939A22022345.en].]
[[[#CITEREF_ALLMAM|Chernasky; Motis; Burgin]], p. 528]
[''Cistugo'' habitats:
* ''Angolan hairy bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/44788/22069073 "''Cistugo seabrae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T44788A22069073. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T44788A22069073.en 10.2305/IUCN.UK.2017-2.RLTS.T44788A22069073.en].
* ''Lesueur's hairy bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/44787/22069233 "''Cistugo lesueuri''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T44787A22069233. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T44787A22069233.en 10.2305/IUCN.UK.2017-2.RLTS.T44787A22069233.en].
]
[[[#CITEREF_ALLMAM|Chernasky; Motis; Burgin]], pp. 527–528]
[''Miniopterus'' habitats:
* ''Aellen's long-fingered bat'': Goodman, S. (2017). [https://www.iucnredlist.org/species/81629770/95642245 "''Miniopterus aelleni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T81629770A95642245. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T81629770A95642245.en 10.2305/IUCN.UK.2017-2.RLTS.T81629770A95642245.en].
* ''African long-fingered bat'': Waldien, D. L.; et al. (2020). [https://www.iucnredlist.org/species/44859/22073089 "''Miniopterus africanus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T44859A22073089. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T44859A22073089.en 10.2305/IUCN.UK.2020-2.RLTS.T44859A22073089.en].
* ''Common bent-wing bat'': Cistrone, L.; et al. (2023). [https://www.iucnredlist.org/species/230918147/230918550 "''Miniopterus schreibersii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2023''': e.T230918147A230918550. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2023-1.RLTS.T230918147A230918550.en 10.2305/IUCN.UK.2023-1.RLTS.T230918147A230918550.en].
* ''Eger's long-fingered bat'': Goodman, S. (2017). [https://www.iucnredlist.org/species/81633146/95642260 "''Miniopterus egeri''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T81633146A95642260. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T81633146A95642260.en 10.2305/IUCN.UK.2017-2.RLTS.T81633146A95642260.en].
* ''Glen's long-fingered bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/81633094/22046191 "''Miniopterus gleni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T81633094A22046191. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T81633094A22046191.en 10.2305/IUCN.UK.2017-2.RLTS.T81633094A22046191.en].
* ''Great bent-winged bat'': Armstrong, K. N.; et al. (2021) [amended version of 2019 assessment]. [https://www.iucnredlist.org/species/13571/209530159 "''Miniopterus tristis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T13571A209530159. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T13571A209530159.en 10.2305/IUCN.UK.2021-3.RLTS.T13571A209530159.en].
* ''Greater long-fingered bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/13565/22104819 "''Miniopterus inflatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T13565A22104819. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T13565A22104819.en 10.2305/IUCN.UK.2017-2.RLTS.T13565A22104819.en].
* ''Griffith's long-fingered bat'': Goodman, S. (2017). [https://www.iucnredlist.org/species/81633105/95642250 "''Miniopterus griffithsi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T81633105A95642250. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T81633105A95642250.en 10.2305/IUCN.UK.2017-2.RLTS.T81633105A95642250.en].
* ''Griveaud's long-fingered bat'': Juste, J. (2019). [https://www.iucnredlist.org/species/136752/22035638 "''Miniopterus griveaudi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136752A22035638. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-2.RLTS.T136752A22035638.en 10.2305/IUCN.UK.2019-2.RLTS.T136752A22035638.en].
* ''Intermediate long-fingered bat'': Armstrong, K. N.; et al. (2021) [amended version of 2019 assessment]. [https://www.iucnredlist.org/species/13567/209529904 "''Miniopterus medius''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T13567A209529904. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T13567A209529904.en 10.2305/IUCN.UK.2021-3.RLTS.T13567A209529904.en].
* ''Least long-fingered bat'': Jacobs, D.; et al. (2019). [https://www.iucnredlist.org/species/13568/22105217 "''Miniopterus minor''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T13568A22105217. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-2.RLTS.T13568A22105217.en 10.2305/IUCN.UK.2019-2.RLTS.T13568A22105217.en].
* ''Lesser long-fingered bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/13563/22104581 "''Miniopterus fraterculus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T13563A22104581. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T13563A22104581.en 10.2305/IUCN.UK.2017-2.RLTS.T13563A22104581.en].
* ''Little bent-wing bat'': Armstrong, K. N.; et al. (2021) [amended version of 2019 assessment]. [https://www.iucnredlist.org/species/13562/209528942 "''Miniopterus australis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T13562A209528942. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T13562A209528942.en 10.2305/IUCN.UK.2021-3.RLTS.T13562A209528942.en].
* ''Loyalty bent-winged bat'': Waldien, D. L.; et al. (2020). [https://www.iucnredlist.org/species/13570/22103451 "''Miniopterus robustior''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T13570A22103451. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T13570A22103451.en 10.2305/IUCN.UK.2020-3.RLTS.T13570A22103451.en].
* ''Madagascar long-fingered bat'': Goodman, S. (2017). [https://www.iucnredlist.org/species/81629758/95642235 "''Miniopterus brachytragos''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T81629758A95642235. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T81629758A95642235.en 10.2305/IUCN.UK.2017-2.RLTS.T81629758A95642235.en].
* ''Maghrebian bent-wing bat'': Benda, P.; et al. (2017). [https://www.iucnredlist.org/species/81633156/95642265 "''Miniopterus maghrebensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T81633156A95642265. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-3.RLTS.T81633156A95642265.en 10.2305/IUCN.UK.2017-3.RLTS.T81633156A95642265.en].
* ''Mahafaly long-fingered bat'': Goodman, S. (2017). [https://www.iucnredlist.org/species/81629764/95642240 "''Miniopterus mahafaliensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T81629764A95642240. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T81629764A95642240.en 10.2305/IUCN.UK.2017-2.RLTS.T81629764A95642240.en].
* ''Major's long-fingered bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/40039/22061249 "''Miniopterus majori''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T40039A22061249. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T40039A22061249.en 10.2305/IUCN.UK.2017-2.RLTS.T40039A22061249.en].
* ''Manavi long-fingered bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/81629742/22061538 "''Miniopterus manavi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T81629742A22061538. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T81629742A22061538.en 10.2305/IUCN.UK.2017-2.RLTS.T81629742A22061538.en].
* ''Montagne d'Ambre long-fingered bat'': Goodman, S. (2017). [https://www.iucnredlist.org/species/81633128/95642255 "''Miniopterus ambohitrensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T81633128A95642255. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T81633128A95642255.en 10.2305/IUCN.UK.2017-2.RLTS.T81633128A95642255.en].
* ''Natal long-fingered bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/44862/22073129 "''Miniopterus natalensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T44862A22073129. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T44862A22073129.en 10.2305/IUCN.UK.2017-2.RLTS.T44862A22073129.en].
* ''Newton's long-fingered bat'': Juste, J. (2019). [https://www.iucnredlist.org/species/136310/22019007 "''Miniopterus newtoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136310A22019007. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-2.RLTS.T136310A22019007.en 10.2305/IUCN.UK.2019-2.RLTS.T136310A22019007.en].
* ''Pale bent-wing bat'': Çoraman, E. (2021). [https://www.iucnredlist.org/species/81633088/89457387 "''Miniopterus pallidus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T81633088A89457387. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T81633088A89457387.en 10.2305/IUCN.UK.2021-2.RLTS.T81633088A89457387.en].
* ''Peterson's long-fingered bat'': Jenkins, R. K. B.; et al. (2019). [https://www.iucnredlist.org/species/81633135/22035230 "''Miniopterus petersoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T81633135A22035230. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T81633135A22035230.en 10.2305/IUCN.UK.2019-3.RLTS.T81633135A22035230.en].
* ''Philippine long-fingered bat'': Bouillard, N. (2021). [https://www.iucnredlist.org/species/136233/22001879 "''Miniopterus paululus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T136233A22001879. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T136233A22001879.en 10.2305/IUCN.UK.2021-2.RLTS.T136233A22001879.en].
* ''Shortridge's long-fingered bat'': Chiozza, F.; et al. (2016). [https://www.iucnredlist.org/species/136827/22044684 "''Miniopterus shortridgei''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136827A22044684. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T136827A22044684.en 10.2305/IUCN.UK.2016-2.RLTS.T136827A22044684.en].
* ''Small bent-winged bat'': Bumrungsri, S.; et al. (2021). [https://www.iucnredlist.org/species/13569/22103542 "''Miniopterus pusillus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T13569A22103542. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T13569A22103542.en 10.2305/IUCN.UK.2021-2.RLTS.T13569A22103542.en].
* ''Small melanesian long-fingered bat'': Armstrong, K. N.; et al. (2021) [amended version of 2019 assessment]. [https://www.iucnredlist.org/species/136579/209529376 "''Miniopterus macrocneme''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T136579A209529376. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T136579A209529376.en 10.2305/IUCN.UK.2021-3.RLTS.T136579A209529376.en].
* ''Sororcula long-fingered bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/136401/22015600 "''Miniopterus sororculus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T136401A22015600. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T136401A22015600.en 10.2305/IUCN.UK.2017-2.RLTS.T136401A22015600.en].
* ''Southeast Asian long-fingered bat'': Fukui, D.; et al. (2021) [amended version of 2020 assessment]. [https://www.iucnredlist.org/species/13564/209553784 "''Miniopterus fuscus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T13564A209553784. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T13564A209553784.en 10.2305/IUCN.UK.2021-3.RLTS.T13564A209553784.en].
* ''Western bent-winged bat'': Armstrong, K. N.; et al. (2021) [amended version of 2019 assessment]. [https://www.iucnredlist.org/species/13566/209529644 "''Miniopterus magnater''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T13566A209529644. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T13566A209529644.en 10.2305/IUCN.UK.2021-3.RLTS.T13566A209529644.en].
]
[[[#CITEREF_ALLMAM|Chernasky; Motis; Burgin]], pp. 515–525]
[''Austronomus'' habitats:
* ''White-striped free-tailed bat'': Pennay, M. (2020). [https://www.iucnredlist.org/species/21313/22121905 "''Austronomus australis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T21313A22121905. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T21313A22121905.en 10.2305/IUCN.UK.2020-3.RLTS.T21313A22121905.en].
* ''New Guinea free-tailed bat'': Armstrong, K. N. (2021). [https://www.iucnredlist.org/species/136201/22009294 "''Austronomus kuboriensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T136201A22009294. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T136201A22009294.en 10.2305/IUCN.UK.2021-3.RLTS.T136201A22009294.en].
]
[''Cheiromeles'' habitats:
* ''Hairless bat'': Senawi, J.; et al. (2019). [https://www.iucnredlist.org/species/4601/22035361 "''Cheiromeles torquatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T4601A22035361. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T4601A22035361.en 10.2305/IUCN.UK.2019-3.RLTS.T4601A22035361.en].
* ''Lesser naked bat'': Alviola, P. A.; et al. (2019). [https://www.iucnredlist.org/species/4600/22034921 "''Cheiromeles parvidens''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T4600A22034921. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T4600A22034921.en 10.2305/IUCN.UK.2019-3.RLTS.T4600A22034921.en].
]
[''Cynomops'' habitats:
* ''Cinnamon dog-faced bat'': Barquez, R.; et al. (2016). [https://www.iucnredlist.org/species/13637/22109417 "''Cynomops abrasus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T13637A22109417. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T13637A22109417.en 10.2305/IUCN.UK.2016-2.RLTS.T13637A22109417.en].
* ''Greenhall's dog-faced bat'': Solari, S. (2015). [https://www.iucnredlist.org/species/13639/22109178 "''Cynomops greenhalli''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T13639A22109178. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T13639A22109178.en 10.2305/IUCN.UK.2015-4.RLTS.T13639A22109178.en].
* ''Mexican dog-faced bat'': Rodriguez, B.; et al. (2015). [https://www.iucnredlist.org/species/136611/21987867 "''Cynomops mexicanus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T136611A21987867. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T136611A21987867.en 10.2305/IUCN.UK.2015-4.RLTS.T136611A21987867.en].
* ''Miller's dog-faced bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/87993512/87993515 "''Cynomops milleri''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T87993512A87993515. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T87993512A87993515.en 10.2305/IUCN.UK.2016-3.RLTS.T87993512A87993515.en].
* ''Para dog-faced bat'': Barquez, R.; et al. (2016). [https://www.iucnredlist.org/species/87993365/87993377 "''Cynomops paranus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T87993365A87993377. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T87993365A87993377.en 10.2305/IUCN.UK.2016-1.RLTS.T87993365A87993377.en].
* ''Southern dog-faced bat'': Barquez, R.; et al. (2015). [https://www.iucnredlist.org/species/13642/22108538 "''Cynomops planirostris''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T13642A22108538. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T13642A22108538.en 10.2305/IUCN.UK.2015-4.RLTS.T13642A22108538.en].
]
[''Eumops'' habitats:
* ''Big bonneted bat'': Barquez, R.; et al. (2015). [https://www.iucnredlist.org/species/8243/22026659 "''Eumops dabbenei''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T8243A22026659. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T8243A22026659.en 10.2305/IUCN.UK.2015-4.RLTS.T8243A22026659.en].
* ''Black bonneted bat'': Barquez, R.; et al. (2016) [errata version of 2015 assessment]. [https://www.iucnredlist.org/species/8241/97206888 "''Eumops auripendulus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T8241A97206888. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T8241A22026938.en 10.2305/IUCN.UK.2015-4.RLTS.T8241A22026938.en].
* ''Colombian bonneted bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/136809/22043483 "''Eumops trumbulli''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136809A22043483. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T136809A22043483.en 10.2305/IUCN.UK.2019-1.RLTS.T136809A22043483.en].
* ''Delta bonneted bat'': Solari, S. (2018). [https://www.iucnredlist.org/species/87993965/87993968 "''Eumops delticus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T87993965A87993968. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T87993965A87993968.en 10.2305/IUCN.UK.2018-2.RLTS.T87993965A87993968.en].
* ''Dwarf bonneted bat'': Barquez, R.; et al. (2016). [https://www.iucnredlist.org/species/87993837/22026755 "''Eumops bonariensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T87993837A22026755. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T87993837A22026755.en 10.2305/IUCN.UK.2016-3.RLTS.T87993837A22026755.en].
* ''Fierce bonneted bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/87994072/87994075 "''Eumops ferox''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T87994072A87994075. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-2.RLTS.T87994072A87994075.en 10.2305/IUCN.UK.2019-2.RLTS.T87994072A87994075.en].
* ''Florida bonneted bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/136433/21984011 "''Eumops floridanus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136433A21984011. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T136433A21984011.en 10.2305/IUCN.UK.2016-1.RLTS.T136433A21984011.en].
* ''Guianan bonneted bat'': Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/8246/22026206 "''Eumops maurus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T8246A22026206. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T8246A22026206.en 10.2305/IUCN.UK.2016-2.RLTS.T8246A22026206.en].
* ''Northern dwarf bonneted bat'': Solari, S. (2017). [https://www.iucnredlist.org/species/87994060/87994063 "''Eumops nanus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T87994060A87994063. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T87994060A87994063.en 10.2305/IUCN.UK.2017-2.RLTS.T87994060A87994063.en].
* ''Patagonian bonneted bat'': Barquez, R.; et al. (2015). [https://www.iucnredlist.org/species/136825/22044762 "''Eumops patagonicus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T136825A22044762. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T136825A22044762.en 10.2305/IUCN.UK.2015-4.RLTS.T136825A22044762.en].
* ''Sanborn's bonneted bat'': Pineda, J.; et al. (2015). [https://www.iucnredlist.org/species/8245/22026314 "''Eumops hansae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T8245A22026314. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T8245A22026314.en 10.2305/IUCN.UK.2015-4.RLTS.T8245A22026314.en].
* ''Underwood's bonneted bat'': Miller, B.; et al. (2016). [https://www.iucnredlist.org/species/8248/22025754 "''Eumops underwoodi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T8248A22025754. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T8248A22025754.en 10.2305/IUCN.UK.2016-2.RLTS.T8248A22025754.en].
* ''Wagner's bonneted bat'': Barquez, R.; et al. (2016). [https://www.iucnredlist.org/species/87994083/22026467 "''Eumops glaucinus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T87994083A22026467. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T87994083A22026467.en 10.2305/IUCN.UK.2016-3.RLTS.T87994083A22026467.en].
* ''Western mastiff bat'': Barquez, R.; et al. (2016) [errata version of 2015 assessment]. [https://www.iucnredlist.org/species/8247/97207171 "''Eumops perotis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T8247A97207171. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T8247A22026043.en 10.2305/IUCN.UK.2015-4.RLTS.T8247A22026043.en].
* ''Wilson's bonneted bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/87993523/87993526 "''Eumops wilsoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T87993523A87993526. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T87993523A87993526.en 10.2305/IUCN.UK.2016-3.RLTS.T87993523A87993526.en].
]
[McConville, A.; et al. (2020). [https://www.iucnredlist.org/species/76776686/22084304 "''Micronomus norfolkensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T76776686A22084304. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T76776686A22084304.en 10.2305/IUCN.UK.2020-3.RLTS.T76776686A22084304.en].]
[''Molossops'' habitats:
* ''Dwarf dog-faced bat'': Barquez, R.; et al. (2015). [https://www.iucnredlist.org/species/13643/22108409 "''Molossops temminckii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T13643A22108409. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T13643A22108409.en 10.2305/IUCN.UK.2015-4.RLTS.T13643A22108409.en].
* ''Equatorial dog-faced bat'': Tirira, D. (2016). [https://www.iucnredlist.org/species/13638/22109325 "''Molossops aequatorianus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T13638A22109325. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T13638A22109325.en 10.2305/IUCN.UK.2016-1.RLTS.T13638A22109325.en].
* ''Mato Grosso dog-faced bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/13640/22109057 "''Molossops mattogrossensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T13640A22109057. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T13640A22109057.en 10.2305/IUCN.UK.2019-1.RLTS.T13640A22109057.en].
* ''Rufous dog-faced bat'': Barquez, R.; et al. (2016). [https://www.iucnredlist.org/species/13641/22108928 "''Molossops neglectus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T13641A22108928. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T13641A22108928.en 10.2305/IUCN.UK.2016-2.RLTS.T13641A22108928.en].
]
[''Molossus'' habitats:
* ''Alvarez's mastiff bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/88087329/88087332 "''Molossus alvarezi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T88087329A88087332. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T88087329A88087332.en 10.2305/IUCN.UK.2016-3.RLTS.T88087329A88087332.en].
* ''Aztec mastiff bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/13645/22107522 "''Molossus aztecus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T13645A22107522. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T13645A22107522.en 10.2305/IUCN.UK.2019-1.RLTS.T13645A22107522.en].
* ''Black mastiff bat'': Barquez, R.; et al. (2015). [https://www.iucnredlist.org/species/13644/22107969 "''Molossus rufus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T13644A22107969. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T13644A22107969.en 10.2305/IUCN.UK.2015-4.RLTS.T13644A22107969.en].
* ''Bonda mastiff bat'': Solari, S. (2017). [https://www.iucnredlist.org/species/88087507/88087516 "''Molossus bondae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T88087507A88087516. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T88087507A88087516.en 10.2305/IUCN.UK.2017-2.RLTS.T88087507A88087516.en].
* ''Coiban mastiff bat'': Sampaio, E.; et al. (2017). [https://www.iucnredlist.org/species/102208365/22106904 "''Molossus coibensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T102208365A22106904. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T102208365A22106904.en 10.2305/IUCN.UK.2017-2.RLTS.T102208365A22106904.en].
* ''Miller's mastiff bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/13649/22106312 "''Molossus pretiosus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T13649A22106312. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T13649A22106312.en 10.2305/IUCN.UK.2019-1.RLTS.T13649A22106312.en].
* ''Sinaloan mastiff bat'': Miller, B.; et al. (2016). [https://www.iucnredlist.org/species/13650/22106433 "''Molossus sinaloae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T13650A22106433. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T13650A22106433.en 10.2305/IUCN.UK.2016-2.RLTS.T13650A22106433.en].
* ''Thomas's mastiff bat'': Barquez, R.; et al. (2016). [https://www.iucnredlist.org/species/88087340/22107231 "''Molossus currentium''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T88087340A22107231. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T88087340A22107231.en 10.2305/IUCN.UK.2016-3.RLTS.T88087340A22107231.en].
* ''Velvety free-tailed bat'': Barquez, R.; et al. (2015). [https://www.iucnredlist.org/species/13648/22106602 "''Molossus molossus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T13648A22106602. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T13648A22106602.en 10.2305/IUCN.UK.2015-4.RLTS.T13648A22106602.en].
]
[''Mops'' habitats:
* ''Angolan free-tailed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/13838/22075340 "''Mops condylurus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T13838A22075340. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T13838A22075340.en 10.2305/IUCN.UK.2017-2.RLTS.T13838A22075340.en].
* ''Ansorge's free-tailed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/4306/22020564 "''Chaerephon ansorgei''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T4306A22020564. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T4306A22020564.en 10.2305/IUCN.UK.2017-2.RLTS.T4306A22020564.en].
* ''Black and red free-tailed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/136393/22014976 "''Chaerephon jobimena''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T136393A22014976. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T136393A22014976.en 10.2305/IUCN.UK.2017-2.RLTS.T136393A22014976.en].
* ''Chapin's free-tailed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/4310/22019424 "''Chaerephon chapini''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T4310A22019424. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T4310A22019424.en 10.2305/IUCN.UK.2017-2.RLTS.T4310A22019424.en].
* ''Duke of Abruzzi's free-tailed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/4305/22020676 "''Chaerephon aloysiisabaudiae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T4305A22020676. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T4305A22020676.en 10.2305/IUCN.UK.2017-2.RLTS.T4305A22020676.en].
* ''Dwarf free-tailed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/13843/22079835 "''Mops nanulus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T13843A22079835. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T13843A22079835.en 10.2305/IUCN.UK.2017-2.RLTS.T13843A22079835.en].
* ''Fijian mastiff bat'': Waldien, D. L.; et al. (2021) [errata version of 2019 assessment]. [https://www.iucnredlist.org/species/4309/209550994 "''Chaerephon bregullae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T4309A209550994. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T4309A209550994.en 10.2305/IUCN.UK.2019-3.RLTS.T4309A209550994.en].
* ''Gallagher's free-tailed bat'': Mickleburgh, S.; et al. (2019). [https://www.iucnredlist.org/species/4311/22019365 "''Chaerephon gallagheri''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T4311A22019365. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-2.RLTS.T4311A22019365.en 10.2305/IUCN.UK.2019-2.RLTS.T4311A22019365.en].
* ''Gland-tailed free-tailed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/4307/22020379 "''Chaerephon bemmeleni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T4307A22020379. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T4307A22020379.en 10.2305/IUCN.UK.2017-2.RLTS.T4307A22020379.en].
* ''Grandidier's free-tailed bat'': Ramasindrazana, B. (2021). [https://www.iucnredlist.org/species/40038/22061204 "''Mops leucogaster''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T40038A22061204. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T40038A22061204.en 10.2305/IUCN.UK.2021-1.RLTS.T40038A22061204.en].
* ''Lappet-eared free-tailed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/4314/22018874 "''Chaerephon major''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T4314A22018874. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T4314A22018874.en 10.2305/IUCN.UK.2017-2.RLTS.T4314A22018874.en].
* ''Little free-tailed bat'': Mickleburgh, S.; et al. (2019). [https://www.iucnredlist.org/species/67362271/22018113 "''Chaerephon pumilus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T67362271A22018113. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T67362271A22018113.en 10.2305/IUCN.UK.2019-3.RLTS.T67362271A22018113.en].
* ''Madagascar free-tailed bat'': Goodman, S. (2017). [https://www.iucnredlist.org/species/67360705/67360707 "''Chaerephon atsinanana''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T67360705A67360707. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T67360705A67360707.en 10.2305/IUCN.UK.2017-2.RLTS.T67360705A67360707.en].
* ''Malagasy white-bellied free-tailed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/40024/22061983 "''Mops leucostigma''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T40024A22061983. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T40024A22061983.en 10.2305/IUCN.UK.2017-2.RLTS.T40024A22061983.en].
* ''Malayan free-tailed bat'': Senawi, J.; et al. (2020). [https://www.iucnredlist.org/species/13842/22079559 "''Mops mops''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T13842A22079559. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T13842A22079559.en 10.2305/IUCN.UK.2020-2.RLTS.T13842A22079559.en].
* ''Medje free-tailed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/13839/22075809 "''Mops congicus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T13839A22075809. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T13839A22075809.en 10.2305/IUCN.UK.2017-2.RLTS.T13839A22075809.en].
* ''Midas free-tailed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/13841/22079278 "''Mops midas''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T13841A22079278. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T13841A22079278.en 10.2305/IUCN.UK.2017-2.RLTS.T13841A22079278.en].
* ''Mongalla free-tailed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/13840/22075708 "''Mops demonstrator''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T13840A22075708. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T13840A22075708.en 10.2305/IUCN.UK.2017-2.RLTS.T13840A22075708.en].
* ''Niangara free-tailed bat'': Mickleburgh, S.; et al. (2019). [https://www.iucnredlist.org/species/13844/22080151 "''Mops niangarae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T13844A22080151. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-2.RLTS.T13844A22080151.en 10.2305/IUCN.UK.2019-2.RLTS.T13844A22080151.en].
* ''Nigerian free-tailed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/4315/22018693 "''Chaerephon nigeriae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T4315A22018693. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T4315A22018693.en 10.2305/IUCN.UK.2017-2.RLTS.T4315A22018693.en].
* ''Northern freetail bat'': Armstrong, K. N. (2021) [amended version of 2019 assessment]. [https://www.iucnredlist.org/species/4312/209520861 "''Chaerephon jobensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T4312A209520861. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T4312A209520861.en 10.2305/IUCN.UK.2021-3.RLTS.T4312A209520861.en].
* ''Northern free-tailed bat'': Senawi, J.; et al. (2020). [https://www.iucnredlist.org/species/4313/22019065 "''Chaerephon johorensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T4313A22019065. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T4313A22019065.en 10.2305/IUCN.UK.2020-2.RLTS.T4313A22019065.en].
* ''Peterson's free-tailed bat'': Bakwo Fils, E. M.; et al. (2021). [https://www.iucnredlist.org/species/13846/203829430 "''Mops petersoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T13846A203829430. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T13846A203829430.en 10.2305/IUCN.UK.2021-3.RLTS.T13846A203829430.en].
* ''Railer bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/13849/22077236 "''Mops thersites''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T13849A22077236. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T13849A22077236.en 10.2305/IUCN.UK.2017-2.RLTS.T13849A22077236.en].
* ''Russet free-tailed bat'': Mickleburgh, S.; et al. (2019). [https://www.iucnredlist.org/species/4319/22017886 "''Chaerephon russatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T4319A22017886. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T4319A22017886.en 10.2305/IUCN.UK.2019-3.RLTS.T4319A22017886.en].
* ''São Tomé free-tailed bat'': Monadjem, A.; et al. (2019). [https://www.iucnredlist.org/species/4321/21981234 "''Chaerephon tomensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T4321A21981234. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T4321A21981234.en 10.2305/IUCN.UK.2019-3.RLTS.T4321A21981234.en].
* ''Seychelles free-tailed bat'': Bielsa, M.; et al. (2020). [https://www.iucnredlist.org/species/4318/22017997 "''Mops pusillus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T4318A22017997. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T4318A22017997.en 10.2305/IUCN.UK.2020-3.RLTS.T4318A22017997.en].
* ''Sierra Leone free-tailed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/13837/22075549 "''Mops brachypterus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T13837A22075549. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T13837A22075549.en 10.2305/IUCN.UK.2017-2.RLTS.T13837A22075549.en].
* ''Solomons mastiff bat'': Pennay, M.; et al. (2020). [https://www.iucnredlist.org/species/4320/22017829 "''Chaerephon solomonis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T4320A22017829. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T4320A22017829.en 10.2305/IUCN.UK.2020-2.RLTS.T4320A22017829.en].
* ''Spotted free-tailed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/4308/22020251 "''Chaerephon bivittatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T4308A22020251. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T4308A22020251.en 10.2305/IUCN.UK.2017-2.RLTS.T4308A22020251.en].
* ''Spurrell's free-tailed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/13848/22078917 "''Mops spurrelli''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T13848A22078917. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T13848A22078917.en 10.2305/IUCN.UK.2017-2.RLTS.T13848A22078917.en].
* ''Sulawesi free-tailed bat'': Rosell-Ambal, R. G. B.; et al. (2016). [https://www.iucnredlist.org/species/13847/22078424 "''Mops sarasinorum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T13847A22078424. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T13847A22078424.en 10.2305/IUCN.UK.2016-2.RLTS.T13847A22078424.en].
* ''Trevor's free-tailed bat'': Mickleburgh, S.; et al. (2019). [https://www.iucnredlist.org/species/13850/22077590 "''Mops trevori''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T13850A22077590. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-2.RLTS.T13850A22077590.en 10.2305/IUCN.UK.2019-2.RLTS.T13850A22077590.en].
* ''White-bellied free-tailed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/13845/22078081 "''Mops niveiventer''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T13845A22078081. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T13845A22078081.en 10.2305/IUCN.UK.2017-2.RLTS.T13845A22078081.en].
* ''Wrinkle-lipped free-tailed bat'': Csorba, G.; et al. (2020). [https://www.iucnredlist.org/species/4316/22018444 "''Chaerephon plicatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T4316A22018444. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T4316A22018444.en 10.2305/IUCN.UK.2020-2.RLTS.T4316A22018444.en].
]
[''Mormopterus'' habitats:
* ''Incan little mastiff bat'': Velazco, P. (2016). [https://www.iucnredlist.org/species/13887/22083688 "''Mormopterus phrudus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T13887A22083688. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T13887A22083688.en 10.2305/IUCN.UK.2016-2.RLTS.T13887A22083688.en].
* ''Kalinowski's mastiff bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/13883/22082910 "''Mormopterus kalinowskii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T13883A22082910. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T13883A22082910.en 10.2305/IUCN.UK.2019-1.RLTS.T13883A22082910.en].
* ''Little goblin bat'': Mancina, C. (2015). [https://www.iucnredlist.org/species/13884/22083165 "''Mormopterus minutus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T13884A22083165. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T13884A22083165.en 10.2305/IUCN.UK.2015-4.RLTS.T13884A22083165.en].
* ''Natal free-tailed bat'': Bergmans, W.; et al. (2017). [https://www.iucnredlist.org/species/71733227/22085232 "''Mormopterus acetabulosus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T71733227A22085232. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T71733227A22085232.en 10.2305/IUCN.UK.2017-2.RLTS.T71733227A22085232.en].
* ''Peters's wrinkle-lipped bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/13882/22083579 "''Mormopterus jugularis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T13882A22083579. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T13882A22083579.en 10.2305/IUCN.UK.2017-2.RLTS.T13882A22083579.en].
* ''Reunion little mastiff bat'': Goodman, S. (2017). [https://www.iucnredlist.org/species/71727235/71727484 "''Mormopterus francoismoutoui''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T71727235A71727484. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T71727235A71727484.en 10.2305/IUCN.UK.2017-2.RLTS.T71727235A71727484.en].
* ''Sumatran mastiff bat'': Hutson, A. M.; et al. (2016). [https://www.iucnredlist.org/species/13881/22083290 "''Mormopterus doriae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T13881A22083290. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T13881A22083290.en 10.2305/IUCN.UK.2016-2.RLTS.T13881A22083290.en].
]
[''Myopterus'' habitats:
* ''Bini free-tailed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/14103/22046293 "''Myopterus whitleyi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T14103A22046293. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T14103A22046293.en 10.2305/IUCN.UK.2017-2.RLTS.T14103A22046293.en].
* ''Daubenton's free-tailed bat'': Mickleburgh, S.; et al. (2019). [https://www.iucnredlist.org/species/14102/22046398 "''Myopterus daubentonii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T14102A22046398. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T14102A22046398.en 10.2305/IUCN.UK.2019-3.RLTS.T14102A22046398.en].
]
[''Nyctinomops'' habitats:
* ''Big free-tailed bat'': Barquez, R.; et al. (2016) [errata version of 2015 assessment]. [https://www.iucnredlist.org/species/14996/97207443 "''Nyctinomops macrotis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T14996A97207443. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T14996A22010988.en 10.2305/IUCN.UK.2015-4.RLTS.T14996A22010988.en].
* ''Broad-eared bat'': Barquez, R.; et al. (2015). [https://www.iucnredlist.org/species/14995/22011208 "''Nyctinomops laticaudatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T14995A22011208. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T14995A22011208.en 10.2305/IUCN.UK.2015-4.RLTS.T14995A22011208.en].
* ''Peale's free-tailed bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/14993/22010682 "''Nyctinomops aurispinosus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T14993A22010682. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T14993A22010682.en 10.2305/IUCN.UK.2019-1.RLTS.T14993A22010682.en].
* ''Pocketed free-tailed bat'': Arroyo-Cabrales, J.; et al. (2015). [https://www.iucnredlist.org/species/14994/22010542 "''Nyctinomops femorosaccus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T14994A22010542. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T14994A22010542.en 10.2305/IUCN.UK.2015-4.RLTS.T14994A22010542.en].
]
[''Otomops'' habitats:
* ''Big-eared mastiff bat'': Armstrong, K. N. (2021) [amended version of 2020 assessment]. [https://www.iucnredlist.org/species/15649/209523988 "''Otomops papuensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T15649A209523988. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T15649A209523988.en 10.2305/IUCN.UK.2021-3.RLTS.T15649A209523988.en].
* ''Harrison's large-eared giant mastiff bat'': Richards, L. R. (2017). [https://www.iucnredlist.org/species/95558305/95558309 "''Otomops harrisoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T95558305A95558309. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T95558305A95558309.en 10.2305/IUCN.UK.2017-2.RLTS.T95558305A95558309.en].
* ''Javan mastiff bat'': Hutson, A. M.; et al. (2016). [https://www.iucnredlist.org/species/15645/22112831 "''Otomops formosus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T15645A22112831. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T15645A22112831.en 10.2305/IUCN.UK.2016-2.RLTS.T15645A22112831.en].
* ''Johnstone's mastiff bat'': Hutson, A. M.; et al. (2016). [https://www.iucnredlist.org/species/15647/22112472 "''Otomops johnstonei''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T15647A22112472. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T15647A22112472.en 10.2305/IUCN.UK.2016-2.RLTS.T15647A22112472.en].
* ''Large-eared free-tailed bat'': Richards, L. R.; et al. (2018) [errata version of 2017 assessment]. [https://www.iucnredlist.org/species/15648/123791222 "''Otomops martiensseni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T15648A123791222. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-3.RLTS.T15648A22112617.en 10.2305/IUCN.UK.2017-3.RLTS.T15648A22112617.en].
* ''Madagascar free-tailed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/136564/21991318 "''Otomops madagascariensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T136564A21991318. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T136564A21991318.en 10.2305/IUCN.UK.2017-2.RLTS.T136564A21991318.en].
* ''Mantled mastiff bat'': Armstrong, K. N. (2021) [amended version of 2020 assessment]. [https://www.iucnredlist.org/species/15650/209524157 "''Otomops secundus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T15650A209524157. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T15650A209524157.en 10.2305/IUCN.UK.2021-3.RLTS.T15650A209524157.en].
* ''Wroughton's free-tailed bat'': Prabhukhanolkar, R. (2016). [https://www.iucnredlist.org/species/15646/22112971 "''Otomops wroughtoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T15646A22112971. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T15646A22112971.en 10.2305/IUCN.UK.2016-2.RLTS.T15646A22112971.en].
]
[''Ozimops'' habitats:
* ''Beccari's free-tailed bat'': Reardon, T. B. (2021) [errata version of 2017 assessment]. [https://www.iucnredlist.org/species/13880/209551736 "''Ozimops beccarii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T13880A209551736. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T13880A209551736.en 10.2305/IUCN.UK.2017-2.RLTS.T13880A209551736.en].
* ''Cape York free-tailed bat'': Reardon, T. B.; et al. (2021) [amended version of 2017 assessment]. [https://www.iucnredlist.org/species/71532803/209534023 "''Ozimops halli''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T71532803A209534023. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T71532803A209534023.en 10.2305/IUCN.UK.2021-3.RLTS.T71532803A209534023.en].
* ''Inland free-tailed bat'': Reardon, T. B.; et al. (2021) [amended version of 2020 assessment]. [https://www.iucnredlist.org/species/71534469/209554228 "''Ozimops petersi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T71534469A209554228. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T71534469A209554228.en 10.2305/IUCN.UK.2021-3.RLTS.T71534469A209554228.en].
* ''Loria's free-tailed bat'': Reardon, T. B.; et al. (2021) [amended version of 2019 assessment]. [https://www.iucnredlist.org/species/82345325/209533844 "''Ozimops loriae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T82345325A209533844. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T82345325A209533844.en 10.2305/IUCN.UK.2021-3.RLTS.T82345325A209533844.en].
* ''Lumsden's free-tailed bat'': Reardon, T. B.; et al. (2021) [amended version of 2020 assessment]. [https://www.iucnredlist.org/species/71531227/209535016 "''Ozimops lumsdenae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T71531227A209535016. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T71531227A209535016.en 10.2305/IUCN.UK.2021-3.RLTS.T71531227A209535016.en].
* ''Northern coastal free-tailed bat'': Reardon, T. B.; et al. (2021) [errata version of 2017 assessment]. [https://www.iucnredlist.org/species/71536513/209550699 "''Ozimops cobourgianus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T71536513A209550699. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T71536513A209550699.en 10.2305/IUCN.UK.2017-2.RLTS.T71536513A209550699.en].
* ''Ride's free-tailed bat'': Reardon, T. B.; et al. (2021) [errata version of 2017 assessment]. [https://www.iucnredlist.org/species/71533043/209550467 "''Ozimops ridei''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T71533043A209550467. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T71533043A209550467.en 10.2305/IUCN.UK.2017-2.RLTS.T71533043A209550467.en].
* ''South-western free-tailed bat'': Reardon, T. B.; et al. (2021) [amended version of 2020 assessment]. [https://www.iucnredlist.org/species/71532724/209534747 "''Ozimops kitcheneri''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T71532724A209534747. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T71532724A209534747.en 10.2305/IUCN.UK.2021-3.RLTS.T71532724A209534747.en].
* ''Southern free-tailed bat'': Lumsden, L. F.; et al. (2021). [https://www.iucnredlist.org/species/71732146/22084197 "''Ozimops planiceps''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T71732146A22084197. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T71732146A22084197.en 10.2305/IUCN.UK.2021-1.RLTS.T71732146A22084197.en].
]
[Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/44692/22074935 "''Platymops setiger''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T44692A22074935. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T44692A22074935.en 10.2305/IUCN.UK.2017-2.RLTS.T44692A22074935.en].]
[''Promops'' habitats:
* ''Big crested mastiff bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/88087651/22036112 "''Promops centralis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T88087651A22036112. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T88087651A22036112.en 10.2305/IUCN.UK.2019-1.RLTS.T88087651A22036112.en].
* ''Brown mastiff bat'': Barquez, R.; et al. (2015). [https://www.iucnredlist.org/species/18341/22035986 "''Promops nasutus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T18341A22035986. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T18341A22035986.en 10.2305/IUCN.UK.2015-4.RLTS.T18341A22035986.en].
* ''Davison's mastiff bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/88087551/88087580 "''Promops davisoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T88087551A88087580. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T88087551A88087580.en 10.2305/IUCN.UK.2016-3.RLTS.T88087551A88087580.en].
]
[Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/44693/22074483 "''Sauromys petrophilus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T44693A22074483. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T44693A22074483.en 10.2305/IUCN.UK.2017-2.RLTS.T44693A22074483.en].]
[Woinarski, J. C. Z.; et al. (2021) [amended version of 2020 assessment]. [https://www.iucnredlist.org/species/71529901/209553422 "''Mormopterus eleryi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T71529901A209553422. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T71529901A209553422.en 10.2305/IUCN.UK.2021-3.RLTS.T71529901A209553422.en].]
[''Tadarida'' habitats:
* ''African giant free-tailed bat'': Mickleburgh, S.; et al. (2019). [https://www.iucnredlist.org/species/21318/22121418 "''Tadarida ventralis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T21318A22121418. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T21318A22121418.en 10.2305/IUCN.UK.2019-3.RLTS.T21318A22121418.en].
* ''East Asian free-tailed bat'': Fukui, D.; et al. (2019). [https://www.iucnredlist.org/species/136716/22036641 "''Tadarida insignis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136716A22036641. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T136716A22036641.en 10.2305/IUCN.UK.2019-3.RLTS.T136716A22036641.en].
* ''Egyptian free-tailed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/21312/22115459 "''Tadarida aegyptiaca''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T21312A22115459. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T21312A22115459.en 10.2305/IUCN.UK.2017-2.RLTS.T21312A22115459.en].
* ''European free-tailed bat'': Benda, P.; et al. (2016). [https://www.iucnredlist.org/species/21311/22114995 "''Tadarida teniotis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T21311A22114995. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T21311A22114995.en 10.2305/IUCN.UK.2016-2.RLTS.T21311A22114995.en].
* ''Kenyan big-eared free-tailed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/21317/22121550 "''Tadarida lobata''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T21317A22121550. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T21317A22121550.en 10.2305/IUCN.UK.2017-2.RLTS.T21317A22121550.en].
* ''La Touche's free-tailed bat'': Thong, V. D.; et al. (2020). [https://www.iucnredlist.org/species/40036/22060323 "''Tadarida latouchei''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T40036A22060323. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T40036A22060323.en 10.2305/IUCN.UK.2020-2.RLTS.T40036A22060323.en].
* ''Madagascan large free-tailed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/21316/22122012 "''Tadarida fulminans''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T21316A22122012. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T21316A22122012.en 10.2305/IUCN.UK.2017-2.RLTS.T21316A22122012.en].
* ''Mexican free-tailed bat'': Barquez, R.; et al. (2015). [https://www.iucnredlist.org/species/21314/22121621 "''Tadarida brasiliensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T21314A22121621. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T21314A22121621.en 10.2305/IUCN.UK.2015-4.RLTS.T21314A22121621.en].
]
[Velazco, P. (2016). [https://www.iucnredlist.org/species/21982/21975053 "''Tomopeas ravus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T21982A21975053. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T21982A21975053.en 10.2305/IUCN.UK.2016-1.RLTS.T21982A21975053.en].]
[[[#CITEREF_ALLMAM|Chernasky; Motis; Burgin]], p. 491]
[Velazco, P.; et al. (2015). [https://www.iucnredlist.org/species/1154/22070889 "''Amorphochilus schnablii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T1154A22070889. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T1154A22070889.en 10.2305/IUCN.UK.2015-4.RLTS.T1154A22070889.en].]
[Miller, B.; et al. (2016). [https://www.iucnredlist.org/species/8771/21971535 "''Furipterus horrens''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T8771A21971535. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T8771A21971535.en 10.2305/IUCN.UK.2016-2.RLTS.T8771A21971535.en].]
[[[#CITEREF_ALLMAM|Chernasky; Motis; Burgin]], p. 492]
[''Mormoops'' habitats:
* ''Antillean ghost-faced bat'': Miller, B.; et al. (2016). [https://www.iucnredlist.org/species/13877/22085914 "''Mormoops blainvillei''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T13877A22085914. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T13877A22085914.en 10.2305/IUCN.UK.2016-2.RLTS.T13877A22085914.en].
* ''Ghost-faced bat'': Davalos, L.; et al. (2019). [https://www.iucnredlist.org/species/13878/22086060 "''Mormoops megalophylla''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T13878A22086060. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T13878A22086060.en 10.2305/IUCN.UK.2019-1.RLTS.T13878A22086060.en].
]
[''Pteronotus'' habitats:
* ''Big naked-backed bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/18706/22077065 "''Pteronotus gymnonotus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T18706A22077065. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T18706A22077065.en 10.2305/IUCN.UK.2019-1.RLTS.T18706A22077065.en].
* ''Davy's naked-backed bat'': Solari, S.; et al. (2019). [https://www.iucnredlist.org/species/18705/22077399 "''Pteronotus davyi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T18705A22077399. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T18705A22077399.en 10.2305/IUCN.UK.2019-1.RLTS.T18705A22077399.en].
* ''Macleay's mustached bat'': Mancina, C.; et al. (2019). [https://www.iucnredlist.org/species/18707/22077903 "''Pteronotus macleayii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T18707A22077903. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T18707A22077903.en 10.2305/IUCN.UK.2019-1.RLTS.T18707A22077903.en].
* ''Mesoamerican common mustached bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/88018392/88018395 "''Pteronotus mesoamericanus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T88018392A88018395. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T88018392A88018395.en 10.2305/IUCN.UK.2016-3.RLTS.T88018392A88018395.en].
* ''Paraguana moustached bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/136610/21987754 "''Pteronotus paraguanensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136610A21987754. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T136610A21987754.en 10.2305/IUCN.UK.2016-1.RLTS.T136610A21987754.en].
* ''Parnell's mustached bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/88017638/22077695 "''Pteronotus parnellii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T88017638A22077695. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T88017638A22077695.en 10.2305/IUCN.UK.2016-3.RLTS.T88017638A22077695.en].
* ''Sooty mustached bat'': Miller, B.; et al. (2016). [https://www.iucnredlist.org/species/18710/22076753 "''Pteronotus quadridens''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T18710A22076753. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T18710A22076753.en 10.2305/IUCN.UK.2016-2.RLTS.T18710A22076753.en].
* ''Wagner's common mustached bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/88018592/88018595 "''Pteronotus rubiginosus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T88018592A88018595. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T88018592A88018595.en 10.2305/IUCN.UK.2016-3.RLTS.T88018592A88018595.en].
* ''Wagner's mustached bat'': Davalos, L.; et al. (2017) [errata version of 2016 assessment]. [https://www.iucnredlist.org/species/18709/115145223 "''Pteronotus personatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T18709A115145223. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T18709A22076876.en 10.2305/IUCN.UK.2016-3.RLTS.T18709A22076876.en].
]
[[[#CITEREF_ALLMAM|Chernasky; Motis; Burgin]], p. 490]
[''Mystacina'' habitats:
* ''New Zealand greater short-tailed bat'': O'Donnell, C. (2021). [https://www.iucnredlist.org/species/14260/22070387 "''Mystacina robusta''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T14260A22070387. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T14260A22070387.en 10.2305/IUCN.UK.2021-1.RLTS.T14260A22070387.en].
* ''New Zealand lesser short-tailed bat'': O'Donnell, C. (2021). [https://www.iucnredlist.org/species/14261/22070543 "''Mystacina tuberculata''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T14261A22070543. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T14261A22070543.en 10.2305/IUCN.UK.2021-2.RLTS.T14261A22070543.en].
]
[[[#CITEREF_ALLMAM|Chernasky; Motis; Burgin]], p. 490]
[''Myzopoda'' habitats:
* ''Madagascar sucker-footed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/14288/22073303 "''Myzopoda aurita''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T14288A22073303. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T14288A22073303.en 10.2305/IUCN.UK.2017-2.RLTS.T14288A22073303.en].
* ''Western sucker-footed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/136465/21986182 "''Myzopoda schliemanni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T136465A21986182. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T136465A21986182.en 10.2305/IUCN.UK.2017-2.RLTS.T136465A21986182.en].
]
[[[#CITEREF_ALLMAM|Chernasky; Motis; Burgin]], p. 491]
[''Noctilio'' habitats:
* ''Lesser bulldog bat'': Barquez, R.; et al. (2015). [https://www.iucnredlist.org/species/14829/22019978 "''Noctilio albiventris''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T14829A22019978. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T14829A22019978.en 10.2305/IUCN.UK.2015-4.RLTS.T14829A22019978.en].
* ''Greater bulldog bat'': Barquez, R.; et al. (2015). [https://www.iucnredlist.org/species/14830/22019554 "''Noctilio leporinus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T14830A22019554. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T14830A22019554.en 10.2305/IUCN.UK.2015-4.RLTS.T14830A22019554.en].
]
[[[#CITEREF_ALLMAM|Chernasky; Motis; Burgin]], p. 514]
[''Chilonatalus'' habitats:
* ''Bahaman funnel-eared bat'': Solari, S. (2018). [https://www.iucnredlist.org/species/14361/22041195 "''Chilonatalus tumidifrons''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T14361A22041195. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T14361A22041195.en 10.2305/IUCN.UK.2018-2.RLTS.T14361A22041195.en].
* ''Cuban funnel-eared bat'': Solari, S. (2018). [https://www.iucnredlist.org/species/88088852/22040831 "''Chilonatalus micropus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T88088852A22040831. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T88088852A22040831.en 10.2305/IUCN.UK.2018-2.RLTS.T88088852A22040831.en].
* ''Cuban lesser funnel-eared bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/88088745/88088756 "''Chilonatalus macer''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T88088745A88088756. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T88088745A88088756.en 10.2305/IUCN.UK.2019-1.RLTS.T88088745A88088756.en].
]
[''Natalus'' habitats:
* ''Brazilian funnel-eared bat'': Tejedor, A.; et al. (2016). [https://www.iucnredlist.org/species/136448/21983924 "''Natalus espiritosantensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136448A21983924. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T136448A21983924.en 10.2305/IUCN.UK.2016-2.RLTS.T136448A21983924.en].
* ''Cuban greater funnel-eared bat'': Mancina, C. (2016). [https://www.iucnredlist.org/species/136777/22032828 "''Natalus primus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136777A22032828. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T136777A22032828.en 10.2305/IUCN.UK.2016-1.RLTS.T136777A22032828.en].
* ''Hispaniolan greater funnel-eared bat'': Miller, B.; et al. (2016). [https://www.iucnredlist.org/species/136548/21992984 "''Natalus major''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136548A21992984. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T136548A21992984.en 10.2305/IUCN.UK.2016-2.RLTS.T136548A21992984.en].
* ''Jamaican greater funnel-eared bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/136824/22043871 "''Natalus jamaicensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136824A22043871. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T136824A22043871.en 10.2305/IUCN.UK.2016-1.RLTS.T136824A22043871.en].
* ''Mexican funnel-eared bat'': Davalos, L.; et al. (2016). [https://www.iucnredlist.org/species/14360/22040956 "''Natalus stramineus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14360A22040956. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T14360A22040956.en 10.2305/IUCN.UK.2016-3.RLTS.T14360A22040956.en].
* ''Mexican greater funnel-eared bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/123984355/22011975 "''Natalus mexicanus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T123984355A22011975. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-2.RLTS.T123984355A22011975.en 10.2305/IUCN.UK.2019-2.RLTS.T123984355A22011975.en].
* ''Trinidadian funnel-eared bat'': Davalos, L.; et al. (2016). [https://www.iucnredlist.org/species/14362/22041401 "''Natalus tumidirostris''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14362A22041401. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T14362A22041401.en 10.2305/IUCN.UK.2016-3.RLTS.T14362A22041401.en].
]
[Davalos, L.; et al. (2016). [https://www.iucnredlist.org/species/14358/22040604 "''Nyctiellus lepidus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14358A22040604. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T14358A22040604.en 10.2305/IUCN.UK.2016-3.RLTS.T14358A22040604.en].]
[[[#CITEREF_ALLMAM|Chernasky; Motis; Burgin]], pp. 489–490]
[''Nycteris'' habitats:
* ''Andersen's slit-faced bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/14927/22017608 "''Nycteris aurita''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T14927A22017608. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T14927A22017608.en 10.2305/IUCN.UK.2017-2.RLTS.T14927A22017608.en].
* ''Bates's slit-faced bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/14926/22016999 "''Nycteris arge''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T14926A22016999. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T14926A22016999.en 10.2305/IUCN.UK.2017-2.RLTS.T14926A22016999.en].
* ''Dwarf slit-faced bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/14935/22013866 "''Nycteris nana''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T14935A22013866. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T14935A22013866.en 10.2305/IUCN.UK.2017-2.RLTS.T14935A22013866.en].
* ''Egyptian slit-faced bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/14936/22014183 "''Nycteris thebaica''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T14936A22014183. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T14936A22014183.en 10.2305/IUCN.UK.2017-2.RLTS.T14936A22014183.en].
* ''Gambian slit-faced bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/14928/22017299 "''Nycteris gambiensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T14928A22017299. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T14928A22017299.en 10.2305/IUCN.UK.2017-2.RLTS.T14928A22017299.en].
* ''Hairy slit-faced bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/14930/22012843 "''Nycteris hispida''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T14930A22012843. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T14930A22012843.en 10.2305/IUCN.UK.2017-2.RLTS.T14930A22012843.en].
* ''Intermediate slit-faced bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/14931/22013102 "''Nycteris intermedia''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T14931A22013102. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T14931A22013102.en 10.2305/IUCN.UK.2017-2.RLTS.T14931A22013102.en].
* ''Ja slit-faced bat'': Mickleburgh, S.; et al. (2019). [https://www.iucnredlist.org/species/14934/22013659 "''Nycteris major''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T14934A22013659. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T14934A22013659.en 10.2305/IUCN.UK.2019-3.RLTS.T14934A22013659.en].
* ''Javan slit-faced bat'': Waldien, D. L.; et al. (2021). [https://www.iucnredlist.org/species/14932/22013241 "''Nycteris javanica''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T14932A22013241. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T14932A22013241.en 10.2305/IUCN.UK.2021-2.RLTS.T14932A22013241.en].
* ''Large slit-faced bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/14929/22012638 "''Nycteris grandis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T14929A22012638. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T14929A22012638.en 10.2305/IUCN.UK.2017-2.RLTS.T14929A22012638.en].
* ''Large-eared slit-faced bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/14933/22013415 "''Nycteris macrotis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T14933A22013415. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T14933A22013415.en 10.2305/IUCN.UK.2017-2.RLTS.T14933A22013415.en].
* ''Malagasy slit-faced bat'': Hutson, A. M.; et al. (2019). [https://www.iucnredlist.org/species/40022/22062299 "''Nycteris madagascariensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T40022A22062299. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T40022A22062299.en 10.2305/IUCN.UK.2019-3.RLTS.T40022A22062299.en].
* ''Malayan slit-faced bat'': Jayaraj, V. K. (2020). [https://www.iucnredlist.org/species/14937/22014643 "''Nycteris tragata''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T14937A22014643. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T14937A22014643.en 10.2305/IUCN.UK.2020-2.RLTS.T14937A22014643.en].
* ''Parissi's slit-faced bat'': Mickleburgh, S.; et al. (2019). [https://www.iucnredlist.org/species/44695/22074582 "''Nycteris parisii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T44695A22074582. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T44695A22074582.en 10.2305/IUCN.UK.2019-3.RLTS.T44695A22074582.en].
* ''Vinson's slit-faced bat'': Mickleburgh, S.; et al. (2019). [https://www.iucnredlist.org/species/44696/22074669 "''Nycteris vinsoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T44696A22074669. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T44696A22074669.en 10.2305/IUCN.UK.2019-3.RLTS.T44696A22074669.en].
* ''Wood's slit-faced bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/14939/22014842 "''Nycteris woodi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T14939A22014842. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T14939A22014842.en 10.2305/IUCN.UK.2017-2.RLTS.T14939A22014842.en].
]
[[[#CITEREF_ALLMAM|Chernasky; Motis; Burgin]], pp. 494–513]
[''Carollia'' habitats:
* ''Benkeith's short-tailed bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/88110352/88110355 "''Carollia benkeithi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T88110352A88110355. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T88110352A88110355.en 10.2305/IUCN.UK.2019-1.RLTS.T88110352A88110355.en].
* ''Chestnut short-tailed bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/88110411/88110432 "''Carollia castanea''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T88110411A88110432. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T88110411A88110432.en 10.2305/IUCN.UK.2016-1.RLTS.T88110411A88110432.en].
* ''Gray short-tailed bat'': Miller, B.; et al. (2015). [https://www.iucnredlist.org/species/3906/22133926 "''Carollia subrufa''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T3906A22133926. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T3906A22133926.en 10.2305/IUCN.UK.2015-4.RLTS.T3906A22133926.en].
* ''Manu short-tailed bat'': Velazco, P.; et al. (2015). [https://www.iucnredlist.org/species/136782/22033116 "''Carollia manu''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T136782A22033116. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T136782A22033116.en 10.2305/IUCN.UK.2015-4.RLTS.T136782A22033116.en].
* ''Mono's short-tailed bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/88110257/88110260 "''Carollia monohernandezi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T88110257A88110260. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-2.RLTS.T88110257A88110260.en 10.2305/IUCN.UK.2019-2.RLTS.T88110257A88110260.en].
* ''Seba's short-tailed bat'': Barquez, R.; et al. (2015). [https://www.iucnredlist.org/species/3905/22133716 "''Carollia perspicillata''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T3905A22133716. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T3905A22133716.en 10.2305/IUCN.UK.2015-4.RLTS.T3905A22133716.en].
* ''Silky short-tailed bat'': Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/3903/22134642 "''Carollia brevicauda''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T3903A22134642. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T3903A22134642.en 10.2305/IUCN.UK.2016-2.RLTS.T3903A22134642.en].
* ''Sowell's short-tailed bat'': Miller, B.; et al. (2015). [https://www.iucnredlist.org/species/136268/22003903 "''Carollia sowelli''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T136268A22003903. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T136268A22003903.en 10.2305/IUCN.UK.2015-4.RLTS.T136268A22003903.en].
]
[Barquez, R.; et al. (2015). [https://www.iucnredlist.org/species/6510/21979045 "''Desmodus rotundus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T6510A21979045. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T6510A21979045.en 10.2305/IUCN.UK.2015-4.RLTS.T6510A21979045.en].]
[Barquez, R.; et al. (2015). [https://www.iucnredlist.org/species/6520/21982777 "''Diaemus youngi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T6520A21982777. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T6520A21982777.en 10.2305/IUCN.UK.2015-4.RLTS.T6520A21982777.en].]
[Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/6628/22040157 "''Diphylla ecaudata''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T6628A22040157. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T6628A22040157.en 10.2305/IUCN.UK.2016-2.RLTS.T6628A22040157.en].]
[''Anoura'' habitats:
* ''Broad-toothed tailless bat'': Mantilla, H.; et al. (2015). [https://www.iucnredlist.org/species/1568/22106814 "''Anoura latidens''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T1568A22106814. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T1568A22106814.en 10.2305/IUCN.UK.2015-4.RLTS.T1568A22106814.en].
* ''Cadena's tailless bat'': Solari, S. (2017). [https://www.iucnredlist.org/species/88109476/88109479 "''Anoura cadenai''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T88109476A88109479. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T88109476A88109479.en 10.2305/IUCN.UK.2017-2.RLTS.T88109476A88109479.en].
* ''Equatorial tailless bat'': Aguirre, L.; et al. (2019). [https://www.iucnredlist.org/species/88109381/88109461 "''Anoura aequatoris''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T88109381A88109461. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-2.RLTS.T88109381A88109461.en 10.2305/IUCN.UK.2019-2.RLTS.T88109381A88109461.en].
* ''Geoffroy's tailless bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/88109511/88109515 "''Anoura geoffroyi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T88109511A88109515. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T88109511A88109515.en 10.2305/IUCN.UK.2016-1.RLTS.T88109511A88109515.en].
* ''Handley's tailless bat'': Molinari, J.; et al. (2016). [https://www.iucnredlist.org/species/1566/22107379 "''Anoura cultrata''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T1566A22107379. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T1566A22107379.en 10.2305/IUCN.UK.2016-2.RLTS.T1566A22107379.en].
* ''Luis Manuel's tailless bat'': Solari, S. (2018). [https://www.iucnredlist.org/species/1569/22105320 "''Anoura luismanueli''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T1569A22105320. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T1569A22105320.en 10.2305/IUCN.UK.2018-2.RLTS.T1569A22105320.en].
* ''Tailed tailless bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/88108473/88185102 "''Anoura caudifer''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T88108473A88185102. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T88108473A88185102.en 10.2305/IUCN.UK.2016-1.RLTS.T88108473A88185102.en].
* ''Tschudi's tailless bat'': Tirira, D. G.; et al. (2019). [https://www.iucnredlist.org/species/88109497/88109500 "''Anoura peruana''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T88109497A88109500. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-2.RLTS.T88109497A88109500.en 10.2305/IUCN.UK.2019-2.RLTS.T88109497A88109500.en].
* ''Tube-lipped nectar bat'': Solari, S. (2018). [https://www.iucnredlist.org/species/136239/22001222 "''Anoura fistulata''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T136239A22001222. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T136239A22001222.en 10.2305/IUCN.UK.2018-2.RLTS.T136239A22001222.en].
]
[''Brachyphylla'' habitats:
* ''Antillean fruit-eating bat'': Rodriguez Duran, A.; et al. (2019). [https://www.iucnredlist.org/species/2982/22039359 "''Brachyphylla cavernarum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T2982A22039359. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T2982A22039359.en 10.2305/IUCN.UK.2019-1.RLTS.T2982A22039359.en].
* ''Cuban fruit-eating bat'': Davalos, L.; et al. (2019). [https://www.iucnredlist.org/species/2983/22039031 "''Brachyphylla nana''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T2983A22039031. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T2983A22039031.en 10.2305/IUCN.UK.2019-1.RLTS.T2983A22039031.en].
]
[''Choeroniscus'' habitats:
* ''Godman's long-tailed bat'': Tavares, V.; et al. (2015). [https://www.iucnredlist.org/species/4772/22041805 "''Choeroniscus godmani''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T4772A22041805. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T4772A22041805.en 10.2305/IUCN.UK.2015-4.RLTS.T4772A22041805.en].
* ''Greater long-tailed bat'': Tirira, D. (2015). [https://www.iucnredlist.org/species/4775/22042360 "''Choeroniscus periosus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T4775A22042360. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T4775A22042360.en 10.2305/IUCN.UK.2015-4.RLTS.T4775A22042360.en].
* ''Lesser long-tongued bat'': Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/4774/22042243 "''Choeroniscus minor''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T4774A22042243. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T4774A22042243.en 10.2305/IUCN.UK.2016-3.RLTS.T4774A22042243.en].
]
[Solari, S. (2018). [https://www.iucnredlist.org/species/4776/22042479 "''Choeronycteris mexicana''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T4776A22042479. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T4776A22042479.en 10.2305/IUCN.UK.2018-2.RLTS.T4776A22042479.en].]
[Solari, S. (2020) [amended version of 2019 assessment]. [https://www.iucnredlist.org/species/88120233/166613008 "''Dryadonycteris capixaba''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T88120233A166613008. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-1.RLTS.T88120233A166613008.en 10.2305/IUCN.UK.2020-1.RLTS.T88120233A166613008.en].]
[''Erophylla'' habitats:
* ''Brown flower bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/136247/22003184 "''Erophylla bombifrons''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136247A22003184. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T136247A22003184.en 10.2305/IUCN.UK.2019-1.RLTS.T136247A22003184.en].
* ''Buffy flower bat'': Mancina, C.; et al. (2019). [https://www.iucnredlist.org/species/8033/22106213 "''Erophylla sezekorni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T8033A22106213. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T8033A22106213.en 10.2305/IUCN.UK.2019-1.RLTS.T8033A22106213.en].
]
[''Glossophaga'' habitats:
* ''Commissaris's long-tongued bat'': Miller, B.; et al. (2016). [https://www.iucnredlist.org/species/9273/22108801 "''Glossophaga commissarisi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T9273A22108801. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T9273A22108801.en 10.2305/IUCN.UK.2016-2.RLTS.T9273A22108801.en].
* ''Gray long-tongued bat'': Miller, B.; et al. (2018) [errata version of 2016 assessment]. [https://www.iucnredlist.org/species/9274/128959800 "''Glossophaga leachii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T9274A128959800. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T9274A22108679.en 10.2305/IUCN.UK.2016-2.RLTS.T9274A22108679.en].
* ''Miller's long-tongued bat'': Solari, S. (2018). [https://www.iucnredlist.org/species/9275/22108249 "''Glossophaga longirostris''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T9275A22108249. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T9275A22108249.en 10.2305/IUCN.UK.2018-2.RLTS.T9275A22108249.en].
* ''Pallas's long-tongued bat'': Barquez, R.; et al. (2015). [https://www.iucnredlist.org/species/9277/22107768 "''Glossophaga soricina''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T9277A22107768. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T9277A22107768.en 10.2305/IUCN.UK.2015-4.RLTS.T9277A22107768.en].
* ''Western long-tongued bat'': Arroyo-Cabrales, J.; et al. (2015). [https://www.iucnredlist.org/species/9276/22108155 "''Glossophaga morenoi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T9276A22108155. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T9276A22108155.en 10.2305/IUCN.UK.2015-4.RLTS.T9276A22108155.en].
]
[Miller, B.; et al. (2016). [https://www.iucnredlist.org/species/10598/22036808 "''Hylonycteris underwoodi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T10598A22036808. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T10598A22036808.en 10.2305/IUCN.UK.2016-3.RLTS.T10598A22036808.en].]
[''Leptonycteris'' habitats:
* ''Greater long-nosed bat'': Medellín, R. (2016). [https://www.iucnredlist.org/species/11697/22126172 "''Leptonycteris nivalis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T11697A22126172. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T11697A22126172.en 10.2305/IUCN.UK.2016-1.RLTS.T11697A22126172.en].
* ''Lesser long-nosed bat'': Medellín, R. (2016). [https://www.iucnredlist.org/species/136659/21988965 "''Leptonycteris yerbabuenae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136659A21988965. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T136659A21988965.en 10.2305/IUCN.UK.2016-1.RLTS.T136659A21988965.en].
* ''Southern long-nosed bat'': Nassar, J. (2015). [https://www.iucnredlist.org/species/11699/22126917 "''Leptonycteris curasoae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T11699A22126917. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T11699A22126917.en 10.2305/IUCN.UK.2015-4.RLTS.T11699A22126917.en].
]
[''Lichonycteris'' habitats:
* ''Dark long-tongued bat'': Solari, S. (2018). [https://www.iucnredlist.org/species/88120245/22057648 "''Lichonycteris obscura''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T88120245A22057648. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T88120245A22057648.en 10.2305/IUCN.UK.2018-2.RLTS.T88120245A22057648.en].
* ''Pale brown long-nosed bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/88120307/88120310 "''Lichonycteris degener''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T88120307A88120310. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T88120307A88120310.en 10.2305/IUCN.UK.2019-1.RLTS.T88120307A88120310.en].
]
[''Monophyllus'' habitats:
* ''Insular single leaf bat'': Rodriguez Duran, A.; et al. (2018). [https://www.iucnredlist.org/species/13719/22112320 "''Monophyllus plethodon''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T13719A22112320. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T13719A22112320.en 10.2305/IUCN.UK.2018-2.RLTS.T13719A22112320.en].
* ''Leach's single leaf bat'': Solari, S. (2018). [https://www.iucnredlist.org/species/13720/22112192 "''Monophyllus redmani''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T13720A22112192. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T13720A22112192.en 10.2305/IUCN.UK.2018-2.RLTS.T13720A22112192.en].
]
[Arroyo-Cabrales, J.; et al. (2015). [https://www.iucnredlist.org/species/14003/22099002 "''Musonycteris harrisoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T14003A22099002. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T14003A22099002.en 10.2305/IUCN.UK.2015-4.RLTS.T14003A22099002.en].]
[''Phyllonycteris'' habitats:
* ''Cuban flower bat'': Mancina, C.; et al. (2019). [https://www.iucnredlist.org/species/17175/22133601 "''Phyllonycteris poeyi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T17175A22133601. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T17175A22133601.en 10.2305/IUCN.UK.2019-1.RLTS.T17175A22133601.en].
* ''Jamaican flower bat'': Koenig, S.; et al. (2015). [https://www.iucnredlist.org/species/17173/22133396 "''Phyllonycteris aphylla''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T17173A22133396. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T17173A22133396.en 10.2305/IUCN.UK.2015-4.RLTS.T17173A22133396.en].
]
[Pacheco, V.; et al. (2016). [https://www.iucnredlist.org/species/17487/21988884 "''Platalina genovensium''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T17487A21988884. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T17487A21988884.en 10.2305/IUCN.UK.2016-2.RLTS.T17487A21988884.en].]
[Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/20033/22027237 "''Scleronycteris ega''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T20033A22027237. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T20033A22027237.en 10.2305/IUCN.UK.2016-3.RLTS.T20033A22027237.en].]
[Solari, S. (2015). [https://www.iucnredlist.org/species/136321/22021092 "''Xeronycteris vieirai''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T136321A22021092. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T136321A22021092.en 10.2305/IUCN.UK.2015-4.RLTS.T136321A22021092.en].]
[''Glyphonycteris'' habitats:
* ''Behn's bat'': Zortea, M.; et al. (2016). [https://www.iucnredlist.org/species/13375/22130995 "''Glyphonycteris behnii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T13375A22130995. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T13375A22130995.en 10.2305/IUCN.UK.2016-2.RLTS.T13375A22130995.en].
* ''Davies's big-eared bat'': Solari, S. (2018). [https://www.iucnredlist.org/species/13377/22124873 "''Glyphonycteris daviesi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T13377A22124873. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T13377A22124873.en 10.2305/IUCN.UK.2018-2.RLTS.T13377A22124873.en].
* ''Tricolored big-eared bat'': Solari, S. (2018). [https://www.iucnredlist.org/species/13384/22123687 "''Glyphonycteris sylvestris''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T13384A22123687. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T13384A22123687.en 10.2305/IUCN.UK.2018-2.RLTS.T13384A22123687.en].
]
[Aguiar, L.; et al. (2016). [https://www.iucnredlist.org/species/13382/22123269 "''Neonycteris pusilla''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T13382A22123269. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T13382A22123269.en 10.2305/IUCN.UK.2016-2.RLTS.T13382A22123269.en].]
[Tavares, V.; et al. (2015). [https://www.iucnredlist.org/species/13381/22123365 "''Trinycteris nicefori''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T13381A22123365. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T13381A22123365.en 10.2305/IUCN.UK.2015-4.RLTS.T13381A22123365.en].]
[Solari, S. (2018). [https://www.iucnredlist.org/species/12078/22099972 "''Lionycteris spurrelli''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T12078A22099972. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T12078A22099972.en 10.2305/IUCN.UK.2018-2.RLTS.T12078A22099972.en].]
[''Lonchophylla'' habitats:
* ''Bokermann's nectar bat'': Aguiar, L. (2016). [https://www.iucnredlist.org/species/12263/22038287 "''Lonchophylla bokermanni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T12263A22038287. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T12263A22038287.en 10.2305/IUCN.UK.2016-3.RLTS.T12263A22038287.en].
* ''Cadena's long-tongued bat'': Solari, S. (2018). [https://www.iucnredlist.org/species/88149262/88149265 "''Lonchophylla cadenai''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T88149262A88149265. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T88149262A88149265.en 10.2305/IUCN.UK.2018-2.RLTS.T88149262A88149265.en].
* ''Central American nectar bat'': Davalos, L.; et al. (2016). [https://www.iucnredlist.org/species/136706/22036934 "''Lonchophylla concava''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136706A22036934. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T136706A22036934.en 10.2305/IUCN.UK.2016-2.RLTS.T136706A22036934.en].
* ''Chocoan long-tongued bat'': Davalos, L.; et al. (2016). [https://www.iucnredlist.org/species/136348/22023706 "''Lonchophylla chocoana''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136348A22023706. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T136348A22023706.en 10.2305/IUCN.UK.2016-2.RLTS.T136348A22023706.en].
* ''Dekeyser's nectar bat'': Aguiar, L.; et al. (2016). [https://www.iucnredlist.org/species/12264/22038149 "''Lonchophylla dekeyseri''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T12264A22038149. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T12264A22038149.en 10.2305/IUCN.UK.2016-2.RLTS.T12264A22038149.en].
* ''Eastern Cordilleran nectar bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/88150966/88150969 "''Lonchophylla orienticollina''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T88150966A88150969. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T88150966A88150969.en 10.2305/IUCN.UK.2019-1.RLTS.T88150966A88150969.en].
* ''Goldman's nectar bat'': Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/12267/22038521 "''Lonchophylla mordax''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T12267A22038521. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T12267A22038521.en 10.2305/IUCN.UK.2016-3.RLTS.T12267A22038521.en].
* ''Handley's nectar bat'': Davalos, L.; et al. (2018). [https://www.iucnredlist.org/species/12265/22038809 "''Lonchophylla handleyi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T12265A22038809. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T12265A22038809.en 10.2305/IUCN.UK.2018-2.RLTS.T12265A22038809.en].
* ''Orange nectar bat'': Dávalos, L.; et al. (2015). [https://www.iucnredlist.org/species/12268/22038399 "''Lonchophylla robusta''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T12268A22038399. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T12268A22038399.en 10.2305/IUCN.UK.2015-4.RLTS.T12268A22038399.en].
* ''Orcés's long-tongued bat'': Burneo, S.; et al. (2015). [https://www.iucnredlist.org/species/136735/22037057 "''Lonchophylla orcesi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T136735A22037057. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T136735A22037057.en 10.2305/IUCN.UK.2015-4.RLTS.T136735A22037057.en].
* ''Pacific Forest long-tongued bat'': Solari, S. (2020) [amended version of 2019 assessment]. [https://www.iucnredlist.org/species/88150313/166613263 "''Lonchophylla fornicata''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T88150313A166613263. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-1.RLTS.T88150313A166613263.en 10.2305/IUCN.UK.2020-1.RLTS.T88150313A166613263.en].
* ''Patton's long-tongued bat'': Solari, S. (2018). [https://www.iucnredlist.org/species/88149229/88149238 "''Lonchophylla pattoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T88149229A88149238. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T88149229A88149238.en 10.2305/IUCN.UK.2018-2.RLTS.T88149229A88149238.en].
* ''Peracchi's nectar bat'': Solari, S. (2017). [https://www.iucnredlist.org/species/88150984/88150992 "''Lonchophylla peracchii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T88150984A88150992. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T88150984A88150992.en 10.2305/IUCN.UK.2017-2.RLTS.T88150984A88150992.en].
* ''Thomas's nectar bat'': Solari, S. (2015). [https://www.iucnredlist.org/species/12269/22039689 "''Lonchophylla thomasi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T12269A22039689. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T12269A22039689.en 10.2305/IUCN.UK.2015-4.RLTS.T12269A22039689.en].
* ''Western nectar bat'': Solari, S.; et al. (2015). [https://www.iucnredlist.org/species/12266/22038705 "''Lonchophylla hesperia''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T12266A22038705. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T12266A22038705.en 10.2305/IUCN.UK.2015-4.RLTS.T12266A22038705.en].
]
[''Lonchorhina'' habitats:
* ''Fernandez's sword-nosed bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/12271/22039142 "''Lonchorhina fernandezi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T12271A22039142. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T12271A22039142.en 10.2305/IUCN.UK.2016-2.RLTS.T12271A22039142.en].
* ''Marinkelle's sword-nosed bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/12272/22038923 "''Lonchorhina marinkellei''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T12272A22038923. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T12272A22038923.en 10.2305/IUCN.UK.2016-2.RLTS.T12272A22038923.en].
* ''Northern sword-nosed bat'': Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/40027/22064066 "''Lonchorhina inusitata''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T40027A22064066. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T40027A22064066.en 10.2305/IUCN.UK.2016-2.RLTS.T40027A22064066.en].
* ''Orinoco sword-nosed bat'': Solari, S. (2020) [amended version of 2016 assessment]. [https://www.iucnredlist.org/species/12273/166505026 "''Lonchorhina orinocensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T12273A166505026. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-1.RLTS.T12273A166505026.en 10.2305/IUCN.UK.2020-1.RLTS.T12273A166505026.en].
* ''Tomes's sword-nosed bat'': Solari, S. (2015). [https://www.iucnredlist.org/species/12270/22039503 "''Lonchorhina aurita''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T12270A22039503. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T12270A22039503.en 10.2305/IUCN.UK.2015-4.RLTS.T12270A22039503.en].
]
[''Macrotus'' habitats:
* ''California leaf-nosed bat'': Solari, S. (2018). [https://www.iucnredlist.org/species/12652/22031754 "''Macrotus californicus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T12652A22031754. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T12652A22031754.en 10.2305/IUCN.UK.2018-2.RLTS.T12652A22031754.en].
* ''Waterhouse's leaf-nosed bat'': Solari, S. (2018). [https://www.iucnredlist.org/species/12653/22032004 "''Macrotus waterhousii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T12653A22032004. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T12653A22032004.en 10.2305/IUCN.UK.2018-2.RLTS.T12653A22032004.en].
]
[Solari, S. (2018). [https://www.iucnredlist.org/species/13376/22131330 "''Lampronycteris brachyotis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T13376A22131330. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T13376A22131330.en 10.2305/IUCN.UK.2018-2.RLTS.T13376A22131330.en].]
[''Micronycteris'' habitats:
* ''Brosset's big-eared bat'': Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/40028/22064188 "''Micronycteris brosseti''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T40028A22064188. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T40028A22064188.en 10.2305/IUCN.UK.2016-2.RLTS.T40028A22064188.en].
* ''Common big-eared bat'': Solari, S.; et al. (2019). [https://www.iucnredlist.org/species/136424/21985267 "''Micronycteris microtis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136424A21985267. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-2.RLTS.T136424A21985267.en 10.2305/IUCN.UK.2019-2.RLTS.T136424A21985267.en].
* ''Giovanni's big-eared bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/88120398/88120573 "''Micronycteris giovanniae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T88120398A88120573. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T88120398A88120573.en 10.2305/IUCN.UK.2016-3.RLTS.T88120398A88120573.en].
* ''Hairy big-eared bat'': Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/13378/22124582 "''Micronycteris hirsuta''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T13378A22124582. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T13378A22124582.en 10.2305/IUCN.UK.2016-3.RLTS.T13378A22124582.en].
* ''Little big-eared bat'': Solari, S. (2015). [https://www.iucnredlist.org/species/13379/22125168 "''Micronycteris megalotis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T13379A22125168. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T13379A22125168.en 10.2305/IUCN.UK.2015-4.RLTS.T13379A22125168.en].
* ''Matses's big-eared bat'': Velazco, P. (2015). [https://www.iucnredlist.org/species/136207/22010307 "''Micronycteris matses''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T136207A22010307. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T136207A22010307.en 10.2305/IUCN.UK.2015-4.RLTS.T136207A22010307.en].
* ''Saint Vincent big-eared bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/88120333/88120336 "''Micronycteris buriri''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T88120333A88120336. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T88120333A88120336.en 10.2305/IUCN.UK.2016-3.RLTS.T88120333A88120336.en].
* ''Sanborn's big-eared bat'': Solari, S. (2018). [https://www.iucnredlist.org/species/40029/22063748 "''Micronycteris sanborni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T40029A22063748. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T40029A22063748.en 10.2305/IUCN.UK.2018-2.RLTS.T40029A22063748.en].
* ''Schmidts's big-eared bat'': Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/13383/22124156 "''Micronycteris schmidtorum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T13383A22124156. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T13383A22124156.en 10.2305/IUCN.UK.2016-2.RLTS.T13383A22124156.en].
* ''White-bellied big-eared bat'': Solari, S. (2015). [https://www.iucnredlist.org/species/13380/22125019 "''Micronycteris minuta''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T13380A22125019. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T13380A22125019.en 10.2305/IUCN.UK.2015-4.RLTS.T13380A22125019.en].
* ''Yates's big-eared bat'': Solari, S. (2017). [https://www.iucnredlist.org/species/88132568/88132571 "''Micronycteris yatesi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T88132568A88132571. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T88132568A88132571.en 10.2305/IUCN.UK.2017-2.RLTS.T88132568A88132571.en].
]
[Barquez, R.; et al. (2015). [https://www.iucnredlist.org/species/4811/22042605 "''Chrotopterus auritus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T4811A22042605. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T4811A22042605.en 10.2305/IUCN.UK.2015-4.RLTS.T4811A22042605.en].]
[''Gardnerycteris'' habitats:
* ''Koepcke's hairy-nosed bat'': Velazco, P.; et al. (2019). [https://www.iucnredlist.org/species/136266/88183296 "''Gardnerycteris koepckeae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136266A88183296. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T136266A88183296.en 10.2305/IUCN.UK.2019-1.RLTS.T136266A88183296.en].
* ''Striped hairy-nosed bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/13560/88177260 "''Gardnerycteris crenulatum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T13560A88177260. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T13560A88177260.en 10.2305/IUCN.UK.2019-1.RLTS.T13560A88177260.en].
]
[''Lophostoma'' habitats:
* ''Carriker's round-eared bat'': Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/99783878/22041541 "''Lophostoma carrikeri''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T99783878A22041541. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T99783878A22041541.en 10.2305/IUCN.UK.2016-3.RLTS.T99783878A22041541.en].
* ''Davis's round-eared bat'': Solari, S. (2018). [https://www.iucnredlist.org/species/21986/22041302 "''Lophostoma evotis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T21986A22041302. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T21986A22041302.en 10.2305/IUCN.UK.2018-2.RLTS.T21986A22041302.en].
* ''Kalko's round-eared bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/88149216/88149219 "''Lophostoma kalkoae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T88149216A88149219. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T88149216A88149219.en 10.2305/IUCN.UK.2016-3.RLTS.T88149216A88149219.en].
* ''Pygmy round-eared bat'': Sampaio, E.; et al. (2017) [errata version of 2016 assessment]. [https://www.iucnredlist.org/species/21984/115164165 "''Lophostoma brasiliense''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T21984A115164165. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T21984A21975227.en 10.2305/IUCN.UK.2016-3.RLTS.T21984A21975227.en].
* ''Schultz's round-eared bat'': Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/21987/22041951 "''Lophostoma schulzi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T21987A22041951. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T21987A22041951.en 10.2305/IUCN.UK.2016-2.RLTS.T21987A22041951.en].
* ''Western round-eared bat'': Solari, S. (2020) [amended version of 2016 assessment]. [https://www.iucnredlist.org/species/88149174/166525772 "''Lophostoma occidentalis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T88149174A166525772. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-1.RLTS.T88149174A166525772.en 10.2305/IUCN.UK.2020-1.RLTS.T88149174A166525772.en].
* ''White-throated round-eared bat'': Barquez, R.; et al. (2016). [https://www.iucnredlist.org/species/88149202/22041651 "''Lophostoma silvicolum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T88149202A22041651. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T88149202A22041651.en 10.2305/IUCN.UK.2016-3.RLTS.T88149202A22041651.en].
]
[Rodriguez, B.; et al. (2015). [https://www.iucnredlist.org/species/12615/22025883 "''Macrophyllum macrophyllum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T12615A22025883. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T12615A22025883.en 10.2305/IUCN.UK.2015-4.RLTS.T12615A22025883.en].]
[''Mimon'' habitats:
* ''Cozumelan golden bat'': Arroyo-Cabrales, J.; et al. (2015). [https://www.iucnredlist.org/species/136561/21991024 "''Mimon cozumelae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T136561A21991024. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T136561A21991024.en 10.2305/IUCN.UK.2015-4.RLTS.T136561A21991024.en].
* ''Golden bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/13559/22105562 "''Mimon bennettii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T13559A22105562. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T13559A22105562.en 10.2305/IUCN.UK.2019-1.RLTS.T13559A22105562.en].
]
[Solari, S. (2015). [https://www.iucnredlist.org/species/17168/22134036 "''Phylloderma stenops''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T17168A22134036. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T17168A22134036.en 10.2305/IUCN.UK.2015-4.RLTS.T17168A22134036.en].]
[''Phyllostomus'' habitats:
* ''Greater spear-nosed bat'': Barquez, R.; et al. (2015). [https://www.iucnredlist.org/species/17218/22135955 "''Phyllostomus hastatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T17218A22135955. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T17218A22135955.en 10.2305/IUCN.UK.2015-4.RLTS.T17218A22135955.en].
* ''Guianan spear-nosed bat'': Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/17219/22136110 "''Phyllostomus latifolius''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T17219A22136110. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T17219A22136110.en 10.2305/IUCN.UK.2016-3.RLTS.T17219A22136110.en].
* ''Lesser spear-nosed bat'': Solari, S. (2015). [https://www.iucnredlist.org/species/17217/22135836 "''Phyllostomus elongatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T17217A22135836. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T17217A22135836.en 10.2305/IUCN.UK.2015-4.RLTS.T17217A22135836.en].
* ''Pale spear-nosed bat'': Barquez, R.; et al. (2015). [https://www.iucnredlist.org/species/17216/22136476 "''Phyllostomus discolor''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T17216A22136476. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T17216A22136476.en 10.2305/IUCN.UK.2015-4.RLTS.T17216A22136476.en].
]
[''Tonatia'' habitats:
* ''Greater round-eared bat'': Barquez, R.; et al. (2016). [https://www.iucnredlist.org/species/21983/21975435 "''Tonatia bidens''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T21983A21975435. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T21983A21975435.en 10.2305/IUCN.UK.2016-2.RLTS.T21983A21975435.en].
]
[Miller, B.; et al. (2015). [https://www.iucnredlist.org/species/22029/22042903 "''Trachops cirrhosus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T22029A22042903. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T22029A22042903.en 10.2305/IUCN.UK.2015-4.RLTS.T22029A22042903.en].]
[Solari, S. (2018). [https://www.iucnredlist.org/species/22843/22059426 "''Vampyrum spectrum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T22843A22059426. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T22843A22059426.en 10.2305/IUCN.UK.2018-2.RLTS.T22843A22059426.en].]
[''Rhinophylla'' habitats:
* ''Dwarf little fruit bat'': Solari, S. (2015). [https://www.iucnredlist.org/species/19593/22000844 "''Rhinophylla pumilio''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T19593A22000844. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T19593A22000844.en 10.2305/IUCN.UK.2015-4.RLTS.T19593A22000844.en].
* ''Fischer's little fruit bat'': Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/19592/21998306 "''Rhinophylla fischerae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T19592A21998306. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T19592A21998306.en 10.2305/IUCN.UK.2016-2.RLTS.T19592A21998306.en].
* ''Hairy little fruit bat'': Solari, S. (2018). [https://www.iucnredlist.org/species/19591/21998419 "''Rhinophylla alethina''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T19591A21998419. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T19591A21998419.en 10.2305/IUCN.UK.2018-2.RLTS.T19591A21998419.en].
]
[Miller, B.; et al. (2017) [errata version of 2016 assessment]. [https://www.iucnredlist.org/species/1137/115055683 "''Ametrida centurio''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T1137A115055683. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T1137A22070667.en 10.2305/IUCN.UK.2016-3.RLTS.T1137A22070667.en].]
[Davalos, L.; et al. (2019). [https://www.iucnredlist.org/species/2089/21994786 "''Ardops nichollsi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T2089A21994786. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T2089A21994786.en 10.2305/IUCN.UK.2019-1.RLTS.T2089A21994786.en].]
[Davalos, L.; et al. (2019). [https://www.iucnredlist.org/species/2110/21992222 "''Ariteus flavescens''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T2110A21992222. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T2110A21992222.en 10.2305/IUCN.UK.2019-1.RLTS.T2110A21992222.en].]
[''Artibeus'' habitats:
* ''Brown fruit-eating bat'': Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/2125/21999726 "''Artibeus concolor''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T2125A21999726. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T2125A21999726.en 10.2305/IUCN.UK.2016-2.RLTS.T2125A21999726.en].
* ''Dark fruit-eating bat'': Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/2137/21998064 "''Artibeus obscurus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T2137A21998064. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T2137A21998064.en 10.2305/IUCN.UK.2016-2.RLTS.T2137A21998064.en].
* ''Ecuadorian fruit-eating bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/88109970/88109973 "''Artibeus aequatorialis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T88109970A88109973. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T88109970A88109973.en 10.2305/IUCN.UK.2019-1.RLTS.T88109970A88109973.en].
* ''Flat-faced fruit-eating bat'': Barquez, R.; et al. (2015). [https://www.iucnredlist.org/species/2139/21997607 "''Artibeus planirostris''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T2139A21997607. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T2139A21997607.en 10.2305/IUCN.UK.2015-4.RLTS.T2139A21997607.en].
* ''Fraternal fruit-eating bat'': Molinari, J.; et al. (2015). [https://www.iucnredlist.org/species/2127/21998872 "''Artibeus fraterculus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T2127A21998872. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T2127A21998872.en 10.2305/IUCN.UK.2015-4.RLTS.T2127A21998872.en].
* ''Fringed fruit-eating bat'': Barquez, R.; et al. (2015). [https://www.iucnredlist.org/species/2126/21999829 "''Artibeus fimbriatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T2126A21999829. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T2126A21999829.en 10.2305/IUCN.UK.2015-4.RLTS.T2126A21999829.en].
* ''Great fruit-eating bat'': Barquez, R.; et al. (2015). [https://www.iucnredlist.org/species/2136/21995720 "''Artibeus lituratus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T2136A21995720. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T2136A21995720.en 10.2305/IUCN.UK.2015-4.RLTS.T2136A21995720.en].
* ''Hairy fruit-eating bat'': Arroyo-Cabrales, J.; et al. (2015). [https://www.iucnredlist.org/species/2131/21996678 "''Artibeus hirsutus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T2131A21996678. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T2131A21996678.en 10.2305/IUCN.UK.2015-4.RLTS.T2131A21996678.en].
* ''Honduran fruit-eating bat'': Reid, F.; et al. (2016). [https://www.iucnredlist.org/species/2132/21996586 "''Artibeus inopinatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T2132A21996586. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T2132A21996586.en 10.2305/IUCN.UK.2016-2.RLTS.T2132A21996586.en].
* ''Jamaican fruit bat'': Miller, B.; et al. (2016). [https://www.iucnredlist.org/species/88109731/21995883 "''Artibeus jamaicensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T88109731A21995883. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T88109731A21995883.en 10.2305/IUCN.UK.2016-3.RLTS.T88109731A21995883.en].
* ''Large fruit-eating bat'': Solari, S. (2018). [https://www.iucnredlist.org/species/2121/22000620 "''Artibeus amplus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T2121A22000620. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T2121A22000620.en 10.2305/IUCN.UK.2018-2.RLTS.T2121A22000620.en].
* ''Schwartz's fruit-eating bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/88109897/88109919 "''Artibeus schwartzi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T88109897A88109919. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T88109897A88109919.en 10.2305/IUCN.UK.2016-3.RLTS.T88109897A88109919.en].
]
[Miller, B.; et al. (2016). [https://www.iucnredlist.org/species/4133/22009493 "''Centurio senex''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T4133A22009493. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T4133A22009493.en 10.2305/IUCN.UK.2016-2.RLTS.T4133A22009493.en].]
[''Chiroderma'' habitats:
* ''Brazilian big-eyed bat'': Tavares, V.; et al. (2015). [https://www.iucnredlist.org/species/4664/22037141 "''Chiroderma doriae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T4664A22037141. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T4664A22037141.en 10.2305/IUCN.UK.2015-4.RLTS.T4664A22037141.en].
* ''Guadeloupe big-eyed bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/4665/22037238 "''Chiroderma improvisum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T4665A22037238. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T4665A22037238.en 10.2305/IUCN.UK.2016-1.RLTS.T4665A22037238.en].
* ''Hairy big-eyed bat'': Solari, S. (2015). [https://www.iucnredlist.org/species/4668/22037709 "''Chiroderma villosum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T4668A22037709. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T4668A22037709.en 10.2305/IUCN.UK.2015-4.RLTS.T4668A22037709.en].
* ''Little big-eyed bat'': Miller, B.; et al. (2016). [https://www.iucnredlist.org/species/4667/22037580 "''Chiroderma trinitatum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T4667A22037580. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T4667A22037580.en 10.2305/IUCN.UK.2016-2.RLTS.T4667A22037580.en].
* ''Salvin's big-eyed bat'': Aguirre, L.; et al. (2015). [https://www.iucnredlist.org/species/4666/22037356 "''Chiroderma salvini''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T4666A22037356. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T4666A22037356.en 10.2305/IUCN.UK.2015-4.RLTS.T4666A22037356.en].
]
[''Dermanura'' habitats:
* ''Andersen's fruit-eating bat'': Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/2122/22000743 "''Dermanura anderseni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T2122A22000743. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T2122A22000743.en 10.2305/IUCN.UK.2016-2.RLTS.T2122A22000743.en].
* ''Aztec fruit-eating bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/2123/22000362 "''Dermanura azteca''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T2123A22000362. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T2123A22000362.en 10.2305/IUCN.UK.2016-2.RLTS.T2123A22000362.en].
* ''Bogota fruit-eating bat'': Solari, S. (2017). [https://www.iucnredlist.org/species/83683094/83683100 "''Dermanura bogotensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T83683094A83683100. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T83683094A83683100.en 10.2305/IUCN.UK.2017-2.RLTS.T83683094A83683100.en].
* ''Gervais's fruit-eating bat'': Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/2124/22000480 "''Dermanura cinerea''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T2124A22000480. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T2124A22000480.en 10.2305/IUCN.UK.2016-2.RLTS.T2124A22000480.en].
* ''Gnome fruit-eating bat'': Solari, S. (2016) [errata version of 2015 assessment]. [https://www.iucnredlist.org/species/2129/97207684 "''Dermanura gnoma''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T2129A97207684. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T2129A21997242.en 10.2305/IUCN.UK.2015-4.RLTS.T2129A21997242.en].
* ''Little fruit-eating bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/83683265/83683270 "''Dermanura rava''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T83683265A83683270. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T83683265A83683270.en 10.2305/IUCN.UK.2019-1.RLTS.T83683265A83683270.en].
* ''Pygmy fruit-eating bat'': Miller, B.; et al. (2015). [https://www.iucnredlist.org/species/83683287/21997769 "''Dermanura phaeotis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T83683287A21997769. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T83683287A21997769.en 10.2305/IUCN.UK.2015-4.RLTS.T83683287A21997769.en].
* ''Rosenberg's fruit-eating bat'': Solari, S.; et al. (2016). [https://www.iucnredlist.org/species/136505/21972501 "''Dermanura rosenbergi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136505A21972501. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T136505A21972501.en 10.2305/IUCN.UK.2016-2.RLTS.T136505A21972501.en].
* ''Silver fruit-eating bat'': Solari, S. (2015). [https://www.iucnredlist.org/species/83683065/21999615 "''Dermanura glauca''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T83683065A21999615. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T83683065A21999615.en 10.2305/IUCN.UK.2015-4.RLTS.T83683065A21999615.en].
* ''Thomas's fruit-eating bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/99586593/21997358 "''Dermanura watsoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T99586593A21997358. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T99586593A21997358.en 10.2305/IUCN.UK.2016-3.RLTS.T99586593A21997358.en].
* ''Toltec fruit-eating bat'': Rodriguez, B.; et al. (2015). [https://www.iucnredlist.org/species/2140/21997479 "''Dermanura tolteca''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T2140A21997479. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T2140A21997479.en 10.2305/IUCN.UK.2015-4.RLTS.T2140A21997479.en].
]
[Rodriguez, B. and Pineda; et al. (2015). [https://www.iucnredlist.org/species/7030/22027138 "''Ectophylla alba''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T7030A22027138. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T7030A22027138.en 10.2305/IUCN.UK.2015-4.RLTS.T7030A22027138.en].]
[Solari, S. (2018). [https://www.iucnredlist.org/species/2130/21996891 "''Enchisthenes hartii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T2130A21996891. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T2130A21996891.en 10.2305/IUCN.UK.2018-2.RLTS.T2130A21996891.en].]
[Solari, S. (2015). [https://www.iucnredlist.org/species/13240/21987618 "''Mesophylla macconnelli''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T13240A21987618. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T13240A21987618.en 10.2305/IUCN.UK.2015-4.RLTS.T13240A21987618.en].]
[Solari, S.; et al. (2019). [https://www.iucnredlist.org/species/17176/22133485 "''Phyllops falcatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T17176A22133485. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T17176A22133485.en 10.2305/IUCN.UK.2019-1.RLTS.T17176A22133485.en].]
[''Platyrrhinus'' habitats:
* ''Alberico's broad-nosed bat'': Velazco, P. (2015). [https://www.iucnredlist.org/species/136203/22009876 "''Platyrrhinus albericoi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T136203A22009876. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T136203A22009876.en 10.2305/IUCN.UK.2015-4.RLTS.T136203A22009876.en].
* ''Brown-bellied broad-nosed bat'': Solari, S. (2019) [amended version of 2017 assessment]. [https://www.iucnredlist.org/species/88160339/146605973 "''Platyrrhinus fusciventris''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T88160339A146605973.
* ''Buffy broad-nosed bat'': Velazco, P. (2015). [https://www.iucnredlist.org/species/17571/21971889 "''Platyrrhinus infuscus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T17571A21971889. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T17571A21971889.en 10.2305/IUCN.UK.2015-4.RLTS.T17571A21971889.en].
* ''Darien broad-nosed bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/88160364/88160367 "''Platyrrhinus aquilus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T88160364A88160367. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T88160364A88160367.en 10.2305/IUCN.UK.2016-3.RLTS.T88160364A88160367.en].
* ''Eldorado broad-nosed bat'': Sampaio, E.; et al. (2017) [errata version of 2016 assessment]. [https://www.iucnredlist.org/species/17566/115141196 "''Platyrrhinus aurarius''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T17566A115141196. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T17566A21987335.en 10.2305/IUCN.UK.2016-3.RLTS.T17566A21987335.en].
* ''Greater broad-nosed bat'': Velazco, P. (2015). [https://www.iucnredlist.org/species/17574/21972409 "''Platyrrhinus vittatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T17574A21972409. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T17574A21972409.en 10.2305/IUCN.UK.2015-4.RLTS.T17574A21972409.en].
* ''Heller's broad-nosed bat'': Arroyo-Cabrales, J.; et al. (2016). [https://www.iucnredlist.org/species/88159886/88159952 "''Platyrrhinus helleri''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T88159886A88159952. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T88159886A88159952.en 10.2305/IUCN.UK.2016-1.RLTS.T88159886A88159952.en].
* ''Incan broad-nosed bat'': Solari, S. (2017). [https://www.iucnredlist.org/species/88160214/88160217 "''Platyrrhinus incarum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T88160214A88160217. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T88160214A88160217.en 10.2305/IUCN.UK.2017-2.RLTS.T88160214A88160217.en].
* ''Ismael's broad-nosed bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/136232/22002129 "''Platyrrhinus ismaeli''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136232A22002129. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T136232A22002129.en 10.2305/IUCN.UK.2016-2.RLTS.T136232A22002129.en].
* ''Matapalo broad-nosed bat'': Velazco, P. (2016). [https://www.iucnredlist.org/species/136378/22012522 "''Platyrrhinus matapalensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136378A22012522. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T136378A22012522.en 10.2305/IUCN.UK.2016-2.RLTS.T136378A22012522.en].
* ''Quechua broad-nosed bat'': Velazco, P. (2015). [https://www.iucnredlist.org/species/136577/21998517 "''Platyrrhinus masu''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T136577A21998517. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T136577A21998517.en 10.2305/IUCN.UK.2015-4.RLTS.T136577A21998517.en].
* ''Recife broad-nosed bat'': Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/17572/21971681 "''Platyrrhinus recifinus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T17572A21971681. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T17572A21971681.en 10.2305/IUCN.UK.2016-2.RLTS.T17572A21971681.en].
* ''Shadowy broad-nosed bat'': Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/95908089/21973968 "''Platyrrhinus umbratus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T95908089A21973968. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T95908089A21973968.en 10.2305/IUCN.UK.2016-3.RLTS.T95908089A21973968.en].
* ''Short-headed broad-nosed bat'': Solari, S. (2015). [https://www.iucnredlist.org/species/17567/21986909 "''Platyrrhinus brachycephalus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T17567A21986909. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T17567A21986909.en 10.2305/IUCN.UK.2015-4.RLTS.T17567A21986909.en].
* ''Slender broad-nosed bat'': Solari, S. (2017). [https://www.iucnredlist.org/species/88160255/88160258 "''Platyrrhinus angustirostris''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T88160255A88160258. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T88160255A88160258.en 10.2305/IUCN.UK.2017-2.RLTS.T88160255A88160258.en].
* ''Thomas's broad-nosed bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/88160389/88160395 "''Platyrrhinus dorsalis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T88160389A88160395. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T88160389A88160395.en 10.2305/IUCN.UK.2016-1.RLTS.T88160389A88160395.en].
* ''Western broad-nosed bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/88160517/88160521 "''Platyrrhinus nitelinea''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T88160517A88160521. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T88160517A88160521.en 10.2305/IUCN.UK.2016-3.RLTS.T88160517A88160521.en].
* ''White-lined broad-nosed bat'': Barquez, R.; et al. (2015). [https://www.iucnredlist.org/species/17565/21987212 "''Platyrrhinus lineatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T17565A21987212. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T17565A21987212.en 10.2305/IUCN.UK.2015-4.RLTS.T17565A21987212.en].
]
[Barquez, R.; et al. (2015). [https://www.iucnredlist.org/species/18945/22103088 "''Pygoderma bilabiatum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T18945A22103088. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T18945A22103088.en 10.2305/IUCN.UK.2015-4.RLTS.T18945A22103088.en].]
[Solari, S. (2018). [https://www.iucnredlist.org/species/20599/22078791 "''Sphaeronycteris toxophyllum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T20599A22078791. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T20599A22078791.en 10.2305/IUCN.UK.2018-2.RLTS.T20599A22078791.en].]
[Rodriguez Duran, A. (2016). [https://www.iucnredlist.org/species/20743/22065638 "''Stenoderma rufum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T20743A22065638. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T20743A22065638.en 10.2305/IUCN.UK.2016-1.RLTS.T20743A22065638.en].]
[''Sturnira'' habitats:
* ''Aratathomas's yellow-shouldered bat'': Pacheco, V. (2016). [https://www.iucnredlist.org/species/20949/22052176 "''Sturnira aratathomasi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T20949A22052176. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T20949A22052176.en 10.2305/IUCN.UK.2016-2.RLTS.T20949A22052176.en].
* ''Baker's yellow-shouldered bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/88152001/88152004 "''Sturnira bakeri''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T88152001A88152004. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T88152001A88152004.en 10.2305/IUCN.UK.2019-1.RLTS.T88152001A88152004.en].
* ''Bidentate yellow-shouldered bat'': Solari, S. (2018). [https://www.iucnredlist.org/species/20950/22052060 "''Sturnira bidens''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T20950A22052060. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T20950A22052060.en 10.2305/IUCN.UK.2018-2.RLTS.T20950A22052060.en].
* ''Bogotá yellow-shouldered bat'': Solari, S. (2018). [https://www.iucnredlist.org/species/20951/22053090 "''Sturnira bogotensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T20951A22053090. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T20951A22053090.en 10.2305/IUCN.UK.2018-2.RLTS.T20951A22053090.en].
* ''Burton's yellow-shouldered bat'': Solari, S. (2017). [https://www.iucnredlist.org/species/88152206/88152209 "''Sturnira burtonlimi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T88152206A88152209. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T88152206A88152209.en 10.2305/IUCN.UK.2017-2.RLTS.T88152206A88152209.en].
* ''Choco yellow-shouldered bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/88159599/88159604 "''Sturnira koopmanhilli''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T88159599A88159604. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T88159599A88159604.en 10.2305/IUCN.UK.2016-3.RLTS.T88159599A88159604.en].
* ''Greater yellow-shouldered bat'': Pacheco, V.; et al. (2015). [https://www.iucnredlist.org/species/20956/22049622 "''Sturnira magna''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T20956A22049622. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T20956A22049622.en 10.2305/IUCN.UK.2015-4.RLTS.T20956A22049622.en].
* ''Guadeloupe yellow-shouldered bat'', ''Thomas's yellow-shouldered bat'': Solari, S. (2024) [errata version of 2019 assessment]. [https://www.iucnredlist.org/species/88154322/258005117 "''Sturnira angeli''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T88154322A258005117. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T88154322A258005117.en 10.2305/IUCN.UK.2019-3.RLTS.T88154322A258005117.en].
* ''Hairy yellow-shouldered bat'': Barquez, R.; et al. (2015). [https://www.iucnredlist.org/species/20952/22052982 "''Sturnira erythromos''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T20952A22052982. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T20952A22052982.en 10.2305/IUCN.UK.2015-4.RLTS.T20952A22052982.en].
* ''Highland yellow-shouldered bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/88159722/88159731 "''Sturnira ludovici''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T88159722A88159731. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T88159722A88159731.en 10.2305/IUCN.UK.2016-1.RLTS.T88159722A88159731.en].
* ''Honduran yellow-shouldered bat'': Solari, S. (2017). [https://www.iucnredlist.org/species/88154577/88154581 "''Sturnira hondurensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T88154577A88154581. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T88154577A88154581.en 10.2305/IUCN.UK.2017-2.RLTS.T88154577A88154581.en].
* ''Lesser yellow-shouldered bat'': Solari, S.; et al. (2016). [https://www.iucnredlist.org/species/20958/22050195 "''Sturnira nana''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T20958A22050195. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T20958A22050195.en 10.2305/IUCN.UK.2016-1.RLTS.T20958A22050195.en].
* ''Little yellow-shouldered bat'': Velazco, P.; et al. (2017). [https://www.iucnredlist.org/species/88159688/22049384 "''Sturnira lilium''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T88159688A22049384. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T88159688A22049384.en 10.2305/IUCN.UK.2017-2.RLTS.T88159688A22049384.en].
* ''Louis's yellow-shouldered bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/20955/22049788 "''Sturnira luisi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T20955A22049788. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T20955A22049788.en 10.2305/IUCN.UK.2019-1.RLTS.T20955A22049788.en].
* ''Mistratoan yellow-shouldered bat'': Mantilla-Meluk, H. (2015). [https://www.iucnredlist.org/species/136591/22000285 "''Sturnira mistratensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T136591A22000285. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T136591A22000285.en 10.2305/IUCN.UK.2015-4.RLTS.T136591A22000285.en].
* ''Northern yellow-shouldered bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/88154376/88154380 "''Sturnira parvidens''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T88154376A88154380. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-2.RLTS.T88154376A88154380.en 10.2305/IUCN.UK.2019-2.RLTS.T88154376A88154380.en].
* ''Paulson's yellow-shouldered bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/88154558/88154562 "''Sturnira paulsoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T88154558A88154562. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T88154558A88154562.en 10.2305/IUCN.UK.2019-3.RLTS.T88154558A88154562.en].
* ''Perla yellow-shouldered bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/88159664/88159667 "''Sturnira perla''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T88159664A88159667. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T88159664A88159667.en 10.2305/IUCN.UK.2016-3.RLTS.T88159664A88159667.en].
* ''Soriano's yellow-shouldered bat'': Pacheco, V. (2015). [https://www.iucnredlist.org/species/136778/22032744 "''Sturnira sorianoi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T136778A22032744. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T136778A22032744.en 10.2305/IUCN.UK.2015-4.RLTS.T136778A22032744.en].
* ''Talamancan yellow-shouldered bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/20957/22050440 "''Sturnira mordax''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T20957A22050440. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-2.RLTS.T20957A22050440.en 10.2305/IUCN.UK.2019-2.RLTS.T20957A22050440.en].
* ''Tilda's yellow-shouldered bat'': Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/20960/22050501 "''Sturnira tildae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T20960A22050501. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T20960A22050501.en 10.2305/IUCN.UK.2016-2.RLTS.T20960A22050501.en].
* ''Tschudi's yellow-shouldered bat'': Barquez, R.; et al. (2020) [amended version of 2016 assessment]. [https://www.iucnredlist.org/species/136494/166501281 "''Sturnira oporaphilum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T136494A166501281. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-1.RLTS.T136494A166501281.en 10.2305/IUCN.UK.2020-1.RLTS.T136494A166501281.en].
]
[''Uroderma'' habitats:
* ''Brown tent-making bat'': Solari, S. (2015). [https://www.iucnredlist.org/species/22783/22048094 "''Uroderma magnirostrum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T22783A22048094. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T22783A22048094.en 10.2305/IUCN.UK.2015-4.RLTS.T22783A22048094.en].
* ''Tent-making bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/22782/22048748 "''Uroderma bilobatum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T22782A22048748. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-2.RLTS.T22782A22048748.en 10.2305/IUCN.UK.2019-2.RLTS.T22782A22048748.en].
]
[''Vampyressa'' habitats:
* ''Melissa's yellow-eared bat'': Ramirez-Chaves, H.; et al. (2015). [https://www.iucnredlist.org/species/22839/22058315 "''Vampyressa melissa''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T22839A22058315. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T22839A22058315.en 10.2305/IUCN.UK.2015-4.RLTS.T22839A22058315.en].
* ''Northern little yellow-eared bat'': Tavares, V.; et al. (2015). [https://www.iucnredlist.org/species/136671/21989318 "''Vampyressa thyone''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T136671A21989318. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T136671A21989318.en 10.2305/IUCN.UK.2015-4.RLTS.T136671A21989318.en].
* ''Southern little yellow-eared bat'': Barquez, R.; et al. (2016). [https://www.iucnredlist.org/species/22841/22060007 "''Vampyressa pusilla''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T22841A22060007. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T22841A22060007.en 10.2305/IUCN.UK.2016-2.RLTS.T22841A22060007.en].
]
[''Vampyriscus'' habitats:
* ''Bidentate yellow-eared bat'': Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/22837/22059000 "''Vampyriscus bidens''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T22837A22059000. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T22837A22059000.en 10.2305/IUCN.UK.2016-2.RLTS.T22837A22059000.en].
* ''Brock's yellow-eared bat'': Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/22838/22059321 "''Vampyriscus brocki''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T22838A22059321. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T22838A22059321.en 10.2305/IUCN.UK.2016-2.RLTS.T22838A22059321.en].
* ''Striped yellow-eared bat'': Tavares, V.; et al. (2015). [https://www.iucnredlist.org/species/22840/22058669 "''Vampyriscus nymphaea''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T22840A22058669. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T22840A22058669.en 10.2305/IUCN.UK.2015-4.RLTS.T22840A22058669.en].
]
[''Vampyrodes'' habitats:
* ''Great stripe-faced bat'': Miller, B.; et al. (2016). [https://www.iucnredlist.org/species/88151904/22060515 "''Vampyrodes caraccioli''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T88151904A22060515. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T88151904A22060515.en 10.2305/IUCN.UK.2016-3.RLTS.T88151904A22060515.en].
* ''Greater stripe-faced bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/88151984/88151987 "''Vampyrodes major''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T88151984A88151987. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T88151984A88151987.en 10.2305/IUCN.UK.2016-3.RLTS.T88151984A88151987.en].
]
[[[#CITEREF_ALLMAM|Chernasky; Motis; Burgin]], p. 491–492]
[''Thyroptera'' habitats:
* ''De Vivo's disk-winged bat'': Solari, S. (2015). [https://www.iucnredlist.org/species/136594/21996185 "''Thyroptera devivoi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T136594A21996185. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T136594A21996185.en 10.2305/IUCN.UK.2015-4.RLTS.T136594A21996185.en].
* ''Peters's disk-winged bat'': Solari, S.; et al. (2018). [https://www.iucnredlist.org/species/21877/21985811 "''Thyroptera discifera''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T21877A21985811. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T21877A21985811.en 10.2305/IUCN.UK.2018-2.RLTS.T21877A21985811.en].
* ''LaVal's disk-winged bat'': Solari, S.; et al. (2016). [https://www.iucnredlist.org/species/21878/21985717 "''Thyroptera lavali''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T21878A21985717. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T21878A21985717.en 10.2305/IUCN.UK.2016-2.RLTS.T21878A21985717.en].
* ''Spix's disk-winged bat'': Tavares, V.; et al. (2016) [errata version of 2015 assessment]. [https://www.iucnredlist.org/species/21879/97207863 "''Thyroptera tricolor''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2015''': e.T21879A97207863. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2015-4.RLTS.T21879A21985559.en 10.2305/IUCN.UK.2015-4.RLTS.T21879A21985559.en].
* ''Patricia's disk-winged bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/88151033/88151036 "''Thyroptera wynneae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T88151033A88151036. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T88151033A88151036.en 10.2305/IUCN.UK.2016-3.RLTS.T88151033A88151036.en].
]
[[[#CITEREF_ALLMAM|Chernasky; Motis; Burgin]], p. 448–465]
[''Aethalops'' habitats:
* ''Borneo fruit bat'': Jayaraj, J. V. K.; et al. (2016). [https://www.iucnredlist.org/species/136541/21977630 "''Aethalops aequalis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136541A21977630. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T136541A21977630.en 10.2305/IUCN.UK.2016-2.RLTS.T136541A21977630.en].
* ''Pygmy fruit bat'': White, A. L.; et al. (2023). [https://www.iucnredlist.org/species/565/229798079 "''Aethalops alecto''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2023''': e.T565A229798079. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2023-1.RLTS.T565A229798079.en 10.2305/IUCN.UK.2023-1.RLTS.T565A229798079.en].
]
[Mildenstein, T. (2016). [https://www.iucnredlist.org/species/843/22037501 "''Alionycteris paucidentata''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T843A22037501. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T843A22037501.en 10.2305/IUCN.UK.2016-1.RLTS.T843A22037501.en].]
[''Balionycteris'' habitats:
* ''Malayan spotted-winged fruit bat'': Tan, P. (2021). [https://www.iucnredlist.org/species/84454980/84454984 "''Balionycteris seimundi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T84454980A84454984. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T84454980A84454984.en 10.2305/IUCN.UK.2021-1.RLTS.T84454980A84454984.en].
* ''Spotted-winged fruit bat'': Bates, P.; et al. (2021). [https://www.iucnredlist.org/species/84454322/22030208 "''Balionycteris maculata''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T84454322A22030208. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T84454322A22030208.en 10.2305/IUCN.UK.2021-1.RLTS.T84454322A22030208.en].
]
[Tsang, S. M.; et al. (2020). [https://www.iucnredlist.org/species/4670/22037874 "''Chironax melanocephalus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T4670A22037874. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T4670A22037874.en 10.2305/IUCN.UK.2020-3.RLTS.T4670A22037874.en].]
[''Cynopterus'' habitats:
* ''Greater short-nosed fruit bat'': Bates, P.; et al. (2019). [https://www.iucnredlist.org/species/6106/22113656 "''Cynopterus sphinx''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T6106A22113656. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T6106A22113656.en 10.2305/IUCN.UK.2019-3.RLTS.T6106A22113656.en].
* ''Horsfield's fruit bat'': Bates, P.; et al. (2019). [https://www.iucnredlist.org/species/6104/22113239 "''Cynopterus horsfieldii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T6104A22113239. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T6104A22113239.en 10.2305/IUCN.UK.2019-3.RLTS.T6104A22113239.en].
* ''Indonesian short-nosed fruit bat'': Tsang, S. M. (2016). [https://www.iucnredlist.org/species/6107/22114054 "''Cynopterus titthaecheilus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T6107A22114054. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T6107A22114054.en 10.2305/IUCN.UK.2016-2.RLTS.T6107A22114054.en].
* ''Lesser short-nosed fruit bat'': Csorba, G.; et al. (2019). [https://www.iucnredlist.org/species/6103/22113381 "''Cynopterus brachyotis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T6103A22113381. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T6103A22113381.en 10.2305/IUCN.UK.2019-3.RLTS.T6103A22113381.en].
* ''Minute fruit bat'': Ruedas, L.; et al. (2019). [https://www.iucnredlist.org/species/136423/21985433 "''Cynopterus minutus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136423A21985433. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T136423A21985433.en 10.2305/IUCN.UK.2019-3.RLTS.T136423A21985433.en].
* ''Nusatenggara short-nosed fruit bat'': Ruedas, L.; et al. (2019). [https://www.iucnredlist.org/species/6105/22113935 "''Cynopterus nusatenggara''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T6105A22113935. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T6105A22113935.en 10.2305/IUCN.UK.2019-3.RLTS.T6105A22113935.en].
* ''Peters's fruit bat'': Rosell-Ambal, G.; et al. (2019). [https://www.iucnredlist.org/species/136798/22035092 "''Cynopterus luzoniensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136798A22035092. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T136798A22035092.en 10.2305/IUCN.UK.2019-3.RLTS.T136798A22035092.en].
]
[''Dyacopterus'' habitats:
* ''Brooks's dyak fruit bat'': Tsang, S. M. (2020). [https://www.iucnredlist.org/species/136356/22011865 "''Dyacopterus brooksi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T136356A22011865. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T136356A22011865.en 10.2305/IUCN.UK.2020-3.RLTS.T136356A22011865.en].
* ''Rickart's dyak fruit bat'': Gomez, R.; et al. (2020). [https://www.iucnredlist.org/species/84457541/95642280 "''Dyacopterus rickarti''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T84457541A95642280. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T84457541A95642280.en 10.2305/IUCN.UK.2020-2.RLTS.T84457541A95642280.en].
* ''Dayak fruit bat'': Csorba, G.; et al. (2020). [https://www.iucnredlist.org/species/6931/22029918 "''Dyacopterus spadiceus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T6931A22029918. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T6931A22029918.en 10.2305/IUCN.UK.2020-3.RLTS.T6931A22029918.en].
]
[Duya, M. R.; et al. (2021). [https://www.iucnredlist.org/species/9690/22136653 "''Haplonycteris fischeri''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T9690A22136653. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T9690A22136653.en 10.2305/IUCN.UK.2021-1.RLTS.T9690A22136653.en].]
[Srinivasulu, C.; et al. (2020). [https://www.iucnredlist.org/species/11374/22103756 "''Latidens salimalii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T11374A22103756. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T11374A22103756.en 10.2305/IUCN.UK.2020-3.RLTS.T11374A22103756.en].]
[''Megaerops'' habitats:
* ''Javan tailless fruit bat'': Waldien, D. L.; et al. (2021). [https://www.iucnredlist.org/species/12945/22024115 "''Megaerops kusnotoi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T12945A22024115. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T12945A22024115.en 10.2305/IUCN.UK.2021-2.RLTS.T12945A22024115.en].
* ''Ratanaworabhan's fruit bat'': Bates, P.; et al. (2021). [https://www.iucnredlist.org/species/12947/22024550 "''Megaerops niphanae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T12947A22024550. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T12947A22024550.en 10.2305/IUCN.UK.2021-1.RLTS.T12947A22024550.en].
* ''Tailless fruit bat'': Bates, P.; et al. (2021). [https://www.iucnredlist.org/species/12946/22023972 "''Megaerops ecaudatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T12946A22023972. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T12946A22023972.en 10.2305/IUCN.UK.2021-1.RLTS.T12946A22023972.en].
* ''White-collared fruit bat'': Rosell-Ambal, G.; et al. (2008). [https://www.iucnredlist.org/species/12948/3401295 "''Megaerops wetmorei''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2008''': e.T12948A3401295. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2008.RLTS.T12948A3401295.en 10.2305/IUCN.UK.2008.RLTS.T12948A3401295.en].
]
[Ong, P.; et al. (2020). [https://www.iucnredlist.org/species/15665/22122206 "''Otopteropus cartilagonodus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T15665A22122206. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T15665A22122206.en 10.2305/IUCN.UK.2020-2.RLTS.T15665A22122206.en].]
[Waldien, D. L.; et al. (2020). [https://www.iucnredlist.org/species/16563/22055450 "''Penthetor lucasi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T16563A22055450. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T16563A22055450.en 10.2305/IUCN.UK.2020-2.RLTS.T16563A22055450.en].]
[''Ptenochirus'' habitats:
* ''Greater musky fruit bat'': Alviola, P. A.; et al. (2021). [https://www.iucnredlist.org/species/18653/22071217 "''Ptenochirus jagori''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T18653A22071217. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T18653A22071217.en 10.2305/IUCN.UK.2021-1.RLTS.T18653A22071217.en].
* ''Lesser musky fruit bat'': Alviola, P. A.; et al. (2021). [https://www.iucnredlist.org/species/18654/22071330 "''Ptenochirus minor''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T18654A22071330. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T18654A22071330.en 10.2305/IUCN.UK.2021-1.RLTS.T18654A22071330.en].
]
[Wortham, G.; et al. (2021). [https://www.iucnredlist.org/species/20521/22100101 "''Sphaerias blanfordi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T20521A22100101. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T20521A22100101.en 10.2305/IUCN.UK.2021-3.RLTS.T20521A22100101.en].]
[''Thoopterus'' habitats:
* ''Suhaniah fruit bat'': Wiantoro, S. (2020). [https://www.iucnredlist.org/species/84463939/84463943 "''Thoopterus suhaniahae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T84463939A84463943. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T84463939A84463943.en 10.2305/IUCN.UK.2020-2.RLTS.T84463939A84463943.en].
* ''Swift fruit bat'': Wiantoro, S.; et al. (2020). [https://www.iucnredlist.org/species/21815/21989441 "''Thoopterus nigrescens''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T21815A21989441. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T21815A21989441.en 10.2305/IUCN.UK.2020-2.RLTS.T21815A21989441.en].
]
[''Eidolon'' habitats:
* ''Madagascan fruit bat'': Andriafidison, D.; et al. (2020). [https://www.iucnredlist.org/species/7083/22027891 "''Eidolon dupreanum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T7083A22027891. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T7083A22027891.en 10.2305/IUCN.UK.2020-2.RLTS.T7083A22027891.en].
* ''Straw-coloured fruit bat'': Cooper-Bohannon, R.; et al. (2020). [https://www.iucnredlist.org/species/7084/22028026 "''Eidolon helvum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T7084A22028026. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T7084A22028026.en 10.2305/IUCN.UK.2020-2.RLTS.T7084A22028026.en].
]
[Aplin, K.; et al. (2021) [amended version of 2016 assessment]. [https://www.iucnredlist.org/species/1933/209536462 "''Aproteles bulmerae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T1933A209536462. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T1933A209536462.en 10.2305/IUCN.UK.2021-3.RLTS.T1933A209536462.en].]
[Wiantoro, S.; et al. (2020). [https://www.iucnredlist.org/species/19749/22002714 "''Boneia bidens''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T19749A22002714. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T19749A22002714.en 10.2305/IUCN.UK.2020-2.RLTS.T19749A22002714.en].]
[''Dobsonia'' habitats:
* ''Andersen's naked-backed fruit bat'': Leary, T.; et al. (2020). [https://www.iucnredlist.org/species/136374/22012133 "''Dobsonia anderseni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T136374A22012133. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T136374A22012133.en 10.2305/IUCN.UK.2020-3.RLTS.T136374A22012133.en].
* ''Bare-backed fruit bat'': Tsang, S. M. (2016). [https://www.iucnredlist.org/species/84882605/22033630 "''Dobsonia moluccensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T84882605A22033630. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T84882605A22033630.en 10.2305/IUCN.UK.2016-3.RLTS.T84882605A22033630.en].
* ''Beaufort's naked-backed fruit bat'': Mildenstein, T. (2016). [https://www.iucnredlist.org/species/6772/22034699 "''Dobsonia beauforti''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T6772A22034699. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T6772A22034699.en 10.2305/IUCN.UK.2016-1.RLTS.T6772A22034699.en].
* ''Biak naked-backed fruit bat'': Leary, T.; et al. (2020). [https://www.iucnredlist.org/species/6774/22033892 "''Dobsonia emersa''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T6774A22033892. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T6774A22033892.en 10.2305/IUCN.UK.2020-3.RLTS.T6774A22033892.en].
* ''Greenish naked-backed fruit bat'': Tsang, S. M. (2016). [https://www.iucnredlist.org/species/6780/22033412 "''Dobsonia viridis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T6780A22033412. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T6780A22033412.en 10.2305/IUCN.UK.2016-2.RLTS.T6780A22033412.en].
* ''Halmahera naked-backed fruit bat'': Hutson, A. M.; et al. (2019). [https://www.iucnredlist.org/species/136571/21992386 "''Dobsonia crenulata''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136571A21992386. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T136571A21992386.en 10.2305/IUCN.UK.2019-3.RLTS.T136571A21992386.en].
* ''Lesser naked-backed fruit bat'': Leary, T.; et al. (2020). [https://www.iucnredlist.org/species/6770/22034445 "''Dobsonia minor''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T6770A22034445. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T6770A22034445.en 10.2305/IUCN.UK.2020-3.RLTS.T6770A22034445.en].
* ''New Britain naked-backed fruit bat'': Leary, T.; et al. (2020). [https://www.iucnredlist.org/species/6777/22033332 "''Dobsonia praedatrix''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T6777A22033332. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T6777A22033332.en 10.2305/IUCN.UK.2020-3.RLTS.T6777A22033332.en].
* ''New Guinea naked-backed fruit bat'': Aplin, K.; et al. (2021) [amended version of 2020 assessment]. [https://www.iucnredlist.org/species/84882338/209549260 "''Dobsonia magna''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T84882338A209549260. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T84882338A209549260.en 10.2305/IUCN.UK.2021-3.RLTS.T84882338A209549260.en].
* ''Panniet naked-backed fruit bat'': Leary, T.; et al. (2020). [https://www.iucnredlist.org/species/6776/22034157 "''Dobsonia pannietensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T6776A22034157. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T6776A22034157.en 10.2305/IUCN.UK.2020-3.RLTS.T6776A22034157.en].
* ''Philippine naked-backed fruit bat'': Waldien, D. L. (2020). [https://www.iucnredlist.org/species/6773/22033978 "''Dobsonia chapmani''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T6773A22033978. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T6773A22033978.en 10.2305/IUCN.UK.2020-3.RLTS.T6773A22033978.en].
* ''Solomon's naked-backed fruit bat'': Lavery, T. H.; et al. (2016). [https://www.iucnredlist.org/species/6778/22033222 "''Dobsonia inermis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T6778A22033222. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T6778A22033222.en 10.2305/IUCN.UK.2016-2.RLTS.T6778A22033222.en].
* ''Sulawesi naked-backed fruit bat'': Hutson, A. M.; et al. (2019). [https://www.iucnredlist.org/species/6775/22034230 "''Dobsonia exoleta''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T6775A22034230. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T6775A22034230.en 10.2305/IUCN.UK.2019-3.RLTS.T6775A22034230.en].
* ''Western naked-backed fruit bat'': Hutson, A. M.; et al. (2019). [https://www.iucnredlist.org/species/6771/22034782 "''Dobsonia peronii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T6771A22034782. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T6771A22034782.en 10.2305/IUCN.UK.2019-3.RLTS.T6771A22034782.en].
]
[''Harpyionycteris'' habitats:
* ''Harpy fruit bat'': Duya, M. R.; et al. (2021). [https://www.iucnredlist.org/species/9740/22045044 "''Harpyionycteris whiteheadi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T9740A22045044. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T9740A22045044.en 10.2305/IUCN.UK.2021-1.RLTS.T9740A22045044.en].
* ''Sulawesi harpy fruit bat'': Sheherazade, Waldien; et al. (2021). [https://www.iucnredlist.org/species/136776/22034516 "''Harpyionycteris celebensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T136776A22034516. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T136776A22034516.en 10.2305/IUCN.UK.2021-1.RLTS.T136776A22034516.en].
]
[''Nyctimene'' habitats:
* ''Broad-striped tube-nosed fruit bat'': Armstrong, K. N. (2021). [https://www.iucnredlist.org/species/14954/22008855 "''Nyctimene aello''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T14954A22008855. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T14954A22008855.en 10.2305/IUCN.UK.2021-3.RLTS.T14954A22008855.en].
* ''Common tube-nosed fruit bat'': Aplin, K.; et al. (2021) [amended version of 2016 assessment]. [https://www.iucnredlist.org/species/14962/209535483 "''Nyctimene albiventer''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T14962A209535483. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T14962A209535483.en 10.2305/IUCN.UK.2021-3.RLTS.T14962A209535483.en].
* ''Demonic tube-nosed fruit bat'': Leary, T.; et al. (2020). [https://www.iucnredlist.org/species/14959/22008122 "''Nyctimene masalai''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T14959A22008122. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T14959A22008122.en 10.2305/IUCN.UK.2020-3.RLTS.T14959A22008122.en].
* ''Dragon tube-nosed fruit bat'': Armstrong, K. N. (2021). [https://www.iucnredlist.org/species/14956/22008640 "''Nyctimene draconilla''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T14956A22008640. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T14956A22008640.en 10.2305/IUCN.UK.2021-3.RLTS.T14956A22008640.en].
* ''Eastern tube-nosed bat'': Freudmann, A. (2021). [https://www.iucnredlist.org/species/14966/22007008 "''Nyctimene robinsoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T14966A22007008. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T14966A22007008.en 10.2305/IUCN.UK.2021-2.RLTS.T14966A22007008.en].
* ''Island tube-nosed fruit bat'': Lamoreux, J. (2020). [https://www.iucnredlist.org/species/14965/22007085 "''Nyctimene major''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T14965A22007085. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T14965A22007085.en 10.2305/IUCN.UK.2020-2.RLTS.T14965A22007085.en].
* ''Keast's tube-nosed fruit bat'': Helgen, K.; et al. (2020). [https://www.iucnredlist.org/species/136441/21983677 "''Nyctimene keasti''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T136441A21983677. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T136441A21983677.en 10.2305/IUCN.UK.2020-3.RLTS.T136441A21983677.en].
* ''Lesser tube-nosed bat'': Tsang, S. M.; et al. (2021). [https://www.iucnredlist.org/species/14960/22008183 "''Nyctimene minutus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T14960A22008183. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T14960A22008183.en 10.2305/IUCN.UK.2021-1.RLTS.T14960A22008183.en].
* ''Malaita tube-nosed fruit bat'': Lavery, T. H. (2017). [https://www.iucnredlist.org/species/14958/22008343 "''Nyctimene malaitensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T14958A22008343. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T14958A22008343.en 10.2305/IUCN.UK.2017-2.RLTS.T14958A22008343.en].
* ''Mountain tube-nosed fruit bat'': Armstrong, K. N. (2021). [https://www.iucnredlist.org/species/14964/22007226 "''Nyctimene certans''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T14964A22007226. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T14964A22007226.en 10.2305/IUCN.UK.2021-3.RLTS.T14964A22007226.en].
* ''Nendo tube-nosed fruit bat'': Leary, T.; et al. (2020). [https://www.iucnredlist.org/species/14961/22008025 "''Nyctimene sanctacrucis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T14961A22008025. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T14961A22008025.en 10.2305/IUCN.UK.2020-2.RLTS.T14961A22008025.en].
* ''New Guinea tube-nosed bat'': Armstrong, K. N. (2022). [https://www.iucnredlist.org/species/218361332/218361352 "''Nyctimene wrightae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2022''': e.T218361332A218361352. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2022-2.RLTS.T218361332A218361352.en 10.2305/IUCN.UK.2022-2.RLTS.T218361332A218361352.en].
* ''Pallas's tube-nosed bat'': Tsang, S. M. (2016). [https://www.iucnredlist.org/species/14963/22007414 "''Nyctimene cephalotes''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14963A22007414. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T14963A22007414.en 10.2305/IUCN.UK.2016-2.RLTS.T14963A22007414.en].
* ''Philippine tube-nosed fruit bat'': Ong, P.; et al. (2020). [https://www.iucnredlist.org/species/14953/22008716 "''Nyctimene rabori''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T14953A22008716. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T14953A22008716.en 10.2305/IUCN.UK.2020-3.RLTS.T14953A22008716.en].
* ''Round-eared tube-nosed fruit bat'': Armstrong, K. N. (2021). [https://www.iucnredlist.org/species/14955/22008406 "''Nyctimene cyclotis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T14955A22008406. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T14955A22008406.en 10.2305/IUCN.UK.2021-3.RLTS.T14955A22008406.en].
* ''Umboi tube-nosed fruit bat'': Leary, T.; et al. (2020). [https://www.iucnredlist.org/species/14967/22006804 "''Nyctimene vizcaccia''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T14967A22006804. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T14967A22006804.en 10.2305/IUCN.UK.2020-3.RLTS.T14967A22006804.en].
]
[''Paranyctimene'' habitats:
* ''Lesser tube-nosed fruit bat'': Armstrong, K. N. (2021). [https://www.iucnredlist.org/species/16174/22070463 "''Paranyctimene raptor''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T16174A22070463. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T16174A22070463.en 10.2305/IUCN.UK.2021-3.RLTS.T16174A22070463.en].
* ''Steadfast tube-nosed fruit bat'': Armstrong, K. N. (2021). [https://www.iucnredlist.org/species/136836/22041117 "''Paranyctimene tenax''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T136836A22041117. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T136836A22041117.en 10.2305/IUCN.UK.2021-3.RLTS.T136836A22041117.en].
]
[''Acerodon'' habitats:
* ''Giant golden-crowned flying fox'': Mildenstein, T.; et al. (2016). [https://www.iucnredlist.org/species/139/21988328 "''Acerodon jubatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T139A21988328. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T139A21988328.en 10.2305/IUCN.UK.2016-2.RLTS.T139A21988328.en].
* ''Palawan fruit bat'': Mildenstein, T.; et al. (2020). [https://www.iucnredlist.org/species/140/21988055 "''Acerodon leucotis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T140A21988055. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T140A21988055.en 10.2305/IUCN.UK.2020-3.RLTS.T140A21988055.en].
* ''Sulawesi flying fox'': Sheherazade, Tsang; et al. (2022). [https://www.iucnredlist.org/species/137/220501878 "''Acerodon celebensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2022''': e.T137A220501878. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2022-2.RLTS.T137A220501878.en 10.2305/IUCN.UK.2022-2.RLTS.T137A220501878.en].
* ''Sunda flying fox'': Mildenstein, T. . (2016). [https://www.iucnredlist.org/species/142/21989107 "''Acerodon mackloti''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T142A21989107. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T142A21989107.en 10.2305/IUCN.UK.2016-1.RLTS.T142A21989107.en].
* ''Talaud flying fox'': Mildenstein, T. (2017) [errata version of 2016 assessment]. [https://www.iucnredlist.org/species/138/115517951 "''Acerodon humilis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T138A115517951. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T138A21988535.en 10.2305/IUCN.UK.2016-3.RLTS.T138A21988535.en].
]
[''Desmalopex'' habitats:
* ''Small white-winged flying fox'', ''White-winged flying fox'': Cielo, K. L. S.; et al. (2019). [https://www.iucnredlist.org/species/84457227/84457393 "''Desmalopex microleucopterus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T84457227A84457393. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T84457227A84457393.en 10.2305/IUCN.UK.2019-3.RLTS.T84457227A84457393.en].
]
[Scanlon, A. (2019). [https://www.iucnredlist.org/species/18655/22071017 "''Mirimiri acrodonta''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T18655A22071017. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T18655A22071017.en 10.2305/IUCN.UK.2019-3.RLTS.T18655A22071017.en].]
[Tsang, S. M. (2017) [errata version of 2016 assessment]. [https://www.iucnredlist.org/species/14560/115122474 "''Neopteryx frosti''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14560A115122474. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T14560A22032953.en 10.2305/IUCN.UK.2016-3.RLTS.T14560A22032953.en].]
[''Pteralopex'' habitats:
* ''Bougainville monkey-faced bat'': Lavery, T. H. (2017). [https://www.iucnredlist.org/species/18656/22071126 "''Pteralopex anceps''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T18656A22071126. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T18656A22071126.en 10.2305/IUCN.UK.2017-2.RLTS.T18656A22071126.en].
* ''Greater monkey-faced bat'': Lavery, T. H. (2017). [https://www.iucnredlist.org/species/136587/21998747 "''Pteralopex flanneryi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T136587A21998747. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T136587A21998747.en 10.2305/IUCN.UK.2017-2.RLTS.T136587A21998747.en].
* ''Guadalcanal monkey-faced bat'': Lavery, T. H. (2017). [https://www.iucnredlist.org/species/18657/22074222 "''Pteralopex atrata''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T18657A22074222. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T18657A22074222.en 10.2305/IUCN.UK.2017-2.RLTS.T18657A22074222.en].
* ''Montane monkey-faced bat'': Lavery, T. H. (2018) [amended version of 2017 assessment]. [https://www.iucnredlist.org/species/18658/128950188 "''Pteralopex pulchra''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T18658A128950188. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-1.RLTS.T18658A128950188.en 10.2305/IUCN.UK.2018-1.RLTS.T18658A128950188.en].
* ''New Georgian monkey-faced bat'': Lavery, T. H. (2017). [https://www.iucnredlist.org/species/29473/22066155 "''Pteralopex taki''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T29473A22066155. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T29473A22066155.en 10.2305/IUCN.UK.2017-2.RLTS.T29473A22066155.en].
]
[''Pteropus'' habitats:
* ''Admiralty flying fox'': Lavery, T. H.; et al. (2020). [https://www.iucnredlist.org/species/18713/22079752 "''Pteropus admiralitatum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T18713A22079752. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T18713A22079752.en 10.2305/IUCN.UK.2020-2.RLTS.T18713A22079752.en].
* ''Aldabra flying fox'': Waldien, D. L.; et al. (2020). [https://www.iucnredlist.org/species/18714/22079192 "''Pteropus aldabrensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T18714A22079192. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T18714A22079192.en 10.2305/IUCN.UK.2020-2.RLTS.T18714A22079192.en].
* ''Andersen's flying fox'': Soisook, P.; et al. (2020). [https://www.iucnredlist.org/species/136841/22042098 "''Pteropus intermedius''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T136841A22042098. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T136841A22042098.en 10.2305/IUCN.UK.2020-2.RLTS.T136841A22042098.en].
* ''Aru flying fox'': Tsang, S. M. (2016). [https://www.iucnredlist.org/species/136504/21974958 "''Pteropus aruensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136504A21974958. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T136504A21974958.en 10.2305/IUCN.UK.2016-2.RLTS.T136504A21974958.en].
* ''Ashy-headed flying fox'': Tsang, S. M. (2016). [https://www.iucnredlist.org/species/18719/22079034 "''Pteropus caniceps''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T18719A22079034. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T18719A22079034.en 10.2305/IUCN.UK.2016-2.RLTS.T18719A22079034.en].
* ''Banks flying fox'': Lavery, T. H.; et al. (2020). [https://www.iucnredlist.org/species/18724/22080348 "''Pteropus fundatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T18724A22080348. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T18724A22080348.en 10.2305/IUCN.UK.2020-2.RLTS.T18724A22080348.en].
* ''Big-eared flying fox'': Leary, T.; et al. (2020). [https://www.iucnredlist.org/species/18735/22082074 "''Pteropus macrotis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T18735A22082074. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T18735A22082074.en 10.2305/IUCN.UK.2020-3.RLTS.T18735A22082074.en].
* ''Bismarck masked flying fox'': Pennay, M.; et al. (2021). [https://www.iucnredlist.org/species/84891540/22012219 "''Pteropus capistratus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T84891540A22012219. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T84891540A22012219.en 10.2305/IUCN.UK.2021-3.RLTS.T84891540A22012219.en].
* ''Black flying fox'': Roberts, B.; et al. (2017). [https://www.iucnredlist.org/species/18715/22080057 "''Pteropus alecto''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T18715A22080057. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T18715A22080057.en 10.2305/IUCN.UK.2017-2.RLTS.T18715A22080057.en].
* ''Black-bearded flying fox'': Tsang, S. (2016). [https://www.iucnredlist.org/species/18739/22082983 "''Pteropus melanopogon''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T18739A22082983. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T18739A22082983.en 10.2305/IUCN.UK.2016-3.RLTS.T18739A22082983.en].
* ''Black-eared flying fox'': Todd, C. M.; et al. (2021). [https://www.iucnredlist.org/species/18740/22082634 "''Pteropus melanotus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T18740A22082634. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T18740A22082634.en 10.2305/IUCN.UK.2021-3.RLTS.T18740A22082634.en].
* ''Bonin flying fox'': Vincenot, C. (2017). [https://www.iucnredlist.org/species/18752/22085351 "''Pteropus pselaphon''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T18752A22085351. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T18752A22085351.en 10.2305/IUCN.UK.2017-2.RLTS.T18752A22085351.en].
* ''Caroline flying fox'': Waldien, D. L.; et al. (2020). [https://www.iucnredlist.org/species/18741/22084572 "''Pteropus molossinus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T18741A22084572. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T18741A22084572.en 10.2305/IUCN.UK.2020-2.RLTS.T18741A22084572.en].
* ''Ceram fruit bat'': Tsang, S. M. (2017) [errata version of 2016 assessment]. [https://www.iucnredlist.org/species/18745/115145424 "''Pteropus ocularis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T18745A115145424. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T18745A22085054.en 10.2305/IUCN.UK.2016-3.RLTS.T18745A22085054.en].
* ''Chuuk flying fox'': Wiles, G. (2020). [https://www.iucnredlist.org/species/85043053/22081930 "''Pteropus pelagicus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T85043053A22081930. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T85043053A22081930.en 10.2305/IUCN.UK.2020-2.RLTS.T85043053A22081930.en].
* ''Dwarf flying fox'': Lavery, T. H.; et al. (2017). [https://www.iucnredlist.org/species/18769/22089578 "''Pteropus woodfordi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T18769A22089578. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T18769A22089578.en 10.2305/IUCN.UK.2017-2.RLTS.T18769A22089578.en].
* ''Geelvink Bay flying fox'': Mildenstein, T. (2016). [https://www.iucnredlist.org/species/18750/22085786 "''Pteropus pohlei''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T18750A22085786. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T18750A22085786.en 10.2305/IUCN.UK.2016-1.RLTS.T18750A22085786.en].
* ''Gilliard's flying fox'': Leary, T.; et al. (2020). [https://www.iucnredlist.org/species/18726/22081235 "''Pteropus gilliardorum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T18726A22081235. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T18726A22081235.en 10.2305/IUCN.UK.2020-2.RLTS.T18726A22081235.en].
* ''Gray flying fox'': Tsang, S. M.; et al. (2020). [https://www.iucnredlist.org/species/18727/22080757 "''Pteropus griseus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T18727A22080757. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T18727A22080757.en 10.2305/IUCN.UK.2020-3.RLTS.T18727A22080757.en].
* ''Great flying fox'': Leary, T.; et al. (2020). [https://www.iucnredlist.org/species/18742/22084430 "''Pteropus neohibernicus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T18742A22084430. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T18742A22084430.en 10.2305/IUCN.UK.2020-3.RLTS.T18742A22084430.en].
* ''Grey-headed flying fox'': Eby, P.; et al. (2021). [https://www.iucnredlist.org/species/18751/22085511 "''Pteropus poliocephalus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T18751A22085511. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T18751A22085511.en 10.2305/IUCN.UK.2021-3.RLTS.T18751A22085511.en].
* ''Indian flying fox'': Ahmed, T.; et al. (2024). [https://www.iucnredlist.org/species/18725/230958344 "''Pteropus medius''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2024''': e.T18725A230958344. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2024-2.RLTS.T18725A230958344.en 10.2305/IUCN.UK.2024-2.RLTS.T18725A230958344.en].
* ''Insular flying fox'': Lavery, T. H.; et al. (2020). [https://www.iucnredlist.org/species/18764/22088495 "''Pteropus tonganus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T18764A22088495. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T18764A22088495.en 10.2305/IUCN.UK.2020-2.RLTS.T18764A22088495.en].
* ''Kei flying fox'': Tsang, S. M. (2016). [https://www.iucnredlist.org/species/136528/21980435 "''Pteropus keyensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136528A21980435. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T136528A21980435.en 10.2305/IUCN.UK.2016-2.RLTS.T136528A21980435.en].
* ''Kosrae flying fox'': Hayes, F. E.; et al. (2020). [https://www.iucnredlist.org/species/136531/21979719 "''Pteropus ualanus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T136531A21979719. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T136531A21979719.en 10.2305/IUCN.UK.2020-3.RLTS.T136531A21979719.en].
* ''Large flying fox'': Mildenstein, T.; et al. (2022). [https://www.iucnredlist.org/species/18766/22088824 "''Pteropus vampyrus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2022''': e.T18766A22088824. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2022-2.RLTS.T18766A22088824.en 10.2305/IUCN.UK.2022-2.RLTS.T18766A22088824.en].
* ''Lesser flying fox'': Lavery, T. H. (2017). [https://www.iucnredlist.org/species/18736/22082180 "''Pteropus mahaganus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T18736A22082180. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T18736A22082180.en 10.2305/IUCN.UK.2017-2.RLTS.T18736A22082180.en].
* ''Little golden-mantled flying fox'': Heaney, L.; et al. (2020). [https://www.iucnredlist.org/species/18753/22086307 "''Pteropus pumilus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T18753A22086307. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T18753A22086307.en 10.2305/IUCN.UK.2020-2.RLTS.T18753A22086307.en].
* ''Little red flying fox'': Eby, P.; et al. (2016). [https://www.iucnredlist.org/species/18758/22087637 "''Pteropus scapulatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T18758A22087637. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T18758A22087637.en 10.2305/IUCN.UK.2016-1.RLTS.T18758A22087637.en].
* ''Livingstone's fruit bat'': Sewall, B. J.; et al. (2016). [https://www.iucnredlist.org/species/18732/22081502 "''Pteropus livingstonii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T18732A22081502. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T18732A22081502.en 10.2305/IUCN.UK.2016-2.RLTS.T18732A22081502.en].
* ''Lombok flying fox'': Tsang, S. M. (2016). [https://www.iucnredlist.org/species/18733/22082270 "''Pteropus lombocensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T18733A22082270. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T18733A22082270.en 10.2305/IUCN.UK.2016-2.RLTS.T18733A22082270.en].
* ''Lyle's flying fox'': Waldien, D. L.; et al. (2021). [https://www.iucnredlist.org/species/18734/22082429 "''Pteropus lylei''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T18734A22082429. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T18734A22082429.en 10.2305/IUCN.UK.2021-1.RLTS.T18734A22082429.en].
* ''Madagascan flying fox'': Racey, P. A. (2016). [https://www.iucnredlist.org/species/18756/22087230 "''Pteropus rufus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T18756A22087230. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T18756A22087230.en 10.2305/IUCN.UK.2016-1.RLTS.T18756A22087230.en].
* ''Makira flying fox'': Lavery, T. H. (2017). [https://www.iucnredlist.org/species/136397/22014516 "''Pteropus cognatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T136397A22014516. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T136397A22014516.en 10.2305/IUCN.UK.2017-2.RLTS.T136397A22014516.en].
* ''Mariana fruit bat'': Mildenstein, T. (2020). [https://www.iucnredlist.org/species/188566753/22083400 "''Pteropus mariannus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T188566753A22083400. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T188566753A22083400.en 10.2305/IUCN.UK.2020-3.RLTS.T188566753A22083400.en].
* ''Masked flying fox'': Tsang, S. M. (2016). [https://www.iucnredlist.org/species/18747/22084787 "''Pteropus personatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T18747A22084787. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T18747A22084787.en 10.2305/IUCN.UK.2016-2.RLTS.T18747A22084787.en].
* ''Mauritian flying fox'': Kingston, T.; et al. (2018). [https://www.iucnredlist.org/species/18743/86475525 "''Pteropus niger''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T18743A86475525. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-1.RLTS.T18743A86475525.en 10.2305/IUCN.UK.2018-1.RLTS.T18743A86475525.en].
* ''Moluccan flying fox'': Tsang, S. M. (2016). [https://www.iucnredlist.org/species/99688187/22078625 "''Pteropus chrysoproctus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T99688187A22078625. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T99688187A22078625.en 10.2305/IUCN.UK.2016-3.RLTS.T99688187A22078625.en].
* ''New Caledonia flying fox'': Brescia, F. (2020). [https://www.iucnredlist.org/species/18767/22089080 "''Pteropus vetulus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T18767A22089080. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T18767A22089080.en 10.2305/IUCN.UK.2020-2.RLTS.T18767A22089080.en].
* ''New Ireland masked flying fox'': Tsang, S. M.; et al. (2022). [https://www.iucnredlist.org/species/84883915/209887353 "''Pteropus ennisae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2022''': e.T84883915A209887353. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2022-1.RLTS.T84883915A209887353.en 10.2305/IUCN.UK.2022-1.RLTS.T84883915A209887353.en].
* ''Nicobar flying fox'': Tsang, S. M.; et al. (2019). [https://www.iucnredlist.org/species/18723/22080230 "''Pteropus faunulus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T18723A22080230. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T18723A22080230.en 10.2305/IUCN.UK.2019-3.RLTS.T18723A22080230.en].
* ''Okinawa flying fox'': Fukui, D. (2020). [https://www.iucnredlist.org/species/18773/22089728 "''Pteropus loochoensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T18773A22089728. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T18773A22089728.en 10.2305/IUCN.UK.2020-2.RLTS.T18773A22089728.en].
* ''Ontong Java flying fox'': Fisher, D.; et al. (2021). [https://www.iucnredlist.org/species/18728/22080900 "''Pteropus howensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T18728A22080900. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T18728A22080900.en 10.2305/IUCN.UK.2021-1.RLTS.T18728A22080900.en].
* ''Ornate flying fox'': Brescia, F.; et al. (2020). [https://www.iucnredlist.org/species/18746/22084917 "''Pteropus ornatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T18746A22084917. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T18746A22084917.en 10.2305/IUCN.UK.2020-2.RLTS.T18746A22084917.en].
* ''Pelew flying fox'': Wiles, G.; et al. (2021) [amended version of 2020 assessment]. [https://www.iucnredlist.org/species/118093652/206768055 "''Pteropus pelewensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T118093652A206768055. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T118093652A206768055.en 10.2305/IUCN.UK.2021-3.RLTS.T118093652A206768055.en].
* ''Pemba flying fox'': Entwistle, A. C.; et al. (2016). [https://www.iucnredlist.org/species/18768/22089205 "''Pteropus voeltzkowi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T18768A22089205. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T18768A22089205.en 10.2305/IUCN.UK.2016-1.RLTS.T18768A22089205.en].
* ''Philippine gray flying fox'': Tsang, S. M.; et al. (2020). [https://www.iucnredlist.org/species/18760/22087948 "''Pteropus speciosus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T18760A22087948. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T18760A22087948.en 10.2305/IUCN.UK.2020-2.RLTS.T18760A22087948.en].
* ''Rennell flying fox'': Lavery, T. H. (2017). [https://www.iucnredlist.org/species/136685/22038028 "''Pteropus rennelli''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T136685A22038028. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T136685A22038028.en 10.2305/IUCN.UK.2017-2.RLTS.T136685A22038028.en].
* ''Rodrigues flying fox'': Tatayah, V.; et al. (2017). [https://www.iucnredlist.org/species/18755/22087057 "''Pteropus rodricensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T18755A22087057. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T18755A22087057.en 10.2305/IUCN.UK.2017-2.RLTS.T18755A22087057.en].
* ''Ryukyu flying fox'': Vincenot, C. (2017). [https://www.iucnredlist.org/species/18722/22080614 "''Pteropus dasymallus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T18722A22080614. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T18722A22080614.en 10.2305/IUCN.UK.2017-2.RLTS.T18722A22080614.en].
* ''Samoa flying fox'': Scanlon, A.; et al. (2020). [https://www.iucnredlist.org/species/18757/22087415 "''Pteropus samoensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T18757A22087415. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T18757A22087415.en 10.2305/IUCN.UK.2020-2.RLTS.T18757A22087415.en].
* ''Seychelles fruit bat'': Bergmans, W.; et al. (2017). [https://www.iucnredlist.org/species/18759/22087745 "''Pteropus seychellensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T18759A22087745. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T18759A22087745.en 10.2305/IUCN.UK.2017-2.RLTS.T18759A22087745.en].
* ''Small flying fox'': Tsang, S. M. (2020). [https://www.iucnredlist.org/species/18729/22081642 "''Pteropus hypomelanus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T18729A22081642. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T18729A22081642.en 10.2305/IUCN.UK.2020-2.RLTS.T18729A22081642.en].
* ''Solomons flying fox'': Lavery, T. H. (2017). [https://www.iucnredlist.org/species/18754/22086707 "''Pteropus rayneri''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T18754A22086707. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T18754A22086707.en 10.2305/IUCN.UK.2017-2.RLTS.T18754A22086707.en].
* ''Spectacled flying fox'': Roberts, B.; et al. (2020). [https://www.iucnredlist.org/species/18721/22080456 "''Pteropus conspicillatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T18721A22080456. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T18721A22080456.en 10.2305/IUCN.UK.2020-3.RLTS.T18721A22080456.en].
* ''Temminck's flying fox'': Tsang, S. (2016). [https://www.iucnredlist.org/species/18762/22088270 "''Pteropus temminckii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T18762A22088270. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T18762A22088270.en 10.2305/IUCN.UK.2016-2.RLTS.T18762A22088270.en].
* ''Temotu flying fox'': Leary, T.; et al. (2020). [https://www.iucnredlist.org/species/18744/22083923 "''Pteropus nitendiensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T18744A22083923. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T18744A22083923.en 10.2305/IUCN.UK.2020-2.RLTS.T18744A22083923.en].
* ''Vanikoro flying fox'': Lavery, T. H.; et al. (2020). [https://www.iucnredlist.org/species/18765/22088712 "''Pteropus tuberculatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T18765A22088712. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T18765A22088712.en 10.2305/IUCN.UK.2020-2.RLTS.T18765A22088712.en].
* ''Vanuatu flying fox'': Leary, T.; et al. (2020). [https://www.iucnredlist.org/species/18716/22079958 "''Pteropus anetianus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T18716A22079958. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T18716A22079958.en 10.2305/IUCN.UK.2020-3.RLTS.T18716A22079958.en].
]
[''Styloctenium'' habitats:
* ''Mindoro stripe-faced fruit bat'': Cielo, K. L. S.; et al. (2019). [https://www.iucnredlist.org/species/136534/21979633 "''Styloctenium mindorensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136534A21979633. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T136534A21979633.en 10.2305/IUCN.UK.2019-3.RLTS.T136534A21979633.en].
* ''Sulawesi stripe-faced fruit bat'': Sheherazade (2021). [https://www.iucnredlist.org/species/21100/203829571 "''Styloctenium wallacei''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T21100A203829571. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T21100A203829571.en 10.2305/IUCN.UK.2021-3.RLTS.T21100A203829571.en].
]
[''Casinycteris'' habitats:
* ''Campo-Ma'an fruit bat'': Hassanin, A. (2022) [errata version of 2017 assessment]. [https://www.iucnredlist.org/species/84455300/214846046 "''Casinycteris campomaanensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T84455300A214846046.
* ''Short-palated fruit bat'': Webala, P.; et al. (2019) [errata version of 2016 assessment]. [https://www.iucnredlist.org/species/7787/22128326 "''Casinycteris argynnis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T3999A145600125. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T3999A145600125.en 10.2305/IUCN.UK.2016-1.RLTS.T3999A145600125.en].
]
[''Eonycteris'' habitats:
* ''Cave nectar bat'': Waldien, D. L.; et al. (2020). [https://www.iucnredlist.org/species/7787/22128326 "''Eonycteris spelaea''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T7787A22128326. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T7787A22128326.en 10.2305/IUCN.UK.2020-3.RLTS.T7787A22128326.en].
* ''Greater nectar bat'': Waldien, D. L.; et al. (2021). [https://www.iucnredlist.org/species/7786/22128071 "''Eonycteris major''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T7786A22128071. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T7786A22128071.en 10.2305/IUCN.UK.2021-1.RLTS.T7786A22128071.en].
* ''Philippine dawn bat'': Waldien, D. L.; et al. (2020). [https://www.iucnredlist.org/species/136768/22036300 "''Eonycteris robusta''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T136768A22036300. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T136768A22036300.en 10.2305/IUCN.UK.2020-3.RLTS.T136768A22036300.en].
]
[''Epomophorus'' habitats:
* ''Angolan epauletted fruit bat'': Mildenstein, T. (2016). [https://www.iucnredlist.org/species/7901/22122903 "''Epomophorus angolensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T7901A22122903. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T7901A22122903.en 10.2305/IUCN.UK.2016-1.RLTS.T7901A22122903.en].
* ''Ansell's epauletted fruit bat'': Mildenstein, T. (2016). [https://www.iucnredlist.org/species/136351/22024470 "''Epomophorus anselli''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136351A22024470. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T136351A22024470.en 10.2305/IUCN.UK.2016-1.RLTS.T136351A22024470.en].
* ''Dobson's epauletted fruit bat'': Taylor, P. (2016). [https://www.iucnredlist.org/species/7908/22116665 "''Epomops dobsonii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T7908A22116665. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T7908A22116665.en 10.2305/IUCN.UK.2016-1.RLTS.T7908A22116665.en].
* ''East African epauletted fruit bat'': Webala, P. (2016). [https://www.iucnredlist.org/species/7905/22117065 "''Epomophorus minimus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T7905A22117065. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T7905A22117065.en 10.2305/IUCN.UK.2016-2.RLTS.T7905A22117065.en].
* ''Ethiopian epauletted fruit bat'': Taylor, P. (2016). [https://www.iucnredlist.org/species/84457881/22122505 "''Epomophorus labiatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T84457881A22122505. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T84457881A22122505.en 10.2305/IUCN.UK.2016-1.RLTS.T84457881A22122505.en].
* ''Gambian epauletted fruit bat'': Tanshi, I.; et al. (2016). [https://www.iucnredlist.org/species/7903/22122670 "''Epomophorus gambianus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T7903A22122670. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T7903A22122670.en 10.2305/IUCN.UK.2016-2.RLTS.T7903A22122670.en].
* ''Hayman's dwarf epauletted fruit bat'': Mickleburgh, S.; et al. (2020). [https://www.iucnredlist.org/species/13401/22126321 "''Epomophorus intermedius''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T13401A22126321. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T13401A22126321.en 10.2305/IUCN.UK.2020-3.RLTS.T13401A22126321.en].
* ''Lesser Angolan epauletted fruit bat'': Fahr, J.; et al. (2016). [https://www.iucnredlist.org/species/7902/22122832 "''Epomophorus grandis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T7902A22122832. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T7902A22122832.en 10.2305/IUCN.UK.2016-1.RLTS.T7902A22122832.en].
* ''Minor epauletted fruit bat'': Taylor, P. (2016). [https://www.iucnredlist.org/species/84458822/84458832 "''Epomophorus minor''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T84458822A84458832. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T84458822A84458832.en 10.2305/IUCN.UK.2016-1.RLTS.T84458822A84458832.en].
* ''Peters's dwarf epauletted fruit bat'': Bakwo Fils, E. M.; et al. (2020) [amended version of 2016 assessment]. [https://www.iucnredlist.org/species/13402/166518027 "''Epomophorus pusillus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T13402A166518027. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-1.RLTS.T13402A166518027.en 10.2305/IUCN.UK.2020-1.RLTS.T13402A166518027.en].
* ''Peters's epauletted fruit bat'': Taylor, P. (2016). [https://www.iucnredlist.org/species/44697/22073767 "''Epomophorus crypturus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T44697A22073767. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T44697A22073767.en 10.2305/IUCN.UK.2016-1.RLTS.T44697A22073767.en].
* ''Wahlberg's epauletted fruit bat'': Shoeman, C. (2016). [https://www.iucnredlist.org/species/7906/22116891 "''Epomophorus wahlbergi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T7906A22116891. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T7906A22116891.en 10.2305/IUCN.UK.2016-1.RLTS.T7906A22116891.en].
]
[''Epomops'' habitats:
* ''Buettikofer's epauletted fruit bat'': Monadjem, A. (2016). [https://www.iucnredlist.org/species/7907/22116763 "''Epomops buettikoferi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T7907A22116763. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T7907A22116763.en 10.2305/IUCN.UK.2016-1.RLTS.T7907A22116763.en].
* ''Franquet's epauletted fruit bat'': Kityo, R.; et al. (2020) [amended version of 2016 assessment]. [https://www.iucnredlist.org/species/7909/166505893 "''Epomops franqueti''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T7909A166505893. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-1.RLTS.T7909A166505893.en 10.2305/IUCN.UK.2020-1.RLTS.T7909A166505893.en].
]
[Tanshi, I. (2017) [errata version of 2016 assessment]. [https://www.iucnredlist.org/species/10734/115098825 "''Hypsignathus monstrosus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T10734A115098825. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T10734A21999919.en 10.2305/IUCN.UK.2016-3.RLTS.T10734A21999919.en].]
[''Megaloglossus'' habitats:
* ''Azagnyi fruit bat'': Monadjem, A. (2016). [https://www.iucnredlist.org/species/84459322/84462595 "''Megaloglossus azagnyi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T84459322A84462595. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T84459322A84462595.en 10.2305/IUCN.UK.2016-1.RLTS.T84459322A84462595.en].
* ''Woermann's bat'': Bakwo Fils, E. M.; et al. (2020) [amended version of 2016 assessment]. [https://www.iucnredlist.org/species/84462869/166504706 "''Megaloglossus woermanni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T84462869A166504706. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-1.RLTS.T84462869A166504706.en 10.2305/IUCN.UK.2020-1.RLTS.T84462869A166504706.en].
]
[''Myonycteris'' habitats:
* ''Angolan rousette'': Bergmans, W.; et al. (2017). [https://www.iucnredlist.org/species/44698/22073874 "''Lissonycteris angolensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T44698A22073874. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T44698A22073874.en 10.2305/IUCN.UK.2017-2.RLTS.T44698A22073874.en].
* ''East African little collared fruit bat'': Taylor, P. (2016). [https://www.iucnredlist.org/species/14098/22046760 "''Myonycteris relicta''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14098A22046760. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T14098A22046760.en 10.2305/IUCN.UK.2016-1.RLTS.T14098A22046760.en].
* ''Little collared fruit bat'': Bakwo Fils, E. M.; et al. (2016). [https://www.iucnredlist.org/species/84463104/22046504 "''Myonycteris torquata''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T84463104A22046504. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T84463104A22046504.en 10.2305/IUCN.UK.2016-1.RLTS.T84463104A22046504.en].
* ''Sierra Leone collared fruit bat'': Monadjem, A. (2020) [amended version of 2016 assessment]. [https://www.iucnredlist.org/species/84463728/166525357 "''Myonycteris leptodon''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T84463728A166525357. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-1.RLTS.T84463728A166525357.en 10.2305/IUCN.UK.2020-1.RLTS.T84463728A166525357.en].
* ''São Tomé collared fruit bat'': Juste, J. (2016). [https://www.iucnredlist.org/species/14097/22046657 "''Myonycteris brachycephala''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14097A22046657. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T14097A22046657.en 10.2305/IUCN.UK.2016-2.RLTS.T14097A22046657.en].
]
[Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/14333/22043635 "''Nanonycteris veldkampii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T14333A22043635. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T14333A22043635.en 10.2305/IUCN.UK.2017-2.RLTS.T14333A22043635.en].]
[Wiantoro, S.; et al. (2020). [https://www.iucnredlist.org/species/19755/22000964 "''Rousettus celebensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T19755A22000964. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T19755A22000964.en 10.2305/IUCN.UK.2020-2.RLTS.T19755A22000964.en].]
[Stone, E. (2021). [https://www.iucnredlist.org/species/17618/21981114 "''Plerotes anchietae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T17618A21981114. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T17618A21981114.en 10.2305/IUCN.UK.2021-1.RLTS.T17618A21981114.en].]
[''Rousettus'' habitats:
* ''Bare-backed rousette'': Francis, C. M.; et al. (2021). [https://www.iucnredlist.org/species/19751/22002553 "''Rousettus spinalatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T19751A22002553. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T19751A22002553.en 10.2305/IUCN.UK.2021-2.RLTS.T19751A22002553.en].
* ''Comoro rousette'': Sewall, B. J. (2020) [amended version of 2016 assessment]. [https://www.iucnredlist.org/species/19757/166527449 "''Rousettus obliviosus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T19757A166527449. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-1.RLTS.T19757A166527449.en 10.2305/IUCN.UK.2020-1.RLTS.T19757A166527449.en].
* ''Egyptian fruit bat'': Korine, C. (2016). [https://www.iucnredlist.org/species/29730/22043105 "''Rousettus aegyptiacus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T29730A22043105. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T29730A22043105.en 10.2305/IUCN.UK.2016-2.RLTS.T29730A22043105.en].
* ''Geoffroy's rousette'': Waldien, D. L.; et al. (2019). [https://www.iucnredlist.org/species/19754/22001514 "''Rousettus amplexicaudatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T19754A22001514. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T19754A22001514.en 10.2305/IUCN.UK.2019-3.RLTS.T19754A22001514.en].
* ''Leschenault's rousette'': Bouillard, N.; et al. (2021). [https://www.iucnredlist.org/species/19756/22001287 "''Rousettus leschenaultii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T19756A22001287. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T19756A22001287.en 10.2305/IUCN.UK.2021-3.RLTS.T19756A22001287.en].
* ''Linduan rousette'': Wiantoro, S.; et al. (2020). [https://www.iucnredlist.org/species/136593/21996293 "''Rousettus linduensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T136593A21996293. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T136593A21996293.en 10.2305/IUCN.UK.2020-2.RLTS.T136593A21996293.en].
* ''Madagascan rousette'': Andrianaivoarivelo, R.; et al. (2019). [https://www.iucnredlist.org/species/19750/22002909 "''Rousettus madagascariensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T19750A22002909. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T19750A22002909.en 10.2305/IUCN.UK.2019-3.RLTS.T19750A22002909.en].
]
[''Scotonycteris'' habitats:
* ''Bergmans's fruit bat'': Hassanin, A. (2020). [https://www.iucnredlist.org/species/84466436/84466645 "''Scotonycteris bergmansi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T84466436A84466645. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T84466436A84466645.en 10.2305/IUCN.UK.2020-2.RLTS.T84466436A84466645.en].
* ''Hayman's fruit bat'': Tanshi, I. (2021). [https://www.iucnredlist.org/species/84466273/84466694 "''Scotonycteris occidentalis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T84466273A84466694. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T84466273A84466694.en 10.2305/IUCN.UK.2021-1.RLTS.T84466273A84466694.en].
* ''Zenker's fruit bat'': Obitte, B. (2021). [https://www.iucnredlist.org/species/84464403/192236400 "''Scotonycteris zenkeri''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T84464403A192236400. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T84464403A192236400.en 10.2305/IUCN.UK.2021-1.RLTS.T84464403A192236400.en].
]
[Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/19758/22001971 "''Rousettus lanosus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T19758A22001971. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T19758A22001971.en 10.2305/IUCN.UK.2017-2.RLTS.T19758A22001971.en].]
[''Macroglossus'' habitats:
* ''Long-tongued fruit bat'': Hutson, A. M.; et al. (2021). [https://www.iucnredlist.org/species/12595/22027530 "''Macroglossus sobrinus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T12595A22027530. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T12595A22027530.en 10.2305/IUCN.UK.2021-1.RLTS.T12595A22027530.en].
* ''Long-tongued nectar bat'': Waldien, D. L.; et al. (2021). [https://www.iucnredlist.org/species/12594/22027337 "''Macroglossus minimus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T12594A22027337. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T12594A22027337.en 10.2305/IUCN.UK.2021-3.RLTS.T12594A22027337.en].
]
[Pennay, M. (2021). [https://www.iucnredlist.org/species/13139/21977021 "''Melonycteris melanops''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T13139A21977021. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T13139A21977021.en 10.2305/IUCN.UK.2021-3.RLTS.T13139A21977021.en].]
[''Nesonycteris'' habitats:
* ''Fardoulis's blossom bat'': Lavery, T. H.; et al. (2020). [https://www.iucnredlist.org/species/13141/21978862 "''Melonycteris fardoulisi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T13141A21978862. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T13141A21978862.en 10.2305/IUCN.UK.2020-2.RLTS.T13141A21978862.en].
* ''Woodford's fruit bat'': Lavery, T. H. (2017). [https://www.iucnredlist.org/species/13140/21977332 "''Melonycteris woodfordi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T13140A21977332. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T13140A21977332.en 10.2305/IUCN.UK.2017-2.RLTS.T13140A21977332.en].
]
[''Notopteris'' habitats:
* ''Long-tailed fruit bat'': Scanlon, A. (2019). [https://www.iucnredlist.org/species/14876/22023433 "''Notopteris macdonaldi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T14876A22023433. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T14876A22023433.en 10.2305/IUCN.UK.2019-3.RLTS.T14876A22023433.en].
* ''New Caledonia blossom bat'': Brescia, F.; et al. (2019). [https://www.iucnredlist.org/species/136519/21982137 "''Notopteris neocaledonica''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136519A21982137. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T136519A21982137.en 10.2305/IUCN.UK.2019-3.RLTS.T136519A21982137.en].
]
[''Syconycteris'' habitats:
* ''Common blossom bat'': Aplin, K.; et al. (2021) [amended version of 2016 assessment]. [https://www.iucnredlist.org/species/21185/209535645 "''Syconycteris australis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T21185A209535645. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T21185A209535645.en 10.2305/IUCN.UK.2021-3.RLTS.T21185A209535645.en].
* ''Halmahera blossom bat'': Waldien, D. L.; et al. (2021). [https://www.iucnredlist.org/species/21184/22125551 "''Syconycteris carolinae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T21184A22125551. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T21184A22125551.en 10.2305/IUCN.UK.2021-1.RLTS.T21184A22125551.en].
* ''Moss-forest blossom bat'': Aplin, K.; et al. (2021) [amended version of 2016 assessment]. [https://www.iucnredlist.org/species/21183/209535849 "''Syconycteris hobbit''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T21183A209535849. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T21183A209535849.en 10.2305/IUCN.UK.2021-3.RLTS.T21183A209535849.en].
]
[[[#CITEREF_ALLMAM|Chernasky; Motis; Burgin]], pp. 475–483]
[''Rhinolophus'' habitats:
* ''Acuminate horseshoe bat'': Thong, V. D.; et al. (2019). [https://www.iucnredlist.org/species/19520/21974227 "''Rhinolophus acuminatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T19520A21974227. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T19520A21974227.en 10.2305/IUCN.UK.2019-3.RLTS.T19520A21974227.en].
* ''Adam's horseshoe bat'': Jacobs, D.; et al. (2019). [https://www.iucnredlist.org/species/19521/21982298 "''Rhinolophus adami''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T19521A21982298. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T19521A21982298.en 10.2305/IUCN.UK.2019-3.RLTS.T19521A21982298.en].
* ''Andaman horseshoe bat'': Aul, B.; et al. (2016). [https://www.iucnredlist.org/species/19533/21981807 "''Rhinolophus cognatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T19533A21981807. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T19533A21981807.en 10.2305/IUCN.UK.2016-2.RLTS.T19533A21981807.en].
* ''Arcuate horseshoe bat'': Alviola, P. A.; et al. (2021). [https://www.iucnredlist.org/species/84372137/21983371 "''Rhinolophus arcuatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T84372137A21983371. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T84372137A21983371.en 10.2305/IUCN.UK.2021-3.RLTS.T84372137A21983371.en].
* ''Beddome's horseshoe bat'': Srinivasulu, B.; et al. (2019). [https://www.iucnredlist.org/species/40023/22061859 "''Rhinolophus beddomei''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T40023A22061859. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T40023A22061859.en 10.2305/IUCN.UK.2019-3.RLTS.T40023A22061859.en].
* ''Big-eared horseshoe bat'': Tu, V.; et al. (2019). [https://www.iucnredlist.org/species/19550/21978583 "''Rhinolophus macrotis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T19550A21978583. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T19550A21978583.en 10.2305/IUCN.UK.2019-3.RLTS.T19550A21978583.en].
* ''Blasius's horseshoe bat'': Taylor, P. (2016). [https://www.iucnredlist.org/species/19515/21972073 "''Rhinolophus blasii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T19515A21972073. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T19515A21972073.en 10.2305/IUCN.UK.2016-2.RLTS.T19515A21972073.en].
* ''Blyth's horseshoe bat'': Srinivasulu, B.; et al. (2019). [https://www.iucnredlist.org/species/19547/21977419 "''Rhinolophus lepidus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T19547A21977419. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T19547A21977419.en 10.2305/IUCN.UK.2019-3.RLTS.T19547A21977419.en].
* ''Bokhara horseshoe bat'': Benda, P.; et al. (2019). [https://www.iucnredlist.org/species/19526/21983564 "''Rhinolophus bocharicus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T19526A21983564. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T19526A21983564.en 10.2305/IUCN.UK.2019-3.RLTS.T19526A21983564.en].
* ''Bornean horseshoe bat'': Jayaraj, V. K. (2020). [https://www.iucnredlist.org/species/19527/21982599 "''Rhinolophus borneensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T19527A21982599. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T19527A21982599.en 10.2305/IUCN.UK.2020-2.RLTS.T19527A21982599.en].
* ''Bornean woolly horseshoe bat'': Patrick, L.; et al. (2017). [https://www.iucnredlist.org/species/84372306/84372372 "''Rhinolophus proconsulis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T84372306A84372372. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T84372306A84372372.en 10.2305/IUCN.UK.2017-2.RLTS.T84372306A84372372.en].
* ''Bourret's horseshoe bat'': Bates, P.; et al. (2008). [https://www.iucnredlist.org/species/19558/8976934 "''Rhinolophus paradoxolophus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2008''': e.T19558A8976934. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2008.RLTS.T19558A8976934.en 10.2305/IUCN.UK.2008.RLTS.T19558A8976934.en].
* ''Broad-eared horseshoe bat'': Armstrong, K. N.; et al. (2021) [amended version of 2017 assessment]. [https://www.iucnredlist.org/species/84372418/209537830 "''Rhinolophus euryotis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T84372418A209537830. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T84372418A209537830.en 10.2305/IUCN.UK.2021-3.RLTS.T84372418A209537830.en].
* ''Bushveld horseshoe bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/19568/21994351 "''Rhinolophus simulator''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T19568A21994351. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T19568A21994351.en 10.2305/IUCN.UK.2017-2.RLTS.T19568A21994351.en].
* ''Canut's horseshoe bat'': Waldien, D. L.; et al. (2021). [https://www.iucnredlist.org/species/19528/21982962 "''Rhinolophus canuti''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T19528A21982962. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T19528A21982962.en 10.2305/IUCN.UK.2021-2.RLTS.T19528A21982962.en].
* ''Cape horseshoe bat'': Jacobs, D.; et al. (2017). [https://www.iucnredlist.org/species/19529/21980883 "''Rhinolophus capensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T19529A21980883. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T19529A21980883.en 10.2305/IUCN.UK.2017-2.RLTS.T19529A21980883.en].
* ''Chiewkwee's horseshoe bat'': Waldien, D. L. (2020). [https://www.iucnredlist.org/species/84372474/84372528 "''Rhinolophus chiewkweeae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T84372474A84372528. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T84372474A84372528.en 10.2305/IUCN.UK.2020-2.RLTS.T84372474A84372528.en].
* ''Chinese rufous horseshoe bat'': Sun, K. (2019). [https://www.iucnredlist.org/species/41529/22005184 "''Rhinolophus sinicus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T41529A22005184. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T41529A22005184.en 10.2305/IUCN.UK.2019-3.RLTS.T41529A22005184.en].
* ''Cohen's horseshoe bat'': Cohen, L.; et al. (2017). [https://www.iucnredlist.org/species/64587154/64587542 "''Rhinolophus cohenae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T64587154A64587542. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T64587154A64587542.en 10.2305/IUCN.UK.2017-2.RLTS.T64587154A64587542.en].
* ''Convex horseshoe bat'': Csorba, G.; et al. (2016). [https://www.iucnredlist.org/species/40037/22060825 "''Rhinolophus convexus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T40037A22060825. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T40037A22060825.en 10.2305/IUCN.UK.2016-2.RLTS.T40037A22060825.en].
* ''Creagh's horseshoe bat'': Jayaraj, V. K. (2020). [https://www.iucnredlist.org/species/19535/21981495 "''Rhinolophus creaghi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T19535A21981495. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T19535A21981495.en 10.2305/IUCN.UK.2020-2.RLTS.T19535A21981495.en].
* ''Croslet horseshoe bat'': Furey, N.; et al. (2020). [https://www.iucnredlist.org/species/19532/21980746 "''Rhinolophus coelophyllus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T19532A21980746. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T19532A21980746.en 10.2305/IUCN.UK.2020-3.RLTS.T19532A21980746.en].
* ''Damara horseshoe bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/67369846/67369914 "''Rhinolophus damarensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T67369846A67369914. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T67369846A67369914.en 10.2305/IUCN.UK.2017-2.RLTS.T67369846A67369914.en].
* ''Darling's horseshoe bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/67369483/21981665 "''Rhinolophus darlingi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T67369483A21981665. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T67369483A21981665.en 10.2305/IUCN.UK.2017-2.RLTS.T67369483A21981665.en].
* ''Decken's horseshoe bat'': Shapiro, J.; et al. (2020). [https://www.iucnredlist.org/species/19537/21979537 "''Rhinolophus deckenii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T19537A21979537. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T19537A21979537.en 10.2305/IUCN.UK.2020-2.RLTS.T19537A21979537.en].
* ''Dent's horseshoe bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/19538/21979433 "''Rhinolophus denti''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T19538A21979433. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T19538A21979433.en 10.2305/IUCN.UK.2017-2.RLTS.T19538A21979433.en].
* ''Dobson's horseshoe bat'': Bates, P. J. J.; et al. (2019). [https://www.iucnredlist.org/species/19576/21991423 "''Rhinolophus yunanensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T19576A21991423. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T19576A21991423.en 10.2305/IUCN.UK.2019-3.RLTS.T19576A21991423.en].
* ''Eloquent horseshoe bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/19539/21979320 "''Rhinolophus eloquens''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T19539A21979320. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T19539A21979320.en 10.2305/IUCN.UK.2017-2.RLTS.T19539A21979320.en].
* ''Forest horseshoe bat'': Cotterill, F. P. D. (2019). [https://www.iucnredlist.org/species/19567/21994523 "''Rhinolophus silvestris''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T19567A21994523. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T19567A21994523.en 10.2305/IUCN.UK.2019-3.RLTS.T19567A21994523.en].
* ''Formosan woolly horseshoe bat'': Huang, J. C. -C.; et al. (2019). [https://www.iucnredlist.org/species/136644/21989870 "''Rhinolophus formosae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136644A21989870. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T136644A21989870.en 10.2305/IUCN.UK.2019-3.RLTS.T136644A21989870.en].
* ''Geoffroy's horseshoe bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/19531/21980500 "''Rhinolophus clivosus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T19531A21980500. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T19531A21980500.en 10.2305/IUCN.UK.2017-2.RLTS.T19531A21980500.en].
* ''Great woolly horseshoe bat'': Thong, V. D.; et al. (2019). [https://www.iucnredlist.org/species/19548/21977086 "''Rhinolophus luctus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T19548A21977086. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T19548A21977086.en 10.2305/IUCN.UK.2019-3.RLTS.T19548A21977086.en].
* ''Greater horseshoe bat'': Piraccini, R. (2016). [https://www.iucnredlist.org/species/19517/21973253 "''Rhinolophus ferrumequinum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T19517A21973253. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T19517A21973253.en 10.2305/IUCN.UK.2016-2.RLTS.T19517A21973253.en].
* ''Guinean horseshoe bat'': Shapiro, J.; et al. (2020). [https://www.iucnredlist.org/species/19542/21980043 "''Rhinolophus guineensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T19542A21980043. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T19542A21980043.en 10.2305/IUCN.UK.2020-2.RLTS.T19542A21980043.en].
* ''Halcyon horseshoe bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/19523/21981963 "''Rhinolophus alcyone''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T19523A21981963. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T19523A21981963.en 10.2305/IUCN.UK.2017-2.RLTS.T19523A21981963.en].
* ''Hildebrandt's horseshoe bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/64586080/21979893 "''Rhinolophus hildebrandtii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T64586080A21979893. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T64586080A21979893.en 10.2305/IUCN.UK.2017-2.RLTS.T64586080A21979893.en].
* ''Hill's horseshoe bat'': Webala, P.; et al. (2021). [https://www.iucnredlist.org/species/44781/203829053 "''Rhinolophus hilli''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T44781A203829053. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T44781A203829053.en 10.2305/IUCN.UK.2021-3.RLTS.T44781A203829053.en].
* ''Hills' horseshoe bat'': Obitte, B.; et al. (2022). [https://www.iucnredlist.org/species/44782/203829273 "''Rhinolophus hillorum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2022''': e.T44782A203829273. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2022-2.RLTS.T44782A203829273.en 10.2305/IUCN.UK.2022-2.RLTS.T44782A203829273.en].
* ''Indo-Chinese lesser brown horseshoe bat'': Soisook, P. (2017). [https://www.iucnredlist.org/species/84384558/84384597 "''Rhinolophus microglobosus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T84384558A84384597. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T84384558A84384597.en 10.2305/IUCN.UK.2017-2.RLTS.T84384558A84384597.en].
* ''Insular horseshoe bat'': Csorba, G.; et al. (2016). [https://www.iucnredlist.org/species/19577/21992519 "''Rhinolophus keyensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T19577A21992519. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T19577A21992519.en 10.2305/IUCN.UK.2016-2.RLTS.T19577A21992519.en].
* ''Intermediate horseshoe bat'': Furey, N.; et al. (2020). [https://www.iucnredlist.org/species/19522/21982358 "''Rhinolophus affinis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T19522A21982358. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T19522A21982358.en 10.2305/IUCN.UK.2020-3.RLTS.T19522A21982358.en].
* ''King horseshoe bat'': Sun, K. (2020). [https://www.iucnredlist.org/species/19562/21994639 "''Rhinolophus rex''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T19562A21994639. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T19562A21994639.en 10.2305/IUCN.UK.2020-2.RLTS.T19562A21994639.en].
* ''Lander's horseshoe bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/19546/21977797 "''Rhinolophus landeri''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T19546A21977797. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T19546A21977797.en 10.2305/IUCN.UK.2017-2.RLTS.T19546A21977797.en].
* ''Large rufous horseshoe bat'': Alviola, P. A.; et al. (2019). [https://www.iucnredlist.org/species/19564/21995212 "''Rhinolophus rufus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T19564A21995212. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T19564A21995212.en 10.2305/IUCN.UK.2019-3.RLTS.T19564A21995212.en].
* ''Large-eared horseshoe bat'': Armstrong, K. N. (2021). [https://www.iucnredlist.org/species/19560/21992817 "''Rhinolophus philippinensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T19560A21992817. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T19560A21992817.en 10.2305/IUCN.UK.2021-3.RLTS.T19560A21992817.en].
* ''Least horseshoe bat'': Fukui, D. (2019). [https://www.iucnredlist.org/species/85707059/21994916 "''Rhinolophus pusillus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T85707059A21994916. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T85707059A21994916.en 10.2305/IUCN.UK.2019-3.RLTS.T85707059A21994916.en].
* ''Lesser brown horseshoe bat'': Bates, P. J. J.; et al. (2019). [https://www.iucnredlist.org/species/84383122/21991664 "''Rhinolophus stheno''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T84383122A21991664. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T84383122A21991664.en 10.2305/IUCN.UK.2019-3.RLTS.T84383122A21991664.en].
* ''Lesser horseshoe bat'': Taylor, P. (2016). [https://www.iucnredlist.org/species/19518/21972794 "''Rhinolophus hipposideros''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T19518A21972794. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T19518A21972794.en 10.2305/IUCN.UK.2016-2.RLTS.T19518A21972794.en].
* ''Lesser woolly horseshoe bat'': Jayaraj, V. K. (2020). [https://www.iucnredlist.org/species/19565/21994153 "''Rhinolophus sedulus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T19565A21994153. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T19565A21994153.en 10.2305/IUCN.UK.2020-2.RLTS.T19565A21994153.en].
* ''Little Japanese horseshoe bat'': Chiroptera Specialist Group (2024). [https://www.iucnredlist.org/species/19534/8957242 "''Rhinolophus cornutus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''1996''': e.T19534A8957242. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.1996.RLTS.T19534A8957242.en 10.2305/IUCN.UK.1996.RLTS.T19534A8957242.en].
* ''Little Nepalese horseshoe bat'': Srinivasulu, B.; et al. (2019). [https://www.iucnredlist.org/species/19570/21991844 "''Rhinolophus subbadius''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T19570A21991844. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T19570A21991844.en 10.2305/IUCN.UK.2019-3.RLTS.T19570A21991844.en].
* ''Maclaud's horseshoe bat'': Shapiro, J.; et al. (2019). [https://www.iucnredlist.org/species/19549/21978925 "''Rhinolophus maclaudi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T19549A21978925. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T19549A21978925.en 10.2305/IUCN.UK.2019-3.RLTS.T19549A21978925.en].
* ''Madura horseshoe bat'': Csorba, G.; et al. (2016). [https://www.iucnredlist.org/species/136410/22016850 "''Rhinolophus madurensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136410A22016850. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T136410A22016850.en 10.2305/IUCN.UK.2016-2.RLTS.T136410A22016850.en].
* ''Maendeleo horseshoe bat'': Cooper-Bohannon, R. (2020). [https://www.iucnredlist.org/species/44783/22067758 "''Rhinolophus maendeleo''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T44783A22067758. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T44783A22067758.en 10.2305/IUCN.UK.2020-2.RLTS.T44783A22067758.en].
* ''Malayan horseshoe bat'': Bates, P.; et al. (2019). [https://www.iucnredlist.org/species/19551/21978424 "''Rhinolophus malayanus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T19551A21978424. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T19551A21978424.en 10.2305/IUCN.UK.2019-3.RLTS.T19551A21978424.en].
* ''Marshall's horseshoe bat'': Thong, V. D.; et al. (2019). [https://www.iucnredlist.org/species/19552/21978274 "''Rhinolophus marshalli''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T19552A21978274. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T19552A21978274.en 10.2305/IUCN.UK.2019-3.RLTS.T19552A21978274.en].
* ''McIntyre's horseshoe bat'': Patrick, L.; et al. (2017). [https://www.iucnredlist.org/species/84372245/84372277 "''Rhinolophus mcintyrei''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T84372245A84372277. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T84372245A84372277.en 10.2305/IUCN.UK.2017-2.RLTS.T84372245A84372277.en].
* ''Mediterranean horseshoe bat'': Juste, J.; et al. (2016). [https://www.iucnredlist.org/species/19516/21971185 "''Rhinolophus euryale''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T19516A21971185. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T19516A21971185.en 10.2305/IUCN.UK.2016-2.RLTS.T19516A21971185.en].
* ''Mehely's horseshoe bat'': Alcaldé, J.; et al. (2016). [https://www.iucnredlist.org/species/19519/21974380 "''Rhinolophus mehelyi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T19519A21974380. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T19519A21974380.en 10.2305/IUCN.UK.2016-2.RLTS.T19519A21974380.en].
* ''Mitred horseshoe bat'': Csorba, G.; et al. (2016). [https://www.iucnredlist.org/species/19554/21993304 "''Rhinolophus mitratus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T19554A21993304. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T19554A21993304.en 10.2305/IUCN.UK.2016-2.RLTS.T19554A21993304.en].
* ''Mount Mabu horseshoe bat'': Taylor, P. (2019). [https://www.iucnredlist.org/species/64588047/64588304 "''Rhinolophus mabuensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T64588047A64588304. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T64588047A64588304.en 10.2305/IUCN.UK.2019-1.RLTS.T64588047A64588304.en].
* ''Mozambican horseshoe bat'': Shoeman, C. (2017). [https://www.iucnredlist.org/species/64589126/64589338 "''Rhinolophus mossambicus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T64589126A64589338. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T64589126A64589338.en 10.2305/IUCN.UK.2017-2.RLTS.T64589126A64589338.en].
* ''Neriad horseshoe bat'': Bates, P.; et al. (2016). [https://www.iucnredlist.org/species/19556/21993688 "''Rhinolophus nereis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T19556A21993688. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T19556A21993688.en 10.2305/IUCN.UK.2016-2.RLTS.T19556A21993688.en].
* ''Osgood's horseshoe bat'': Sun, K. (2020). [https://www.iucnredlist.org/species/19557/21992735 "''Rhinolophus osgoodi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T19557A21992735. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T19557A21992735.en 10.2305/IUCN.UK.2020-3.RLTS.T19557A21992735.en].
* ''Pearson's horseshoe bat'': Bates, P. J. J.; et al. (2019). [https://www.iucnredlist.org/species/19559/21993105 "''Rhinolophus pearsonii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T19559A21993105. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T19559A21993105.en 10.2305/IUCN.UK.2019-3.RLTS.T19559A21993105.en].
* ''Peninsular horseshoe bat'': Jayaraj, V. K. (2020). [https://www.iucnredlist.org/species/136496/21976144 "''Rhinolophus robinsoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T136496A21976144. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T136496A21976144.en 10.2305/IUCN.UK.2020-2.RLTS.T136496A21976144.en].
* ''Philippine forest horseshoe bat'': Duya, M. R.; et al. (2019). [https://www.iucnredlist.org/species/19545/21978063 "''Rhinolophus inops''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T19545A21978063. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T19545A21978063.en 10.2305/IUCN.UK.2019-3.RLTS.T19545A21978063.en].
* ''Poso horseshoe bat'': Patrick, L.; et al. (2017). [https://www.iucnredlist.org/species/84372084/95642275 "''Rhinolophus belligerator''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T84372084A95642275. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T84372084A95642275.en 10.2305/IUCN.UK.2017-2.RLTS.T84372084A95642275.en].
* ''Rufous horseshoe bat'': Srinivasulu, C.; et al. (2019). [https://www.iucnredlist.org/species/84379218/21995537 "''Rhinolophus rouxii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T84379218A21995537. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T84379218A21995537.en 10.2305/IUCN.UK.2019-3.RLTS.T84379218A21995537.en].
* ''Ruwenzori horseshoe bat'': Fahr, J.; et al. (2020). [https://www.iucnredlist.org/species/44784/22067834 "''Rhinolophus ruwenzorii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T44784A22067834. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T44784A22067834.en 10.2305/IUCN.UK.2020-2.RLTS.T44784A22067834.en].
* ''Rüppell's horseshoe bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/19541/21980197 "''Rhinolophus fumigatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T19541A21980197. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T19541A21980197.en 10.2305/IUCN.UK.2017-2.RLTS.T19541A21980197.en].
* ''Sakeji horseshoe bat'': Cotterill, F. P. D. (2019). [https://www.iucnredlist.org/species/44785/22068998 "''Rhinolophus sakejiensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T44785A22068998. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T44785A22068998.en 10.2305/IUCN.UK.2019-3.RLTS.T44785A22068998.en].
* ''Shamel's horseshoe bat'': Furey, N.; et al. (2020). [https://www.iucnredlist.org/species/19566/21993823 "''Rhinolophus shameli''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T19566A21993823. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T19566A21993823.en 10.2305/IUCN.UK.2020-3.RLTS.T19566A21993823.en].
* ''Shortridge's horseshoe bat'': Sun, K. (2020). [https://www.iucnredlist.org/species/136631/21987430 "''Rhinolophus shortridgei''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T136631A21987430. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T136631A21987430.en 10.2305/IUCN.UK.2020-2.RLTS.T136631A21987430.en].
* ''Small rufous horseshoe bat'': Ong, P.; et al. (2016). [https://www.iucnredlist.org/species/19571/21992005 "''Rhinolophus subrufus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T19571A21992005. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T19571A21992005.en 10.2305/IUCN.UK.2016-2.RLTS.T19571A21992005.en].
* ''Smaller horseshoe bat'': Armstrong, K. N.; et al. (2021) [amended version of 2017 assessment]. [https://www.iucnredlist.org/species/19553/209537963 "''Rhinolophus megaphyllus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T19553A209537963. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T19553A209537963.en 10.2305/IUCN.UK.2021-3.RLTS.T19553A209537963.en].
* ''Smithers's horseshoe bat'': Taylor, P. (2017). [https://www.iucnredlist.org/species/64588371/64589277 "''Rhinolophus smithersi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T64588371A64589277. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T64588371A64589277.en 10.2305/IUCN.UK.2017-2.RLTS.T64588371A64589277.en].
* ''Sulawesi broad-eared horseshoe bat'': Patrick, L.; et al. (2017). [https://www.iucnredlist.org/species/84372447/84372450 "''Rhinolophus tatar''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T84372447A84372450. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T84372447A84372450.en 10.2305/IUCN.UK.2017-2.RLTS.T84372447A84372450.en].
* ''Sulawesi horseshoe bat'': Bouillard, N.; et al. (2021). [https://www.iucnredlist.org/species/19530/21980994 "''Rhinolophus celebensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T19530A21980994. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T19530A21980994.en 10.2305/IUCN.UK.2021-2.RLTS.T19530A21980994.en].
* ''Swinny's horseshoe bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/19572/21992092 "''Rhinolophus swinnyi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T19572A21992092. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T19572A21992092.en 10.2305/IUCN.UK.2017-2.RLTS.T19572A21992092.en].
* ''Thai horseshoe bat'': Tu, V.; et al. (2019). [https://www.iucnredlist.org/species/136651/21990143 "''Rhinolophus siamensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136651A21990143. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T136651A21990143.en 10.2305/IUCN.UK.2019-3.RLTS.T136651A21990143.en].
* ''Thailand horseshoe bat'': Bouillard, N. (2021). [https://www.iucnredlist.org/species/82348077/82348673 "''Rhinolophus thailandensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T82348077A82348673. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T82348077A82348673.en 10.2305/IUCN.UK.2021-2.RLTS.T82348077A82348673.en].
* ''Thomas's horseshoe bat'': Thong, V. D.; et al. (2019). [https://www.iucnredlist.org/species/19573/21990671 "''Rhinolophus thomasi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T19573A21990671. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T19573A21990671.en 10.2305/IUCN.UK.2019-3.RLTS.T19573A21990671.en].
* ''Timorese horseshoe bat'': Armstrong, K. N.; et al. (2021) [amended version of 2016 assessment]. [https://www.iucnredlist.org/species/136248/209538154 "''Rhinolophus montanus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T136248A209538154. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T136248A209538154.en 10.2305/IUCN.UK.2021-3.RLTS.T136248A209538154.en].
* ''Trefoil horseshoe bat'': Huang, J. C. -C. (2020). [https://www.iucnredlist.org/species/19574/21990821 "''Rhinolophus trifoliatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T19574A21990821. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T19574A21990821.en 10.2305/IUCN.UK.2020-2.RLTS.T19574A21990821.en].
* ''Wedge-sellaed horseshoe bat'': Zhou, Z.; et al. (2017). [https://www.iucnredlist.org/species/82348701/82349975 "''Rhinolophus xinanzhongguoensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T82348701A82349975. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T82348701A82349975.en 10.2305/IUCN.UK.2017-2.RLTS.T82348701A82349975.en].
* ''Willard's horseshoe bat'': Monadjem, A. (2020). [https://www.iucnredlist.org/species/82346260/82347169 "''Rhinolophus willardi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T82346260A82347169. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T82346260A82347169.en 10.2305/IUCN.UK.2020-2.RLTS.T82346260A82347169.en].
* ''Yaeyama little horseshoe bat'': Fukui, D.; et al. (2020). [https://www.iucnredlist.org/species/85707170/85707174 "''Rhinolophus perditus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T85707170A85707174. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T85707170A85707174.en 10.2305/IUCN.UK.2020-2.RLTS.T85707170A85707174.en].
* ''Yellow-faced horseshoe bat'': Duya, M. R.; et al. (2019). [https://www.iucnredlist.org/species/19575/21991148 "''Rhinolophus virgo''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T19575A21991148. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T19575A21991148.en 10.2305/IUCN.UK.2019-3.RLTS.T19575A21991148.en].
* ''Ziama horseshoe bat'': Cooper-Bohannon, R.; et al. (2020). [https://www.iucnredlist.org/species/44786/22068674 "''Rhinolophus ziama''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T44786A22068674. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T44786A22068674.en 10.2305/IUCN.UK.2020-2.RLTS.T44786A22068674.en].
]
[[[#CITEREF_ALLMAM|Chernasky; Motis; Burgin]], pp. 466–467]
[Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/4983/22028899 "''Cloeotis percivali''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T4983A22028899. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T4983A22028899.en 10.2305/IUCN.UK.2017-2.RLTS.T4983A22028899.en].]
[''Paratriaenops'' habitats:
* ''Grandidier's trident bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/40025/22064746 "''Paratriaenops auritus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T40025A22064746. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T40025A22064746.en 10.2305/IUCN.UK.2017-2.RLTS.T40025A22064746.en].
* ''Trouessart's trident bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/81060220/22040490 "''Paratriaenops furculus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T81060220A22040490. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T81060220A22040490.en 10.2305/IUCN.UK.2017-2.RLTS.T81060220A22040490.en].
* ''Paulian's trident bat'': Goodman, S. (2017). [https://www.iucnredlist.org/species/81068840/95642220 "''Paratriaenops pauliani''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T81068840A95642220. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T81068840A95642220.en 10.2305/IUCN.UK.2017-2.RLTS.T81068840A95642220.en].
]
[Armstrong, K. N.; et al. (2021) [amended version of 2017 assessment]. [https://www.iucnredlist.org/species/19589/209539734 "''Rhinonicteris aurantia''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T19589A209539734. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T19589A209539734.en 10.2305/IUCN.UK.2021-3.RLTS.T19589A209539734.en].]
[''Triaenops'' habitats:
* ''African trident bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/81081036/95642225 "''Triaenops afer''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T81081036A95642225. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T81081036A95642225.en 10.2305/IUCN.UK.2017-2.RLTS.T81081036A95642225.en].
* ''Rufous trident bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/40026/22065029 "''Triaenops rufus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T40026A22065029. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T40026A22065029.en 10.2305/IUCN.UK.2017-2.RLTS.T40026A22065029.en].
* ''Yemeni trident leaf-nosed bat'': Benda, P. (2017). [https://www.iucnredlist.org/species/81082829/89457381 "''Triaenops parvus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T81082829A89457381. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T81082829A89457381.en 10.2305/IUCN.UK.2017-2.RLTS.T81082829A89457381.en].
* ''Persian trident bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/81069403/22040322 "''Triaenops persicus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T81069403A22040322. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T81069403A22040322.en 10.2305/IUCN.UK.2017-2.RLTS.T81069403A22040322.en].
]
[[[#CITEREF_ALLMAM|Chernasky; Motis; Burgin]], p. 465]
[''Rhinolophus'' habitats:
* ''Egyptian mouse-tailed bat'': Benda, P. (2017). [https://www.iucnredlist.org/species/82345555/82345569 "''Rhinopoma cystops''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T82345555A82345569. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T82345555A82345569.en 10.2305/IUCN.UK.2017-2.RLTS.T82345555A82345569.en].
* ''Yemeni mouse-tailed bat'': Benda, P. (2017). [https://www.iucnredlist.org/species/82345696/95642270 "''Rhinopoma hadramauticum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T82345696A95642270. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T82345696A95642270.en 10.2305/IUCN.UK.2017-2.RLTS.T82345696A95642270.en].
* ''Lesser mouse-tailed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/82345477/21999269 "''Rhinopoma hardwickii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T82345477A21999269. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T82345477A21999269.en 10.2305/IUCN.UK.2017-2.RLTS.T82345477A21999269.en].
* ''Macinnes's mouse-tailed bat'': Aulagnier, S. (2019). [https://www.iucnredlist.org/species/19601/21997048 "''Rhinopoma macinnesi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T19601A21997048. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T19601A21997048.en 10.2305/IUCN.UK.2019-3.RLTS.T19601A21997048.en].
* ''Greater mouse-tailed bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/19600/21998943 "''Rhinopoma microphyllum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T19600A21998943. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T19600A21998943.en 10.2305/IUCN.UK.2017-2.RLTS.T19600A21998943.en].
* ''Small mouse-tailed bat'': Srinivasulu, B.; et al. (2019). [https://www.iucnredlist.org/species/19602/21997131 "''Rhinopoma muscatellum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T19602A21997131. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T19602A21997131.en 10.2305/IUCN.UK.2019-3.RLTS.T19602A21997131.en].
]
[[[#CITEREF_ALLMAM|Chernasky; Motis; Burgin]], pp. 528–565]
[''Kerivoula'' habitats:
* ''Bismarck trumpet-eared bat'': Aplin, K.; et al. (2021). [https://www.iucnredlist.org/species/10980/22022572 "''Kerivoula myrella''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T10980A22022572. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T10980A22022572.en 10.2305/IUCN.UK.2021-1.RLTS.T10980A22022572.en].
* ''Clear-winged woolly bat'': Nor Zalipah, M. (2020). [https://www.iucnredlist.org/species/10983/22021330 "''Kerivoula pellucida''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T10983A22021330. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T10983A22021330.en 10.2305/IUCN.UK.2020-2.RLTS.T10983A22021330.en].
* ''Copper woolly bat'': Fahr., J. (2019). [https://www.iucnredlist.org/species/10971/21971772 "''Kerivoula cuprosa''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T10971A21971772. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T10971A21971772.en 10.2305/IUCN.UK.2019-3.RLTS.T10971A21971772.en].
* ''Cryptic woolly bat'': Tu, V.; et al. (2021). [https://www.iucnredlist.org/species/154196297/154196362 "''Kerivoula crypta''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T154196297A154196362. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T154196297A154196362.en 10.2305/IUCN.UK.2021-2.RLTS.T154196297A154196362.en].
* ''Damara woolly bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/10969/21970780 "''Kerivoula argentata''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T10969A21970780. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T10969A21970780.en 10.2305/IUCN.UK.2017-2.RLTS.T10969A21970780.en].
* ''Dark woolly bat'': Tu, V.; et al. (2021). [https://www.iucnredlist.org/species/154196065/154196068 "''Kerivoula furva''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T154196065A154196068. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T154196065A154196068.en 10.2305/IUCN.UK.2021-2.RLTS.T154196065A154196068.en].
* ''Ethiopian woolly bat'': Fahr., J. (2019). [https://www.iucnredlist.org/species/10972/21971992 "''Kerivoula eriophora''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T10972A21971992. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T10972A21971992.en 10.2305/IUCN.UK.2019-3.RLTS.T10972A21971992.en].
* ''Flat-skulled woolly bat'': Tu, V.; et al. (2021). [https://www.iucnredlist.org/species/154195907/154195912 "''Kerivoula depressa''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T154195907A154195912. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T154195907A154195912.en 10.2305/IUCN.UK.2021-2.RLTS.T154195907A154195912.en].
* ''Flores woolly bat'': Waldien, D. L.; et al. (2021). [https://www.iucnredlist.org/species/10973/21972598 "''Kerivoula flora''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T10973A21972598. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T10973A21972598.en 10.2305/IUCN.UK.2021-2.RLTS.T10973A21972598.en].
* ''Fly River trumpet-eared bat'': Aplin, K.; et al. (2021) [amended version of 2017 assessment]. [https://www.iucnredlist.org/species/10979/209536068 "''Kerivoula muscina''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T10979A209536068. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T10979A209536068.en 10.2305/IUCN.UK.2021-3.RLTS.T10979A209536068.en].
* ''Hardwicke's woolly bat'': Tu, V.; et al. (2020). [https://www.iucnredlist.org/species/154195594/21973742 "''Kerivoula hardwickii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T154195594A21973742. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T154195594A21973742.en 10.2305/IUCN.UK.2020-2.RLTS.T154195594A21973742.en].
* ''Indochinese woolly bat'': Tu, V.; et al. (2021). [https://www.iucnredlist.org/species/154195951/154195959 "''Kerivoula dongduongana''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T154195951A154195959. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T154195951A154195959.en 10.2305/IUCN.UK.2021-2.RLTS.T154195951A154195959.en].
* ''Kachin woolly bat'': Bates, P. J. J.; et al. (2019). [https://www.iucnredlist.org/species/136240/22001145 "''Kerivoula kachinensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136240A22001145. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T136240A22001145.en 10.2305/IUCN.UK.2019-3.RLTS.T136240A22001145.en].
* ''Krau woolly bat'': Nor Zalipah, M. (2020). [https://www.iucnredlist.org/species/136572/21992300 "''Kerivoula krauensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T136572A21992300. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T136572A21992300.en 10.2305/IUCN.UK.2020-2.RLTS.T136572A21992300.en].
* ''Least woolly bat'': Nor Zalipah, M. (2020). [https://www.iucnredlist.org/species/10978/22022086 "''Kerivoula minuta''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T10978A22022086. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T10978A22022086.en 10.2305/IUCN.UK.2020-2.RLTS.T10978A22022086.en].
* ''Lenis woolly bat'': Srinivasulu, C.; et al. (2019). [https://www.iucnredlist.org/species/136428/21984385 "''Kerivoula lenis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136428A21984385. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T136428A21984385.en 10.2305/IUCN.UK.2019-3.RLTS.T136428A21984385.en].
* ''Lesser woolly bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/10977/22021700 "''Kerivoula lanosa''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T10977A22021700. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T10977A22021700.en 10.2305/IUCN.UK.2017-2.RLTS.T10977A22021700.en].
* ''Painted bat'': Huang, J. C. -C.; et al. (2020). [https://www.iucnredlist.org/species/10985/22022952 "''Kerivoula picta''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T10985A22022952. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T10985A22022952.en 10.2305/IUCN.UK.2020-2.RLTS.T10985A22022952.en].
* ''Papillose woolly bat'': Hutson, A. M.; et al. (2021). [https://www.iucnredlist.org/species/10981/22020906 "''Kerivoula papillosa''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T10981A22020906. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T10981A22020906.en 10.2305/IUCN.UK.2021-1.RLTS.T10981A22020906.en].
* ''Small woolly bat'': Nor Zalipah, M. (2020). [https://www.iucnredlist.org/species/10975/21974054 "''Kerivoula intermedia''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T10975A21974054. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T10975A21974054.en 10.2305/IUCN.UK.2020-2.RLTS.T10975A21974054.en].
* ''Smith's woolly bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/10986/22023189 "''Kerivoula smithii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T10986A22023189. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T10986A22023189.en 10.2305/IUCN.UK.2017-2.RLTS.T10986A22023189.en].
* ''Spurrell's woolly bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/10984/22021608 "''Kerivoula phalaena''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T10984A22021608. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T10984A22021608.en 10.2305/IUCN.UK.2017-2.RLTS.T10984A22021608.en].
* ''St. Aignan's trumpet-eared bat'': Aplin, K.; et al. (2021) [amended version of 2020 assessment]. [https://www.iucnredlist.org/species/10968/209548421 "''Kerivoula agnella''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T10968A209548421. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T10968A209548421.en 10.2305/IUCN.UK.2021-3.RLTS.T10968A209548421.en].
* ''Tanzanian woolly bat'': Cooper-Bohannon, R.; et al. (2020). [https://www.iucnredlist.org/species/10966/21975149 "''Kerivoula africana''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T10966A21975149. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T10966A21975149.en 10.2305/IUCN.UK.2020-2.RLTS.T10966A21975149.en].
* ''Titania's woolly bat'': Bates, P. J. J.; et al. (2019). [https://www.iucnredlist.org/species/136817/22044302 "''Kerivoula titania''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136817A22044302. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T136817A22044302.en 10.2305/IUCN.UK.2019-3.RLTS.T136817A22044302.en].
* ''Whitehead's woolly bat'': Duya, M. R.; et al. (2019). [https://www.iucnredlist.org/species/10987/22023276 "''Kerivoula whiteheadi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T10987A22023276. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T10987A22023276.en 10.2305/IUCN.UK.2019-3.RLTS.T10987A22023276.en].
]
[''Phoniscus'' habitats:
* ''Dubious trumpet-eared bat'': Francis, C. M.; et al. (2022). [https://www.iucnredlist.org/species/10967/21975373 "''Phoniscus aerosus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2022''': e.T10967A21975373. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2022-2.RLTS.T10967A21975373.en 10.2305/IUCN.UK.2022-2.RLTS.T10967A21975373.en].
* ''Golden-tipped bat'': Loyd, A. M.; et al. (2021). [https://www.iucnredlist.org/species/10982/22021190 "''Phoniscus papuensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T10982A22021190. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T10982A22021190.en 10.2305/IUCN.UK.2021-1.RLTS.T10982A22021190.en].
* ''Groove-toothed bat'': Jayaraj, V. K. (2020). [https://www.iucnredlist.org/species/10970/21970973 "''Phoniscus atrox''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T10970A21970973. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T10970A21970973.en 10.2305/IUCN.UK.2020-2.RLTS.T10970A21970973.en].
* ''Peters's trumpet-eared bat'': Oo, S. S. L.; et al. (2019). [https://www.iucnredlist.org/species/10976/21974660 "''Phoniscus jagorii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T10976A21974660. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T10976A21974660.en 10.2305/IUCN.UK.2019-3.RLTS.T10976A21974660.en].
]
[Csorba, G.; et al. (2019). [https://www.iucnredlist.org/species/99711843/22045367 "''Harpiocephalus harpia''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T99711843A22045367. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T99711843A22045367.en 10.2305/IUCN.UK.2019-3.RLTS.T99711843A22045367.en].]
[''Harpiola'' habitats:
* ''Formosan golden tube-nosed bat'': Kuo, H.; et al. (2020). [https://www.iucnredlist.org/species/136445/21983827 "''Harpiola isodon''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T136445A21983827. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T136445A21983827.en 10.2305/IUCN.UK.2020-2.RLTS.T136445A21983827.en].
* ''Peters's tube-nosed bat'': Csorba, G.; et al. (2016). [https://www.iucnredlist.org/species/13941/22093890 "''Harpiola grisea''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T13941A22093890. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T13941A22093890.en 10.2305/IUCN.UK.2016-2.RLTS.T13941A22093890.en].
]
[''Murina'' habitats:
* ''Annam tube-nosed bat'': Francis, C. M. (2020). [https://www.iucnredlist.org/species/84487907/84487915 "''Murina annamitica''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T84487907A84487915. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T84487907A84487915.en 10.2305/IUCN.UK.2020-2.RLTS.T84487907A84487915.en].
* ''Bala tube-nosed bat'': Soisook, P. (2017). [https://www.iucnredlist.org/species/84487939/84487985 "''Murina balaensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T84487939A84487985. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T84487939A84487985.en 10.2305/IUCN.UK.2017-2.RLTS.T84487939A84487985.en].
* ''Beelzebub's tube-nosed bat'': Csorba, G.; et al. (2019). [https://www.iucnredlist.org/species/84488085/84488093 "''Murina beelzebub''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T84488085A84488093. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T84488085A84488093.en 10.2305/IUCN.UK.2019-3.RLTS.T84488085A84488093.en].
* ''Bicolored tube-nosed bat'': Lee, L.; et al. (2017). [https://www.iucnredlist.org/species/84488443/84488449 "''Murina bicolor''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T84488443A84488449. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T84488443A84488449.en 10.2305/IUCN.UK.2017-2.RLTS.T84488443A84488449.en].
* ''Bronze tube-nosed bat'': Azhar, M. I.; et al. (2020). [https://www.iucnredlist.org/species/13936/22091750 "''Murina aenea''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T13936A22091750. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T13936A22091750.en 10.2305/IUCN.UK.2020-2.RLTS.T13936A22091750.en].
* ''Brown tube-nosed bat'': Azhar, M. I.; et al. (2020). [https://www.iucnredlist.org/species/13947/22096800 "''Murina suilla''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T13947A22096800. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T13947A22096800.en 10.2305/IUCN.UK.2020-2.RLTS.T13947A22096800.en].
* ''Da Lat tube-nosed bat'': Kruskop, S. V. (2020). [https://www.iucnredlist.org/species/84562293/84562296 "''Murina harpioloides''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T84562293A84562296. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T84562293A84562296.en 10.2305/IUCN.UK.2020-2.RLTS.T84562293A84562296.en].
* ''Dusky tube-nosed bat'': Wu, Y.; et al. (2020). [https://www.iucnredlist.org/species/13940/22094085 "''Murina fusca''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T13940A22094085. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T13940A22094085.en 10.2305/IUCN.UK.2020-2.RLTS.T13940A22094085.en].
* ''Elery's tube-nosed bat'': Furey, N.; et al. (2021). [https://www.iucnredlist.org/species/84557696/84557699 "''Murina eleryi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T84557696A84557699. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T84557696A84557699.en 10.2305/IUCN.UK.2021-1.RLTS.T84557696A84557699.en].
* ''Fea's tube-nosed bat'': Csorba, G. (2020). [https://www.iucnredlist.org/species/84561002/84561005 "''Murina feae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T84561002A84561005. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T84561002A84561005.en 10.2305/IUCN.UK.2020-2.RLTS.T84561002A84561005.en].
* ''Fiona's tube-nosed bat'': Francis, C. M. (2020). [https://www.iucnredlist.org/species/84500852/84500855 "''Murina fionae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T84500852A84500855. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T84500852A84500855.en 10.2305/IUCN.UK.2020-2.RLTS.T84500852A84500855.en].
* ''Flute-nosed bat'': Pennay, M. (2021). [https://www.iucnredlist.org/species/13939/22094567 "''Murina florium''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T13939A22094567. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T13939A22094567.en 10.2305/IUCN.UK.2021-3.RLTS.T13939A22094567.en].
* ''Gilded tube-nosed bat'': Khan, F. A. A.; et al. (2020). [https://www.iucnredlist.org/species/13945/22097407 "''Murina rozendaali''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T13945A22097407. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T13945A22097407.en 10.2305/IUCN.UK.2020-2.RLTS.T13945A22097407.en].
* ''Gloomy tube-nosed bat'': Fukui, D.; et al. (2019). [https://www.iucnredlist.org/species/13948/22096705 "''Murina tenebrosa''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T13948A22096705. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T13948A22096705.en 10.2305/IUCN.UK.2019-3.RLTS.T13948A22096705.en].
* ''Golden-haired tube-nosed bat'': Bouillard, N. (2021). [https://www.iucnredlist.org/species/84500863/84500868 "''Murina chrysochaetes''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T84500863A84500868. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T84500863A84500868.en 10.2305/IUCN.UK.2021-2.RLTS.T84500863A84500868.en].
* ''Greater tube-nosed bat'': Stubbe, M.; et al. (2016). [https://www.iucnredlist.org/species/13943/22093328 "''Murina leucogaster''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T13943A22093328. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T13943A22093328.en 10.2305/IUCN.UK.2016-2.RLTS.T13943A22093328.en].
* ''Harrison's tube-nosed bat'': Csorba, G.; et al. (2016). [https://www.iucnredlist.org/species/99712630/21995130 "''Murina harrisoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T99712630A21995130. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T99712630A21995130.en 10.2305/IUCN.UK.2016-2.RLTS.T99712630A21995130.en].
* ''Hidden tube-nosed bat'': Lee, L.; et al. (2017). [https://www.iucnredlist.org/species/84500842/84500845 "''Murina recondita''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T84500842A84500845. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T84500842A84500845.en 10.2305/IUCN.UK.2017-2.RLTS.T84500842A84500845.en].
* ''Hilgendorf's tube-nosed bat'': Fukui, D.; et al. (2019). [https://www.iucnredlist.org/species/136409/22017193 "''Murina hilgendorfi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136409A22017193. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T136409A22017193.en 10.2305/IUCN.UK.2019-3.RLTS.T136409A22017193.en].
* ''Hutton's tube-nosed bat'': Csorba, G.; et al. (2019). [https://www.iucnredlist.org/species/13942/22093516 "''Murina huttoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T13942A22093516. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T13942A22093516.en 10.2305/IUCN.UK.2019-3.RLTS.T13942A22093516.en].
* ''Jaintia tube-nosed bat'': Ruedi, M.; et al. (2017). [https://www.iucnredlist.org/species/84547975/84547978 "''Murina jaintiana''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T84547975A84547978. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T84547975A84547978.en 10.2305/IUCN.UK.2017-2.RLTS.T84547975A84547978.en].
* ''Little tube-nosed bat'': Yu, W.; et al. (2020). [https://www.iucnredlist.org/species/13937/22095123 "''Murina aurata''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T13937A22095123. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T13937A22095123.en 10.2305/IUCN.UK.2020-3.RLTS.T13937A22095123.en].
* ''Lorelie's tube-nosed bat'': Yu, W.; et al. (2020). [https://www.iucnredlist.org/species/84500876/84500879 "''Murina lorelieae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T84500876A84500879. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T84500876A84500879.en 10.2305/IUCN.UK.2020-2.RLTS.T84500876A84500879.en].
* ''Rainforest tube-nosed bat'': Ruedi, M.; et al. (2017). [https://www.iucnredlist.org/species/84548064/84548082 "''Murina pluvialis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T84548064A84548082. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T84548064A84548082.en 10.2305/IUCN.UK.2017-2.RLTS.T84548064A84548082.en].
* ''Round-eared tube-nosed bat'': Csorba, G.; et al. (2020). [https://www.iucnredlist.org/species/154196798/22094685 "''Murina cyclotis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T154196798A22094685. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T154196798A22094685.en 10.2305/IUCN.UK.2020-2.RLTS.T154196798A22094685.en].
* ''Ryukyu tube-nosed bat'': Fukui, D.; et al. (2019). [https://www.iucnredlist.org/species/29485/22066512 "''Murina ryukyuana''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T29485A22066512. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T29485A22066512.en 10.2305/IUCN.UK.2019-3.RLTS.T29485A22066512.en].
* ''Scully's tube-nosed bat'': Srinivasulu, C.; et al. (2019). [https://www.iucnredlist.org/species/84560827/22096188 "''Murina tubinaris''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T84560827A22096188. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T84560827A22096188.en 10.2305/IUCN.UK.2019-3.RLTS.T84560827A22096188.en].
* ''Shuipu tube-nosed bat'': Yu, W.; et al. (2020). [https://www.iucnredlist.org/species/84501698/84501702 "''Murina shuipuensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T84501698A84501702. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T84501698A84501702.en 10.2305/IUCN.UK.2020-2.RLTS.T84501698A84501702.en].
* ''Slender tube-nosed bat'': Lee, L.; et al. (2017). [https://www.iucnredlist.org/species/84500832/84500835 "''Murina gracilis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T84500832A84500835. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T84500832A84500835.en 10.2305/IUCN.UK.2017-2.RLTS.T84500832A84500835.en].
* ''Taiwan tube-nosed bat'': Huang, J. C. -C.; et al. (2019). [https://www.iucnredlist.org/species/13944/22093018 "''Murina puta''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T13944A22093018. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T13944A22093018.en 10.2305/IUCN.UK.2019-3.RLTS.T13944A22093018.en].
* ''Ussuri tube-nosed bat'': Fukui, D.; et al. (2019). [https://www.iucnredlist.org/species/84562332/22095832 "''Murina ussuriensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T84562332A22095832. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T84562332A22095832.en 10.2305/IUCN.UK.2019-3.RLTS.T84562332A22095832.en].
* ''Walston's tube-nosed bat'': Csorba, G.; et al. (2020). [https://www.iucnredlist.org/species/84562267/84562270 "''Murina walstoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T84562267A84562270. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T84562267A84562270.en 10.2305/IUCN.UK.2020-3.RLTS.T84562267A84562270.en].
]
[Soisook, P.; et al. (2016). [https://www.iucnredlist.org/species/8168/22028419 "''Eudiscopus denticulus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T8168A22028419. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T8168A22028419.en 10.2305/IUCN.UK.2016-2.RLTS.T8168A22028419.en].]
[''Myotis'' habitats:
* ''Alcathoe bat'': Hutson, A. M.; et al. (2016). [https://www.iucnredlist.org/species/136680/518740 "''Myotis alcathoe''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136680A518740. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T136680A518740.en 10.2305/IUCN.UK.2016-2.RLTS.T136680A518740.en].
* ''Anjouan myotis'': Jacobs, D. (2019). [https://www.iucnredlist.org/species/44863/22073545 "''Myotis anjouanensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T44863A22073545. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T44863A22073545.en 10.2305/IUCN.UK.2019-3.RLTS.T44863A22073545.en].
* ''Anna Tess's bat'': Srinivasulu, C.; et al. (2019). [https://www.iucnredlist.org/species/85342605/85342608 "''Myotis annatessae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T85342605A85342608. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T85342605A85342608.en 10.2305/IUCN.UK.2019-3.RLTS.T85342605A85342608.en].
* ''Annamit myotis'': Kruskop, S. V. (2016). [https://www.iucnredlist.org/species/136279/22006224 "''Myotis annamiticus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136279A22006224. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T136279A22006224.en 10.2305/IUCN.UK.2016-2.RLTS.T136279A22006224.en].
* ''Arizona myotis'': Solari, S. (2018). [https://www.iucnredlist.org/species/136650/21990499 "''Myotis occultus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T136650A21990499. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T136650A21990499.en 10.2305/IUCN.UK.2018-2.RLTS.T136650A21990499.en].
* ''Atacama myotis'': Vargas-Rodríguez, R.; et al. (2016). [https://www.iucnredlist.org/species/14143/22050638 "''Myotis atacamensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14143A22050638. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T14143A22050638.en 10.2305/IUCN.UK.2016-1.RLTS.T14143A22050638.en].
* ''Australian myotis'': Reardon, T. B.; et al. (2020). [https://www.iucnredlist.org/species/14146/22060248 "''Myotis australis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T14146A22060248. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T14146A22060248.en 10.2305/IUCN.UK.2020-3.RLTS.T14146A22060248.en].
* ''Barbados myotis'': Larsen, R. (2016). [https://www.iucnredlist.org/species/76435059/76435083 "''Myotis nyctor''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T76435059A76435083. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T76435059A76435083.en 10.2305/IUCN.UK.2016-1.RLTS.T76435059A76435083.en].
* ''Bechstein's bat'': Paunović, M. (2016). [https://www.iucnredlist.org/species/14123/22053752 "''Myotis bechsteinii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14123A22053752. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T14123A22053752.en 10.2305/IUCN.UK.2016-2.RLTS.T14123A22053752.en].
* ''Beijing mouse-eared bat'': Feng, J.; et al. (2019). [https://www.iucnredlist.org/species/14190/22066613 "''Myotis pequinius''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T14190A22066613. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T14190A22066613.en 10.2305/IUCN.UK.2019-3.RLTS.T14190A22066613.en].
* ''Black myotis'': Solari, S. (2019). [https://www.iucnredlist.org/species/14185/22066939 "''Myotis nigricans''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T14185A22066939. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-2.RLTS.T14185A22066939.en 10.2305/IUCN.UK.2019-2.RLTS.T14185A22066939.en].
* ''Bocharic myotis'': Srinivasulu, B.; et al. (2019). [https://www.iucnredlist.org/species/136219/22011494 "''Myotis bucharensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136219A22011494. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T136219A22011494.en 10.2305/IUCN.UK.2019-3.RLTS.T136219A22011494.en].
* ''Bornean whiskered myotis'': Görföl, T.; et al. (2017). [https://www.iucnredlist.org/species/85568289/85568292 "''Myotis borneoensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T85568289A85568292. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T85568289A85568292.en 10.2305/IUCN.UK.2017-2.RLTS.T85568289A85568292.en].
* ''Brandt's bat'': Gazaryan, S.; et al. (2021) [errata version of 2020 assessment]. [https://www.iucnredlist.org/species/85566997/195857637 "''Myotis brandtii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T85566997A195857637. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T85566997A195857637.en 10.2305/IUCN.UK.2020-2.RLTS.T85566997A195857637.en].
* ''Burmese whiskered myotis'': Görföl, T.; et al. (2020). [https://www.iucnredlist.org/species/85567622/22065126 "''Myotis montivagus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T85567622A22065126. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T85567622A22065126.en 10.2305/IUCN.UK.2020-2.RLTS.T85567622A22065126.en].
* ''California myotis'': Arroyo-Cabrales, J.; et al. (2017). [https://www.iucnredlist.org/species/14150/22061366 "''Myotis californicus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T14150A22061366. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T14150A22061366.en 10.2305/IUCN.UK.2017-2.RLTS.T14150A22061366.en].
* ''Cape hairy bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/14207/22063832 "''Myotis tricolor''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T14207A22063832. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T14207A22063832.en 10.2305/IUCN.UK.2017-2.RLTS.T14207A22063832.en].
* ''Cave myotis'': Solari, S. (2019). [https://www.iucnredlist.org/species/14208/22063586 "''Myotis velifer''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T14208A22063586. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T14208A22063586.en 10.2305/IUCN.UK.2019-1.RLTS.T14208A22063586.en].
* ''Chilean myotis'': Barquez, R.; et al. (2016). [https://www.iucnredlist.org/species/14151/22061103 "''Myotis chiloensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14151A22061103. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T14151A22061103.en 10.2305/IUCN.UK.2016-3.RLTS.T14151A22061103.en].
* ''Chinese water myotis'': Feng, J.; et al. (2019). [https://www.iucnredlist.org/species/136429/21984685 "''Myotis laniger''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136429A21984685. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T136429A21984685.en 10.2305/IUCN.UK.2019-3.RLTS.T136429A21984685.en].
* ''Cinnamon myotis'': Perez, S.; et al. (2017). [https://www.iucnredlist.org/species/14161/22056846 "''Myotis fortidens''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T14161A22056846. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T14161A22056846.en 10.2305/IUCN.UK.2017-2.RLTS.T14161A22056846.en].
* ''Cryptic myotis'': Russo, D.; et al. (2024) [errata version of 2023 assessment]. [https://www.iucnredlist.org/species/215154989/254355251 "''Myotis crypticus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2023''': e.T215154989A254355251.
* ''Csorba's mouse-eared bat'': Csorba, G.; et al. (2016). [https://www.iucnredlist.org/species/29420/22070788 "''Myotis csorbai''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T29420A22070788. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T29420A22070788.en 10.2305/IUCN.UK.2016-2.RLTS.T29420A22070788.en].
* ''Curacao myotis'': Solari, S. (2016). [https://www.iucnredlist.org/species/14184/22065759 "''Myotis nesopolus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14184A22065759. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T14184A22065759.en 10.2305/IUCN.UK.2016-1.RLTS.T14184A22065759.en].
* ''Dark-nosed small-footed myotis'': Arroyo-Cabrales, J.; et al. (2017). [https://www.iucnredlist.org/species/136784/22033542 "''Myotis melanorhinus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T136784A22033542. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T136784A22033542.en 10.2305/IUCN.UK.2017-2.RLTS.T136784A22033542.en].
* ''Daubenton's bat'': Kruskop, S. V.; et al. (2021) [errata version of 2020 assessment]. [https://www.iucnredlist.org/species/85342710/195858793 "''Myotis daubentonii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T85342710A195858793. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T85342710A195858793.en 10.2305/IUCN.UK.2020-2.RLTS.T85342710A195858793.en].
* ''David's myotis'': Jiang, T. L.; et al. (2019). [https://www.iucnredlist.org/species/136250/22003049 "''Myotis davidii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136250A22003049. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T136250A22003049.en 10.2305/IUCN.UK.2019-3.RLTS.T136250A22003049.en].
* ''Diminutive bat'': Solari, S. (2017). [https://www.iucnredlist.org/species/88151417/88151431 "''Myotis diminutus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T88151417A88151431. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T88151417A88151431.en 10.2305/IUCN.UK.2017-2.RLTS.T88151417A88151431.en].
* ''Dinelli's myotis'': Barquez, R.; et al. (2016). [https://www.iucnredlist.org/species/136204/22009702 "''Myotis dinellii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136204A22009702. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T136204A22009702.en 10.2305/IUCN.UK.2016-3.RLTS.T136204A22009702.en].
* ''Dominican myotis'': Larsen, R. (2016). [https://www.iucnredlist.org/species/14155/22057933 "''Myotis dominicensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14155A22057933. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T14155A22057933.en 10.2305/IUCN.UK.2016-1.RLTS.T14155A22057933.en].
* ''Eastern long-fingered bat'': Fukui, D.; et al. (2019). [https://www.iucnredlist.org/species/14177/22065868 "''Myotis macrodactylus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T14177A22065868. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T14177A22065868.en 10.2305/IUCN.UK.2019-3.RLTS.T14177A22065868.en].
* ''Eastern small-footed myotis'': Solari, S. (2018). [https://www.iucnredlist.org/species/14172/22055716 "''Myotis leibii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T14172A22055716. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T14172A22055716.en 10.2305/IUCN.UK.2018-2.RLTS.T14172A22055716.en].
* ''Eastern water bat'': Fukui, D.; et al. (2020). [https://www.iucnredlist.org/species/85342726/85342734 "''Myotis petax''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T85342726A85342734. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T85342726A85342734.en 10.2305/IUCN.UK.2020-2.RLTS.T85342726A85342734.en].
* ''Elegant myotis'': Miller, B.; et al. (2017) [errata version of 2016 assessment]. [https://www.iucnredlist.org/species/14156/115121563 "''Myotis elegans''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14156A115121563. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T14156A22057814.en 10.2305/IUCN.UK.2016-3.RLTS.T14156A22057814.en].
* ''Escalera's bat'': Russo, D.; et al. (2023). [https://www.iucnredlist.org/species/85733126/211003991 "''Myotis escalerai''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2023''': e.T85733126A211003991. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2023-1.RLTS.T85733126A211003991.en 10.2305/IUCN.UK.2023-1.RLTS.T85733126A211003991.en].
* ''Far Eastern myotis'': Fukui, D.; et al. (2019). [https://www.iucnredlist.org/species/14149/22061650 "''Myotis bombinus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T14149A22061650. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T14149A22061650.en 10.2305/IUCN.UK.2019-3.RLTS.T14149A22061650.en].
* ''Felten's myotis'': Juste, J.; et al. (2016). [https://www.iucnredlist.org/species/44864/22073410 "''Myotis punicus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T44864A22073410. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T44864A22073410.en 10.2305/IUCN.UK.2016-2.RLTS.T44864A22073410.en].
* ''Fish-eating bat'': Arroyo-Cabrales, J.; et al. (2016). [https://www.iucnredlist.org/species/14209/22069146 "''Myotis vivesi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14209A22069146. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T14209A22069146.en 10.2305/IUCN.UK.2016-1.RLTS.T14209A22069146.en].
* ''Findley's myotis'': Arroyo-Cabrales, J.; et al. (2016). [https://www.iucnredlist.org/species/14159/22058800 "''Myotis findleyi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14159A22058800. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T14159A22058800.en 10.2305/IUCN.UK.2016-1.RLTS.T14159A22058800.en].
* ''Flat-headed myotis'': Arroyo-Cabrales, J.; et al. (2016). [https://www.iucnredlist.org/species/14191/22066742 "''Myotis planiceps''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14191A22066742. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T14191A22066742.en 10.2305/IUCN.UK.2016-1.RLTS.T14191A22066742.en].
* ''Fraternal myotis'': Vincenot, C. E.; et al. (2021). [https://www.iucnredlist.org/species/85566806/22056940 "''Myotis frater''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T85566806A22056940. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T85566806A22056940.en 10.2305/IUCN.UK.2021-2.RLTS.T85566806A22056940.en].
* ''Fringed long-footed myotis'': Jiang, T. L.; et al. (2019). [https://www.iucnredlist.org/species/85735587/22058886 "''Myotis fimbriatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T85735587A22058886. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T85735587A22058886.en 10.2305/IUCN.UK.2019-3.RLTS.T85735587A22058886.en].
* ''Fringed myotis'': Arroyo-Cabrales, J.; et al. (2017). [https://www.iucnredlist.org/species/14206/22063246 "''Myotis thysanodes''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T14206A22063246. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T14206A22063246.en 10.2305/IUCN.UK.2017-2.RLTS.T14206A22063246.en].
* ''Frosted myotis'': Fukui, D.; et al. (2021) [errata version of 2019 assessment]. [https://www.iucnredlist.org/species/14192/209551299 "''Myotis pruinosus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T14192A209551299. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T14192A209551299.en 10.2305/IUCN.UK.2019-3.RLTS.T14192A209551299.en].
* ''Geoffroy's bat'': Piraccini, R. (2016). [https://www.iucnredlist.org/species/14129/22051191 "''Myotis emarginatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14129A22051191. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T14129A22051191.en 10.2305/IUCN.UK.2016-2.RLTS.T14129A22051191.en].
* ''Gomantong myotis'': Waldien, D. L.; et al. (2021). [https://www.iucnredlist.org/species/40035/22060096 "''Myotis gomantongensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T40035A22060096. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T40035A22060096.en 10.2305/IUCN.UK.2021-3.RLTS.T40035A22060096.en].
* ''Gray bat'': Solari, S. (2018). [https://www.iucnredlist.org/species/14132/22051652 "''Myotis grisescens''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T14132A22051652. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T14132A22051652.en 10.2305/IUCN.UK.2018-2.RLTS.T14132A22051652.en].
* ''Greater mouse-eared bat'': Coroiu, I.; et al. (2016). [https://www.iucnredlist.org/species/14133/22051759 "''Myotis myotis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14133A22051759. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T14133A22051759.en 10.2305/IUCN.UK.2016-2.RLTS.T14133A22051759.en].
* ''Guatemalan myotis'': Cajas C., J.; et al. (2016). [https://www.iucnredlist.org/species/14154/22058031 "''Myotis cobanensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14154A22058031. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T14154A22058031.en 10.2305/IUCN.UK.2016-2.RLTS.T14154A22058031.en].
* ''Hairy-faced bat'': Görföl, T.; et al. (2020). [https://www.iucnredlist.org/species/14142/22050272 "''Myotis annectans''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T14142A22050272. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T14142A22050272.en 10.2305/IUCN.UK.2020-2.RLTS.T14142A22050272.en].
* ''Hairy-legged myotis'': Barquez, R.; et al. (2016). [https://www.iucnredlist.org/species/14170/22056048 "''Myotis keaysi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14170A22056048. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T14170A22056048.en 10.2305/IUCN.UK.2016-3.RLTS.T14170A22056048.en].
* ''Herman's myotis'': Csorba, G.; et al. (2016). [https://www.iucnredlist.org/species/14165/22057251 "''Myotis hermani''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14165A22057251. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T14165A22057251.en 10.2305/IUCN.UK.2016-2.RLTS.T14165A22057251.en].
* ''Himalayan whiskered bat'': Santiago, K.; et al. (2021). [https://www.iucnredlist.org/species/14203/22064839 "''Myotis siligorensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T14203A22064839. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T14203A22064839.en 10.2305/IUCN.UK.2021-3.RLTS.T14203A22064839.en].
* ''Hodgson's bat'': Huang, J. C. -C.; et al. (2020). [https://www.iucnredlist.org/species/85736120/95642290 "''Myotis formosus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T85736120A95642290. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T85736120A95642290.en 10.2305/IUCN.UK.2020-2.RLTS.T85736120A95642290.en].
* ''Horsfield's bat'': Phelps, K.; et al. (2019). [https://www.iucnredlist.org/species/14166/22057415 "''Myotis horsfieldii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T14166A22057415. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T14166A22057415.en 10.2305/IUCN.UK.2019-3.RLTS.T14166A22057415.en].
* ''Ikonnikov's bat'': Zhigalin, A.; et al. (2020). [https://www.iucnredlist.org/species/14168/22057122 "''Myotis ikonnikovi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T14168A22057122. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T14168A22057122.en 10.2305/IUCN.UK.2020-3.RLTS.T14168A22057122.en].
* ''Indiana bat'': Arroyo-Cabrales, J.; et al. (2016). [https://www.iucnredlist.org/species/14136/22053184 "''Myotis sodalis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14136A22053184. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T14136A22053184.en 10.2305/IUCN.UK.2016-1.RLTS.T14136A22053184.en].
* ''Indochinese mouse-eared bat'': Son, N.; et al. (2019). [https://www.iucnredlist.org/species/85342688/85342691 "''Myotis indochinensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T85342688A85342691. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T85342688A85342691.en 10.2305/IUCN.UK.2019-3.RLTS.T85342688A85342691.en].
* ''Insular myotis'': Helgen, K.; et al. (2020). [https://www.iucnredlist.org/species/14169/22055968 "''Myotis insularum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T14169A22055968. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T14169A22055968.en 10.2305/IUCN.UK.2020-2.RLTS.T14169A22055968.en].
* ''Izecksohn's myotis'': Solari, S. (2017). [https://www.iucnredlist.org/species/88151563/88151572 "''Myotis izecksohni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T88151563A88151572. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T88151563A88151572.en 10.2305/IUCN.UK.2017-2.RLTS.T88151563A88151572.en].
* ''Kashmir cave bat'': Kruskop, S. V. (2016). [https://www.iucnredlist.org/species/14175/22056206 "''Myotis longipes''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14175A22056206. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T14175A22056206.en 10.2305/IUCN.UK.2016-2.RLTS.T14175A22056206.en].
* ''Keen's myotis'': Arroyo-Cabrales, J.; et al. (2017). [https://www.iucnredlist.org/species/14171/22055579 "''Myotis keenii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T14171A22055579. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T14171A22055579.en 10.2305/IUCN.UK.2017-2.RLTS.T14171A22055579.en].
* ''Kei myotis'': Bouillard, N. (2021). [https://www.iucnredlist.org/species/14205/22063416 "''Myotis stalkeri''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T14205A22063416. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T14205A22063416.en 10.2305/IUCN.UK.2021-3.RLTS.T14205A22063416.en].
* ''Kock's mouse-eared bat'': Happold., M. (2019). [https://www.iucnredlist.org/species/136678/22038629 "''Myotis dieteri''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136678A22038629. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T136678A22038629.en 10.2305/IUCN.UK.2019-3.RLTS.T136678A22038629.en].
* ''Large myotis'': Jiang, T. L.; et al. (2019). [https://www.iucnredlist.org/species/14152/22060946 "''Myotis chinensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T14152A22060946. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T14152A22060946.en 10.2305/IUCN.UK.2019-3.RLTS.T14152A22060946.en].
* ''Large-footed bat'': Bouillard, N. (2021). [https://www.iucnredlist.org/species/85735326/22049231 "''Myotis adversus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T85735326A22049231. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T85735326A22049231.en 10.2305/IUCN.UK.2021-2.RLTS.T85735326A22049231.en].
* ''Large-footed myotis'': Gorecki , V.; et al. (2021). [https://www.iucnredlist.org/species/136697/22039960 "''Myotis macropus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T136697A22039960. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T136697A22039960.en 10.2305/IUCN.UK.2021-1.RLTS.T136697A22039960.en].
* ''LaVal's myotis'': Solari, S. (2017). [https://www.iucnredlist.org/species/88151601/88151604 "''Myotis lavali''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T88151601A88151604. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T88151601A88151604.en 10.2305/IUCN.UK.2017-2.RLTS.T88151601A88151604.en].
* ''Lesser large-footed bat'': Bates, P. J. J.; et al. (2020). [https://www.iucnredlist.org/species/14164/22056644 "''Myotis hasseltii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T14164A22056644. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T14164A22056644.en 10.2305/IUCN.UK.2020-2.RLTS.T14164A22056644.en].
* ''Lesser mouse-eared bat'': Juste, J.; et al. (2016). [https://www.iucnredlist.org/species/14124/22053297 "''Myotis blythii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14124A22053297. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T14124A22053297.en 10.2305/IUCN.UK.2016-2.RLTS.T14124A22053297.en].
* ''Little brown bat'': Solari, S. (2021) [amended version of 2018 assessment]. [https://www.iucnredlist.org/species/14176/208031565 "''Myotis lucifugus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T14176A208031565. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T14176A208031565.en 10.2305/IUCN.UK.2021-3.RLTS.T14176A208031565.en].
* ''Long-eared myotis'': Arroyo-Cabrales, J.; et al. (2017). [https://www.iucnredlist.org/species/14157/22059133 "''Myotis evotis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T14157A22059133. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T14157A22059133.en 10.2305/IUCN.UK.2017-2.RLTS.T14157A22059133.en].
* ''Long-fingered bat'': Paunović, M. (2016). [https://www.iucnredlist.org/species/14126/22054131 "''Myotis capaccinii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14126A22054131. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T14126A22054131.en 10.2305/IUCN.UK.2016-2.RLTS.T14126A22054131.en].
* ''Long-legged myotis'': Solari, S. (2019). [https://www.iucnredlist.org/species/14210/22069325 "''Myotis volans''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T14210A22069325. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T14210A22069325.en 10.2305/IUCN.UK.2019-1.RLTS.T14210A22069325.en].
* ''Long-tailed myotis'': Vincenot, C. E.; et al. (2021). [https://www.iucnredlist.org/species/85566977/85566980 "''Myotis longicaudatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T85566977A85566980. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T85566977A85566980.en 10.2305/IUCN.UK.2021-2.RLTS.T85566977A85566980.en].
* ''Long-toed myotis'': Ruedi, M.; et al. (2017). [https://www.iucnredlist.org/species/85342651/85342654 "''Myotis secundus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T85342651A85342654. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T85342651A85342654.en 10.2305/IUCN.UK.2017-2.RLTS.T85342651A85342654.en].
* ''Malagasy mouse-eared bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/14163/22056541 "''Myotis goudoti''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T14163A22056541. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T14163A22056541.en 10.2305/IUCN.UK.2017-2.RLTS.T14163A22056541.en].
* ''Malaysian whiskered myotis'': Görföl, T.; et al. (2017). [https://www.iucnredlist.org/species/85568302/85568305 "''Myotis federatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T85568302A85568305. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T85568302A85568305.en 10.2305/IUCN.UK.2017-2.RLTS.T85568302A85568305.en].
* ''Maluku myotis'': Armstrong, K. N. (2021). [https://www.iucnredlist.org/species/136770/22033795 "''Myotis moluccarum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T136770A22033795. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T136770A22033795.en 10.2305/IUCN.UK.2021-3.RLTS.T136770A22033795.en].
* ''Mandelli's mouse-eared bat'': Srinivasulu, B.; et al. (2019). [https://www.iucnredlist.org/species/14202/22063965 "''Myotis sicarius''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T14202A22063965. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T14202A22063965.en 10.2305/IUCN.UK.2019-3.RLTS.T14202A22063965.en].
* ''Montane myotis'': Solari, S. (2018). [https://www.iucnredlist.org/species/14187/22067211 "''Myotis oxyotus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T14187A22067211. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T14187A22067211.en 10.2305/IUCN.UK.2018-2.RLTS.T14187A22067211.en].
* ''Morris's bat'': Jacobs, D.; et al. (2019). [https://www.iucnredlist.org/species/14182/22065314 "''Myotis morrisi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T14182A22065314. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T14182A22065314.en 10.2305/IUCN.UK.2019-3.RLTS.T14182A22065314.en].
* ''Natterer's bat'': Russo, D.; et al. (2023). [https://www.iucnredlist.org/species/215492021/211005466 "''Myotis nattereri''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2023''': e.T215492021A211005466. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2023-1.RLTS.T215492021A211005466.en 10.2305/IUCN.UK.2023-1.RLTS.T215492021A211005466.en].
* ''Nepal myotis'': Srinivasulu, B.; et al. (2019). [https://www.iucnredlist.org/species/136495/21976309 "''Myotis nipalensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136495A21976309. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T136495A21976309.en 10.2305/IUCN.UK.2019-3.RLTS.T136495A21976309.en].
* ''Nimba myotis'': Bakwo Fils, E. M.; et al. (2022). [https://www.iucnredlist.org/species/216617275/216617367 "''Myotis nimbaensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2022''': e.T216617275A216617367. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2022-2.RLTS.T216617275A216617367.en 10.2305/IUCN.UK.2022-2.RLTS.T216617275A216617367.en].
* ''Northern long-eared bat'': Solari, S. (2018). [https://www.iucnredlist.org/species/14201/22064312 "''Myotis septentrionalis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T14201A22064312. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T14201A22064312.en 10.2305/IUCN.UK.2018-2.RLTS.T14201A22064312.en].
* ''Orange-fingered myotis'': Csorba, G.; et al. (2016). [https://www.iucnredlist.org/species/136411/22017446 "''Myotis rufopictus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136411A22017446. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T136411A22017446.en 10.2305/IUCN.UK.2016-2.RLTS.T136411A22017446.en].
* ''Pallid large-footed myotis'': Duya, M. R.; et al. (2019). [https://www.iucnredlist.org/species/14178/22065997 "''Myotis macrotarsus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T14178A22065997. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T14178A22065997.en 10.2305/IUCN.UK.2019-3.RLTS.T14178A22065997.en].
* ''Peninsular myotis'': Arroyo-Cabrales, J.; et al. (2016). [https://www.iucnredlist.org/species/14189/22066405 "''Myotis peninsularis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14189A22066405. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T14189A22066405.en 10.2305/IUCN.UK.2016-1.RLTS.T14189A22066405.en].
* ''Peters's myotis'': Wiles, G.; et al. (2021). [https://www.iucnredlist.org/species/14144/22050847 "''Myotis ater''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T14144A22050847. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T14144A22050847.en 10.2305/IUCN.UK.2021-2.RLTS.T14144A22050847.en].
* ''Peyton's myotis'': Csorba, G.; et al. (2017). [https://www.iucnredlist.org/species/85568321/85568324 "''Myotis peytoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T85568321A85568324. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T85568321A85568324.en 10.2305/IUCN.UK.2017-2.RLTS.T85568321A85568324.en].
* ''Pond bat'': Piraccini, R. (2016). [https://www.iucnredlist.org/species/14127/22055164 "''Myotis dasycneme''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14127A22055164. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T14127A22055164.en 10.2305/IUCN.UK.2016-2.RLTS.T14127A22055164.en].
* ''Red myotis'': Solari, S. (2019). [https://www.iucnredlist.org/species/14197/22062092 "''Myotis ruber''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T14197A22062092. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T14197A22062092.en 10.2305/IUCN.UK.2019-3.RLTS.T14197A22062092.en].
* ''Reddish myotis'': Ruedi, M.; et al. (2017). [https://www.iucnredlist.org/species/85342662/85342666 "''Myotis soror''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T85342662A85342666. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T85342662A85342666.en 10.2305/IUCN.UK.2017-2.RLTS.T85342662A85342666.en].
* ''Reddish-black myotis'': Csorba, G.; et al. (2020). [https://www.iucnredlist.org/species/85735909/85735913 "''Myotis rufoniger''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T85735909A85735913. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T85735909A85735913.en 10.2305/IUCN.UK.2020-3.RLTS.T85735909A85735913.en].
* ''Rickett's big-footed bat'': Jiang, T. L.; et al. (2019). [https://www.iucnredlist.org/species/14193/22062554 "''Myotis pilosus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T14193A22062554. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T14193A22062554.en 10.2305/IUCN.UK.2019-3.RLTS.T14193A22062554.en].
* ''Ridley's bat'': Azhar, M. I. (2020). [https://www.iucnredlist.org/species/14194/22062376 "''Myotis ridleyi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T14194A22062376. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T14194A22062376.en 10.2305/IUCN.UK.2020-2.RLTS.T14194A22062376.en].
* ''Riparian myotis'': Barquez, R.; et al. (2016). [https://www.iucnredlist.org/species/14195/22062950 "''Myotis riparius''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14195A22062950. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T14195A22062950.en 10.2305/IUCN.UK.2016-1.RLTS.T14195A22062950.en].
* ''Rufous mouse-eared bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/14148/22059585 "''Myotis bocagii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T14148A22059585. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T14148A22059585.en 10.2305/IUCN.UK.2017-2.RLTS.T14148A22059585.en].
* ''Schaub's myotis'': Piraccini, R. (2016). [https://www.iucnredlist.org/species/14198/22061746 "''Myotis schaubi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14198A22061746. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T14198A22061746.en 10.2305/IUCN.UK.2016-2.RLTS.T14198A22061746.en].
* ''Schwartz's myotis'': Larsen, R. (2016). [https://www.iucnredlist.org/species/76435251/22066280 "''Myotis martiniquensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T76435251A22066280. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T76435251A22066280.en 10.2305/IUCN.UK.2016-1.RLTS.T76435251A22066280.en].
* ''Scott's mouse-eared bat'': Benda, P.; et al. (2017). [https://www.iucnredlist.org/species/14199/22062198 "''Myotis scotti''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T14199A22062198. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T14199A22062198.en 10.2305/IUCN.UK.2017-2.RLTS.T14199A22062198.en].
* ''Siberian bat'': Zhigalin, A. (2020). [https://www.iucnredlist.org/species/85567062/85567065 "''Myotis sibiricus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T85567062A85567065. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T85567062A85567065.en 10.2305/IUCN.UK.2020-2.RLTS.T85567062A85567065.en].
* ''Silver-tipped myotis'': Barquez, R.; et al. (2016). [https://www.iucnredlist.org/species/14140/22049892 "''Myotis albescens''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14140A22049892. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T14140A22049892.en 10.2305/IUCN.UK.2016-1.RLTS.T14140A22049892.en].
* ''Singapore whiskered bat'': Csorba, G.; et al. (2016). [https://www.iucnredlist.org/species/14186/22067080 "''Myotis oreias''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14186A22067080. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T14186A22067080.en 10.2305/IUCN.UK.2016-2.RLTS.T14186A22067080.en].
* ''Southeastern myotis'': Arroyo-Cabrales, J.; et al. (2017). [https://www.iucnredlist.org/species/14147/22059907 "''Myotis austroriparius''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T14147A22059907. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T14147A22059907.en 10.2305/IUCN.UK.2017-2.RLTS.T14147A22059907.en].
* ''Southern myotis'': Barquez, R.; et al. (2017) [errata version of 2016 assessment]. [https://www.iucnredlist.org/species/14139/115121458 "''Myotis aelleni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14139A115121458. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T14139A22049723.en 10.2305/IUCN.UK.2016-3.RLTS.T14139A22049723.en].
* ''Southwestern myotis'': Arroyo-Cabrales, J.; et al. (2017). [https://www.iucnredlist.org/species/14145/22060698 "''Myotis auriculus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T14145A22060698. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T14145A22060698.en 10.2305/IUCN.UK.2017-2.RLTS.T14145A22060698.en].
* ''Szechwan myotis'': Jiang, T. L.; et al. (2019). [https://www.iucnredlist.org/species/14141/22050057 "''Myotis altarium''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T14141A22050057. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T14141A22050057.en 10.2305/IUCN.UK.2019-3.RLTS.T14141A22050057.en].
* ''Thick-thumbed myotis'': Csorba, G.; et al. (2020). [https://www.iucnredlist.org/species/14196/22062800 "''Myotis rosseti''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T14196A22062800. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T14196A22062800.en 10.2305/IUCN.UK.2020-2.RLTS.T14196A22062800.en].
* ''Velvety myotis'': Barquez, R.; et al. (2016). [https://www.iucnredlist.org/species/14204/22064642 "''Myotis simus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14204A22064642. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T14204A22064642.en 10.2305/IUCN.UK.2016-2.RLTS.T14204A22064642.en].
* ''Wall-roosting mouse-eared bat'': Srinivasulu, C.; et al. (2019). [https://www.iucnredlist.org/species/85537578/22065403 "''Myotis muricola''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T85537578A22065403. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T85537578A22065403.en 10.2305/IUCN.UK.2019-3.RLTS.T85537578A22065403.en].
* ''Weber's myotis'': Bouillard, N.; et al. (2021). [https://www.iucnredlist.org/species/85736011/85736023 "''Myotis weberi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T85736011A85736023. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T85736011A85736023.en 10.2305/IUCN.UK.2021-2.RLTS.T85736011A85736023.en].
* ''Welwitsch's bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/14211/22068792 "''Myotis welwitschii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T14211A22068792. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T14211A22068792.en 10.2305/IUCN.UK.2017-2.RLTS.T14211A22068792.en].
* ''Western small-footed bat'': Arroyo-Cabrales, J.; et al. (2017). [https://www.iucnredlist.org/species/14153/22058110 "''Myotis ciliolabrum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T14153A22058110. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T14153A22058110.en 10.2305/IUCN.UK.2017-2.RLTS.T14153A22058110.en].
* ''Whiskered bat'': Coroiu, I. (2016). [https://www.iucnredlist.org/species/14134/22052250 "''Myotis mystacinus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14134A22052250. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T14134A22052250.en 10.2305/IUCN.UK.2016-2.RLTS.T14134A22052250.en].
* ''Yanbaru whiskered bat'': Fukui, D.; et al. (2021) [errata version of 2019 assessment]. [https://www.iucnredlist.org/species/29484/209551473 "''Myotis yanbarensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T29484A209551473. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T29484A209551473.en 10.2305/IUCN.UK.2019-3.RLTS.T29484A209551473.en].
* ''Yellowish myotis'': Barquez, R.; et al. (2017) [errata version of 2016 assessment]. [https://www.iucnredlist.org/species/14174/115121699 "''Myotis levis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14174A115121699. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T14174A22056440.en 10.2305/IUCN.UK.2016-3.RLTS.T14174A22056440.en].
* ''Yuma myotis'': Solari, S. (2019). [https://www.iucnredlist.org/species/14213/22068335 "''Myotis yumanensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T14213A22068335. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T14213A22068335.en 10.2305/IUCN.UK.2019-1.RLTS.T14213A22068335.en].
]
[Ruedi, M.; et al. (2017). [https://www.iucnredlist.org/species/85537971/85537974 "''Submyotodon latirostris''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T85537971A85537974. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T85537971A85537974.en 10.2305/IUCN.UK.2017-2.RLTS.T85537971A85537974.en].]
[Arroyo-Cabrales, J.; et al. (2017). [https://www.iucnredlist.org/species/1790/22129152 "''Antrozous pallidus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T1790A22129152. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T1790A22129152.en 10.2305/IUCN.UK.2017-2.RLTS.T1790A22129152.en].]
[''Arielulus'' habitats:
* ''Bronze sprite'': Bates, P.; et al. (2019). [https://www.iucnredlist.org/species/41534/22005596 "''Arielulus circumdatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T41534A22005596. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T41534A22005596.en 10.2305/IUCN.UK.2019-3.RLTS.T41534A22005596.en].
* ''Coppery sprite'': MacArthur, E. (2016). [https://www.iucnredlist.org/species/40775/22134373 "''Arielulus cuprosus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T40775A22134373. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T40775A22134373.en 10.2305/IUCN.UK.2016-2.RLTS.T40775A22134373.en].
* ''Necklace sprite'': Huang, J. C. -C.; et al. (2019). [https://www.iucnredlist.org/species/40032/22063510 "''Arielulus torquatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T40032A22063510. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T40032A22063510.en 10.2305/IUCN.UK.2019-3.RLTS.T40032A22063510.en].
* ''Social sprite'': Francis, C. M.; et al. (2020). [https://www.iucnredlist.org/species/40776/22134204 "''Arielulus societatis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T40776A22134204. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T40776A22134204.en 10.2305/IUCN.UK.2020-3.RLTS.T40776A22134204.en].
]
[''Baeodon'' habitats:
* ''Allen's yellow bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/19679/21989577 "''Baeodon alleni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T19679A21989577. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T19679A21989577.en 10.2305/IUCN.UK.2019-1.RLTS.T19679A21989577.en].
* ''Slender yellow bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/19681/22007578 "''Baeodon gracilis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T19681A22007578. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T19681A22007578.en 10.2305/IUCN.UK.2019-1.RLTS.T19681A22007578.en].
]
[''Barbastella'' habitats:
* ''Arabian barbastelle'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/85181182/22029016 "''Barbastella leucomelas''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T85181182A22029016. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T85181182A22029016.en 10.2305/IUCN.UK.2017-2.RLTS.T85181182A22029016.en].
* ''Beijing barbastelle'': Kruskop, S. V.; et al. (2021). [https://www.iucnredlist.org/species/85180824/85180839 "''Barbastella beijingensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T85180824A85180839. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T85180824A85180839.en 10.2305/IUCN.UK.2021-1.RLTS.T85180824A85180839.en].
* ''Eastern barbastelle'': Kruskop, S. V. (2021). [https://www.iucnredlist.org/species/85197261/85197270 "''Barbastella darjelingensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T85197261A85197270. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T85197261A85197270.en 10.2305/IUCN.UK.2021-2.RLTS.T85197261A85197270.en].
* ''Western barbastelle'': Piraccini, R. (2016). [https://www.iucnredlist.org/species/2553/22029285 "''Barbastella barbastellus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T2553A22029285. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T2553A22029285.en 10.2305/IUCN.UK.2016-2.RLTS.T2553A22029285.en].
]
[Solari, S. (2018). [https://www.iucnredlist.org/species/1789/22129523 "''Bauerus dubiaquercus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T1789A22129523. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T1789A22129523.en 10.2305/IUCN.UK.2018-2.RLTS.T1789A22129523.en].]
[''Chalinolobus'' habitats:
* ''Chocolate wattled bat'': Lumsden, L. F.; et al. (2021) [amended version of 2019 assessment]. [https://www.iucnredlist.org/species/4419/209530864 "''Chalinolobus morio''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T4419A209530864. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T4419A209530864.en 10.2305/IUCN.UK.2021-3.RLTS.T4419A209530864.en].
* ''Gould's wattled bat'': Lumsden, L. F.; et al. (2021) [amended version of 2020 assessment]. [https://www.iucnredlist.org/species/4417/209548746 "''Chalinolobus gouldii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T4417A209548746. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T4417A209548746.en 10.2305/IUCN.UK.2021-3.RLTS.T4417A209548746.en].
* ''Hoary wattled bat'': Hutson, A. M.; et al. (2020). [https://www.iucnredlist.org/species/4421/21984276 "''Chalinolobus nigrogriseus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T4421A21984276. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T4421A21984276.en 10.2305/IUCN.UK.2020-3.RLTS.T4421A21984276.en].
* ''Large-eared pied bat'': Pennay, M. (2020). [https://www.iucnredlist.org/species/4414/21986274 "''Chalinolobus dwyeri''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T4414A21986274. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T4414A21986274.en 10.2305/IUCN.UK.2020-3.RLTS.T4414A21986274.en].
* ''Little pied bat'': Pennay, M. (2020). [https://www.iucnredlist.org/species/4422/21984147 "''Chalinolobus picatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T4422A21984147. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T4422A21984147.en 10.2305/IUCN.UK.2020-3.RLTS.T4422A21984147.en].
* ''New Caledonian wattled bat'': Brescia, F. (2020). [https://www.iucnredlist.org/species/4420/21984825 "''Chalinolobus neocaledonicus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T4420A21984825. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T4420A21984825.en 10.2305/IUCN.UK.2020-3.RLTS.T4420A21984825.en].
* ''New Zealand long-tailed bat'': O'Donnell, C. (2021). [https://www.iucnredlist.org/species/4425/21985132 "''Chalinolobus tuberculatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T4425A21985132. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T4425A21985132.en 10.2305/IUCN.UK.2021-1.RLTS.T4425A21985132.en].
]
[''Corynorhinus'' habitats:
* ''Mexican big-eared bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/17599/21976792 "''Corynorhinus mexicanus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T17599A21976792. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T17599A21976792.en 10.2305/IUCN.UK.2019-3.RLTS.T17599A21976792.en].
* ''Rafinesque's big-eared bat'': Arroyo-Cabrales, J.; et al. (2017). [https://www.iucnredlist.org/species/17600/21976905 "''Corynorhinus rafinesquii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T17600A21976905. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T17600A21976905.en 10.2305/IUCN.UK.2017-2.RLTS.T17600A21976905.en].
* ''Townsend's big-eared bat'': Arroyo-Cabrales, J.; et al. (2017). [https://www.iucnredlist.org/species/17598/21976681 "''Corynorhinus townsendii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T17598A21976681. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T17598A21976681.en 10.2305/IUCN.UK.2017-2.RLTS.T17598A21976681.en].
]
[''Eptesicus'' habitats:
* ''Anatolian serotine'': Bouillard, N. (2021). [https://www.iucnredlist.org/species/85198368/85199537 "''Eptesicus anatolicus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T85198368A85199537. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T85198368A85199537.en 10.2305/IUCN.UK.2021-1.RLTS.T85198368A85199537.en].
* ''Argentine brown bat'': Barquez, R.; et al. (2016). [https://www.iucnredlist.org/species/7927/22118013 "''Eptesicus furinalis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T7927A22118013. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T7927A22118013.en 10.2305/IUCN.UK.2016-1.RLTS.T7927A22118013.en].
* ''Big brown bat'': Miller, B.; et al. (2016). [https://www.iucnredlist.org/species/7928/22118197 "''Eptesicus fuscus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T7928A22118197. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T7928A22118197.en 10.2305/IUCN.UK.2016-3.RLTS.T7928A22118197.en].
* ''Bobrinski's serotine'': Srinivasulu, C. (2019). [https://www.iucnredlist.org/species/7914/22114842 "''Eptesicus bobrinskoi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T7914A22114842. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T7914A22114842.en 10.2305/IUCN.UK.2019-3.RLTS.T7914A22114842.en].
* ''Botta's serotine'': Bouillard, N. (2021). [https://www.iucnredlist.org/species/85197425/22114599 "''Eptesicus bottae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T85197425A22114599. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T85197425A22114599.en 10.2305/IUCN.UK.2021-1.RLTS.T85197425A22114599.en].
* ''Brazilian brown bat'': Barquez, R.; et al. (2016). [https://www.iucnredlist.org/species/7916/22114459 "''Eptesicus brasiliensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T7916A22114459. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T7916A22114459.en 10.2305/IUCN.UK.2016-1.RLTS.T7916A22114459.en].
* ''Chiriquinan serotine'': Solari, S. (2019). [https://www.iucnredlist.org/species/136524/21981386 "''Eptesicus chiriquinus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136524A21981386. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T136524A21981386.en 10.2305/IUCN.UK.2019-1.RLTS.T136524A21981386.en].
* ''Diminutive serotine'': González, E. M.; et al. (2017) [errata version of 2016 assessment]. [https://www.iucnredlist.org/species/7922/115087028 "''Eptesicus diminutus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T7922A115087028. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T7922A22118742.en 10.2305/IUCN.UK.2016-3.RLTS.T7922A22118742.en].
* ''Gobi big brown bat'': Srinivasulu, C.; et al. (2019). [https://www.iucnredlist.org/species/41531/22004381 "''Eptesicus gobiensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T41531A22004381. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T41531A22004381.en 10.2305/IUCN.UK.2019-3.RLTS.T41531A22004381.en].
* ''Guadeloupe big brown bat'': Barataud, M. (2016). [https://www.iucnredlist.org/species/7929/22117922 "''Eptesicus guadeloupensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T7929A22117922. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T7929A22117922.en 10.2305/IUCN.UK.2016-1.RLTS.T7929A22117922.en].
* ''Harmless serotine'': Velazco, P.; et al. (2020) [amended version of 2016 assessment]. [https://www.iucnredlist.org/species/7932/166506353 "''Eptesicus innoxius''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T7932A166506353. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-1.RLTS.T7932A166506353.en 10.2305/IUCN.UK.2020-1.RLTS.T7932A166506353.en].
* ''Horn-skinned bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/7926/22118366 "''Eptesicus floweri''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T7926A22118366. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T7926A22118366.en 10.2305/IUCN.UK.2017-2.RLTS.T7926A22118366.en].
* ''Japanese short-tailed bat'': Fukui, D. (2021) [errata version of 2020 assessment]. [https://www.iucnredlist.org/species/136823/209552552 "''Eptesicus japonensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T136823A209552552. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T136823A209552552.en 10.2305/IUCN.UK.2020-2.RLTS.T136823A209552552.en].
* ''Kobayashi's bat'': Fukui, D. (2019). [https://www.iucnredlist.org/species/7933/22117423 "''Eptesicus kobayashii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T7933A22117423. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T7933A22117423.en 10.2305/IUCN.UK.2019-3.RLTS.T7933A22117423.en].
* ''Lagos serotine'': Schlitter, D. (2019). [https://www.iucnredlist.org/species/7937/22120759 "''Eptesicus platyops''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T7937A22120759. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T7937A22120759.en 10.2305/IUCN.UK.2019-3.RLTS.T7937A22120759.en].
* ''Little black serotine'': Molinari, J.; et al. (2016). [https://www.iucnredlist.org/species/7912/22115355 "''Eptesicus andinus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T7912A22115355. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T7912A22115355.en 10.2305/IUCN.UK.2016-1.RLTS.T7912A22115355.en].
* ''Long-tailed house bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/7931/22117704 "''Eptesicus hottentotus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T7931A22117704. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T7931A22117704.en 10.2305/IUCN.UK.2017-2.RLTS.T7931A22117704.en].
* ''Meridional serotine'': Juste, J. (2016). [https://www.iucnredlist.org/species/85200107/85200275 "''Eptesicus isabellinus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T85200107A85200275. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T85200107A85200275.en 10.2305/IUCN.UK.2016-2.RLTS.T85200107A85200275.en].
* ''Northern bat'': Coroiu, I. (2016). [https://www.iucnredlist.org/species/7910/22116204 "''Eptesicus nilssonii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T7910A22116204. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T7910A22116204.en 10.2305/IUCN.UK.2016-2.RLTS.T7910A22116204.en].
* ''Ognev's serotine'': Srinivasulu, C.; et al. (2020). [https://www.iucnredlist.org/species/85198662/85198671 "''Eptesicus ognevi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T85198662A85198671. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T85198662A85198671.en 10.2305/IUCN.UK.2020-3.RLTS.T85198662A85198671.en].
* ''Oriental serotine'': Srinivasulu, C.; et al. (2019). [https://www.iucnredlist.org/species/85200202/85200236 "''Eptesicus pachyomus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T85200202A85200236. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T85200202A85200236.en 10.2305/IUCN.UK.2019-3.RLTS.T85200202A85200236.en].
* ''Serotine bat'': Godlevska, L.; et al. (2021) [amended version of 2020 assessment]. [https://www.iucnredlist.org/species/85199559/195834153 "''Eptesicus serotinus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T85199559A195834153. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T85199559A195834153.en 10.2305/IUCN.UK.2021-1.RLTS.T85199559A195834153.en].
* ''Sombre bat'': Molur, S.; et al. (2016). [https://www.iucnredlist.org/species/7942/22119447 "''Eptesicus tatei''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T7942A22119447. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T7942A22119447.en 10.2305/IUCN.UK.2016-2.RLTS.T7942A22119447.en].
* ''Surat helmeted bat'': Csorba, G.; et al. (2016). [https://www.iucnredlist.org/species/7921/22118595 "''Eptesicus dimissus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T7921A22118595. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T7921A22118595.en 10.2305/IUCN.UK.2016-2.RLTS.T7921A22118595.en].
* ''Taddei's serotine'': Solari, S. (2017). [https://www.iucnredlist.org/species/88151044/88151047 "''Eptesicus taddeii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T88151044A88151047. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T88151044A88151047.en 10.2305/IUCN.UK.2017-2.RLTS.T88151044A88151047.en].
* ''Thick-eared bat'': Srinivasulu, C.; et al. (2019). [https://www.iucnredlist.org/species/7936/22117270 "''Eptesicus pachyotis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T7936A22117270. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T7936A22117270.en 10.2305/IUCN.UK.2019-3.RLTS.T7936A22117270.en].
]
[Arroyo-Cabrales, J.; et al. (2017). [https://www.iucnredlist.org/species/8166/22028573 "''Euderma maculatum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T8166A22028573. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T8166A22028573.en 10.2305/IUCN.UK.2017-2.RLTS.T8166A22028573.en].]
[''Falsistrellus'' habitats:
* ''Eastern false pipistrelle'': Lumsden, L. F.; et al. (2021). [https://www.iucnredlist.org/species/17367/22123618 "''Falsistrellus tasmaniensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T17367A22123618. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T17367A22123618.en 10.2305/IUCN.UK.2021-1.RLTS.T17367A22123618.en].
* ''Western false pipistrelle'': Armstrong, K. N.; et al. (2021) [amended version of 2017 assessment]. [https://www.iucnredlist.org/species/17348/209540109 "''Falsistrellus mackenziei''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T17348A209540109. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T17348A209540109.en 10.2305/IUCN.UK.2021-3.RLTS.T17348A209540109.en].
]
[''Glauconycteris'' habitats:
* ''Abo bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/44798/22069513 "''Glauconycteris poensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T44798A22069513. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T44798A22069513.en 10.2305/IUCN.UK.2017-2.RLTS.T44798A22069513.en].
* ''Allen's spotted bat'': Schlitter, D. (2019). [https://www.iucnredlist.org/species/44795/22070303 "''Glauconycteris humeralis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T44795A22070303. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T44795A22070303.en 10.2305/IUCN.UK.2019-3.RLTS.T44795A22070303.en].
* ''Allen's striped bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/44789/22068173 "''Glauconycteris alboguttata''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T44789A22068173. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T44789A22068173.en 10.2305/IUCN.UK.2017-2.RLTS.T44789A22068173.en].
* ''Beatrix's bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/44791/22068514 "''Glauconycteris beatrix''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T44791A22068514. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T44791A22068514.en 10.2305/IUCN.UK.2017-2.RLTS.T44791A22068514.en].
* ''Bibundi bat'': Jacobs, D.; et al. (2019). [https://www.iucnredlist.org/species/44793/22070128 "''Glauconycteris egeria''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T44793A22070128. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T44793A22070128.en 10.2305/IUCN.UK.2019-3.RLTS.T44793A22070128.en].
* ''Curry's bat'': Schlitter, D. (2019). [https://www.iucnredlist.org/species/44792/22068253 "''Glauconycteris curryae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T44792A22068253. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T44792A22068253.en 10.2305/IUCN.UK.2019-3.RLTS.T44792A22068253.en].
* ''Glen's wattled bat'': Jacobs, D.; et al. (2019). [https://www.iucnredlist.org/species/44794/22070046 "''Glauconycteris gleni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T44794A22070046. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T44794A22070046.en 10.2305/IUCN.UK.2019-3.RLTS.T44794A22070046.en].
* ''Kenyan wattled bat'': Jacobs, D.; et al. (2019). [https://www.iucnredlist.org/species/44796/22070228 "''Glauconycteris kenyacola''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T44796A22070228. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T44796A22070228.en 10.2305/IUCN.UK.2019-3.RLTS.T44796A22070228.en].
* ''Machado's butterfly bat'': Schlitter, D. (2019). [https://www.iucnredlist.org/species/44797/22069652 "''Glauconycteris machadoi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T44797A22069652. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T44797A22069652.en 10.2305/IUCN.UK.2019-3.RLTS.T44797A22069652.en].
* ''Pied butterfly bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/44799/22069930 "''Glauconycteris superba''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T44799A22069930. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T44799A22069930.en 10.2305/IUCN.UK.2017-2.RLTS.T44799A22069930.en].
* ''Silvered bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/44790/22068006 "''Glauconycteris argentata''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T44790A22068006. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T44790A22068006.en 10.2305/IUCN.UK.2017-2.RLTS.T44790A22068006.en].
* ''Variegated butterfly bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/44800/22069727 "''Glauconycteris variegata''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T44800A22069727. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T44800A22069727.en 10.2305/IUCN.UK.2017-2.RLTS.T44800A22069727.en].
]
[''Glischropus'' habitats:
* ''Common thick-thumbed bat'': Bouillard, N.; et al. (2021). [https://www.iucnredlist.org/species/81187867/22105878 "''Glischropus tylopus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T81187867A22105878. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T81187867A22105878.en 10.2305/IUCN.UK.2021-2.RLTS.T81187867A22105878.en].
* ''Indochinese thick-thumbed bat'': Csorba, G.; et al. (2019). [https://www.iucnredlist.org/species/81189973/95642230 "''Glischropus bucephalus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T81189973A95642230. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T81189973A95642230.en 10.2305/IUCN.UK.2019-3.RLTS.T81189973A95642230.en].
* ''Javan thick-thumbed bat'': Görföl, T.; et al. (2016). [https://www.iucnredlist.org/species/9247/22106075 "''Glischropus javanus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T9247A22106075. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T9247A22106075.en 10.2305/IUCN.UK.2016-2.RLTS.T9247A22106075.en].
]
[''Hesperoptenus'' habitats:
* ''Blanford's bat'': Senawi, J.; et al. (2019). [https://www.iucnredlist.org/species/9975/22076582 "''Hesperoptenus blanfordi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T9975A22076582. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T9975A22076582.en 10.2305/IUCN.UK.2019-3.RLTS.T9975A22076582.en].
* ''False serotine bat'': Senawi, J.; et al. (2020). [https://www.iucnredlist.org/species/9976/22076446 "''Hesperoptenus doriae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T9976A22076446. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T9976A22076446.en 10.2305/IUCN.UK.2020-2.RLTS.T9976A22076446.en].
* ''Gaskell's false serotine'': Wortham, G.; et al. (2021). [https://www.iucnredlist.org/species/9977/22076119 "''Hesperoptenus gaskelli''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T9977A22076119. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T9977A22076119.en 10.2305/IUCN.UK.2021-3.RLTS.T9977A22076119.en].
* ''Large false serotine'': Senawi, J.; et al. (2020). [https://www.iucnredlist.org/species/9979/22076259 "''Hesperoptenus tomesi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T9979A22076259. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T9979A22076259.en 10.2305/IUCN.UK.2020-2.RLTS.T9979A22076259.en].
* ''Tickell's bat'': Srinivasulu, B.; et al. (2019). [https://www.iucnredlist.org/species/9978/22075896 "''Hesperoptenus tickelli''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T9978A22075896. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T9978A22075896.en 10.2305/IUCN.UK.2019-3.RLTS.T9978A22075896.en].
]
[''Histiotus'' habitats:
* ''Big-eared brown bat'': Barquez, R.; et al. (2016). [https://www.iucnredlist.org/species/10201/22098780 "''Histiotus macrotus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T10201A22098780. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T10201A22098780.en 10.2305/IUCN.UK.2016-3.RLTS.T10201A22098780.en].
* ''Humboldt big-eared brown bat'': Velazco, P.; et al. (2016). [https://www.iucnredlist.org/species/29606/22046003 "''Histiotus humboldti''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T29606A22046003. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T29606A22046003.en 10.2305/IUCN.UK.2016-2.RLTS.T29606A22046003.en].
* ''Small big-eared brown bat'': Barquez, R.; et al. (2016). [https://www.iucnredlist.org/species/10202/22098875 "''Histiotus montanus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T10202A22098875. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T10202A22098875.en 10.2305/IUCN.UK.2016-3.RLTS.T10202A22098875.en].
* ''Southern big-eared brown bat'': Barquez, R.; et al. (2016). [https://www.iucnredlist.org/species/136292/22017718 "''Histiotus magellanicus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136292A22017718. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T136292A22017718.en 10.2305/IUCN.UK.2016-3.RLTS.T136292A22017718.en].
* ''Strange big-eared brown bat'': González, E. M.; et al. (2016). [https://www.iucnredlist.org/species/10200/22098611 "''Histiotus alienus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T10200A22098611. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T10200A22098611.en 10.2305/IUCN.UK.2016-2.RLTS.T10200A22098611.en].
* ''Thomas's big-eared brown bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/136502/21974854 "''Histiotus laephotis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136502A21974854. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-2.RLTS.T136502A21974854.en 10.2305/IUCN.UK.2019-2.RLTS.T136502A21974854.en].
* ''Tropical big-eared brown bat'': González, E. M.; et al. (2016). [https://www.iucnredlist.org/species/10203/22098684 "''Histiotus velatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T10203A22098684. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T10203A22098684.en 10.2305/IUCN.UK.2016-2.RLTS.T10203A22098684.en].
]
[''Hypsugo'' habitats:
* ''Alashanian pipistrelle'': Fukui, D.; et al. (2019). [https://www.iucnredlist.org/species/136560/21995360 "''Pipistrellus alaschanicus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136560A21995360. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T136560A21995360.en 10.2305/IUCN.UK.2019-3.RLTS.T136560A21995360.en].
* ''Anthony's pipistrelle'': Görföl, T.; et al. (2016). [https://www.iucnredlist.org/species/17327/22131201 "''Hypsugo anthonyi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T17327A22131201. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T17327A22131201.en 10.2305/IUCN.UK.2016-3.RLTS.T17327A22131201.en].
* ''Arabian pipistrelle'': Srinivasulu, C.; et al. (2019). [https://www.iucnredlist.org/species/17328/22131108 "''Pipistrellus arabicus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T17328A22131108. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T17328A22131108.en 10.2305/IUCN.UK.2019-3.RLTS.T17328A22131108.en].
* ''Big-eared pipistrelle'': Görföl, T.; et al. (2016). [https://www.iucnredlist.org/species/17349/22127259 "''Hypsugo macrotis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T17349A22127259. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T17349A22127259.en 10.2305/IUCN.UK.2016-3.RLTS.T17349A22127259.en].
* ''Broad-headed serotine'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/44853/22072238 "''Pipistrellus crassulus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T44853A22072238. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T44853A22072238.en 10.2305/IUCN.UK.2017-2.RLTS.T44853A22072238.en].
* ''Brown pipistrelle'': Wortham, G.; et al. (2021). [https://www.iucnredlist.org/species/17342/22129666 "''Pipistrellus imbricatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T17342A22129666. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-2.RLTS.T17342A22129666.en 10.2305/IUCN.UK.2021-2.RLTS.T17342A22129666.en].
* ''Burma pipistrelle'': Görföl, T.; et al. (2016). [https://www.iucnredlist.org/species/17347/22128627 "''Hypsugo lophurus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T17347A22128627. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T17347A22128627.en 10.2305/IUCN.UK.2016-3.RLTS.T17347A22128627.en].
* ''Cadorna's pipistrelle'': Bates, P. J. J.; et al. (2019). [https://www.iucnredlist.org/species/17331/22130442 "''Pipistrellus cadornae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T17331A22130442. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T17331A22130442.en 10.2305/IUCN.UK.2019-3.RLTS.T17331A22130442.en].
* ''Chinese pipistrelle'': Bates, P.; et al. (2020). [https://www.iucnredlist.org/species/17360/22125729 "''Hypsugo pulveratus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T17360A22125729. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T17360A22125729.en 10.2305/IUCN.UK.2020-2.RLTS.T17360A22125729.en].
* ''Chocolate pipistrelle'': Srinivasulu, B.; et al. (2019). [https://www.iucnredlist.org/species/17324/22131594 "''Falsistrellus affinis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T17324A22131594. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T17324A22131594.en 10.2305/IUCN.UK.2019-3.RLTS.T17324A22131594.en].
* ''Desert pipistrelle'': Benda, P.; et al. (2020). [https://www.iucnredlist.org/species/171619155/22071929 "''Hypsugo ariel''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T171619155A22071929. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T171619155A22071929.en 10.2305/IUCN.UK.2020-2.RLTS.T171619155A22071929.en].
* ''Joffre's bat'': Görföl, T.; et al. (2016). [https://www.iucnredlist.org/species/17345/22127938 "''Hypsugo joffrei''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T17345A22127938. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T17345A22127938.en 10.2305/IUCN.UK.2016-3.RLTS.T17345A22127938.en].
* ''Kirindy serotine'': Goodman, S. (2017). [https://www.iucnredlist.org/species/85200870/85201578 "''Hypsugo bemainty''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T85200870A85201578. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T85200870A85201578.en 10.2305/IUCN.UK.2017-2.RLTS.T85200870A85201578.en].
* ''Long-toothed pipistrelle'': Görföl, T.; et al. (2019). [https://www.iucnredlist.org/species/85201719/85201728 "''Hypsugo dolichodon''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T85201719A85201728. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T85201719A85201728.en 10.2305/IUCN.UK.2019-3.RLTS.T85201719A85201728.en].
* ''Mouselike pipistrelle'': Jacobs, D.; et al. (2020). [https://www.iucnredlist.org/species/44855/22072827 "''Pipistrellus musciculus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T44855A22072827. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T44855A22072827.en 10.2305/IUCN.UK.2020-2.RLTS.T44855A22072827.en].
* ''Savi's pipistrelle'': Juste, J.; et al. (2016). [https://www.iucnredlist.org/species/44856/22072380 "''Hypsugo savii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T44856A22072380. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T44856A22072380.en 10.2305/IUCN.UK.2016-3.RLTS.T44856A22072380.en].
* ''Socotran pipistrelle'': Waldien, D. L. (2020). [https://www.iucnredlist.org/species/85202881/85202890 "''Hypsugo lanzai''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T85202881A85202890. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T85202881A85202890.en 10.2305/IUCN.UK.2020-2.RLTS.T85202881A85202890.en].
* ''Vordermann's pipistrelle'': Görföl, T.; et al. (2016). [https://www.iucnredlist.org/species/44195/22127778 "''Hypsugo vordermanni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T44195A22127778. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T44195A22127778.en 10.2305/IUCN.UK.2016-3.RLTS.T44195A22127778.en].
]
[Jiang, T. L.; et al. (2020). [https://www.iucnredlist.org/species/10755/21993508 "''Ia io''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T10755A21993508. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T10755A21993508.en 10.2305/IUCN.UK.2020-2.RLTS.T10755A21993508.en].]
[Arroyo-Cabrales, J.; et al. (2017). [https://www.iucnredlist.org/species/10790/21990019 "''Idionycteris phyllotis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T10790A21990019. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T10790A21990019.en 10.2305/IUCN.UK.2017-2.RLTS.T10790A21990019.en].]
[''Laephotis'' habitats:
* ''Angolan long-eared bat'': Jacobs, D.; et al. (2019). [https://www.iucnredlist.org/species/11135/22011591 "''Laephotis angolensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T11135A22011591. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T11135A22011591.en 10.2305/IUCN.UK.2019-3.RLTS.T11135A22011591.en].
* ''Botswana long-eared bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/11136/22011659 "''Laephotis botswanae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T11136A22011659. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T11136A22011659.en 10.2305/IUCN.UK.2017-2.RLTS.T11136A22011659.en].
* ''De Winton's long-eared bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/11138/22007754 "''Laephotis wintoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T11138A22007754. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T11138A22007754.en 10.2305/IUCN.UK.2017-2.RLTS.T11138A22007754.en].
* ''Namib long-eared bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/11137/22007950 "''Laephotis namibensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T11137A22007950. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T11137A22007950.en 10.2305/IUCN.UK.2017-2.RLTS.T11137A22007950.en].
]
[Solari, S. (2019). [https://www.iucnredlist.org/species/11339/22122128 "''Lasionycteris noctivagans''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T11339A22122128. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T11339A22122128.en 10.2305/IUCN.UK.2019-1.RLTS.T11339A22122128.en].]
[''Lasiurus'' habitats:
* ''Big red bat'': Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/11351/22119870 "''Lasiurus egregius''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T11351A22119870. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T11351A22119870.en 10.2305/IUCN.UK.2016-2.RLTS.T11351A22119870.en].
* ''Cinnamon red bat'': Solari, S. (2018). [https://www.iucnredlist.org/species/136690/22040066 "''Lasiurus varius''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T136690A22040066. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T136690A22040066.en 10.2305/IUCN.UK.2018-2.RLTS.T136690A22040066.en].
* ''Cuban yellow bat'': Mancina, C. (2016). [https://www.iucnredlist.org/species/136754/22036556 "''Lasiurus insularis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136754A22036556. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T136754A22036556.en 10.2305/IUCN.UK.2016-1.RLTS.T136754A22036556.en].
* ''Eastern red bat'': Arroyo-Cabrales, J.; et al. (2016). [https://www.iucnredlist.org/species/11347/22121017 "''Lasiurus borealis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T11347A22121017. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T11347A22121017.en 10.2305/IUCN.UK.2016-1.RLTS.T11347A22121017.en].
* ''Greater red bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/29607/22046087 "''Lasiurus atratus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T29607A22046087. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T29607A22046087.en 10.2305/IUCN.UK.2019-1.RLTS.T29607A22046087.en].
* ''Hairy-tailed bat'': Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/11349/22119537 "''Lasiurus ebenus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T11349A22119537. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T11349A22119537.en 10.2305/IUCN.UK.2016-2.RLTS.T11349A22119537.en].
* ''Hoary bat'': Gonzalez, E.; et al. (2016). [https://www.iucnredlist.org/species/11345/22120305 "''Lasiurus cinereus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T11345A22120305. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T11345A22120305.en 10.2305/IUCN.UK.2016-1.RLTS.T11345A22120305.en].
* ''Jamaican red bat'': Aguiar, L.; et al. (2016). [https://www.iucnredlist.org/species/136306/22018027 "''Lasiurus degelidus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136306A22018027. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T136306A22018027.en 10.2305/IUCN.UK.2016-2.RLTS.T136306A22018027.en].
* ''Minor red bat'': Rodriguez Duran, A. (2016). [https://www.iucnredlist.org/species/136627/21987501 "''Lasiurus minor''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136627A21987501. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T136627A21987501.en 10.2305/IUCN.UK.2016-1.RLTS.T136627A21987501.en].
* ''Northern yellow bat'': Miller, B.; et al. (2017) [errata version of 2016 assessment]. [https://www.iucnredlist.org/species/11352/115101697 "''Lasiurus intermedius''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T11352A115101697. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T11352A22119630.en 10.2305/IUCN.UK.2016-3.RLTS.T11352A22119630.en].
* ''Pfeiffer's red bat'': Solari, S. (2018). [https://www.iucnredlist.org/species/136217/22011401 "''Lasiurus pfeifferi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T136217A22011401. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T136217A22011401.en 10.2305/IUCN.UK.2018-2.RLTS.T136217A22011401.en].
* ''Saline red bat'': Solari, S. (2017). [https://www.iucnredlist.org/species/88151061/88151064 "''Lasiurus salinae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T88151061A88151064. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T88151061A88151064.en 10.2305/IUCN.UK.2017-2.RLTS.T88151061A88151064.en].
* ''Seminole bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/11353/22119113 "''Lasiurus seminolus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T11353A22119113. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T11353A22119113.en 10.2305/IUCN.UK.2019-1.RLTS.T11353A22119113.en].
* ''Southern red bat'': Gonzalez, E.; et al. (2016). [https://www.iucnredlist.org/species/88151055/22120040 "''Lasiurus blossevillii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T88151055A22120040. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T88151055A22120040.en 10.2305/IUCN.UK.2016-1.RLTS.T88151055A22120040.en].
* ''Southern yellow bat'': Barquez, R.; et al. (2016). [https://www.iucnredlist.org/species/11350/22119259 "''Lasiurus ega''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T11350A22119259. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T11350A22119259.en 10.2305/IUCN.UK.2016-3.RLTS.T11350A22119259.en].
* ''Tacarcuna bat'': Pineda, W.; et al. (2016). [https://www.iucnredlist.org/species/11348/22120924 "''Lasiurus castaneus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T11348A22120924. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T11348A22120924.en 10.2305/IUCN.UK.2016-2.RLTS.T11348A22120924.en].
* ''Western yellow bat'': Arroyo-Cabrales, J.; et al. (2017). [https://www.iucnredlist.org/species/41532/22004260 "''Lasiurus xanthinus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T41532A22004260. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T41532A22004260.en 10.2305/IUCN.UK.2017-2.RLTS.T41532A22004260.en].
]
[Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/13556/22105391 "''Mimetillus moloneyi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T13556A22105391. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T13556A22105391.en 10.2305/IUCN.UK.2017-2.RLTS.T13556A22105391.en].]
[''Neoromicia'' habitats:
* ''Banana serotine'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/44923/22047621 "''Neoromicia nana''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T44923A22047621. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T44923A22047621.en 10.2305/IUCN.UK.2017-2.RLTS.T44923A22047621.en].
* ''Cape serotine'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/44918/22048372 "''Neoromicia capensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T44918A22048372. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T44918A22048372.en 10.2305/IUCN.UK.2017-2.RLTS.T44918A22048372.en].
* ''Dark-brown serotine'': Cooper-Bohannon, R.; et al. (2020). [https://www.iucnredlist.org/species/44917/22048243 "''Neoromicia brunnea''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T44917A22048243. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T44917A22048243.en 10.2305/IUCN.UK.2020-2.RLTS.T44917A22048243.en].
* ''Heller's serotine'': Jacobs, D.; et al. (2019). [https://www.iucnredlist.org/species/44921/22047381 "''Neoromicia helios''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T44921A22047381. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T44921A22047381.en 10.2305/IUCN.UK.2019-3.RLTS.T44921A22047381.en].
* ''Isabelline white-winged serotine'': Decher, J.; et al. (2017). [https://www.iucnredlist.org/species/95558146/95558181 "''Neoromicia isabella''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T95558146A95558181. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T95558146A95558181.en 10.2305/IUCN.UK.2017-2.RLTS.T95558146A95558181.en].
* ''Isalo serotine'': Monadjem, A.; et al. (2019). [https://www.iucnredlist.org/species/136820/22044073 "''Neoromicia malagasyensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136820A22044073. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T136820A22044073.en 10.2305/IUCN.UK.2019-1.RLTS.T136820A22044073.en].
* ''Malagasy serotine'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/40033/22059795 "''Neoromicia matroka''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T40033A22059795. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T40033A22059795.en 10.2305/IUCN.UK.2017-2.RLTS.T40033A22059795.en].
* ''Melck's house bat'': Jacobs, D. (2019). [https://www.iucnredlist.org/species/44922/22047486 "''Neoromicia melckorum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T44922A22047486. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T44922A22047486.en 10.2305/IUCN.UK.2019-3.RLTS.T44922A22047486.en].
* ''Rendall's serotine'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/44924/22047902 "''Neoromicia rendalli''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T44924A22047902. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T44924A22047902.en 10.2305/IUCN.UK.2017-2.RLTS.T44924A22047902.en].
* ''Roberts's serotine'': Goodman, S. (2017). [https://www.iucnredlist.org/species/67359364/67359368 "''Neoromicia robertsi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T67359364A67359368. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T67359364A67359368.en 10.2305/IUCN.UK.2017-2.RLTS.T67359364A67359368.en].
* ''Rosevear's serotine'': Monadjem, A. (2017). [https://www.iucnredlist.org/species/67359375/67359379 "''Neoromicia roseveari''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T67359375A67359379. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T67359375A67359379.en 10.2305/IUCN.UK.2017-2.RLTS.T67359375A67359379.en].
* ''Somali serotine'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/44925/22046866 "''Neoromicia somalica''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T44925A22046866. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T44925A22046866.en 10.2305/IUCN.UK.2017-2.RLTS.T44925A22046866.en].
* ''Tiny serotine'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/44920/22048932 "''Neoromicia guineensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T44920A22048932. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T44920A22048932.en 10.2305/IUCN.UK.2017-2.RLTS.T44920A22048932.en].
* ''White-winged serotine'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/44926/22047067 "''Neoromicia tenuipinnis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T44926A22047067. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T44926A22047067.en 10.2305/IUCN.UK.2017-2.RLTS.T44926A22047067.en].
* ''Zulu serotine'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/44927/22047251 "''Neoromicia zuluensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T44927A22047251. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T44927A22047251.en 10.2305/IUCN.UK.2017-2.RLTS.T44927A22047251.en].
]
[''Nyctalus'' habitats:
* ''Azores noctule'': Russo, D.; et al. (2023). [https://www.iucnredlist.org/species/14922/211008291 "''Nyctalus azoreum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2023''': e.T14922A211008291. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2023-1.RLTS.T14922A211008291.en 10.2305/IUCN.UK.2023-1.RLTS.T14922A211008291.en].
* ''Birdlike noctule'': Fukui, D.; et al. (2019). [https://www.iucnredlist.org/species/14921/22016483 "''Nyctalus aviator''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T14921A22016483. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T14921A22016483.en 10.2305/IUCN.UK.2019-3.RLTS.T14921A22016483.en].
* ''Chinese noctule'': Shi, H. Y.; et al. (2020). [https://www.iucnredlist.org/species/136828/22044480 "''Nyctalus plancyi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T136828A22044480. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T136828A22044480.en 10.2305/IUCN.UK.2020-2.RLTS.T136828A22044480.en].
* ''Common noctule'': Csorba, G.; et al. (2016). [https://www.iucnredlist.org/species/14920/22015682 "''Nyctalus noctula''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14920A22015682. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T14920A22015682.en 10.2305/IUCN.UK.2016-2.RLTS.T14920A22015682.en].
* ''Greater noctule bat'': Alcaldé, J.; et al. (2016). [https://www.iucnredlist.org/species/14918/22015318 "''Nyctalus lasiopterus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14918A22015318. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T14918A22015318.en 10.2305/IUCN.UK.2016-2.RLTS.T14918A22015318.en].
* ''Japanese noctule'': Fukui, D.; et al. (2021) [errata version of 2020 assessment]. [https://www.iucnredlist.org/species/136765/209552009 "''Nyctalus furvus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T136765A209552009. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T136765A209552009.en 10.2305/IUCN.UK.2020-2.RLTS.T136765A209552009.en].
* ''Lesser noctule'': Juste, J.; et al. (2016). [https://www.iucnredlist.org/species/14919/22016159 "''Nyctalus leisleri''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T14919A22016159. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T14919A22016159.en 10.2305/IUCN.UK.2016-2.RLTS.T14919A22016159.en].
* ''Mountain noctule'': Srinivasulu, C.; et al. (2019). [https://www.iucnredlist.org/species/14923/22016710 "''Nyctalus montanus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T14923A22016710. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T14923A22016710.en 10.2305/IUCN.UK.2019-3.RLTS.T14923A22016710.en].
]
[Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/41533/22005999 "''Nycticeinops schlieffeni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T41533A22005999. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T41533A22005999.en 10.2305/IUCN.UK.2017-2.RLTS.T41533A22005999.en].]
[''Nycticeius'' habitats:
* ''Cuban evening bat'': Solari, S. (2018). [https://www.iucnredlist.org/species/136386/22013782 "''Nycticeius cubanus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T136386A22013782. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T136386A22013782.en 10.2305/IUCN.UK.2018-2.RLTS.T136386A22013782.en].
* ''Evening bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/14944/22015223 "''Nycticeius humeralis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T14944A22015223. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T14944A22015223.en 10.2305/IUCN.UK.2019-1.RLTS.T14944A22015223.en].
* ''Temminck's mysterious bat'': Velazco, P.; et al. (2008). [https://www.iucnredlist.org/species/136562/4311281 "''Nycticeius aenobarbus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2008''': e.T136562A4311281. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2008.RLTS.T136562A4311281.en 10.2305/IUCN.UK.2008.RLTS.T136562A4311281.en].
]
[''Nyctophilus'' habitats:
* ''Arnhem long-eared bat'': McKenzie, N.; et al. (2020). [https://www.iucnredlist.org/species/15000/22010474 "''Nyctophilus arnhemensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T15000A22010474. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T15000A22010474.en 10.2305/IUCN.UK.2020-2.RLTS.T15000A22010474.en].
* ''Eastern long-eared bat'': Stawski, C.; et al. (2021). [https://www.iucnredlist.org/species/85289369/85289379 "''Nyctophilus bifax''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T85289369A85289379. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T85289369A85289379.en 10.2305/IUCN.UK.2021-3.RLTS.T85289369A85289379.en].
* ''Gould's long-eared bat'': Armstrong, K. N.; et al. (2022). [https://www.iucnredlist.org/species/218360733/218360491 "''Nyctophilus gouldi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2022''': e.T218360733A218360491. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2022-2.RLTS.T218360733A218360491.en 10.2305/IUCN.UK.2022-2.RLTS.T218360733A218360491.en].
* ''Holts' long-eared bat'': Armstrong, K. N. (2022). [https://www.iucnredlist.org/species/218360290/218360335 "''Nyctophilus holtorum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2022''': e.T218360290A218360335. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2022-2.RLTS.T218360290A218360335.en 10.2305/IUCN.UK.2022-2.RLTS.T218360290A218360335.en].
* ''Lesser long-eared bat'': Lumsden, L. F.; et al. (2021) [amended version of 2020 assessment]. [https://www.iucnredlist.org/species/15003/209533561 "''Nyctophilus geoffroyi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T15003A209533561. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T15003A209533561.en 10.2305/IUCN.UK.2021-3.RLTS.T15003A209533561.en].
* ''Mount Missim long-eared bat'': Parnaby, H. (2020) [amended version of 2017 assessment]. [https://www.iucnredlist.org/species/85289876/166525572 "''Nyctophilus shirleyae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T85289876A166525572. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-1.RLTS.T85289876A166525572.en 10.2305/IUCN.UK.2020-1.RLTS.T85289876A166525572.en].
* ''New Caledonian long-eared bat'': Parnaby, H.; et al. (2020). [https://www.iucnredlist.org/species/136807/22042779 "''Nyctophilus nebulosus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T136807A22042779. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T136807A22042779.en 10.2305/IUCN.UK.2020-3.RLTS.T136807A22042779.en].
* ''New Guinea long-eared bat'': Aplin, K.; et al. (2021) [amended version of 2017 assessment]. [https://www.iucnredlist.org/species/15008/209536224 "''Nyctophilus microtis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T15008A209536224. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T15008A209536224.en 10.2305/IUCN.UK.2021-3.RLTS.T15008A209536224.en].
* ''Pallid long-eared bat'': McKenzie, N. (2020). [https://www.iucnredlist.org/species/85289826/85289849 "''Nyctophilus daedalus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T85289826A85289849. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T85289826A85289849.en 10.2305/IUCN.UK.2020-3.RLTS.T85289826A85289849.en].
* ''Pygmy long-eared bat'': McKenzie, N.; et al. (2020). [https://www.iucnredlist.org/species/15011/22003303 "''Nyctophilus walkeri''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T15011A22003303. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T15011A22003303.en 10.2305/IUCN.UK.2020-2.RLTS.T15011A22003303.en].
* ''Small-toothed long-eared bat'': Armstrong, K. N. (2021). [https://www.iucnredlist.org/species/15007/22009794 "''Nyctophilus microdon''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T15007A22009794. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T15007A22009794.en 10.2305/IUCN.UK.2021-3.RLTS.T15007A22009794.en].
* ''Southeastern long-eared bat'': Parnaby, H. (2020). [https://www.iucnredlist.org/species/85289516/85289576 "''Nyctophilus corbeni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T85289516A85289576. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T85289516A85289576.en 10.2305/IUCN.UK.2020-2.RLTS.T85289516A85289576.en].
* ''Sunda long-eared bat'': Hutson, A. M.; et al. (2016). [https://www.iucnredlist.org/species/15005/22009360 "''Nyctophilus heran''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T15005A22009360. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T15005A22009360.en 10.2305/IUCN.UK.2016-2.RLTS.T15005A22009360.en].
* ''Tasmanian long-eared bat'': Cawthen, L.; et al. (2020). [https://www.iucnredlist.org/species/15009/22003478 "''Nyctophilus sherrini''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T15009A22003478. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T15009A22003478.en 10.2305/IUCN.UK.2020-2.RLTS.T15009A22003478.en].
* ''Western long-eared bat'': McKenzie, N. (2020). [https://www.iucnredlist.org/species/85289614/85289618 "''Nyctophilus major''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T85289614A85289618. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T85289614A85289618.en 10.2305/IUCN.UK.2020-3.RLTS.T85289614A85289618.en].
]
[''Otonycteris'' habitats:
* ''Desert long-eared bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/85294528/22118826 "''Otonycteris hemprichii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T85294528A22118826. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T85294528A22118826.en 10.2305/IUCN.UK.2017-2.RLTS.T85294528A22118826.en].
* ''Turkestani long-eared bat'': Benda, P. (2017). [https://www.iucnredlist.org/species/85295233/85295274 "''Otonycteris leucophaea''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T85295233A85295274. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T85295233A85295274.en 10.2305/IUCN.UK.2017-2.RLTS.T85295233A85295274.en].
]
[Solari, S. (2019). [https://www.iucnredlist.org/species/17341/22129352 "''Pipistrellus hesperus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T17341A22129352. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T17341A22129352.en 10.2305/IUCN.UK.2019-1.RLTS.T17341A22129352.en].]
[Solari, S. (2018). [https://www.iucnredlist.org/species/17366/22123514 "''Perimyotis subflavus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2018''': e.T17366A22123514. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2018-2.RLTS.T17366A22123514.en 10.2305/IUCN.UK.2018-2.RLTS.T17366A22123514.en].]
[Armstrong, K. N.; et al. (2021) [amended version of 2020 assessment]. [https://www.iucnredlist.org/species/16887/209524728 "''Pharotis imogene''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T16887A209524728. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T16887A209524728.en 10.2305/IUCN.UK.2021-3.RLTS.T16887A209524728.en].]
[Rosell-Ambal, R. G. B.; et al. (2020). [https://www.iucnredlist.org/species/16981/22117501 "''Philetor brachypterus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T16981A22117501. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T16981A22117501.en 10.2305/IUCN.UK.2020-2.RLTS.T16981A22117501.en].]
[''Pipistrellus'' habitats:
* ''Aellen's pipistrelle'': Fahr., J. (2019). [https://www.iucnredlist.org/species/17343/22128783 "''Pipistrellus inexspectatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T17343A22128783. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T17343A22128783.en 10.2305/IUCN.UK.2019-3.RLTS.T17343A22128783.en].
* ''Angulate pipistrelle'': Pennay, M.; et al. (2020). [https://www.iucnredlist.org/species/17326/22131495 "''Pipistrellus angulatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T17326A22131495. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T17326A22131495.en 10.2305/IUCN.UK.2020-2.RLTS.T17326A22131495.en].
* ''Broad-headed serotine'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/44853/22072238 "''Pipistrellus crassulus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T44853A22072238. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T44853A22072238.en 10.2305/IUCN.UK.2017-2.RLTS.T44853A22072238.en].
* ''Common pipistrelle'': Godlevska, L.; et al. (2021) [errata version of 2020 assessment]. [https://www.iucnredlist.org/species/85333513/196581936 "''Pipistrellus pipistrellus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T85333513A196581936. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T85333513A196581936.en 10.2305/IUCN.UK.2020-2.RLTS.T85333513A196581936.en].
* ''Dar es Salaam pipistrelle'': Jacobs, D.; et al. (2019). [https://www.iucnredlist.org/species/17358/22125454 "''Pipistrellus permixtus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T17358A22125454. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T17358A22125454.en 10.2305/IUCN.UK.2019-3.RLTS.T17358A22125454.en].
* ''Dobson's pipistrelle'': Jacobs, D.; et al. (2017). [https://www.iucnredlist.org/species/85736277/85736282 "''Pipistrellus grandidieri''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T85736277A85736282. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T85736277A85736282.en 10.2305/IUCN.UK.2017-2.RLTS.T85736277A85736282.en].
* ''Dusky pipistrelle'': Piraccini, R. (2016). [https://www.iucnredlist.org/species/136741/22035802 "''Pipistrellus hesperidus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136741A22035802. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T136741A22035802.en 10.2305/IUCN.UK.2016-2.RLTS.T136741A22035802.en].
* ''Endo's pipistrelle'': Fukui, D.; et al. (2019). [https://www.iucnredlist.org/species/17340/22129827 "''Pipistrellus endoi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T17340A22129827. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T17340A22129827.en 10.2305/IUCN.UK.2019-3.RLTS.T17340A22129827.en].
* ''Forest pipistrelle'': Lumsden, L. F.; et al. (2020). [https://www.iucnredlist.org/species/17321/22131872 "''Pipistrellus adamsi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T17321A22131872. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T17321A22131872.en 10.2305/IUCN.UK.2020-2.RLTS.T17321A22131872.en].
* ''Greater Papuan pipistrelle'': Leary, T.; et al. (2020). [https://www.iucnredlist.org/species/17334/22130362 "''Pipistrellus collinus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T17334A22130362. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T17334A22130362.en 10.2305/IUCN.UK.2020-3.RLTS.T17334A22130362.en].
* ''Hanak's pipistrelle'': Georgiakakis, P.; et al. (2020). [https://www.iucnredlist.org/species/136209/22011859 "''Pipistrellus hanaki''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T136209A22011859. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T136209A22011859.en 10.2305/IUCN.UK.2020-2.RLTS.T136209A22011859.en].
* ''Indian pipistrelle'': Kruskop, S. V.; et al. (2019). [https://www.iucnredlist.org/species/17335/22130140 "''Pipistrellus coromandra''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T17335A22130140. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T17335A22130140.en 10.2305/IUCN.UK.2019-3.RLTS.T17335A22130140.en].
* ''Japanese house bat'': Fukui, D.; et al. (2019). [https://www.iucnredlist.org/species/17320/22131948 "''Pipistrellus abramus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T17320A22131948. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T17320A22131948.en 10.2305/IUCN.UK.2019-3.RLTS.T17320A22131948.en].
* ''Java pipistrelle'': Kruskop, S. V.; et al. (2019). [https://www.iucnredlist.org/species/17344/22128905 "''Pipistrellus javanicus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T17344A22128905. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T17344A22128905.en 10.2305/IUCN.UK.2019-3.RLTS.T17344A22128905.en].
* ''Kelaart's pipistrelle'': Srinivasulu, B.; et al. (2019). [https://www.iucnredlist.org/species/17332/22130600 "''Pipistrellus ceylonicus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T17332A22130600. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T17332A22130600.en 10.2305/IUCN.UK.2019-3.RLTS.T17332A22130600.en].
* ''Kuhl's pipistrelle'': Juste, J.; et al. (2016). [https://www.iucnredlist.org/species/17314/22132946 "''Pipistrellus kuhlii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T17314A22132946. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T17314A22132946.en 10.2305/IUCN.UK.2016-2.RLTS.T17314A22132946.en].
* ''Least pipistrelle'': Srinivasulu, B.; et al. (2019). [https://www.iucnredlist.org/species/186170680/186174039 "''Pipistrellus tenuis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T186170680A186174039. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T186170680A186174039.en 10.2305/IUCN.UK.2019-3.RLTS.T186170680A186174039.en].
* ''Lesser Papuan pipistrelle'': Leary, T.; et al. (2020). [https://www.iucnredlist.org/species/17355/22127056 "''Pipistrellus papuanus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T17355A22127056. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T17355A22127056.en 10.2305/IUCN.UK.2020-3.RLTS.T17355A22127056.en].
* ''Madeira pipistrelle'': Russo, D.; et al. (2023). [https://www.iucnredlist.org/species/17315/211010717 "''Pipistrellus maderensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2023''': e.T17315A211010717. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2023-1.RLTS.T17315A211010717.en 10.2305/IUCN.UK.2023-1.RLTS.T17315A211010717.en].
* ''Minahassa pipistrelle'': Görföl, T.; et al. (2016). [https://www.iucnredlist.org/species/17350/22127132 "''Pipistrellus minahassae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T17350A22127132. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T17350A22127132.en 10.2305/IUCN.UK.2016-2.RLTS.T17350A22127132.en].
* ''Mount Gargues pipistrelle'': Jacobs, D.; et al. (2019). [https://www.iucnredlist.org/species/17323/22131783 "''Pipistrellus aero''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T17323A22131783. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T17323A22131783.en 10.2305/IUCN.UK.2019-3.RLTS.T17323A22131783.en].
* ''Mount Popa pipistrelle'': Bates, P. J. J.; et al. (2019). [https://www.iucnredlist.org/species/17356/22126738 "''Pipistrellus paterculus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T17356A22126738. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T17356A22126738.en 10.2305/IUCN.UK.2019-3.RLTS.T17356A22126738.en].
* ''Narrow-winged pipistrelle'': Jayaraj, V. K. (2020). [https://www.iucnredlist.org/species/17364/22125283 "''Pipistrellus stenopterus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T17364A22125283. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T17364A22125283.en 10.2305/IUCN.UK.2020-2.RLTS.T17364A22125283.en].
* ''Nathusius's pipistrelle'': Paunović, M.; et al. (2016). [https://www.iucnredlist.org/species/17316/22132621 "''Pipistrellus nathusii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T17316A22132621. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T17316A22132621.en 10.2305/IUCN.UK.2016-2.RLTS.T17316A22132621.en].
* ''Northern pipistrelle'': McKenzie, N.; et al. (2020). [https://www.iucnredlist.org/species/17370/22123076 "''Pipistrellus westralis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T17370A22123076. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T17370A22123076.en 10.2305/IUCN.UK.2020-2.RLTS.T17370A22123076.en].
* ''Racey's pipistrelle'': Jenkins, R. K. B.; et al. (2019). [https://www.iucnredlist.org/species/136646/21989768 "''Pipistrellus raceyi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136646A21989768. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T136646A21989768.en 10.2305/IUCN.UK.2019-3.RLTS.T136646A21989768.en].
* ''Rüppell's bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/17361/22124277 "''Pipistrellus rueppellii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T17361A22124277. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T17361A22124277.en 10.2305/IUCN.UK.2017-2.RLTS.T17361A22124277.en].
* ''Rusty pipistrelle'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/17362/22124708 "''Pipistrellus rusticus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T17362A22124708. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T17362A22124708.en 10.2305/IUCN.UK.2017-2.RLTS.T17362A22124708.en].
* ''Soprano pipistrelle'': Benda, P.; et al. (2016). [https://www.iucnredlist.org/species/136649/21990234 "''Pipistrellus pygmaeus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136649A21990234. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T136649A21990234.en 10.2305/IUCN.UK.2016-2.RLTS.T136649A21990234.en].
* ''Tiny pipistrelle'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/17353/22126587 "''Pipistrellus nanulus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T17353A22126587. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T17353A22126587.en 10.2305/IUCN.UK.2017-2.RLTS.T17353A22126587.en].
* ''Watts's pipistrelle'': Pennay, M. (2021). [https://www.iucnredlist.org/species/17369/22122990 "''Pipistrellus wattsi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T17369A22122990. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T17369A22122990.en 10.2305/IUCN.UK.2021-3.RLTS.T17369A22122990.en].
]
[''Plecotus'' habitats:
* ''Alpine long-eared bat'': Piraccini, R. (2016). [https://www.iucnredlist.org/species/136229/22002229 "''Plecotus macrobullaris''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136229A22002229. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T136229A22002229.en 10.2305/IUCN.UK.2016-2.RLTS.T136229A22002229.en].
* ''Brown long-eared bat'': Russo, D.; et al. (2023). [https://www.iucnredlist.org/species/85535522/211015413 "''Plecotus auritus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2023''': e.T85535522A211015413. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2023-1.RLTS.T85535522A211015413.en 10.2305/IUCN.UK.2023-1.RLTS.T85535522A211015413.en].
* ''Canary long-eared bat'': Russo, D.; et al. (2023). [https://www.iucnredlist.org/species/215482954/211021391 "''Plecotus teneriffae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2023''': e.T215482954A211021391. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2023-1.RLTS.T215482954A211021391.en 10.2305/IUCN.UK.2023-1.RLTS.T215482954A211021391.en].
* ''Christie's long-eared bat'': Aulagnier, S.; et al. (2019). [https://www.iucnredlist.org/species/44931/22045680 "''Plecotus christii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T44931A22045680. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T44931A22045680.en 10.2305/IUCN.UK.2019-3.RLTS.T44931A22045680.en].
* ''Ethiopian long-eared bat'': Lavrenchenko, L.; et al. (2019). [https://www.iucnredlist.org/species/44930/22045794 "''Plecotus balensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T44930A22045794. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T44930A22045794.en 10.2305/IUCN.UK.2019-3.RLTS.T44930A22045794.en].
* ''Grey long-eared bat'': Russo, D.; et al. (2023). [https://www.iucnredlist.org/species/85533333/211018209 "''Plecotus austriacus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2023''': e.T85533333A211018209. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2023-1.RLTS.T85533333A211018209.en 10.2305/IUCN.UK.2023-1.RLTS.T85533333A211018209.en].
* ''Himalayan long-eared bat'': Srinivasulu, C.; et al. (2019). [https://www.iucnredlist.org/species/85537505/85537516 "''Plecotus homochrous''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T85537505A85537516. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T85537505A85537516.en 10.2305/IUCN.UK.2019-3.RLTS.T85537505A85537516.en].
* ''Japanese long-eared bat'': Fukui, D.; et al. (2021) [errata version of 2019 assessment]. [https://www.iucnredlist.org/species/136664/209550809 "''Plecotus sacrimontis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136664A209550809. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T136664A209550809.en 10.2305/IUCN.UK.2019-3.RLTS.T136664A209550809.en].
* ''Kozlov's long-eared bat'': Fukui, D.; et al. (2021). [https://www.iucnredlist.org/species/85535146/85535252 "''Plecotus kozlovi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T85535146A85535252. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-1.RLTS.T85535146A85535252.en 10.2305/IUCN.UK.2021-1.RLTS.T85535146A85535252.en].
* ''Mediterranean long-eared bat'': Petr, B.; et al. (2024) [errata version of 2023 assessment]. [https://www.iucnredlist.org/species/216518463/254076042 "''Plecotus kolombatovici''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2023''': e.T216518463A254076042.
* ''Ognev's long-eared bat'': Kruskop, S. V.; et al. (2019). [https://www.iucnredlist.org/species/136598/21996784 "''Plecotus ognevi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136598A21996784. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T136598A21996784.en 10.2305/IUCN.UK.2019-3.RLTS.T136598A21996784.en].
* ''Sardinian long-eared bat'': Russo, D.; et al. (2023). [https://www.iucnredlist.org/species/136503/211020578 "''Plecotus sardus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2023''': e.T136503A211020578. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2023-1.RLTS.T136503A211020578.en 10.2305/IUCN.UK.2023-1.RLTS.T136503A211020578.en].
* ''Strelkov's long-eared bat'': Srinivasulu, C.; et al. (2020). [https://www.iucnredlist.org/species/85535363/85535378 "''Plecotus strelkovi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T85535363A85535378. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T85535363A85535378.en 10.2305/IUCN.UK.2020-2.RLTS.T85535363A85535378.en].
* ''Taiwan long-eared bat'': Huang, J. C. -C.; et al. (2019). [https://www.iucnredlist.org/species/17601/21978172 "''Plecotus taivanus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T17601A21978172. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T17601A21978172.en 10.2305/IUCN.UK.2019-3.RLTS.T17601A21978172.en].
* ''Turkmen long-eared bat'': Srinivasulu, C.; et al. (2019). [https://www.iucnredlist.org/species/85535176/85535233 "''Plecotus turkmenicus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T85535176A85535233. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T85535176A85535233.en 10.2305/IUCN.UK.2019-3.RLTS.T85535176A85535233.en].
* ''Ward's long-eared bat'': Srinivasulu, C.; et al. (2020). [https://www.iucnredlist.org/species/85535265/85535306 "''Plecotus wardi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T85535265A85535306. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T85535265A85535306.en 10.2305/IUCN.UK.2020-3.RLTS.T85535265A85535306.en].
]
[''Rhogeessa'' habitats:
* ''Bickham's little yellow bat'': Solari, S. (2017). [https://www.iucnredlist.org/species/88151726/88151729 "''Rhogeessa bickhami''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T88151726A88151729. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T88151726A88151729.en 10.2305/IUCN.UK.2017-2.RLTS.T88151726A88151729.en].
* ''Black-winged little yellow bat'': Miller, B.; et al. (2016). [https://www.iucnredlist.org/species/19685/22006890 "''Rhogeessa tumida''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T19685A22006890. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-3.RLTS.T19685A22006890.en 10.2305/IUCN.UK.2016-3.RLTS.T19685A22006890.en].
* ''Ecuadorian little yellow bat'': Solari, S. (2017). [https://www.iucnredlist.org/species/88151777/88151780 "''Rhogeessa velilla''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T88151777A88151780. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T88151777A88151780.en 10.2305/IUCN.UK.2017-2.RLTS.T88151777A88151780.en].
* ''Genoways's yellow bat'': Arroyo-Cabrales, J. (2016). [https://www.iucnredlist.org/species/19680/21989676 "''Rhogeessa genowaysi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T19680A21989676. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T19680A21989676.en 10.2305/IUCN.UK.2016-1.RLTS.T19680A21989676.en].
* ''Husson's yellow bat'': Sampaio, E.; et al. (2016). [https://www.iucnredlist.org/species/136220/22011768 "''Rhogeessa hussoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T136220A22011768. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T136220A22011768.en 10.2305/IUCN.UK.2016-2.RLTS.T136220A22011768.en].
* ''Least yellow bat'': Arroyo-Cabrales, J.; et al. (2016). [https://www.iucnredlist.org/species/19683/22007311 "''Rhogeessa mira''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T19683A22007311. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T19683A22007311.en 10.2305/IUCN.UK.2016-1.RLTS.T19683A22007311.en].
* ''Little yellow bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/19684/22007495 "''Rhogeessa parvula''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T19684A22007495. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T19684A22007495.en 10.2305/IUCN.UK.2019-1.RLTS.T19684A22007495.en].
* ''Menchu's little yellow bat'': Solari, S. (2017). [https://www.iucnredlist.org/species/88151749/88151752 "''Rhogeessa menchuae''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T88151749A88151752. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T88151749A88151752.en 10.2305/IUCN.UK.2017-2.RLTS.T88151749A88151752.en].
* ''Thomas's yellow bat'': Soriano, P.; et al. (2016). [https://www.iucnredlist.org/species/88151760/22019853 "''Rhogeessa io''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T88151760A22019853. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T88151760A22019853.en 10.2305/IUCN.UK.2016-1.RLTS.T88151760A22019853.en].
* ''Tiny yellow bat'': Solari, S. (2016). [https://www.iucnredlist.org/species/19682/22007845 "''Rhogeessa minutilla''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T19682A22007845. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-1.RLTS.T19682A22007845.en 10.2305/IUCN.UK.2016-1.RLTS.T19682A22007845.en].
* ''Yucatan yellow bat'': Solari, S. (2019). [https://www.iucnredlist.org/species/136810/22043785 "''Rhogeessa aeneus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136810A22043785. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-1.RLTS.T136810A22043785.en 10.2305/IUCN.UK.2019-1.RLTS.T136810A22043785.en].
]
[Benda, P.; et al. (2019). [https://www.iucnredlist.org/species/7935/22117147 "''Eptesicus nasutus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T7935A22117147. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T7935A22117147.en 10.2305/IUCN.UK.2019-3.RLTS.T7935A22117147.en].]
[Pennay, M. (2020). [https://www.iucnredlist.org/species/14946/22009127 "''Scoteanax rueppellii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T14946A22009127. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T14946A22009127.en 10.2305/IUCN.UK.2020-2.RLTS.T14946A22009127.en].]
[''Scotoecus'' habitats:
* ''Dark-winged lesser house bat'', ''Hinde's lesser house bat'', ''White-bellied lesser house bat'': Cotterill, F.; et al. (2017). [https://www.iucnredlist.org/species/20055/22025420 "''Scotoecus hirundo''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T20055A22025420. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T20055A22025420.en 10.2305/IUCN.UK.2017-2.RLTS.T20055A22025420.en].
* ''Desert yellow bat'': Srinivasulu, B.; et al. (2019). [https://www.iucnredlist.org/species/20056/22025293 "''Scotoecus pallidus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T20056A22025293. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T20056A22025293.en 10.2305/IUCN.UK.2019-3.RLTS.T20056A22025293.en].
* ''Light-winged lesser house bat'': Jacobs, D. (2019). [https://www.iucnredlist.org/species/20054/22025597 "''Scotoecus albofuscus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T20054A22025597. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T20054A22025597.en 10.2305/IUCN.UK.2019-3.RLTS.T20054A22025597.en].
]
[Santiago, K.; et al. (2021). [https://www.iucnredlist.org/species/20058/22025092 "''Scotomanes ornatus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T20058A22025092. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T20058A22025092.en 10.2305/IUCN.UK.2021-3.RLTS.T20058A22025092.en].]
[''Scotophilus'' habitats:
* ''African yellow bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/20066/22030888 "''Scotophilus dinganii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T20066A22030888. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T20066A22030888.en 10.2305/IUCN.UK.2017-2.RLTS.T20066A22030888.en].
* ''Andrew Rebori's house bat'': Monadjem, A. (2017). [https://www.iucnredlist.org/species/84466713/84466716 "''Scotophilus andrewreborii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T84466713A84466716. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T84466713A84466716.en 10.2305/IUCN.UK.2017-2.RLTS.T84466713A84466716.en].
* ''Eastern greenish yellow bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/20073/22032552 "''Scotophilus viridis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T20073A22032552. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T20073A22032552.en 10.2305/IUCN.UK.2017-2.RLTS.T20073A22032552.en].
* ''Ejeta's yellow bat'': Monadjem, A. (2017). [https://www.iucnredlist.org/species/84466810/84466814 "''Scotophilus ejetai''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T84466810A84466814. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T84466810A84466814.en 10.2305/IUCN.UK.2017-2.RLTS.T84466810A84466814.en].
* ''Greater Asiatic yellow bat'': Srinivasulu, B.; et al. (2019). [https://www.iucnredlist.org/species/20067/22031528 "''Scotophilus heathii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T20067A22031528. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T20067A22031528.en 10.2305/IUCN.UK.2019-3.RLTS.T20067A22031528.en].
* ''Lesser Asiatic yellow bat'': Srinivasulu, B.; et al. (2019). [https://www.iucnredlist.org/species/20068/22031278 "''Scotophilus kuhlii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T20068A22031278. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T20068A22031278.en 10.2305/IUCN.UK.2019-3.RLTS.T20068A22031278.en].
* ''Livingstone's yellow bat'': Monadjem, A. (2017). [https://www.iucnredlist.org/species/84466826/84466829 "''Scotophilus livingstonii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T84466826A84466829. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T84466826A84466829.en 10.2305/IUCN.UK.2017-2.RLTS.T84466826A84466829.en].
* ''Malagasy yellow bat'': Jenkins, R. K. B.; et al. (2019). [https://www.iucnredlist.org/species/136675/22039268 "''Scotophilus tandrefana''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T136675A22039268. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T136675A22039268.en 10.2305/IUCN.UK.2019-3.RLTS.T136675A22039268.en].
* ''Marovaza yellow bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/136774/22034361 "''Scotophilus marovaza''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T136774A22034361. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T136774A22034361.en 10.2305/IUCN.UK.2017-2.RLTS.T136774A22034361.en].
* ''Nut-colored yellow bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/20071/22032438 "''Scotophilus nux''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T20071A22032438. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T20071A22032438.en 10.2305/IUCN.UK.2017-2.RLTS.T20071A22032438.en].
* ''Robbins's yellow bat'': Fahr., J. (2019). [https://www.iucnredlist.org/species/44934/22045154 "''Scotophilus nucella''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T44934A22045154. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T44934A22045154.en 10.2305/IUCN.UK.2019-3.RLTS.T44934A22045154.en].
* ''Robust yellow bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/20072/22032313 "''Scotophilus robustus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T20072A22032313. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T20072A22032313.en 10.2305/IUCN.UK.2017-2.RLTS.T20072A22032313.en].
* ''Schreber's yellow bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/20070/22031866 "''Scotophilus nigrita''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T20070A22031866. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T20070A22031866.en 10.2305/IUCN.UK.2017-2.RLTS.T20070A22031866.en].
* ''Sody's yellow bat'': Sinaga, U.; et al. (2008). [https://www.iucnredlist.org/species/136612/4318302 "''Scotophilus collinus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2008''': e.T136612A4318302. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2008.RLTS.T136612A4318302.en 10.2305/IUCN.UK.2008.RLTS.T136612A4318302.en].
* ''Sulawesi yellow bat'': Hutson, A. M.; et al. (2008). [https://www.iucnredlist.org/species/20065/9141459 "''Scotophilus celebensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2008''': e.T20065A9141459. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2008.RLTS.T20065A9141459.en 10.2305/IUCN.UK.2008.RLTS.T20065A9141459.en].
* ''Trujillo's yellow bat'': Monadjem, A. (2017). [https://www.iucnredlist.org/species/84466859/84466867 "''Scotophilus trujilloi''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T84466859A84466867. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T84466859A84466867.en 10.2305/IUCN.UK.2017-2.RLTS.T84466859A84466867.en].
* ''White-bellied yellow bat'': Monadjem, A.; et al. (2017). [https://www.iucnredlist.org/species/20069/22032119 "''Scotophilus leucogaster''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2017''': e.T20069A22032119. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2017-2.RLTS.T20069A22032119.en 10.2305/IUCN.UK.2017-2.RLTS.T20069A22032119.en].
]
[''Scotorepens'' habitats:
* ''Eastern broad-nosed bat'': Lumsden, L. F.; et al. (2021) [amended version of 2020 assessment]. [https://www.iucnredlist.org/species/14945/209531493 "''Scotorepens orion''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T14945A209531493. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T14945A209531493.en 10.2305/IUCN.UK.2021-3.RLTS.T14945A209531493.en].
* ''Inland broad-nosed bat'': Lumsden, L. F.; et al. (2021) [amended version of 2020 assessment]. [https://www.iucnredlist.org/species/14942/209531194 "''Scotorepens balstoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T14942A209531194. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T14942A209531194.en 10.2305/IUCN.UK.2021-3.RLTS.T14942A209531194.en].
* ''Little broad-nosed bat'': Lumsden, L. F.; et al. (2021) [amended version of 2020 assessment]. [https://www.iucnredlist.org/species/14943/209531715 "''Scotorepens greyii''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T14943A209531715. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T14943A209531715.en 10.2305/IUCN.UK.2021-3.RLTS.T14943A209531715.en].
* ''Northern broad-nosed bat'': Hutson, A. M.; et al. (2020). [https://www.iucnredlist.org/species/14947/22008930 "''Scotorepens sanborni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T14947A22008930. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T14947A22008930.en 10.2305/IUCN.UK.2020-3.RLTS.T14947A22008930.en].
]
[Srinivasulu, B.; et al. (2019). [https://www.iucnredlist.org/species/17338/22129897 "''Scotozous dormeri''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T17338A22129897. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T17338A22129897.en 10.2305/IUCN.UK.2019-3.RLTS.T17338A22129897.en].]
[Francis, C. M.; et al. (2020). [https://www.iucnredlist.org/species/40031/22063116 "''Thainycteris aureocollaris''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T40031A22063116. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-3.RLTS.T40031A22063116.en 10.2305/IUCN.UK.2020-3.RLTS.T40031A22063116.en].]
[''Tylonycteris'' habitats:
* ''Pygmy bamboo bat'': Yu, W.; et al. (2020). [https://www.iucnredlist.org/species/85342580/85342583 "''Tylonycteris pygmaeus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T85342580A85342583. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T85342580A85342583.en 10.2305/IUCN.UK.2020-2.RLTS.T85342580A85342583.en].
* ''Greater bamboo bat'': Tu, V.; et al. (2020). [https://www.iucnredlist.org/species/22578/22086856 "''Tylonycteris robustula''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T22578A22086856. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T22578A22086856.en 10.2305/IUCN.UK.2020-2.RLTS.T22578A22086856.en].
* ''Lesser bamboo bat'': Tu, V.; et al. (2020). [https://www.iucnredlist.org/species/22577/22086494 "''Tylonycteris pachypus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T22577A22086494. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T22577A22086494.en 10.2305/IUCN.UK.2020-2.RLTS.T22577A22086494.en].
]
[''Vespadelus'' habitats:
* ''Eastern cave bat'': Pennay, M. (2020). [https://www.iucnredlist.org/species/7944/22119784 "''Vespadelus troughtoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T7944A22119784. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T7944A22119784.en 10.2305/IUCN.UK.2020-2.RLTS.T7944A22119784.en].
* ''Eastern forest bat'': Pennay, M. (2020). [https://www.iucnredlist.org/species/7938/22120244 "''Vespadelus pumilus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T7938A22120244. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T7938A22120244.en 10.2305/IUCN.UK.2020-2.RLTS.T7938A22120244.en].
* ''Finlayson's cave bat'': Armstrong, K. N. (2021). [https://www.iucnredlist.org/species/7924/22118503 "''Vespadelus finlaysoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T7924A22118503. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T7924A22118503.en 10.2305/IUCN.UK.2021-3.RLTS.T7924A22118503.en].
* ''Inland forest bat'': Lumsden, L. F.; et al. (2021) [amended version of 2020 assessment]. [https://www.iucnredlist.org/species/7913/209532128 "''Vespadelus baverstocki''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T7913A209532128. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T7913A209532128.en 10.2305/IUCN.UK.2021-3.RLTS.T7913A209532128.en].
* ''Large forest bat'': Lumsden, L. F.; et al. (2021) [amended version of 2020 assessment]. [https://www.iucnredlist.org/species/7920/209532370 "''Vespadelus darlingtoni''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T7920A209532370. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T7920A209532370.en 10.2305/IUCN.UK.2021-3.RLTS.T7920A209532370.en].
* ''Little forest bat'': Lumsden, L. F.; et al. (2021) [amended version of 2020 assessment]. [https://www.iucnredlist.org/species/7945/209533303 "''Vespadelus vulturnus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T7945A209533303. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T7945A209533303.en 10.2305/IUCN.UK.2021-3.RLTS.T7945A209533303.en].
* ''Northern cave bat'': McKenzie, N.; et al. (2020). [https://www.iucnredlist.org/species/7919/22114386 "''Vespadelus caurinus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2020''': e.T7919A22114386. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2020-2.RLTS.T7919A22114386.en 10.2305/IUCN.UK.2020-2.RLTS.T7919A22114386.en].
* ''Southern forest bat'': Lumsden, L. F.; et al. (2021) [amended version of 2020 assessment]. [https://www.iucnredlist.org/species/7939/209533051 "''Vespadelus regulus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T7939A209533051. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T7939A209533051.en 10.2305/IUCN.UK.2021-3.RLTS.T7939A209533051.en].
* ''Yellow-lipped bat'': Armstrong, K. N.; et al. (2021) [amended version of 2017 assessment]. [https://www.iucnredlist.org/species/7923/209538760 "''Vespadelus douglasorum''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2021''': e.T7923A209538760. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2021-3.RLTS.T7923A209538760.en 10.2305/IUCN.UK.2021-3.RLTS.T7923A209538760.en].
]
[''Vespertilio'' habitats:
* ''Asian particolored bat'': Fukui, D.; et al. (2019). [https://www.iucnredlist.org/species/22949/22071812 "''Vespertilio sinensis''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2019''': e.T22949A22071812. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2019-3.RLTS.T22949A22071812.en 10.2305/IUCN.UK.2019-3.RLTS.T22949A22071812.en].
* ''Parti-coloured bat'': Coroiu, I. (2016). [https://www.iucnredlist.org/species/22947/22071456 "''Vespertilio murinus''"]. ''[[IUCN Red List|IUCN Red List of Threatened Species]]''. '''2016''': e.T22947A22071456. [[doi (identifier)|doi]]:[https://doi.org/10.2305%2FIUCN.UK.2016-2.RLTS.T22947A22071456.en 10.2305/IUCN.UK.2016-2.RLTS.T22947A22071456.en].
]
}}
==Sources==
{{refbegin}}
* {{cite book |title=[[All the Mammals of the World]] |date=2023 |publisher=[[Lynx Nature Books]] |editor-last1=Chernasky |editor-first1=Amy |editor-last2=Motis |editor-first2=Anna |editor-last3=Burgin |editor-first3=Connor |isbn=978-84-16728-66-4 |ref=CITEREF_ALLMAM}}
* {{cite book |title=[[Mammal Species of the World]] |edition=3rd |volume=1 |editor-last1=Wilson |editor-first1=Don E. |editor-link1=Don E. Wilson |editor-last2=Reeder |editor-first2=DeeAnn M. |author-last=Simmons |author-first=Nancy B. |date=2005 |publisher=[[Johns Hopkins University Press]] |isbn=978-0-8018-8221-0 |ref=CITEREF_MSW}}
* {{cite book |first=Ronald M. |last=Nowak |title=Walker's Bats of the World |year=1994 |publisher=[[Johns Hopkins University Press]] |isbn=978-0-8018-4986-2 |url=https://archive.org/details/walkersbatsofwor00rona|url-access=registration |ref=CITEREF_BATWORLD}}
{{refend}}
{{Mammal lists}}
[[Category:Lists of animal genera|Chiropterans]]
[[Category:Lists of bats| ]]