Turing test - Knowledge (XXG)

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noting that Sterrett equates this with the "standard interpretation" rather than the second version of the imitation game. Sterrett agrees that the standard Turing test (STT) has the problems that its critics cite but feels that, in contrast, the original imitation game test (OIG test) so defined is immune to many of them, due to a crucial difference: Unlike the STT, it does not make similarity to human performance the criterion, even though it employs human performance in setting a criterion for machine intelligence. A man can fail the OIG test, but it is argued that it is a virtue of a test of intelligence that failure indicates a lack of resourcefulness: The OIG test requires the resourcefulness associated with intelligence and not merely "simulation of human conversational behaviour." The general structure of the OIG test could even be used with non-verbal versions of imitation games.

56: 1454: 891:. Early Loebner Prize rules restricted conversations: Each entry and hidden-human conversed on a single topic, thus the interrogators were restricted to one line of questioning per entity interaction. The restricted conversation rule was lifted for the 1995 Loebner Prize. Interaction duration between judge and entity has varied in Loebner Prizes. In Loebner 2003, at the University of Surrey, each interrogator was allowed five minutes to interact with an entity, machine or hidden-human. Between 2004 and 2007, the interaction time allowed in Loebner Prizes was more than twenty minutes. 596:, Ayer suggested a protocol to distinguish between a conscious man and an unconscious machine: "The only ground I can have for asserting that an object which appears to be conscious is not really a conscious being, but only a dummy or a machine, is that it fails to satisfy one of the empirical tests by which the presence or absence of consciousness is determined." (This suggestion is very similar to the Turing test, but it is not certain that Ayer's popular philosophical classic was familiar to Turing.) In other words, a thing is not conscious if it fails the consciousness test. 1068:

in the modern scientific tradition of Galileo. Shlomo Danziger promotes a socio-technological interpretation, according to which Turing saw the imitation game not as an intelligence test but as a technological aspiration - one whose realization would likely involve a change in society's attitude toward machines. According to this reading, Turing's celebrated 50-year prediction - that by the end of the 20th century his test will be passed by some machine - actually consists of two distinguishable predictions. The first is a technological prediction:

614:. When Gulliver is brought before the king of the Brobdingnaggians, the king thinks at first that Gulliver might be a "a piece of clock-work (which is in that country arrived to a very great perfection) contrived by some ingenious artist". Even when he hears Gulliver speaking, the king still doubts whether Gulliver was taught "a set of words" to make him "sell at a better price". Gulliver tells that only after "he put several other questions to me, and still received rational answers" the king became satisfied that Gulliver was not a machine. 1306:, when the confederate (tested) humans are misidentified by the interrogators as machines. It has been suggested that what interrogators expect as human responses is not necessarily typical of humans. As a result, some individuals can be categorised as machines. This can therefore work in favour of a competing machine. The humans are instructed to "act themselves", but sometimes their answers are more like what the interrogator expects a machine to say. This raises the question of how to ensure that the humans are motivated to "act human". 831:" thought experiment and argued that the Turing test could not be used to determine if a machine could think. Searle noted that software (such as ELIZA) could pass the Turing test simply by manipulating symbols of which they had no understanding. Without understanding, they could not be described as "thinking" in the same sense people did. Therefore, Searle concluded, the Turing test could not prove that machines could think. Much like the Turing test itself, Searle's argument has been both widely criticised and endorsed. 464:" Because "thinking" is difficult to define, Turing chooses to "replace the question by another, which is closely related to it and is expressed in relatively unambiguous words." Turing describes the new form of the problem in terms of a three-person game called the "imitation game", in which an interrogator asks questions of a man and a woman in another room in order to determine the correct sex of the two players. Turing's new question is: "Are there imaginable digital computers which would do well in the 1733:

live human patients, could a machine be given the intelligence to make such a determination on its own?" and further the letter states: "Before synthetic patient identities become a public health problem, the legitimate EHR market might benefit from applying Turing Test-like techniques to ensure greater data reliability and diagnostic value. Any new techniques must thus consider patients' heterogeneity and are likely to have greater complexity than the Allen eighth-grade-science-test is able to grade."

718:, known as the "imitation game", in which a man and a woman go into separate rooms and guests try to tell them apart by writing a series of questions and reading the typewritten answers sent back. In this game, both the man and the woman aim to convince the guests that they are the other. (Huma Shah argues that this two-human version of the game was presented by Turing only to introduce the reader to the machine-human question-answer test.) Turing described his new version of the game as follows: 1024:

this version, player A is a computer and player B a person of either sex. The role of the interrogator is not to determine which is male and which is female, but which is a computer and which is a human. The fundamental issue with the standard interpretation is that the interrogator cannot differentiate which responder is human, and which is machine. There are issues about duration, but the standard interpretation generally considers this limitation as something that should be reasonable.

711:, defining both the terms "machine" and "think." Turing chooses not to do so; instead, he replaces the question with a new one, "which is closely related to it and is expressed in relatively unambiguous words." In essence he proposes to change the question from "Can machines think?" to "Can machines do what we (as thinking entities) can do?" The advantage of the new question, Turing argues, is that it draws "a fairly sharp line between the physical and intellectual capacities of a man." 1315: 2163:, below. Turing gives a more precise version of the question later in the paper: "hese questions equivalent to this, 'Let us fix our attention on one particular digital computer C. Is it true that by modifying this computer to have an adequate storage, suitably increasing its speed of action, and providing it with an appropriate programme, C can be made to play satisfactorily the part of A in the imitation game, the part of B being taken by a man? 445:

machine, and all participants would be separated from one another. The conversation would be limited to a text-only channel, such as a computer keyboard and screen, so the result would not depend on the machine's ability to render words as speech. If the evaluator could not reliably tell the machine from the human, the machine would be said to have passed the test. The test results would not depend on the machine's ability to give correct

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other experts in the field, pointing out that a language model appearing to mimic human conversation does not indicate that any intelligence is present behind it, despite seeming to pass the Turing test. Widespread discussion from proponents for and against the claim that LaMDA has reached sentience has sparked discussion across social-media platforms, to include defining the meaning of sentience as well as what it means to be human.

990: 1213:, it is thus implicit in the above scenario that the questions to be answered will involve neither specialised factual knowledge nor information processing technique. The challenge for the computer, rather, will be to demonstrate empathy for the role of the female, and to demonstrate as well a characteristic aesthetic sensibility—both of which qualities are on display in this snippet of dialogue which Turing has imagined: 6398:." One such test, a "Construction Challenge", would test perception and physical action—"two important elements of intelligent behavior that were entirely absent from the original Turing test." Another proposal has been to give machines the same standardized tests of science and other disciplines that schoolchildren take. A so far insuperable stumbling block to artificial intelligence is an incapacity for reliable 965: 420: 1103:

replacement. When Colby, FD Hilf, S Weber and AD Kramer tested PARRY, they did so by assuming that the interrogators did not need to know that one or more of those being interviewed was a computer during the interrogation. As Ayse Saygin, Peter Swirski, and others have highlighted, this makes a big difference to the implementation and outcome of the test. An experimental study looking at

1274:"thinking" by comparing its behaviour with human behaviour. Every element of this assumption has been questioned: the reliability of the interrogator's judgement, the value of comparing the machine with a human, and the value of comparing only behaviour. Because of these and other considerations, some AI researchers have questioned the relevance of the test to their field. 759:, worked by examining a user's typed comments for keywords. If a keyword is found, a rule that transforms the user's comments is applied, and the resulting sentence is returned. If a keyword is not found, ELIZA responds either with a generic riposte or by repeating one of the earlier comments. In addition, Weizenbaum developed ELIZA to replicate the behaviour of a 2155:). Turing wrote about the ‘imitation game’ centrally and extensively throughout his 1950 text, but apparently retired the term thereafter. He referred to ‘ test’ four times—three times in pp. 446–447 and once on p. 454. He also referred to it as an ‘experiment’—once on p. 436, twice on p. 455, and twice again on p. 457—and used the term ‘viva voce’ (p. 446), see 1258:". It is further noted, however, that whatever inspiration Turing might be able to lend in this direction depends upon the preservation of his original vision, which is to say, further, that the promulgation of a "standard interpretation" of the Turing test—i.e., one which focuses on a discursive intelligence only—must be regarded with some caution. 792:. Another group of 33 psychiatrists were shown transcripts of the conversations. The two groups were then asked to identify which of the "patients" were human and which were computer programs. The psychiatrists were able to make the correct identification only 52 percent of the time – a figure consistent with random guessing. 531:

if touched in a particular part it may ask what we wish to say to it; if in another part it may exclaim that it is being hurt, and so on. But it never happens that it arranges its speech in various ways, in order to reply appropriately to everything that may be said in its presence, as even the lowest type of man can do.

1357:" published shortly after the first Loebner Prize competition in 1992. The article noted that the first Loebner winner's victory was due, at least in part, to its ability to "imitate human typing errors." Turing himself had suggested that programs add errors into their output, so as to be better "players" of the game. 978:

them only through written notes. By asking questions of player A and player B, player C tries to determine which of the two is the man and which is the woman. Player A's role is to trick the interrogator into making the wrong decision, while player B attempts to assist the interrogator in making the right one.

1206:. Instead, as already noted, the test which he described in his seminal 1950 paper requires the computer to be able to compete successfully in a common party game, and this by performing as well as the typical man in answering a series of questions so as to pretend convincingly to be the woman contestant. 1603:

described the mind as a "mind recognizing apparatus". The challenge would be for the computer to be able to determine if it were interacting with a human or another computer. This is an extension of the original question that Turing attempted to answer but would, perhaps, offer a high enough standard

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Early Loebner Prize competitions used "unsophisticated" interrogators who were easily fooled by the machines. Since 2004, the Loebner Prize organisers have deployed philosophers, computer scientists, and journalists among the interrogators. Nonetheless, some of these experts have been deceived by the

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Chatterbot programs such as ELIZA have repeatedly fooled unsuspecting people into believing that they are communicating with human beings. In these cases, the "interrogators" are not even aware of the possibility that they are interacting with computers. To successfully appear human, there is no need

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Turing thus once again demonstrates his interest in empathy and aesthetic sensitivity as components of an artificial intelligence; and in light of an increasing awareness of the threat from an AI run amok, it has been suggested that this focus perhaps represents a critical intuition on Turing's part,

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a human. While there is some dispute whether this interpretation was intended by Turing, Sterrett believes that it was and thus conflates the second version with this one, while others, such as Traiger, do not – this has nevertheless led to what can be viewed as the "standard interpretation". In

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ow many different automata or moving machines could be made by the industry of man ... For we can easily understand a machine's being constituted so that it can utter words, and even emit some responses to action on it of a corporeal kind, which brings about a change in its organs; for instance,

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A further variation is motivated by the concern that modern Natural Language Processing prove to be highly successful in generating text on the basis of a huge text corpus and could eventually pass the Turing test simply by manipulating words and sentences that have been used in the initial training

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Saygin has suggested that maybe the original game is a way of proposing a less biased experimental design as it hides the participation of the computer. The imitation game also includes a "social hack" not found in the standard interpretation, as in the game both computer and male human are required

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The extent to which we regard something as behaving in an intelligent manner is determined as much by our own state of mind and training as by the properties of the object under consideration. If we are able to explain and predict its behaviour or if there seems to be little underlying plan, we have

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According to Huma Shah, Turing himself was concerned with whether a machine could think and was providing a simple method to examine this: through human-machine question-answer sessions. Shah argues the imitation game which Turing described could be practicalized in two different ways: a) one-to-one

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The first Loebner Prize competition in 1991 led to a renewed discussion of the viability of the Turing test and the value of pursuing it, in both the popular press and academia. The first contest was won by a mindless program with no identifiable intelligence that managed to fool naïve interrogators

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As a gay man who spent nearly his whole life in the closet, Turing must have been keenly aware of the social difficulty of constantly faking your real identity. And there's a delicious irony in the fact that decades of AI scientists have chosen to ignore Turing's gender-twisting test – only to

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is a form of reverse Turing test. Before being allowed to perform some action on a website, the user is presented with alphanumerical characters in a distorted graphic image and asked to type them out. This is intended to prevent automated systems from being used to abuse the site. The rationale is

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A critical aspect of the Turing test is that a machine must give itself away as being a machine by its utterances. An interrogator must then make the "right identification" by correctly identifying the machine as being just that. If however a machine remains silent during a conversation, then it is

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intelligent to an average interrogator. Bernardo Gonçalves shows that although Turing used the rhetoric of introducing his test as a sort of crucial experiment to decide whether machines can be said to think, the actual presentation of his test satisfies well-known properties of thought experiments

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program, preys on Internet users by convincing them to "reveal information about their identities or to lead them to visit a web site that will deliver malicious content to their computers." The program has emerged as a "Valentine-risk" flirting with people "seeking relationships online in order to

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describes the concept of generating a synthetic patient population and proposes a variation of Turing test to assess the difference between synthetic and real patients. The letter states: "In the EHR context, though a human physician can readily distinguish between synthetically generated and real

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A crucial piece of any laboratory test is that there should be a control. Turing never makes clear whether the interrogator in his tests is aware that one of the participants is a computer. He states only that player A is to be replaced with a machine, not that player C is to be made aware of this

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that LaMDA had achieved sentience. Lemoine had been placed on leave by Google for internal assertions to this effect. Agüera y Arcas (a Google Vice President) and Jen Gennai (head of Responsible Innovation) had investigated the claims but dismissed them. Lemoine's assertion was roundly rejected by

2733:, Turing began writing a chess program for a computer that did not yet exist and, in 1952, lacking a computer powerful enough to execute the program, played a game in which he simulated it, taking about half an hour over each move. The game was recorded, and the program lost to Turing's colleague 1555:

humans, rather than augmenting or extending human capabilities, the Turing Test risks directing research and implementation toward technologies that substitute for humans and thereby drive down wages and income for workers. As they lose economic power, these workers may also lose political power,

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I do not wish to give the impression that I think there is no mystery about consciousness. There is, for instance, something of a paradox connected with any attempt to localise it. But I do not think these mysteries necessarily need to be solved before we can answer the question with which we are

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Turing's remark, they are not equivalent. The test that employs the party game and compares frequencies of success is referred to as the "Original Imitation Game Test", whereas the test consisting of a human judge conversing with a human and a machine is referred to as the "Standard Turing Test",

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Turing's original article describes a simple party game involving three players. Player A is a man, player B is a woman and player C (who plays the role of the interrogator) is of either gender. In the imitation game, player C is unable to see either player A or player B, and can communicate with

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Turing, in particular, had been running the notion of machine intelligence since at least 1941 and one of the earliest-known mentions of "computer intelligence" was made by him in 1947. In Turing's report, "Intelligent Machinery," he investigated "the question of whether or not it is possible for

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Saul Traiger argues that there are at least three primary versions of the Turing test, two of which are offered in "Computing Machinery and Intelligence" and one that he describes as the "Standard Interpretation". While there is some debate regarding whether the "Standard Interpretation" is that

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The imitation game, as described by Alan Turing in "Computing Machinery and Intelligence". Player C, through a series of written questions, attempts to determine which of the other two players is a man, and which of the two is the woman. Player A, the man, tries to trick player C into making the

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are capable of responding to human interactions but argues that such automata cannot respond appropriately to things said in their presence in the way that any human can. Descartes therefore prefigures the Turing test by defining the insufficiency of appropriate linguistic response as that which

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Another well known objection raised towards the Turing Test concerns its exclusive focus on the linguistic behaviour (i.e. it is only a "language-based" experiment, while all the other cognitive faculties are not tested). This drawback downsizes the role of other modality-specific "intelligent

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Still other writers have interpreted Turing as proposing that the imitation game itself is the test, without specifying how to take into account Turing's statement that the test that he proposed using the party version of the imitation game is based upon a criterion of comparative frequency of

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The standard interpretation is not included in the original paper, but is both accepted and debated. Common understanding has it that the purpose of the Turing test is not specifically to determine whether a computer is able to fool an interrogator into believing that it is a human, but rather

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Later in the paper, Turing suggests an "equivalent" alternative formulation involving a judge conversing only with a computer and a man. While neither of these formulations precisely matches the version of the Turing test that is more generally known today, he proposed a third in 1952. In this

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Nevertheless, the Turing test has been proposed as a measure of a machine's "ability to think" or its "intelligence". This proposal has received criticism from both philosophers and computer scientists. The interpretation makes the assumption that an interrogator can determine if a machine is

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It is not difficult to devise a paper machine which will play a not very bad game of chess. Now get three men A, B and C as subjects for the experiment. A and C are to be rather poor chess players, B is the operator who works the paper machine. ... Two rooms are used with some arrangement for

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equivalent to, or indistinguishable from, that of a human. Turing proposed that a human evaluator would judge natural language conversations between a human and a machine designed to generate human-like responses. The evaluator would be aware that one of the two partners in conversation was a

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argues that we should not be surprised that a philosophical idea turns out to be useless for practical applications. He observes that the philosophy of AI is "unlikely to have any more effect on the practice of AI research than philosophy of science generally has on the practice of science."

860:, United States, organised the prizes up to and including the 2003 contest. As Loebner described it, one reason the competition was created is to advance the state of AI research, at least in part, because no one had taken steps to implement the Turing test despite 40 years of discussing it. 1321:

The Turing test does not directly test whether the computer behaves intelligently. It tests only whether the computer behaves like a human being. Since human behaviour and intelligent behaviour are not exactly the same thing, the test can fail to accurately measure intelligence in two ways:

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Turing doesn't specify the precise skills and knowledge required by the interrogator in his description of the test, but he did use the term "average interrogator": " average interrogator would not have more than 70 per cent chance of making the right identification after five minutes of

788:, using a similar (if more advanced) approach to that employed by Weizenbaum. To validate the work, PARRY was tested in the early 1970s using a variation of the Turing test. A group of experienced psychiatrists analysed a combination of real patients and computers running PARRY through 722:

We now ask the question, "What will happen when a machine takes the part of A in this game?" Will the interrogator decide wrongly as often when the game is played like this as he does when the game is played between a man and a woman? These questions replace our original, "Can machines

763:, allowing ELIZA to be "free to assume the pose of knowing almost nothing of the real world." With these techniques, Weizenbaum's program was able to fool some people into believing that they were talking to a real person, with some subjects being "very hard to convince that ELIZA is 423:

The "standard interpretation" of the Turing test, in which player C, the interrogator, is given the task of trying to determine which player – A or B – is a computer and which is a human. The interrogator is limited to using the responses to written questions to make the

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The silver (text only) and gold (audio and visual) prizes have never been won. However, the competition has awarded the bronze medal every year for the computer system that, in the judges' opinions, demonstrates the "most human" conversational behaviour among that year's entries.

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Because it cannot measure intelligence that is beyond the ability of humans, the test cannot be used to build or evaluate systems that are more intelligent than humans. Because of this, several test alternatives that would be able to evaluate super-intelligent systems have been

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Danziger claims further that for Turing, alteration of society's attitude towards machinery is a prerequisite for the existence of intelligent machines: Only when the term "intelligent machine" is no longer seen as an oxymoron the existence of intelligent machines would become

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created an online social experiment titled "Human or Not?". It was played more than 10 million times by more than 2 million people. It is the biggest Turing-style experiment to that date. The results showed that 32% of people couldn't distinguish between humans and machines.

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intelligent than a human being it must deliberately avoid appearing too intelligent. If it were to solve a computational problem that is practically impossible for a human to solve, then the interrogator would know the program is not human, and the machine would fail the

985:"What will happen when a machine takes the part of A in this game? Will the interrogator decide wrongly as often when the game is played like this as he does when the game is played between a man and a woman?" These questions replace our original, "Can machines think?" 449:, only on how closely its answers resembled those a human would give. Since the Turing test is a test of indistinguishability in performance capacity, the verbal version generalizes naturally to all of human performance capacity, verbal as well as nonverbal (robotic). 1145:

The format of the test allows the interrogator to give the machine a wide variety of intellectual tasks. Turing wrote that "the question and answer method seems to be suitable for introducing almost any one of the fields of human endeavour that we wish to include."

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not possible for an interrogator to accurately identify the machine other than by means of a calculated guess. Even taking into account a parallel/hidden human as part of the test may not help the situation as humans can often be misidentified as being a machine.

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1990 marked the fortieth anniversary of the first publication of Turing's "Computing Machinery and Intelligence" paper, and saw renewed interest in the test. Two significant events occurred in that year: the first was the Turing Colloquium, which was held at the

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separates the human from the automaton. Descartes fails to consider the possibility that future automata might be able to overcome such insufficiency, and so does not propose the Turing test as such, even if he prefigures its conceptual framework and criterion.

868:): The winner won, at least in part, because it was able to "imitate human typing errors"; the unsophisticated interrogators were easily fooled; and some researchers in AI have been led to feel that the test is merely a distraction from more fruitful research. 1107:

using transcripts of Loebner's one-to-one (interrogator-hidden interlocutor) Prize for AI contests between 1994 and 1999, Ayse Saygin found significant differences between the responses of participants who knew and did not know about computers being involved.

1270:", or any other human quality. He wanted to provide a clear and understandable alternative to the word "think", which he could then use to reply to criticisms of the possibility of "thinking machines" and to suggest ways that research might move forward. 2821:, pp. 524–525. Turing does not seem to distinguish between "man" as a gender and "man" as a human. In the former case, this formulation would be closer to the imitation game, whereas in the latter it would be closer to current depictions of the test. 1072:

I believe that in about fifty years' time it will be possible to programme computers ... to make them play the imitation game so well that an average interrogator will not have more than 70% chance of making the right identification after five minutes of

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is designed to take advantage of the broad range of topics available to a Turing test. It is a limited form of Turing's question-answer game which compares the machine against the abilities of experts in specific fields such as literature or

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The Turing test does not test for highly intelligent behaviours, such as the ability to solve difficult problems or come up with original insights. In fact, it specifically requires deception on the part of the machine: if the machine is

2281:, p. 948), where they comment, "Turing examined a wide variety of possible objections to the possibility of intelligent machines, including virtually all of those that have been raised in the half century since his paper appeared." 955:

article that "ChatGPT broke the Turing test." Stanford researchers reported that ChatGPT passes the test; they found that ChatGPT-4 "passes a rigorous Turing test, diverging from average human behavior chiefly to be more cooperative."

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The original imitation game test, in which the player A is replaced with a computer. The computer is now charged with the role of the man, while player B continues to attempt to assist the interrogator. Figure adapted from Saygin,

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Second, creating lifelike simulations of human beings is a difficult problem on its own that does not need to be solved to achieve the basic goals of AI research. Believable human characters may be interesting in a work of art, a

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The second version appeared later in Turing's 1950 paper. Similar to the original imitation game test, the role of player A is performed by a computer. However, the role of player B is performed by a man rather than a woman.

4113:, under the heading "The Imitation Game," where he writes, "Instead of attempting such a definition I shall replace the question by another, which is closely related to it and is expressed in relatively unambiguous words." 1651:

of the model. Since the interrogator has no precise understanding of the training data, the model might simply be returning sentences that exist in similar fashion in the enormous amount of training data. For this reason,

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little temptation to imagine intelligence. With the same object therefore it is possible that one man would consider it as intelligent and another would not; the second man would have found out the rules of its behaviour.

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A modification of the Turing test wherein the objective of one or more of the roles have been reversed between machines and humans is termed a reverse Turing test. An example is implied in the work of psychoanalyst

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Google Research Fellow Blaise Agüera y Arcas said the chatbot had demonstrated a degree of understanding of social relationships. Several days later, Google engineer Blake Lemoine claimed in an interview with the

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In practice, the test's results can easily be dominated not by the computer's intelligence, but by the attitudes, skill, or naïveté of the questioner. Numerous experts in the field, including cognitive scientist

1591:, who was particularly fascinated by the "storm" that resulted from the encounter of one mind by another. In his 2000 book, among several other original points with regard to the Turing test, literary scholar 1461:

Mainstream AI researchers argue that trying to pass the Turing test is merely a distraction from more fruitful research. Indeed, the Turing test is not an active focus of much academic or commercial effort—as

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in April, and brought together academics and researchers from a wide variety of disciplines to discuss the Turing test in terms of its past, present, and future; the second was the formation of the annual

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that software sufficiently sophisticated to read and reproduce the distorted image accurately does not exist (or is not available to the average user), so any system able to do so is likely to be a human.

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discussed in detail the idea of what he termed the Swirski test—essentially the reverse Turing test. He pointed out that it overcomes most if not all standard objections levelled at the standard version.

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As a Cambridge honours graduate in mathematics, Turing might have been expected to propose a test of computer intelligence requiring expert knowledge in some highly technical field, and thus anticipating

1696:(1990) makes the case that an interrogator can distinguish human and non-human interlocutors by posing questions that reveal the low-level (i.e., unconscious) processes of human cognition, as studied by 579:) and, therefore, cannot be explained in purely physical terms. According to materialism, the mind can be explained physically, which leaves open the possibility of minds that are produced artificially. 1081:

I believe that at the end of the century the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted.

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as "the maximum abstraction of the Turing test", in which only binary responses (true/false or yes/no) are permitted, to focus only on the capacity for thought. It eliminates text chat problems like

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A related approach to Hutter's prize which appeared much earlier in the late 1990s is the inclusion of compression problems in an extended Turing test. or by tests which are completely derived from

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language. He proposes a test in which the machine is confronted with philosophical questions that do not depend on any prior knowledge and yet require self-reflection to be answered appropriately.

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suggests that a machine passing the test may be able to simulate human conversational behaviour by following a simple (but large) list of mechanical rules, without thinking or having a mind at all.

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Tests where a human judges whether a computer or an alien is intelligent were an established convention in science fiction by the 1940s, and it is likely that Turing would have been aware of these.

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have been unable to provide definitions of "intelligence" and "thinking" that are sufficiently precise and general to be applied to machines. Without such definitions, the central questions of the

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cannot be answered. The Turing test, even if imperfect, at least provides something that can actually be measured. As such, it is a pragmatic attempt to answer a difficult philosophical question.

468:?" This question, Turing believed, was one that could actually be answered. In the remainder of the paper, he argued against all the major objections to the proposition that "machines can think". 1333:

human behaviours, regardless of whether they are intelligent. It even tests for behaviours that may not be considered intelligent at all, such as the susceptibility to insults, the temptation to

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sparked off a more intense debate about the nature of intelligence, the possibility of machines with a conscious mind and the value of the Turing test that continued through the 1980s and 1990s.

495:", regardless of how intelligently or human-like the program may make the computer behave. Searle criticizes Turing's test and claims it is insufficient to detect the presence of consciousness. 4525: 4730: 703:) was the first published paper by Turing to focus exclusively on machine intelligence. Turing begins the 1950 paper with the claim, "I propose to consider the question 'Can machines think? 3188: 1614:

Software that could reverse CAPTCHA with some accuracy by analysing patterns in the generating engine started being developed soon after the creation of CAPTCHA. In 2013, researchers at

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a Turing-test criterion, though with the important implicit limiting assumption maintained, of the participants being natural living beings, rather than considering created artifacts:

1173:. The test can be extended to include video input, as well as a "hatch" through which objects can be passed: this would force the machine to demonstrate skilled use of well designed 1032:

Controversy has arisen over which of the alternative formulations of the test Turing intended. Sterrett argues that two distinct tests can be extracted from his 1950 paper and that,

1481:. To test the intelligence of the programs that solve these problems, AI researchers simply give them the task directly. Stuart Russell and Peter Norvig suggest an analogy with the 3604:

R. Epstein, G. Roberts, G. Poland, (eds.) Parsing the Turing Test: Philosophical and Methodological Issues in the Quest for the Thinking Computer. Springer: Dordrecht, Netherlands

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Turing did not intend for his idea to be used to test the intelligence of programs—he wanted to provide a clear and understandable example to aid in the discussion of the

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Some writers argue that the imitation game is best understood by its social aspects. In his 1948 paper, Turing refers to intelligence as an "emotional concept," and notes that

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described by Turing or, instead, based on a misreading of his paper, these three versions are not regarded as equivalent, and their strengths and weaknesses are distinct.

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Saygin, A.P.; Roberts, Gary; Beber, Grace (2008), "Comments on "Computing Machinery and Intelligence" by Alan Turing", in Epstein, R.; Roberts, G.; Poland, G. (eds.),

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Colby, K. M.; Hilf, F. D.; Weber, S.; Kraemer, H. (1972), "Turing-like indistinguishability tests for the validation of a computer simulation of paranoid processes",

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LaMDA (Language Model for Dialog Applications) chatbot received widespread coverage regarding claims about it having achieved sentience. Initially in an article in

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human." Thus, ELIZA is claimed by some to be one of the programs (perhaps the first) able to pass the Turing test, even though this view is highly contentious (see

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radio broadcast, a jury asks questions of a computer and the role of the computer is to make a significant proportion of the jury believe that it is really a man.

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Is it true that by modifying this computer to have an adequate storage, suitably increasing its speed of action, and providing it with an appropriate programme,

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lists four major turning points in the history of the Turing test – the publication of "Computing Machinery and Intelligence" in 1950, the announcement of

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Turing test, where a machine's response cannot be distinguished from an expert in a given field. This is also known as a "Feigenbaum test" and was proposed by

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Researchers in the United Kingdom had been exploring "machine intelligence" for up to ten years prior to the founding of the field of artificial intelligence (

4135: 658:," where the protagonist falls in love with an automaton. In all these examples, people are fooled by artificial beings that - up to a point - pass as human. 1556:

making it more difficult for them to change the allocation of wealth and income. This can trap them in a bad equilibrium. Erik Brynjolfsson has called this "

6079: 6762: 2938: 2908: 1953:. No agreement emerged for a canonical Turing test, though Bringsjord expressed that a sizeable prize would result in the Turing test being passed sooner. 167: 1763:

than an interrogation. It is typically used to gather statistical data against which the performance of artificial intelligence programs may be measured.

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argument is intended to show that, even if the Turing test is a good operational definition of intelligence, it may not indicate that the machine has a

6406:, often in multiple ways." A prominent example is known as the "pronoun disambiguation problem": a machine has no way of determining to whom or what a 3648: 1700:. Such questions reveal the precise details of the human embodiment of thought and can unmask a computer unless it experiences the world as humans do. 4785: 4734: 4519: 3754: 6362: 1819:

Two major advantages of some of these tests are their applicability to nonhuman intelligences and their absence of a requirement for human testers.

1557: 1230:

Interrogator: In the first line of your sonnet which reads, "Shall I compare thee to a summer's day," would not "a spring day" do as well or better?

266: 244: 6757: 4859: 4633: 3948: 1712:, adds two further requirements to the traditional Turing test. The interrogator can also test the perceptual abilities of the subject (requiring 202: 180: 4199: 852:

The Loebner Prize provides an annual platform for practical Turing tests with the first competition held in November 1991. It is underwritten by

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communicating moves, and a game is played between C and either A or the paper machine. C may find it quite difficult to tell which he is playing.

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machinery to show intelligent behaviour" and, as part of that investigation, proposed what may be considered the forerunner to his later tests:

6724: 5820:(2009a), "Emotion in the Turing Test: A Downward Trend for Machines in Recent Loebner Prizes", in Vallverdú, Jordi; Casacuberta, David (eds.), 3251:"A.I. experts say the Google researcher's claim that his chatbot became 'sentient' is ridiculous—but also highlights big problems in the field" 2036: 1473:

First, there are easier ways to test their programs. Most current research in AI-related fields is aimed at modest and specific goals, such as

1226:

When Turing does introduce some specialised knowledge into one of his imagined dialogues, the subject is not maths or electronics, but poetry:

888: 104: 2509:. In: Moor, J.H. (eds) The Turing Test. Studies in Cognitive Systems, vol 30. Springer, Dordrecht. https://doi.org/10.1007/978-94-010-0105-2_9 6607: 6329: 6311: 6254: 6200: 6143: 6121: 5829: 5738: 5604: 5527: 5504: 5416: 5396: 5367: 5168: 5141: 5119: 5069: 5048: 5005: 2618: 2483: 2352: 1938: 1513: 1134: 472: 399: 325: 279: 234: 229: 5808: 4361: 6695: 740: 696: 453: 1630:

up to 90% of the time. In 2014, Google engineers demonstrated a system that could defeat CAPTCHA challenges with 99.8% accuracy. In 2015,

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Algorithmic IQ, or AIQ for short, is an attempt to convert the theoretical Universal Intelligence Measure from Legg and Hutter (based on

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has argued that external behaviour cannot be used to determine if a machine is "actually" thinking or merely "simulating thinking." His

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Since Turing introduced his test, it has been both highly influential and widely criticized, and has become an important concept in the

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The question of whether it is possible for machines to think has a long history, which is firmly entrenched in the distinction between

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interrogator-machine test, and b) simultaneous comparison of a machine with a human, both questioned in parallel by an interrogator.

338: 207: 197: 187: 5822:

Handbook of Research on Synthetic Emotions and Sociable Robotics: New Applications in Affective Computing and Artificial Intelligence

5314:(2004), "The Annotation Game: On Turing (1950) on Computing, Machinery, and Intelligence", in Epstein, Robert; Peters, Grace (eds.), 3250: 6182: 6072: 5584: 5486: 5016: 2366: 1672: 1203: 310: 256: 222: 89: 1759:, allowing for systems that exceed human intelligence. The questions must each stand on their own, however, making it more like an 1509:, but they are not part of the science of creating intelligent machines, that is, machines that solve problems using intelligence. 1015:

In this version, both player A (the computer) and player B are trying to trick the interrogator into making an incorrect decision.

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as well. Together, these represent almost all of the major problems that artificial intelligence research would like to solve.

74: 6177:(reprinted in The Turing Test: The Elusive Standard of Artificial Intelligence edited by James H. Moor, Kluwer Academic 2003) 6067:(reprinted in The Turing Test: The Elusive Standard of Artificial Intelligence edited by James H. Moor, Kluwer Academic 2003) 5351:

Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence (IJCAI95-1), Montreal, Quebec, Canada.

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Gonçalves, Bernardo (2023a), "Galilean resonances: the role of experiment in Turing's construction of machine intelligence",

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Following this remark and similar ones scattered throughout Turing's publications, Diane Proudfoot claims that Turing held a

3022: 5959: 4383: 2233: 55: 6557: 3164: 2031: 1993: 760: 6506: 5614: 4945: 1287:, insist that the Turing test only shows how easy it is to fool humans and is not an indication of machine intelligence. 6391: 5429: 4611: 4333: 509: 28: 4760: 4719:

An Approximation of the Universal Intelligence Measure, Shane Legg and Joel Veness, 2011 Solomonoff Memorial Conference

3804: 1560:" and argued that there are currently excess incentives for creating machines that imitate rather than augment humans. 1453: 1295:

for the machine to have any intelligence whatsoever and only a superficial resemblance to human behaviour is required.

6266:(January 1966), "ELIZA – A Computer Program For the Study of Natural Language Communication Between Man And Machine", 5078:

Danziger, Shlomo (2022), "Intelligence as a Social Concept: a Socio-Technological Interpretation of the Turing Test",

3219: 1963: 1158: 823: 646: 261: 212: 109: 556:

If they find a parrot who could answer to everything, I would claim it to be an intelligent being without hesitation.

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Between Literature and Science: Poe, Lem, and Explorations in Aesthetics, Cognitive Science, and Literary Knowledge

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Hernandez-Orallo, J; Dowe, D L (2010), "Measuring Universal Intelligence: Towards an Anytime Intelligence Test",

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Numerous other versions of the Turing test, including those expounded above, have been raised through the years.

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into making the wrong identification. This highlighted several of the shortcomings of the Turing test (discussed

655: 592: 162: 6573: 3336:"Study finds ChatGPT's latest bot behaves like humans, only better | Stanford School of Humanities and Sciences" 2930: 2900: 1166: 457: 286: 6457:

and Shah, Huma (2016), "Turing's Imitation Game: Conversations with the Unknown", Cambridge University Press.

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It is unknown what particular "score" on this test—if any—is equivalent to passing a human-level Turing test.

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The data compression test has some advantages over most versions and variations of a Turing test, including:

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write: "AI researchers have devoted little attention to passing the Turing test." There are several reasons.

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believe that compressing natural language text is a hard AI problem, equivalent to passing the Turing test.

736: 667: 522: 441: 67: 47: 6320:

Zylberberg, A.; Calot, E. (2007), "Optimizing Lies in State Oriented Domains based on Genetic Algorithms",

6298:

Whitby, Blay (1996), "The Turing Test: AI's Biggest Blind Alley?", in Millican, Peter; Clark, Andy (eds.),

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M. Bishop & J. Preston (eds.) (2001) Essays on Searle's Chinese Room Argument. Oxford University Press.

1011:

can be made to play satisfactorily the part of A in the imitation game, the part of B being taken by a man?

6348: 5991: 5689: 5317:

The Turing Test Sourcebook: Philosophical and Methodological Issues in the Quest for the Thinking Computer

4672: 3917: 3750: 2062: 1782:

It gives a single number that can be directly used to compare which of two machines is "more intelligent."

1393: 548: 157: 6380:, "Am I Human?: Researchers need new ways to distinguish artificial intelligence from the natural kind", 3189:"Artificial neural networks are making strides towards consciousness, according to Blaise Agüera y Arcas" 876:(A.L.I.C.E.) has won the bronze award on three occasions in recent times (2000, 2001, 2004). Learning AI 6747: 6719: 5321: 2102: 1914: 1806: 1678: 1652: 1489:

texts," they write, "do not define the goal of their field as 'making machines that fly so exactly like

1162: 633: 5715:

Parsing the Turing Test: Philosophical and Methodological Issues in the Quest for the Thinking Computer

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has sufficient skill in terms of intonations, inflections, timing and so forth, to make people laugh.

1655:

proposes a variation of the Turing test that can distinguish between systems that are only capable of

1604:

to define a machine that could "think" in a way that we typically define as characteristically human.

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Turing's paper considered nine putative objections, which include some of the major arguments against

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Several alternatives to the Turing test, designed to evaluate machines more intelligent than humans:

3373: 3293: 2642: 2461: 2057: 2018: 1998: 1871: 1848: 1631: 1354: 948: 99: 2394: 6688: 6627: 6382: 5996: 5694: 4677: 3922: 2067: 1615: 1577: 1338: 618: 587: 572: 251: 6390:

tests of artificial-intelligence efficacy are needed because, "just as there is no single test of

4950:, Society for the Study of Artificial Intelligence and the Simulation of Behaviour, archived from 2981: 1922: 6443: 6287: 6169: 6059: 6009: 5973: 5947: 5889: 5872: 5781: 5744: 5647: 5555: 5451: 5228: 5197: 5095: 4690: 4460: 4281: 4238: 4014: 3988: 3935: 3863: 3001: 2591: 2489: 2358: 1474: 1303: 1122: 835: 446: 301: 21: 4355: 781:

in 1972, a program described as "ELIZA with attitude." It attempted to model the behaviour of a

590:: how do we know that other people have the same conscious experiences that we do? In his book, 1930: 6647: 6435: 6325: 6307: 6263: 6250: 6231: 6196: 6178: 6139: 6117: 6068: 5825: 5734: 5600: 5580: 5566: 5523: 5500: 5482: 5412: 5392: 5363: 5278: 5177: 5164: 5137: 5115: 5065: 5044: 5001: 4985: 4922: 4841: 4273: 4230: 3728: 3407: 3389: 3309: 2624: 2614: 2583: 2479: 2348: 2077: 2047: 2024: 1942: 1886: 1697: 1682: 1600: 1482: 1463: 1436:. (Intentionality is a philosophical term for the power of thoughts to be "about" something.) 752: 651: 622: 517: 79: 5789: 3040: 1063:

approach to intelligence, according to which an intelligent (or thinking) entity is one that

6652: 6427: 6277: 6245:(1952), "Can Automatic Calculating Machines be Said to Think?", in Copeland, B. Jack (ed.), 6223: 6161: 6106: 6049: 6041: 6001: 5937: 5881: 5853: 5773: 5726: 5699: 5637: 5629: 5547: 5474: 5443: 5298: 5268: 5248: 5220: 5208: 5189: 5108: 5087: 5025: 4831: 4682: 4567: 4496: 4450: 4265: 4222: 4169: 4050: 4006: 3927: 3855: 3615: 3397: 3381: 3301: 2993: 2469: 2432: 2338: 1836: 1693: 1170: 1047:

success in that imitation game, rather than a capacity to succeed at one round of the game.

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i.e., that emotional and aesthetic intelligence will play a key role in the creation of a "

6531: 6489: 4599: 3652: 2730: 2208: 2008: 1748: 1713: 1185: 1174: 918: 94: 2327: 1341:. If a machine cannot imitate these unintelligent behaviours in detail it fails the test. 5987: 5722: 5378:

Group Mentality and Having a Mind: Reflections on Bion's work on groups and on psychosis

4827: 4218: 4002: 3402: 3377: 3361: 3297: 2465: 2335:

Proceedings of the 2020 Federated Conference on Computer Science and Information Systems

1642:

sites that would defeat CAPTCHA challenges for a fee, to enable various forms of fraud.

969:

wrong decision, while player B tries to help player C. Figure adapted from Saygin, 2000.

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Warwick, Kevin; Shah, Huma (4 March 2015). "Human misidentification in Turing tests".

1708:

The "Total Turing test" variation of the Turing test, proposed by cognitive scientist

989: 6741: 6632: 6552: 6454: 6013: 5867: 5841: 5817: 5513: 5406: 5311: 5154: 5129: 5099: 5036: 5029: 4860:"Can you distinguish people from AI bots? 'Human or not' online game reveals results" 4464: 4242: 4188:

Gardner, H. (2011). Frames of mind: The theory of multiple intelligences. Hachette Uk

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This does not mean he agrees with this, but that it was already a common argument of

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Turing did not explicitly state that the Turing test could be used as a measure of "

1222:

Contestant: My hair is shingled, and the longest strands are about nine inches long.

460:. It opens with the words: "I propose to consider the question, 'Can machines think? 6395: 6291: 6173: 6063: 5570: 5425: 5384: 3732: 2974: 2521:"Cognition as Computation: From Swift to Turing. | Humanities Bulletin | EBSCOhost" 2493: 1772: 1588: 1467: 1421: 1403: 1387: 1267: 1130: 1034: 853: 828: 813: 628:

Earlier examples of machines or automatons attempting to pass as human include the

561: 480: 419: 291: 6509:

reviews a half-century of work on the Turing Test, from the vantage point of 2000.

6493: 5651: 5273: 4951: 4226: 4018: 2506: 964: 5870:(June 2010j), "Hidden Interlocutor Misidentification in Practical Turing Tests", 4411: 4269: 4055: 3859: 3846:

Kevin Warwick; Huma Shah (June 2014). "Human Misidentification in Turing Tests".

3360:

Mei, Qiaozhu; Xie, Yutong; Yuan, Walter; Jackson, Matthew O. (27 February 2024).

1530:

abilities" concerning human beings that the psychologist Howard Gardner, in his "

707:" As he highlights, the traditional approach to such a question is to start with 6616: 6377: 6353: 6242: 6209: 6188: 5844:(April 2010a), "Testing Turing's five minutes, parallel-paired imitation game", 5757: 5680:

Saygin, A. P.; Cicekli, I. (2002), "Pragmatics in human-computer conversation",

4158:"The Turing Trap: The Promise & Peril of Human-Like Artificial Intelligence" 2181: 2003: 1926: 1919:

Society for the Study of Artificial Intelligence and the Simulation of Behaviour

1882: 1832: 1635: 1486: 1417: 1284: 1255: 877: 818: 789: 755:

created a program which appeared to pass the Turing test. The program, known as

679: 675: 583: 513: 476: 437: 305: 6415: 6227: 5303: 5224: 5180:(2003), "Some challenges and grand challenges for computational intelligence", 5091: 4836: 4811: 4638:

Proceedings of the 4th Conference of the Australasian Cognitive Science Society

4455: 3953:

Proceedings of the 4th Conference of the Australasian Cognitive Science Society

3305: 2225: 1809:. Other related tests in this line are presented by Hernandez-Orallo and Dowe. 6535: 6518: 6431: 6165: 6045: 5885: 5857: 5777: 5730: 5655: 5633: 5252: 4686: 4010: 3931: 2997: 2628: 2445: 2082: 1973: 1828: 1639: 1502: 1126: 1104: 884: 715: 708: 671: 6439: 6235: 5459: 4603: 4327: 4277: 4234: 3393: 2587: 2328:"Game AI Competitions: Motivation for the Imitation Game-Playing Competition" 1534:", proposes to consider (verbal-linguistic abilities are only one of those). 1150:

adds that "understanding the words is not enough; you have to understand the

6403: 6152:

Traiger, Saul (2000), "Making the Right Identification in the Turing Test",

6084: 5551: 5519:

The Emperor's New Mind: Concerning Computers, Minds, and The Laws of Physics

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Capitalism and the enchanted screen: myths and allegories in the digital age

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Svilpis, Janis (2008). "The Science-Fiction Prehistory of the Turing Test".

2072: 1978: 1921:(AISB), hosted a one-day symposium to discuss the Turing test, organised by 1852: 1618:

announced that they had developed a system to solve CAPTCHA challenges from

1478: 1190: 906: 637: 355: 119: 5282: 4845: 4441:(2022), "The Philosophising Machine – a Specification of the Turing Test", 4074:, pp. 958–960) identify Searle's argument with the one Turing answers. 3411: 3313: 1485:: Planes are tested by how well they fly, not by comparing them to birds. " 883:

The Loebner Prize tests conversational intelligence; winners are typically

6282: 6005: 5942: 5447: 5193: 4812:"ChatGPT broke the Turing test — the race is on for new ways to assess AI" 3282:"ChatGPT broke the Turing test — the race is on for new ways to assess AI" 1439:

Turing anticipated this line of criticism in his original paper, writing:

1402: – the external behaviour of the machine. In this regard, it takes a 4174: 4157: 3362:"A Turing test of whether AI chatbots are behaviorally similar to humans" 1717: 1236: 1178: 1121:

The power and appeal of the Turing test derives from its simplicity. The

782: 536: 192: 114: 5559: 5349:

Hayes, Patrick; Ford, Kenneth (1995), "Turing Test Considered Harmful",

5289:

Gonçalves, Bernardo (2023b), "The Turing Test is a Thought Experiment",

2697:

was not published by Turing, and did not see publication until 1968 in:

2595: 1901:, which was first described in 1972, and the Turing Colloquium in 1990. 6407: 6054: 5978: 5642: 4786:"Massive Turing test shows we can only just tell AIs apart from humans" 2882: 2880: 1988: 1983: 1760: 1607: 1581: 941: 932: 800: 796: 739:

that have been raised in the years since the paper was published (see "

360: 2343: 6553:""The first ever (restricted) Turing test", on season 2, episode 5" 6477: 2984:(1997), "Searle's Chinese Box: Debunking the Chinese Room Argument", 2737:, although it is said that it won a game against Champernowne's wife. 2474: 2407: 2184:, one of the few text-only communication systems available in 1950. ( 2117: 1627: 1623: 1619: 1490: 937: 483:, a thought experiment that stipulates that a machine cannot have a " 6108:

The Social and Interactional Dimensions of Human-Computer Interfaces

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Interrogator: How about "a winter's day." That would scan all right.

6582:"Talk:Computer professionals celebrate 10th birthday of A.L.I.C.E." 6247:

The Essential Turing: The ideas that gave birth to the computer age

6193:

The Essential Turing: The ideas that gave birth to the computer age

1756: 1302:

One interesting feature of the Turing test is the frequency of the

670:) research in 1956. It was a common topic among the members of the 6515:, including detailed justifications of their respective positions. 5904: 4521:

The Turing Test: brain-inspired computing's multiple-path approach

4357:

Captcha FAIL: Researchers Crack the Web's Most Popular Turing Test

3993: 3623: 3220:"The Google engineer who thinks the company's AI has come to life" 1898: 1890: 1452: 1411: 1217:

Interrogator: Will X please tell me the length of his or her hair?

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To demonstrate this approach Turing proposes a test inspired by a

418: 6468: 4258:

Journal of Experimental & Theoretical Artificial Intelligence

4207:

Journal of Experimental & Theoretical Artificial Intelligence

1646:

Distinguishing accurate use of language from actual understanding

625:" (1934) provides an example of how nuanced such tests could be. 5928:

Shapiro, Stuart C. (1992), "The Turing Test and the economist",

5497:

The Turing Test: The Elusive Standard of Artificial Intelligence

5041:

The Turing Test: The Elusive Standard of Artificial Intelligence

1789:

The main disadvantages of using data compression as a test are:

1425: 1249:

Witness: Yes, but nobody wants to be compared to a winter's day.

604:

A rudimentary idea of the Turing test appears in the 1726 novel

568: 484: 6589: 6322:

Proceedings VI Ibero-American Symposium on Software Engineering

5579:(2nd ed.), Upper Saddle River, New Jersey: Prentice Hall, 5574: 3848:

Journal of Experimental and Theoretical Artificial Intelligence

1449:

Impracticality and irrelevance: the Turing test and AI research

795:

In the 21st century, versions of these programs (now known as "

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Turing's misunderstood imitation game and IBM's Watson success

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Sterrett, S. G. (2000), "Turing's Two Test of Intelligence",

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Cacm Staff (2017). "A leap from artificial to intelligence".

4094: 4092: 1716:) and the subject's ability to manipulate objects (requiring 1329:

The Turing test requires that the machine be able to execute

6512: 6191:(1948), "Machine Intelligence", in Copeland, B. Jack (ed.), 1003:

Let us fix our attention on one particular digital computer

940:'s chatbot, ChatGPT, released in November 2022, is based on 54: 5134:

Pensees Philosophiques, Addition aux Pensees Philosophiques

4747:

He calls it the "Ebert Test," after Turing's AI standard...

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The Turing test is concerned strictly with how the subject

5536:

Proudfoot, Diane (July 2013), "Rethinking Turing's Test",

5211:(1990), "Subcognition and the Limits of the Turing Test", 3112:. Vol. 324, no. 7770. 1 August 1992. p. 14. 2729:

In 1948, working with his former undergraduate colleague,

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To pass a well-designed Turing test, the machine must use

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Google algorithm busts CAPTCHA with 99.8 percent accuracy

1937:. The speakers included the Royal Institution's Director 1816:) into a working practical test of machine intelligence. 1801:

Other tests based on compression or Kolmogorov complexity

1077:

The second prediction Turing makes is a sociological one:

16:

Test of a machine's ability to imitate human intelligence

6212:(October 1950), "Computing Machinery and Intelligence", 4663:

Jose Hernandez-Orallo (2000), "Beyond the Turing Test",

3908:

Jose Hernandez-Orallo (2000), "Beyond the Turing Test",

3588: 3586: 3584: 3142: 3140: 2775: 2773: 2771: 2769: 2767: 5599:(3rd ed.), Upper Saddle River, NJ: Prentice Hall, 5110:

Discourse on Method and Meditations on First Philosophy

4200:"Taking the fifth amendment in Turing's imitation game" 3101: 3099: 3097: 2973:

There are a large number of arguments against Searle's

2255: 2253: 2251: 636:

who creates a sculpture of a woman that is animated by

4483:. The subject matter expert test is also mentioned in 3675: 3673: 3425: 3423: 3421: 5062:

AI: The Tumultuous Search for Artificial Intelligence

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Arguments such as Searle's and others working on the

650:, about a puppet who wants to become a real boy, and 452:

The test was introduced by Turing in his 1950 paper "

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Genova, J. (1994), "Turing's Sexual Guessing Game",

4707: 4499:, "Subcognition and the Limits of the Turing Test", 2297: 2295: 2293: 2291: 2289: 2287: 1785:

It does not require the computer to lie to the judge

1747:

The minimum intelligent signal test was proposed by

6712: 6666: 4976:Bion, W.S. (1979), "Making the best of a bad job", 3452: 3450: 20:"Imitation game" redirects here. For the film, see 6105: 5903: 5107: 4989: 3751:"The AI Revolution: Our Immortality or Extinction" 3441: 3123: 3121: 3119: 2645:of 1956 are widely considered the "birth of AI". ( 2423:the possibility of artificial minds (for example, 1410:approach to the study of the mind. The example of 1094:to play as pretending to be someone they are not. 586:considered the standard philosophical question of 520:prefigures aspects of the Turing test in his 1637 6410:in a sentence—such as "he", "she" or "it"—refers. 5114:. New Haven & London: Yale University Press. 4413:The Imitation Game: The New Frontline of Security 2196: 2194: 1382:Consciousness vs. the simulation of consciousness 856:. The Cambridge Center for Behavioral Studies in 6386:, vol. 316, no. 3 (March 2017), pp. 58–63. 5481:(2nd ed.), Natick, MA: A. K. Peters, Ltd., 4886:"Is It An AI Chatbot Or A Human? 32% Can't Tell" 1197:Emphasis on emotional and aesthetic intelligence 1098:Should the interrogator know about the computer? 6519:Why The Turing Test is AI's Biggest Blind Alley 6485:– How accurate could the Turing test really be? 6300:Machines and Thought: The Legacy of Alan Turing 5360:Philosophy of Mind: A Contemporary Introduction 4992:Mind As Machine: A History of Cognitive Science 3366:Proceedings of the National Academy of Sciences 1441: 1209:Given the status of human sexual dimorphism as 554: 528: 6561:. Chedd-Angier Production Company. 1991–1992. 6541:New York Times essays on machine intelligence 6394:prowess, there cannot be one ultimate test of 5613:Saygin, A. P.; Cicekli, I.; Akman, V. (2000), 5039:(2003), Moor, James (ed.), "The Turing Test", 4634:"A computational extension to the Turing Test" 3949:"A computational extension to the Turing Test" 3641:have it seized upon by three college-age women 3168:. Chedd-Angier Production Company. 1993–1994. 2613:. New York: Bloomsbury Academic. p. 114. 1310:Human intelligence vs. intelligence in general 874:Artificial Linguistic Internet Computer Entity 6601: 6469:The Turing Test – an Opera by Julian Wagstaff 4545: 4098: 4071: 3880: 3736: 3691: 2313: 2278: 2147: 2145: 1752: 768: 440:in 1950, is a test of a machine's ability to 400: 8: 6574:Computer Science Unplugged teaching activity 4761:"Could you tell if someone was human or AI?" 3833: 2794: 799:") continue to fool people. "CyberLover", a 4310: 4198:Warwick, Kevin; Shah, Huma (4 March 2017). 4128:"The Philosophy of Artificial Intelligence" 1793:It is not possible to test humans this way. 6608: 6594: 6586: 6416:"The Status and Future of the Turing Test" 5596:Artificial Intelligence: A Modern Approach 5593:Russell, Stuart J.; Norvig, Peter (2010), 5576:Artificial Intelligence: A Modern Approach 4665:Journal of Logic, Language and Information 4480: 3910:Journal of Logic, Language and Information 3563: 3551: 3018:Argument against the Chinese Room Argument 2847: 2830: 2156: 407: 393: 38: 6281: 6053: 5995: 5977: 5941: 5693: 5641: 5499:, Dordrecht: Kluwer Academic Publishers, 5302: 5272: 4835: 4676: 4476: 4454: 4173: 4054: 3992: 3921: 3715: 3539: 3508: 3401: 2658: 2473: 2390: 2342: 1835:which is a test whether a computer-based 889:Artificial Conversational Entities (ACE)s 5807:print of the article. See also Searle's 4484: 3575: 3480: 2931:"Online Love Seerkers Warned Flirt Bots" 2682: 2670: 2406:For an example of property dualism, see 1313: 479:would comment on the Turing test in his 5960:"Lessons from a Restricted Turing Test" 5803:Page numbers above refer to a standard 5391:, Cambridge, Massachusetts: MIT Press, 3972:Shane Legg & Marcus Hutter (2007), 3679: 3516: 3468: 3429: 3146: 3131: 3127: 3088: 3076: 2646: 2129: 1638:czar of Google, stated that there were 682:researchers that included Alan Turing. 46: 6778:Computer-related introductions in 1950 5341:Artificial Intelligence: The Very Idea 4947:AISB 2008 Symposium on the Turing Test 4909: 4132:What has AI in Common with Philosophy? 4110: 4083: 3892: 3706:, under "Critique of the New Problem". 3703: 3592: 3527: 3504: 3064: 2961: 2859: 2818: 2806: 2779: 2758: 2746: 2717: 2694: 2301: 2274: 2259: 2232:. The Alan Turing Internet Scrapbook. 2200:Oppy, Graham & Dowe, David (2011) 2185: 2168: 2152: 2137: 2037:List of things named after Alan Turing 1677:Another variation is described as the 700: 6768:Philosophy of artificial intelligence 6365:from the original on 15 February 2017 5914:from the original on 10 February 2023 5343:, Cambridge, Massachusetts: MIT Press 3160:"Turing test, on season 4, episode 3" 2871: 2569: 2567: 2448:(2001), "Language, Truth and Logic", 2427:), any more than dualism necessarily 2337:. IEEE Publishing. pp. 155–160. 1514:philosophy of artificial intelligence 1362:Some intelligent behaviour is inhuman 1326:Some human behaviour is unintelligent 1204:a more recent approach to the subject 1135:philosophy of artificial intelligence 728:version, which Turing discussed in a 473:philosophy of artificial intelligence 7: 6696:Computing Machinery and Intelligence 6569:from the original on 1 January 2006. 6538:that learns from and imitates humans 5717:, Dordrecht, Netherlands: Springer, 5671: 4364:from the original on 3 December 2018 4298: 3512: 3492: 3456: 3176:from the original on 1 January 2006. 2899:Withers, Steven (11 December 2007), 2547:"A Voyage to Brobdingnag. Chapter 3" 2431:the possibility. (See, for example, 2372:from the original on 26 January 2021 1755:, and does not require emulation of 741:Computing Machinery and Intelligence 697:Computing Machinery and Intelligence 454:Computing Machinery and Intelligence 6703:The Chemical Basis of Morphogenesis 6499:Stanford Encyclopedia of Philosophy 6349:"'If Not Turing's Test, Then What?" 6249:, Oxford: Oxford University Press, 6195:, Oxford: Oxford University Press, 3815:from the original on 1 January 2022 3805:"What Comes After the Turing Test?" 3630:from the original on 19 August 2011 2911:from the original on 4 October 2017 2701:Evans, A. D. J.; Robertson (1968), 2213:Stanford Encyclopedia of Philosophy 1211:one of the most ancient of subjects 6763:History of artificial intelligence 6682:Systems of Logic Based on Ordinals 6078:Sundman, John (26 February 2003), 6020:from the original on 17 March 2008 5362:, London and New York: Routledge, 4614:from the original on 31 March 2019 4528:from the original on 23 March 2019 4420:from the original on 23 March 2019 4392:from the original on 23 March 2019 4336:from the original on 23 March 2019 3757:from the original on 23 March 2019 2941:from the original on 24 April 2010 2929:Williams, Ian (10 December 2007), 1969:Artificial intelligence in fiction 662:Alan Turing and the Imitation Game 14: 4978:Clinical Seminars and Four Papers 4729:Alex_Pasternack (18 April 2011). 4632:D L Dowe & A R Hajek (1997), 4156:Brynjolfsson, Erik (1 May 2022). 4138:from the original on 5 April 2019 3947:D L Dowe & A R Hajek (1997), 3784:from the original on 25 June 2017 3778:"Art and Artificial Intelligence" 3261:from the original on 13 June 2022 3230:from the original on 11 June 2022 3036:Why the Chinese Room Doesn't Work 2419:Noting that materialism does not 2236:from the original on 3 April 2019 1673:Subject-matter expert Turing test 1667:Subject matter expert Turing test 1493:that they can fool other pigeons. 5324:from the original on 6 July 2011 4810:Biever, Celeste (25 July 2023). 4708:Hernandez-Orallo & Dowe 2010 4608:Canadian Artificial Intelligence 3442:Saygin, Roberts & Beber 2008 3280:Biever, Celeste (25 July 2023). 3199:from the original on 9 June 2022 3015:Rehman, Warren. (19 July 2009), 1831:proposed in 2011 by film critic 1814:Solomonoff's inductive inference 1337:or, simply, a high frequency of 6402:. "irtually every sentence is 6136:McGill-Queen's University Press 5389:The Age of Intelligent Machines 3727:"These six disciplines," write 1851:, in 2023 the research company 1743:Minimum intelligent signal test 1737:Minimum intelligent signal test 1572:Reverse Turing test and CAPTCHA 865: 674:, an informal group of British 75:Artificial general intelligence 6513:Bet between Kapor and Kurzweil 3776:Smith, G. W. (27 March 2015). 2695:"Intelligent Machinery" (1948) 2180:Turing originally suggested a 1949:, and consciousness scientist 1525:The Language-centric Objection 804:collect their personal data." 1: 6558:Scientific American Frontiers 5766:Behavioral and Brain Sciences 5704:10.1016/S0378-2166(02)80001-7 5615:"Turing Test: 50 Years Later" 5274:10.1080/00033790.2023.2234912 4733:. Motherboard. Archived from 4227:10.1080/0952813X.2015.1132273 3614:Thompson, Clive (July 2005). 3218:Nitasha Tiku (11 June 2022). 3165:Scientific American Frontiers 2901:"Flirty Bot Passes for Human" 2160: 2105:(fictitious Turing test from 2032:Hard problem of consciousness 1994:Computer game bot Turing Test 1827:The Turing test inspired the 1757:unintelligent human behaviour 1346:This objection was raised by 442:exhibit intelligent behaviour 5824:, Information Science, IGI, 5762:"Minds, Brains and Programs" 5064:, New York, NY: BasicBooks, 5030:10.1016/0004-3702(72)90049-5 4980:, Abingdon: Fleetwood Press. 4270:10.1080/0952813X.2014.921734 4056:10.1016/j.artint.2010.09.006 3860:10.1080/0952813X.2014.921734 3803:Marcus, Gary (9 June 2014). 3749:Urban, Tim (February 2015). 3249:Jeremy Kahn (13 June 2022). 3187:Dan Williams (9 June 2022). 2326:Swiechowski, Maciej (2020). 1599:Carrying this idea forward, 1532:multiple intelligence theory 951:. Celeste Biever wrote in a 575:(or, at the very least, has 546:formulates in his 1746 book 29:Turing test (disambiguation) 6507:Turing Test: 50 Years Later 5958:Shieber, Stuart M. (1994), 5902:Shah, Huma (5 April 2011), 5522:, Oxford University Press, 5080:Philosophy & Technology 4759:Key, Alys (21 April 2023). 3033:Thornley, David H. (1997), 2519:Amini, Majid (1 May 2020). 2277:, pp. 442–454 and see 1964:Natural language processing 1117:Tractability and simplicity 824:Minds, Brains, and Programs 647:The Adventures of Pinocchio 110:Natural language processing 6794: 6758:Human–computer interaction 6114:Cambridge University Press 5376:Hinshelwood, R.D. (2001), 5304:10.1007/s11023-022-09616-8 5092:10.1007/s13347-022-00561-z 4837:10.1038/d41586-023-02361-7 4456:10.1007/s11406-022-00480-5 4072:Russell & Norvig (2003 3735:, "represent most of AI." 3306:10.1038/d41586-023-02361-7 2609:Wansbrough, Aleks (2021). 2279:Russell & Norvig (2003 1740: 1689:"Low-level" cognition test 1670: 1659:language and systems that 1575: 1391: 1385: 930: 898: 845: 811: 567:According to dualism, the 535:Here Descartes notes that 163:Hybrid intelligent systems 85:Recursive self-improvement 18: 6623: 6269:Communications of the ACM 6104:Thomas, Peter J. (1995), 5965:Communications of the ACM 5886:10.1007/s11023-010-9219-6 5858:10.1108/03684921011036178 5778:10.1017/S0140525X00005756 5731:10.1007/978-1-4020-6710-5 5539:The Journal of Philosophy 5495:Moor, James, ed. (2003), 5435:Communications of the ACM 5253:10.1080/02691729408578758 4560:Communications of the ACM 4546:Russell & Norvig 2010 4329:Breaking a Visual CAPTCHA 4099:Russell & Norvig 2003 4011:10.1007/s11023-007-9079-x 3881:Saygin & Cicekli 2002 3737:Russell & Norvig 2003 3692:Saygin & Cicekli 2002 2507:How to Pass a Turing Test 2314:Russell & Norvig 2003 2113:Winograd Schema Challenge 2088:Technological singularity 1939:Baroness Susan Greenfield 1730:Communications of the ACM 1724:Electronic health records 1444:concerned in this paper. 1141:Breadth of subject matter 1019:whether a computer could 593:Language, Truth and Logic 6228:10.1093/mind/LIX.236.433 5225:10.1093/mind/xcix.393.53 5106:Descartes, René (1996). 3834:Shah & Warwick 2010j 3106:"Artificial Stupidity". 2795:Shah & Warwick 2010a 2545:Swift, Jonathan (1726). 1909:In parallel to the 2008 1487:Aeronautical engineering 1353:in an article entitled " 1278:Naïveté of interrogators 1105:Gricean maxim violations 769:Naïveté of interrogators 761:Rogerian psychotherapist 504:Philosophical background 458:University of Manchester 432:, originally called the 287:Artificial consciousness 6432:10.1023/A:1011218925467 6414:Moor, James H. (2001), 6347:Cohen, Paul R. (2006), 6304:Oxford University Press 6166:10.1023/A:1011254505902 6130:Swirski, Peter (2000), 6046:10.1023/A:1011242120015 5634:10.1023/A:1011288000451 5552:10.5840/jphil2013110722 5408:The Singularity is Near 5163:, New York: MIT Press, 5017:Artificial Intelligence 4998:Oxford University Press 4927:, University of Reading 4687:10.1023/A:1008367325700 4410:Ghosemajumder, Shuman, 4043:Artificial Intelligence 3932:10.1023/A:1008367325700 3616:"The Other Turing Test" 3386:10.1073/pnas.2313925121 2998:10.1023/A:1008255830248 2705:, University Park Press 2703:Cybernetics: Key Papers 2576:Science Fiction Studies 2505:Rapaport, W.J. (2003). 2226:"The Turing Test, 1950" 2159:, p. 2). See also 737:artificial intelligence 577:non-physical properties 523:Discourse on the Method 456:" while working at the 158:Evolutionary algorithms 48:Artificial intelligence 6080:"Artificial stupidity" 5405:Kurzweil, Ray (2005), 4439:Schwaninger, Arthur C. 2063:Problem of other minds 1945:, Turing's biographer 1771:The organisers of the 1728:A letter published in 1458: 1446: 1394:Synthetic intelligence 1318: 1083: 1075: 1057: 1013: 995: 987: 970: 880:won in 2005 and 2006. 725: 693: 558: 549:Pensées philosophiques 533: 425: 59: 6720:Legacy of Alan Turing 6689:Intelligent Machinery 6675:On Computable Numbers 6530:11 April 2005 at the 6283:10.1145/365153.365168 6006:10.1145/175208.175217 5943:10.1145/141420.141423 5682:Journal of Pragmatics 5448:10.1145/175208.175218 5194:10.1145/602382.602400 5178:Feigenbaum, Edward A. 3651:23 March 2019 at the 3509:Hayes & Ford 1995 2643:Dartmouth conferences 2207:20 March 2012 at the 2103:Voight-Kampff machine 1915:University of Reading 1849:Large Language Models 1807:Kolmogorov complexity 1753:anthropomorphism bias 1679:subject-matter expert 1505:, or a sophisticated 1457:GPT-3 talkbot attempt 1456: 1317: 1235:Witness: It wouldn't 1079: 1070: 1052: 1001: 992: 983: 967: 949:large language models 720: 688: 582:In 1936, philosopher 481:Chinese room argument 422: 58: 6576:for the Turing test. 5291:Minds & Machines 4479:, pp. 503–505, 4175:10.1162/daed_a_01915 3130:, p. 10–11 and 2316:, pp. 2–3, 948. 2058:Philosophical zombie 2019:Graphics Turing Test 1999:Dead Internet theory 1872:University of Sussex 1847:Taking advantage of 1632:Shuman Ghosemajumder 1355:artificial stupidity 895:Google LaMDA chatbot 447:answers to questions 100:General game playing 27:For other uses, see 6628:Turing completeness 6383:Scientific American 5988:1994cmp.lg....4002S 5930:ACM SIGART Bulletin 5723:2009pttt.book.....E 5358:Heil, John (1998), 5241:Social Epistemology 4828:2023Natur.619..686B 4737:on 6 September 2011 4219:2017JETAI..29..287W 4003:2007arXiv0712.3329L 3883:, pp. 227–258. 3378:2024PNAS..12113925M 3340:humsci.stanford.edu 3298:2023Natur.619..686B 2466:1936Natur.138..823G 2136:Image adapted from 2068:Reverse engineering 1905:2008 AISB Symposium 1578:Reverse Turing test 1061:response-dependence 619:Stanley G. Weinbaum 600:Cultural background 516:views of the mind. 252:Machine translation 168:Systems integration 105:Knowledge reasoning 42:Part of a series on 6420:Minds and Machines 6306:, pp. 53–62, 6264:Weizenbaum, Joseph 6154:Minds and Machines 6034:Minds and Machines 5873:Minds and Machines 5674:, pp. 23–78). 5622:Minds and Machines 5567:Russell, Stuart J. 5479:Machines Who Think 5426:Loebner, Hugh Gene 5182:Journal of the ACM 4986:Boden, Margaret A. 4924:Loebner Prize 2008 4518:Gent, Edd (2014), 3981:Minds and Machines 3372:(9): e2313925121. 2986:Minds and Machines 1843:Social Turing Game 1653:Arthur Schwaninger 1475:object recognition 1459: 1319: 1304:confederate effect 1123:philosophy of mind 996: 981:Turing then asks: 971: 836:philosophy of mind 607:Gulliver's Travels 426: 60: 22:The Imitation Game 6773:1950 in computing 6735: 6734: 6494:"The Turing test" 6331:978-9972-2885-1-7 6313:978-0-19-823876-8 6256:978-0-19-825080-7 6202:978-0-19-825080-7 6145:978-0-7735-2078-3 6123:978-0-521-45302-8 5831:978-1-60566-354-8 5792:on 23 August 2000 5740:978-1-4020-9624-2 5606:978-0-13-604259-4 5529:978-0-14-014534-2 5506:978-1-4020-1205-1 5475:McCorduck, Pamela 5418:978-0-670-03384-3 5411:, Penguin Books, 5398:978-0-262-61079-7 5369:978-0-415-13060-8 5261:Annals of Science 5209:French, Robert M. 5170:978-0-06-090613-9 5143:978-2-0807-1249-3 5121:978-0-300-06772-9 5071:978-0-465-02997-6 5050:978-1-4020-1205-1 5007:978-0-19-924144-6 4822:(7971): 686–689. 4497:French, Robert M. 4049:(18): 1508–1539, 3729:Stuart J. Russell 3665:Colby et al. 1972 3292:(7971): 686–689. 3134:, amongst others. 2887:Colby et al. 1972 2620:978-1-5013-5639-1 2551:en.wikisource.org 2525:openurl.ebsco.com 2485:978-0-334-04122-1 2354:978-83-955416-7-4 2344:10.15439/2020F126 2078:Simulated reality 2048:Mind-body problem 1943:Selmer Bringsjord 1887:Joseph Weizenbaum 1865:Turing Colloquium 1837:synthesised voice 1704:Total Turing test 1698:cognitive science 1685:in a 2003 paper. 1683:Edward Feigenbaum 1601:R. D. Hinshelwood 1483:history of flight 905:In June 2022 the 753:Joseph Weizenbaum 652:E. T. A. Hoffmann 623:A Martian Odyssey 417: 416: 153:Bayesian networks 80:Intelligent agent 6785: 6653:Turing reduction 6610: 6603: 6596: 6587: 6570: 6503: 6490:Zalta, Edward N. 6451: 6373: 6372: 6370: 6334: 6316: 6294: 6285: 6259: 6238: 6222:(236): 433–460, 6205: 6176: 6148: 6126: 6111: 6100: 6099: 6097: 6088:, archived from 6066: 6057: 6028: 6027: 6025: 5999: 5981: 5954: 5945: 5922: 5921: 5919: 5909: 5896: 5860: 5834: 5800: 5799: 5797: 5788:, archived from 5751: 5706: 5697: 5669: 5668: 5666: 5660: 5654:, archived from 5645: 5619: 5609: 5589: 5562: 5532: 5509: 5491: 5470: 5469: 5467: 5462:on 14 March 2008 5458:, archived from 5421: 5401: 5380: 5372: 5354: 5344: 5332: 5331: 5329: 5307: 5306: 5285: 5276: 5255: 5235: 5204: 5173: 5146: 5125: 5113: 5102: 5074: 5053: 5032: 5010: 4995: 4981: 4963: 4962: 4961: 4959: 4954:on 18 March 2009 4942: 4936: 4935: 4934: 4932: 4919: 4913: 4907: 4901: 4900: 4898: 4896: 4881: 4875: 4874: 4872: 4870: 4856: 4850: 4849: 4839: 4807: 4801: 4800: 4798: 4796: 4782: 4776: 4775: 4773: 4771: 4765:Evening Standard 4756: 4750: 4749: 4744: 4742: 4726: 4720: 4717: 4711: 4705: 4699: 4698: 4680: 4660: 4654: 4653: 4651: 4649: 4640:, archived from 4629: 4623: 4622: 4621: 4619: 4600:McKinstry, Chris 4596: 4590: 4589: 4582: 4576: 4575: 4555: 4549: 4543: 4537: 4536: 4535: 4533: 4515: 4509: 4508: 4493: 4487: 4474: 4468: 4467: 4458: 4449:(3): 1437–1453, 4435: 4429: 4428: 4427: 4425: 4407: 4401: 4400: 4399: 4397: 4379: 4373: 4372: 4371: 4369: 4351: 4345: 4344: 4343: 4341: 4320: 4314: 4311:Hinshelwood 2001 4308: 4302: 4296: 4290: 4289: 4253: 4247: 4246: 4204: 4195: 4189: 4186: 4180: 4179: 4177: 4153: 4147: 4146: 4145: 4143: 4120: 4114: 4108: 4102: 4096: 4087: 4081: 4075: 4069: 4063: 4060: 4058: 4037: 4035: 4033: 4027: 4021:, archived from 3996: 3978: 3968: 3966: 3964: 3955:, archived from 3943: 3925: 3902: 3896: 3890: 3884: 3878: 3872: 3871: 3843: 3837: 3831: 3825: 3824: 3822: 3820: 3800: 3794: 3793: 3791: 3789: 3773: 3767: 3766: 3764: 3762: 3753:. 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J. 2442: 2436: 2433:Property dualism 2417: 2411: 2404: 2398: 2388: 2382: 2381: 2379: 2377: 2371: 2346: 2332: 2323: 2317: 2311: 2305: 2299: 2282: 2272: 2263: 2257: 2246: 2245: 2243: 2241: 2222: 2216: 2198: 2189: 2178: 2172: 2166: 2157:Gonçalves (2023b 2149: 2140: 2134: 1496: 1159:natural language 808:The Chinese room 706: 526:when he writes: 463: 409: 402: 395: 316:Existential risk 138:Machine learning 39: 32: 25: 6793: 6792: 6788: 6787: 6786: 6784: 6783: 6782: 6738: 6737: 6736: 6731: 6708: 6662: 6619: 6614: 6551: 6532:Wayback Machine 6525:Jabberwacky.com 6488: 6483:The Turing Test 6465: 6460: 6413: 6368: 6366: 6346: 6342: 6340:Further reading 6337: 6332: 6319: 6314: 6302:, vol. 1, 6297: 6262: 6257: 6241: 6208: 6203: 6187: 6151: 6146: 6129: 6124: 6103: 6095: 6093: 6092:on 7 March 2008 6077: 6031: 6023: 6021: 5957: 5927: 5917: 5915: 5901: 5865: 5839: 5832: 5815: 5795: 5793: 5756: 5741: 5712: 5679: 5670:. 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4409: 4408: 4404: 4395: 4393: 4381: 4380: 4376: 4367: 4365: 4353: 4352: 4348: 4339: 4337: 4324:Malik, Jitendra 4322: 4321: 4317: 4309: 4305: 4297: 4293: 4255: 4254: 4250: 4202: 4197: 4196: 4192: 4187: 4183: 4155: 4154: 4150: 4141: 4139: 4122: 4121: 4117: 4109: 4105: 4097: 4090: 4082: 4078: 4070: 4066: 4040: 4031: 4029: 4028:on 18 June 2009 4025: 3976: 3971: 3962: 3960: 3959:on 28 June 2011 3946: 3907: 3903: 3899: 3891: 3887: 3879: 3875: 3845: 3844: 3840: 3832: 3828: 3818: 3816: 3802: 3801: 3797: 3787: 3785: 3775: 3774: 3770: 3760: 3758: 3748: 3747: 3743: 3726: 3722: 3714: 3710: 3702: 3698: 3690: 3686: 3678: 3671: 3663: 3659: 3653:Wayback Machine 3633: 3631: 3613: 3612: 3608: 3603: 3599: 3591: 3582: 3574: 3570: 3564:Gonçalves 2023b 3562: 3558: 3552:Gonçalves 2023a 3550: 3546: 3538: 3534: 3526: 3522: 3503: 3499: 3491: 3487: 3479: 3475: 3467: 3463: 3455: 3448: 3440: 3436: 3428: 3419: 3359: 3358: 3354: 3344: 3342: 3333: 3332: 3328: 3318: 3316: 3279: 3278: 3274: 3264: 3262: 3248: 3247: 3243: 3233: 3231: 3224:Washington Post 3217: 3216: 3212: 3202: 3200: 3186: 3185: 3181: 3158: 3157: 3153: 3145: 3138: 3126: 3117: 3105: 3104: 3095: 3087: 3083: 3075: 3071: 3063: 3059: 3054: 3050: 3032: 3025:on 19 July 2010 3014: 2980: 2972: 2968: 2960: 2953: 2944: 2942: 2928: 2927: 2923: 2914: 2912: 2898: 2897: 2893: 2885: 2878: 2870: 2866: 2858: 2854: 2848:Weizenbaum 1966 2846: 2837: 2831:Weizenbaum 1966 2829: 2825: 2817: 2813: 2805: 2801: 2793: 2786: 2778: 2765: 2757: 2753: 2745: 2741: 2731:DG Champernowne 2728: 2724: 2716: 2712: 2700: 2693: 2689: 2681: 2677: 2669: 2665: 2657: 2653: 2640: 2636: 2621: 2608: 2607: 2603: 2573: 2572: 2565: 2555: 2553: 2544: 2543: 2539: 2529: 2527: 2518: 2517: 2513: 2504: 2500: 2486: 2444: 2443: 2439: 2418: 2414: 2405: 2401: 2389: 2385: 2375: 2373: 2369: 2355: 2330: 2325: 2324: 2320: 2312: 2308: 2300: 2285: 2273: 2266: 2258: 2249: 2239: 2237: 2224: 2223: 2219: 2209:Wayback Machine 2202:The Turing Test 2199: 2192: 2179: 2175: 2164: 2150: 2143: 2135: 2131: 2127: 2122: 2009:Explanatory gap 1959: 1907: 1897:'s creation of 1867: 1862: 1845: 1825: 1803: 1769: 1749:Chris McKinstry 1745: 1739: 1726: 1714:computer vision 1706: 1691: 1675: 1669: 1648: 1584: 1576:Main articles: 1574: 1566: 1558:The Turing Trap 1551:By focusing on 1549: 1547:The Turing Trap 1540: 1527: 1494: 1451: 1396: 1390: 1384: 1339:typing mistakes 1312: 1280: 1264: 1199: 1186:Feigenbaum test 1143: 1119: 1114: 1100: 1030: 1028:Interpretations 962: 935: 929: 919:Washington Post 903: 897: 850: 844: 816: 810: 749: 747:ELIZA and PARRY 704: 664: 654:'s 1816 story " 602: 506: 501: 461: 413: 384: 383: 374: 366: 365: 341: 331: 330: 302:Control problem 282: 272: 271: 183: 173: 172: 133: 125: 124: 95:Computer vision 70: 33: 26: 19: 17: 12: 11: 5: 6791: 6789: 6781: 6780: 6775: 6770: 6765: 6760: 6755: 6750: 6740: 6739: 6733: 6732: 6730: 6729: 6728: 6727: 6716: 6714: 6710: 6709: 6707: 6706: 6699: 6692: 6685: 6678: 6670: 6668: 6664: 6663: 6661: 6660: 6655: 6650: 6648:Turing's proof 6645: 6643:Turing pattern 6640: 6638:Turing machine 6635: 6630: 6624: 6621: 6620: 6615: 6613: 6612: 6605: 6598: 6590: 6584: 6583: 6577: 6571: 6549: 6539: 6522: 6516: 6510: 6504: 6486: 6480: 6471: 6464: 6463:External links 6461: 6459: 6458: 6455:Warwick, Kevin 6452: 6411: 6400:disambiguation 6375: 6343: 6341: 6338: 6336: 6335: 6330: 6317: 6312: 6295: 6260: 6255: 6239: 6206: 6201: 6185: 6149: 6144: 6127: 6122: 6101: 6075: 6029: 5997:10.1.1.54.3277 5979:cmp-lg/9404002 5955: 5924: 5923: 5898: 5897: 5880:(3): 441–454, 5868:Warwick, Kevin 5862: 5861: 5852:(3): 449–465, 5842:Warwick, Kevin 5836: 5835: 5830: 5818:Warwick, Kevin 5813: 5809:original draft 5772:(3): 417–457, 5753: 5752: 5739: 5709: 5708: 5695:10.1.1.12.7834 5688:(3): 227–258, 5676: 5675: 5628:(4): 463–518, 5610: 5605: 5590: 5585: 5563: 5546:(7): 391–411, 5533: 5528: 5514:Penrose, Roger 5510: 5505: 5492: 5487: 5471: 5422: 5417: 5402: 5397: 5381: 5373: 5368: 5355: 5346: 5333: 5312:Harnad, Stevan 5308: 5286: 5267:(3): 359–389, 5256: 5247:(4): 314–326, 5236: 5219:(393): 53–65, 5205: 5174: 5169: 5147: 5142: 5126: 5120: 5103: 5075: 5070: 5054: 5049: 5037:Copeland, Jack 5033: 5011: 5006: 4982: 4972: 4970: 4967: 4965: 4964: 4937: 4914: 4902: 4876: 4851: 4802: 4777: 4751: 4721: 4712: 4700: 4678:10.1.1.44.8943 4671:(4): 447–466, 4655: 4624: 4591: 4577: 4550: 4538: 4510: 4488: 4477:McCorduck 2004 4469: 4430: 4402: 4374: 4354:Pachal, Pete, 4346: 4326:; Mori, Greg, 4315: 4303: 4291: 4264:(2): 123–135. 4248: 4213:(2): 287–297. 4190: 4181: 4168:(2): 272–287. 4148: 4124:McCarthy, John 4115: 4103: 4088: 4076: 4064: 4062: 4061: 4038: 3987:(4): 391–444, 3969: 3944: 3923:10.1.1.44.8943 3916:(4): 447–466, 3897: 3895:, p. 448. 3885: 3873: 3854:(2): 123–135. 3838: 3826: 3809:The New Yorker 3795: 3768: 3741: 3720: 3716:Haugeland 1985 3708: 3696: 3684: 3669: 3657: 3606: 3597: 3595:, p. 442. 3580: 3568: 3556: 3544: 3542:, p. 398. 3540:Proudfoot 2013 3532: 3530:, p. 431. 3520: 3497: 3485: 3473: 3461: 3446: 3434: 3417: 3352: 3326: 3272: 3241: 3210: 3179: 3151: 3136: 3115: 3093: 3081: 3069: 3067:, p. 479. 3057: 3048: 3046: 3045: 3029: 3028: 3011: 3010: 2992:(2): 199–226, 2966: 2951: 2921: 2891: 2889:, p. 220. 2876: 2874:, p. 370. 2864: 2862:, p. 112. 2852: 2835: 2823: 2811: 2809:, p. 446. 2799: 2784: 2782:, p. 434. 2763: 2751: 2739: 2722: 2720:, p. 412. 2710: 2708: 2707: 2687: 2675: 2663: 2659:McCorduck 2004 2651: 2634: 2619: 2601: 2582:(3): 430–449. 2563: 2537: 2511: 2498: 2484: 2437: 2412: 2399: 2391:Descartes 1996 2383: 2353: 2318: 2306: 2283: 2264: 2262:, p. 433. 2247: 2217: 2190: 2188:, p. 433) 2173: 2171:, p. 442) 2141: 2128: 2126: 2123: 2121: 2120: 2115: 2110: 2100: 2098:Uncanny valley 2095: 2093:Theory of mind 2090: 2085: 2080: 2075: 2070: 2065: 2060: 2055: 2050: 2045: 2042:Mark V. Shaney 2039: 2034: 2029: 2021: 2016: 2011: 2006: 2001: 1996: 1991: 1986: 1981: 1976: 1971: 1966: 1960: 1958: 1955: 1906: 1903: 1866: 1863: 1861: 1858: 1844: 1841: 1824: 1821: 1802: 1799: 1798: 1797: 1794: 1787: 1786: 1783: 1768: 1765: 1741:Main article: 1738: 1735: 1725: 1722: 1705: 1702: 1690: 1687: 1671:Main article: 1668: 1665: 1647: 1644: 1573: 1570: 1565: 1562: 1548: 1545: 1539: 1536: 1526: 1523: 1507:user interface 1464:Stuart Russell 1450: 1447: 1434:intentionality 1386:Main article: 1383: 1380: 1379: 1378: 1373: 1372: 1363: 1359: 1358: 1343: 1342: 1327: 1311: 1308: 1291:questioning." 1279: 1276: 1263: 1260: 1251: 1250: 1246: 1245: 1241: 1240: 1232: 1231: 1224: 1223: 1219: 1218: 1198: 1195: 1148:John Haugeland 1142: 1139: 1118: 1115: 1113: 1110: 1099: 1096: 1029: 1026: 961: 958: 931:Main article: 928: 925: 899:Main article: 896: 893: 846:Main article: 843: 840: 827:proposed the " 821:'s 1980 paper 812:Main article: 809: 806: 748: 745: 663: 660: 612:Jonathan Swift 601: 598: 564:at that time. 518:René Descartes 505: 502: 500: 497: 475:. Philosopher 466:imitation game 434:imitation game 424:determination. 415: 414: 412: 411: 404: 397: 389: 386: 385: 382: 381: 375: 372: 371: 368: 367: 364: 363: 358: 353: 348: 342: 337: 336: 333: 332: 329: 328: 323: 318: 313: 308: 299: 294: 289: 283: 278: 277: 274: 273: 270: 269: 264: 259: 254: 249: 248: 247: 237: 232: 227: 226: 225: 220: 215: 205: 200: 198:Earth sciences 195: 190: 188:Bioinformatics 184: 179: 178: 175: 174: 171: 170: 165: 160: 155: 150: 145: 140: 134: 131: 130: 127: 126: 123: 122: 117: 112: 107: 102: 97: 92: 87: 82: 77: 71: 66: 65: 62: 61: 51: 50: 44: 43: 15: 13: 10: 9: 6: 4: 3: 2: 6790: 6779: 6776: 6774: 6771: 6769: 6766: 6764: 6761: 6759: 6756: 6754: 6751: 6749: 6746: 6745: 6743: 6726: 6723: 6722: 6721: 6718: 6717: 6715: 6711: 6704: 6700: 6697: 6693: 6690: 6686: 6683: 6679: 6676: 6672: 6671: 6669: 6665: 6659: 6656: 6654: 6651: 6649: 6646: 6644: 6641: 6639: 6636: 6634: 6633:Turing degree 6631: 6629: 6626: 6625: 6622: 6618: 6611: 6606: 6604: 6599: 6597: 6592: 6591: 6588: 6581: 6578: 6575: 6572: 6568: 6564: 6560: 6559: 6554: 6550: 6548: 6544: 6540: 6537: 6533: 6529: 6526: 6523: 6521:by Blay Witby 6520: 6517: 6514: 6511: 6508: 6505: 6501: 6500: 6495: 6491: 6487: 6484: 6481: 6479: 6475: 6472: 6470: 6467: 6466: 6462: 6456: 6453: 6449: 6445: 6441: 6437: 6433: 6429: 6425: 6421: 6417: 6412: 6409: 6405: 6401: 6397: 6393: 6389: 6385: 6384: 6379: 6376: 6364: 6360: 6356: 6355: 6350: 6345: 6344: 6339: 6333: 6327: 6323: 6318: 6315: 6309: 6305: 6301: 6296: 6293: 6289: 6284: 6279: 6275: 6271: 6270: 6265: 6261: 6258: 6252: 6248: 6244: 6240: 6237: 6233: 6229: 6225: 6221: 6217: 6216: 6211: 6207: 6204: 6198: 6194: 6190: 6186: 6184: 6183:1-4020-1205-5 6180: 6175: 6171: 6167: 6163: 6159: 6155: 6150: 6147: 6141: 6137: 6133: 6128: 6125: 6119: 6115: 6110: 6109: 6102: 6091: 6087: 6086: 6081: 6076: 6074: 6073:1-4020-1205-5 6070: 6065: 6061: 6056: 6051: 6047: 6043: 6039: 6035: 6030: 6019: 6015: 6011: 6007: 6003: 5998: 5993: 5989: 5985: 5980: 5975: 5971: 5967: 5966: 5961: 5956: 5953: 5949: 5944: 5939: 5935: 5931: 5926: 5925: 5913: 5908: 5907: 5900: 5899: 5895: 5891: 5887: 5883: 5879: 5875: 5874: 5869: 5864: 5863: 5859: 5855: 5851: 5847: 5843: 5838: 5837: 5833: 5827: 5823: 5819: 5814: 5812: 5810: 5806: 5791: 5787: 5783: 5779: 5775: 5771: 5767: 5763: 5759: 5755: 5754: 5750: 5746: 5742: 5736: 5732: 5728: 5724: 5720: 5716: 5711: 5710: 5705: 5701: 5696: 5691: 5687: 5683: 5678: 5677: 5673: 5657: 5653: 5649: 5644: 5639: 5635: 5631: 5627: 5623: 5616: 5611: 5608: 5602: 5598: 5597: 5591: 5588: 5586:0-13-790395-2 5582: 5578: 5577: 5572: 5571:Norvig, Peter 5568: 5564: 5561: 5557: 5553: 5549: 5545: 5541: 5540: 5534: 5531: 5525: 5521: 5520: 5515: 5511: 5508: 5502: 5498: 5493: 5490: 5488:1-56881-205-1 5484: 5480: 5476: 5472: 5461: 5457: 5453: 5449: 5445: 5441: 5437: 5436: 5431: 5430:"In response" 5427: 5423: 5420: 5414: 5410: 5409: 5403: 5400: 5394: 5390: 5386: 5385:Kurzweil, Ray 5382: 5379: 5374: 5371: 5365: 5361: 5356: 5352: 5347: 5342: 5338: 5334: 5323: 5319: 5318: 5313: 5309: 5305: 5300: 5296: 5292: 5287: 5284: 5280: 5275: 5270: 5266: 5262: 5257: 5254: 5250: 5246: 5242: 5237: 5234: 5230: 5226: 5222: 5218: 5214: 5210: 5206: 5203: 5199: 5195: 5191: 5187: 5183: 5179: 5175: 5172: 5166: 5162: 5161: 5157: 5152: 5148: 5145: 5139: 5135: 5131: 5127: 5123: 5117: 5112: 5111: 5104: 5101: 5097: 5093: 5089: 5085: 5081: 5076: 5073: 5067: 5063: 5059: 5055: 5052: 5046: 5042: 5038: 5034: 5031: 5027: 5023: 5019: 5018: 5012: 5009: 5003: 4999: 4994: 4993: 4987: 4983: 4979: 4974: 4973: 4968: 4953: 4949: 4948: 4941: 4938: 4926: 4925: 4918: 4915: 4912:, p. 53. 4911: 4906: 4903: 4891: 4887: 4880: 4877: 4865: 4861: 4855: 4852: 4847: 4843: 4838: 4833: 4829: 4825: 4821: 4817: 4813: 4806: 4803: 4791: 4790:New Scientist 4787: 4781: 4778: 4766: 4762: 4755: 4752: 4748: 4736: 4732: 4725: 4722: 4716: 4713: 4709: 4704: 4701: 4696: 4692: 4688: 4684: 4679: 4674: 4670: 4666: 4659: 4656: 4643: 4639: 4635: 4628: 4625: 4613: 4609: 4605: 4601: 4595: 4592: 4587: 4581: 4578: 4573: 4569: 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3779: 3772: 3769: 3756: 3752: 3745: 3742: 3738: 3734: 3730: 3724: 3721: 3717: 3712: 3709: 3705: 3700: 3697: 3693: 3688: 3685: 3681: 3676: 3674: 3670: 3666: 3661: 3658: 3654: 3650: 3647: 3642: 3629: 3625: 3621: 3617: 3610: 3607: 3601: 3598: 3594: 3589: 3587: 3585: 3581: 3577: 3576:Danziger 2022 3572: 3569: 3565: 3560: 3557: 3553: 3548: 3545: 3541: 3536: 3533: 3529: 3524: 3521: 3518: 3514: 3510: 3506: 3501: 3498: 3494: 3489: 3486: 3482: 3481:Sterrett 2000 3477: 3474: 3471:, p. 99. 3470: 3465: 3462: 3458: 3453: 3451: 3447: 3443: 3438: 3435: 3431: 3426: 3424: 3422: 3418: 3413: 3409: 3404: 3399: 3395: 3391: 3387: 3383: 3379: 3375: 3371: 3367: 3363: 3356: 3353: 3341: 3337: 3330: 3327: 3315: 3311: 3307: 3303: 3299: 3295: 3291: 3287: 3283: 3276: 3273: 3260: 3256: 3252: 3245: 3242: 3229: 3225: 3221: 3214: 3211: 3198: 3194: 3193:The Economist 3190: 3183: 3180: 3175: 3171: 3167: 3166: 3161: 3155: 3152: 3149:, p. 77. 3148: 3143: 3141: 3137: 3133: 3129: 3124: 3122: 3120: 3116: 3111: 3110: 3109:The Economist 3102: 3100: 3098: 3094: 3090: 3085: 3082: 3078: 3073: 3070: 3066: 3061: 3058: 3052: 3049: 3042: 3038: 3037: 3031: 3030: 3024: 3020: 3019: 3013: 3012: 3007: 3003: 2999: 2995: 2991: 2987: 2983: 2982:Hauser, Larry 2979: 2978: 2977:. A few are: 2976: 2970: 2967: 2963: 2958: 2956: 2952: 2940: 2936: 2932: 2925: 2922: 2910: 2906: 2902: 2895: 2892: 2888: 2883: 2881: 2877: 2873: 2868: 2865: 2861: 2856: 2853: 2850:, p. 42. 2849: 2844: 2842: 2840: 2836: 2833:, p. 37. 2832: 2827: 2824: 2820: 2815: 2812: 2808: 2803: 2800: 2796: 2791: 2789: 2785: 2781: 2776: 2774: 2772: 2770: 2768: 2764: 2760: 2755: 2752: 2748: 2743: 2740: 2736: 2735:Alick Glennie 2732: 2726: 2723: 2719: 2714: 2711: 2704: 2699: 2698: 2696: 2691: 2688: 2684: 2683:Copeland 2003 2679: 2676: 2672: 2671:Copeland 2003 2667: 2664: 2661:, p. 95. 2660: 2655: 2652: 2649:, p. 49) 2648: 2644: 2638: 2635: 2630: 2626: 2622: 2616: 2612: 2605: 2602: 2597: 2593: 2589: 2585: 2581: 2577: 2570: 2568: 2564: 2552: 2548: 2541: 2538: 2526: 2522: 2515: 2512: 2508: 2502: 2499: 2495: 2491: 2487: 2481: 2476: 2471: 2467: 2463: 2459: 2455: 2451: 2447: 2441: 2438: 2434: 2430: 2426: 2425:Roger Penrose 2422: 2416: 2413: 2409: 2403: 2400: 2396: 2392: 2387: 2384: 2368: 2364: 2360: 2356: 2350: 2345: 2340: 2336: 2329: 2322: 2319: 2315: 2310: 2307: 2303: 2298: 2296: 2294: 2292: 2290: 2288: 2284: 2280: 2276: 2271: 2269: 2265: 2261: 2256: 2254: 2252: 2248: 2235: 2231: 2230:turing.org.uk 2227: 2221: 2218: 2214: 2210: 2206: 2203: 2197: 2195: 2191: 2187: 2183: 2177: 2174: 2170: 2162: 2158: 2154: 2148: 2146: 2142: 2139: 2133: 2130: 2124: 2119: 2116: 2114: 2111: 2108: 2104: 2101: 2099: 2096: 2094: 2091: 2089: 2086: 2084: 2081: 2079: 2076: 2074: 2071: 2069: 2066: 2064: 2061: 2059: 2056: 2054: 2053:Mirror neuron 2051: 2049: 2046: 2043: 2040: 2038: 2035: 2033: 2030: 2027: 2026: 2022: 2020: 2017: 2015: 2014:Functionalism 2012: 2010: 2007: 2005: 2002: 2000: 1997: 1995: 1992: 1990: 1987: 1985: 1982: 1980: 1977: 1975: 1972: 1970: 1967: 1965: 1962: 1961: 1956: 1954: 1952: 1948: 1947:Andrew Hodges 1944: 1940: 1936: 1935:Kevin Warwick 1932: 1928: 1924: 1920: 1916: 1912: 1911:Loebner Prize 1904: 1902: 1900: 1896: 1895:Kenneth Colby 1892: 1888: 1884: 1880: 1879:competition. 1878: 1877:Loebner Prize 1873: 1864: 1859: 1857: 1854: 1850: 1842: 1840: 1838: 1834: 1830: 1822: 1820: 1817: 1815: 1810: 1808: 1800: 1795: 1792: 1791: 1790: 1784: 1781: 1780: 1779: 1776: 1774: 1766: 1764: 1762: 1758: 1754: 1750: 1744: 1736: 1734: 1731: 1723: 1721: 1719: 1715: 1711: 1710:Stevan Harnad 1703: 1701: 1699: 1695: 1694:Robert French 1688: 1686: 1684: 1680: 1674: 1666: 1664: 1662: 1658: 1654: 1645: 1643: 1641: 1640:cybercriminal 1637: 1633: 1629: 1625: 1621: 1617: 1612: 1609: 1605: 1602: 1597: 1594: 1593:Peter Swirski 1590: 1583: 1579: 1571: 1569: 1563: 1561: 1559: 1554: 1546: 1544: 1537: 1535: 1533: 1524: 1522: 1519: 1518:John McCarthy 1515: 1510: 1508: 1504: 1498: 1492: 1488: 1484: 1480: 1476: 1471: 1469: 1465: 1455: 1448: 1445: 1440: 1437: 1435: 1431: 1430:consciousness 1427: 1423: 1419: 1415: 1413: 1409: 1408:functionalist 1405: 1401: 1395: 1389: 1381: 1375: 1374: 1369: 1364: 1361: 1360: 1356: 1352: 1350: 1349:The Economist 1345: 1344: 1340: 1336: 1332: 1328: 1325: 1324: 1323: 1316: 1309: 1307: 1305: 1300: 1296: 1292: 1288: 1286: 1277: 1275: 1271: 1269: 1261: 1259: 1257: 1248: 1247: 1243: 1242: 1238: 1234: 1233: 1229: 1228: 1227: 1221: 1220: 1216: 1215: 1214: 1212: 1207: 1205: 1196: 1194: 1192: 1187: 1182: 1180: 1176: 1172: 1168: 1164: 1160: 1155: 1153: 1149: 1140: 1138: 1136: 1132: 1129:, and modern 1128: 1124: 1116: 1111: 1109: 1106: 1097: 1095: 1091: 1089: 1082: 1078: 1074: 1069: 1066: 1062: 1056: 1051: 1048: 1044: 1040: 1037: 1036: 1027: 1025: 1022: 1016: 1012: 1010: 1006: 1000: 991: 986: 982: 979: 975: 966: 959: 957: 954: 950: 947: 943: 939: 934: 926: 924: 921: 920: 914: 913: 912:The Economist 908: 902: 894: 892: 890: 887:programs, or 886: 881: 879: 875: 869: 867: 861: 859: 858:Massachusetts 855: 849: 848:Loebner Prize 842:Loebner Prize 841: 839: 837: 832: 830: 826: 825: 820: 815: 807: 805: 802: 798: 793: 791: 787: 786:schizophrenic 784: 780: 776: 775:Kenneth Colby 772: 770: 766: 762: 758: 754: 746: 744: 742: 738: 733: 731: 724: 719: 717: 712: 710: 702: 698: 692: 687: 683: 681: 677: 673: 669: 661: 659: 657: 653: 649: 648: 643: 642:Carlo Collodi 639: 635: 631: 630:Ancient Greek 626: 624: 620: 615: 613: 609: 608: 599: 597: 595: 594: 589: 585: 580: 578: 574: 570: 565: 563: 557: 553: 551: 550: 545: 544:Denis Diderot 541: 538: 532: 527: 525: 524: 519: 515: 511: 503: 498: 496: 494: 493:consciousness 490: 489:understanding 486: 482: 478: 474: 469: 467: 459: 455: 450: 448: 443: 439: 435: 431: 421: 410: 405: 403: 398: 396: 391: 390: 388: 387: 380: 377: 376: 370: 369: 362: 359: 357: 354: 352: 349: 347: 344: 343: 340: 335: 334: 327: 324: 322: 319: 317: 314: 312: 309: 307: 303: 300: 298: 295: 293: 290: 288: 285: 284: 281: 276: 275: 268: 265: 263: 260: 258: 255: 253: 250: 246: 245:Mental health 243: 242: 241: 238: 236: 233: 231: 228: 224: 221: 219: 216: 214: 211: 210: 209: 208:Generative AI 206: 204: 201: 199: 196: 194: 191: 189: 186: 185: 182: 177: 176: 169: 166: 164: 161: 159: 156: 154: 151: 149: 148:Deep learning 146: 144: 141: 139: 136: 135: 129: 128: 121: 118: 116: 113: 111: 108: 106: 103: 101: 98: 96: 93: 91: 88: 86: 83: 81: 78: 76: 73: 72: 69: 64: 63: 57: 53: 52: 49: 45: 41: 40: 37: 35: 30: 23: 6748:Turing tests 6667:Publications 6657: 6556: 6497: 6426:(1): 77–93, 6423: 6419: 6396:intelligence 6387: 6381: 6378:Marcus, Gary 6367:, retrieved 6358: 6352: 6321: 6299: 6276:(1): 36–45, 6273: 6267: 6246: 6243:Turing, Alan 6219: 6213: 6210:Turing, Alan 6192: 6189:Turing, Alan 6157: 6153: 6131: 6107: 6094:, retrieved 6090:the original 6083: 6037: 6033: 6022:, retrieved 5972:(6): 70–78, 5969: 5963: 5936:(4): 10–11, 5933: 5929: 5916:, retrieved 5905: 5877: 5871: 5866:Shah, Huma; 5849: 5845: 5840:Shah, Huma; 5821: 5816:Shah, Huma; 5802: 5794:, retrieved 5790:the original 5769: 5765: 5758:Searle, John 5714: 5685: 5681: 5663:, retrieved 5656:the original 5625: 5621: 5595: 5575: 5543: 5537: 5518: 5496: 5478: 5464:, retrieved 5460:the original 5442:(6): 79–82, 5439: 5433: 5407: 5388: 5377: 5359: 5350: 5340: 5326:, retrieved 5316: 5294: 5290: 5264: 5260: 5244: 5240: 5216: 5212: 5188:(1): 32–40, 5185: 5181: 5159: 5155: 5133: 5109: 5083: 5079: 5061: 5043:, Springer, 5040: 5021: 5015: 4991: 4977: 4956:, retrieved 4952:the original 4946: 4940: 4929:, retrieved 4923: 4917: 4905: 4893:. Retrieved 4889: 4884:Press, Gil. 4879: 4867:. Retrieved 4863: 4854: 4819: 4815: 4805: 4793:. Retrieved 4789: 4780: 4768:. Retrieved 4764: 4754: 4746: 4741:12 September 4739:. Retrieved 4735:the original 4724: 4715: 4703: 4668: 4664: 4658: 4646:, retrieved 4642:the original 4637: 4627: 4616:, retrieved 4607: 4594: 4580: 4563: 4559: 4553: 4548:, p. 3. 4541: 4530:, retrieved 4520: 4513: 4507:(393): 53–65 4504: 4500: 4491: 4472: 4446: 4442: 4433: 4422:, retrieved 4412: 4405: 4394:, retrieved 4384: 4382:Tung, Liam, 4377: 4366:, retrieved 4356: 4349: 4338:, retrieved 4328: 4318: 4306: 4294: 4261: 4257: 4251: 4210: 4206: 4193: 4184: 4165: 4161: 4151: 4140:, retrieved 4131: 4118: 4106: 4101:, p. 3. 4079: 4067: 4046: 4042: 4030:, retrieved 4023:the original 3984: 3980: 3961:, retrieved 3957:the original 3952: 3913: 3909: 3900: 3888: 3876: 3851: 3847: 3841: 3829: 3817:. Retrieved 3808: 3798: 3786:. Retrieved 3771: 3759:. Retrieved 3744: 3733:Peter Norvig 3723: 3718:, p. 8. 3711: 3699: 3687: 3680:Swirski 2000 3660: 3646:Full version 3639: 3634:10 September 3632:. Retrieved 3619: 3609: 3600: 3571: 3559: 3547: 3535: 3523: 3517:Dreyfus 1979 3500: 3488: 3476: 3469:Traiger 2000 3464: 3437: 3430:Traiger 2000 3369: 3365: 3355: 3343:. Retrieved 3339: 3329: 3317:. Retrieved 3289: 3285: 3275: 3263:. Retrieved 3254: 3244: 3232:. Retrieved 3223: 3213: 3201:. Retrieved 3192: 3182: 3163: 3154: 3147:Shieber 1994 3132:Shieber 1994 3128:Shapiro 1992 3107: 3089:Loebner 1994 3084: 3077:Sundman 2003 3072: 3060: 3051: 3041:the original 3035: 3023:the original 3017: 2989: 2985: 2975:Chinese room 2969: 2943:, retrieved 2934: 2924: 2913:, retrieved 2904: 2894: 2867: 2855: 2826: 2814: 2802: 2761:, p. 1. 2754: 2742: 2725: 2713: 2702: 2690: 2685:, p. 2. 2678: 2673:, p. 1. 2666: 2654: 2647:Crevier 1993 2637: 2610: 2604: 2579: 2575: 2554:. Retrieved 2550: 2540: 2528:. Retrieved 2524: 2514: 2501: 2453: 2449: 2440: 2428: 2420: 2415: 2402: 2386: 2374:. Retrieved 2334: 2321: 2309: 2238:. Retrieved 2229: 2220: 2212: 2176: 2132: 2107:Blade Runner 2106: 2044:(Usenet bot) 2023: 1951:Owen Holland 1923:John Barnden 1913:held at the 1908: 1881: 1868: 1846: 1826: 1818: 1811: 1804: 1788: 1777: 1773:Hutter Prize 1770: 1767:Hutter Prize 1746: 1729: 1727: 1707: 1692: 1676: 1660: 1656: 1649: 1613: 1606: 1598: 1589:Wilfred Bion 1585: 1567: 1552: 1550: 1541: 1528: 1511: 1499: 1472: 1468:Peter Norvig 1460: 1442: 1438: 1422:Chinese room 1416: 1404:behaviourist 1399: 1397: 1388:Chinese room 1367: 1347: 1330: 1320: 1301: 1297: 1293: 1289: 1281: 1272: 1268:intelligence 1265: 1252: 1225: 1208: 1200: 1183: 1156: 1151: 1144: 1131:neuroscience 1120: 1101: 1092: 1087: 1084: 1080: 1076: 1073:questioning. 1071: 1064: 1060: 1058: 1053: 1049: 1045: 1041: 1033: 1031: 1020: 1017: 1014: 1008: 1004: 1002: 997: 984: 980: 976: 972: 952: 936: 917: 910: 904: 882: 870: 862: 854:Hugh Loebner 851: 833: 829:Chinese room 822: 817: 814:Chinese room 794: 790:teleprinters 773: 764: 750: 734: 726: 721: 713: 694: 689: 684: 665: 645: 627: 616: 605: 603: 591: 581: 573:non-physical 566: 562:materialists 559: 555: 547: 542: 534: 529: 521: 507: 470: 465: 451: 433: 429: 427: 320: 292:Chinese room 181:Applications 36: 34: 6753:Alan Turing 6658:Turing test 6617:Alan Turing 6474:Turing test 6354:AI Magazine 6055:10057/10701 5918:20 December 5643:11693/24987 5328:17 December 5130:Diderot, D. 5024:: 199–221, 4910:Whitby 1996 4443:Philosophia 4424:31 December 4396:31 December 4368:31 December 4340:21 November 4142:26 February 4111:Turing 1950 4084:Turing 1950 3893:Turing 1950 3819:16 December 3739:, p. 3 3704:Turing 1950 3620:Issue 13.07 3593:Turing 1950 3528:Turing 1948 3505:Genova 1994 3065:Saygin 2000 2962:Searle 1980 2945:10 February 2915:10 February 2860:Thomas 1995 2819:Turing 1952 2807:Turing 1950 2780:Turing 1950 2759:Harnad 2004 2749:, p. . 2747:Turing 1948 2718:Turing 1948 2421:necessitate 2393:, pp. 2376:8 September 2302:Saygin 2000 2275:Turing 1950 2260:Turing 1950 2186:Turing 1950 2182:teleprinter 2169:Turing 1950 2153:Turing 1950 2138:Saygin 2000 2004:Explanation 1927:Mark Bishop 1883:Blay Whitby 1860:Conferences 1833:Roger Ebert 1636:click fraud 1418:John Searle 1285:Gary Marcus 1256:friendly AI 878:Jabberwacky 819:John Searle 709:definitions 680:electronics 676:cybernetics 656:The Sandman 588:other minds 584:Alfred Ayer 514:materialist 477:John Searle 438:Alan Turing 430:Turing test 321:Turing test 297:Friendly AI 68:Major goals 6742:Categories 6580:Wiki News: 6536:chatterbot 6160:(4): 561, 6040:(4): 541, 5846:Kybernetes 5672:Moor (2003 5320:, Klewer, 4969:References 4532:18 October 3780:. 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