Jump to content

Turing test

From Wikipedia, the free encyclopedia

This is an old revision of this page, as edited by Adam1213 (talk | contribs) at 07:38, 17 October 2008 (Undid revision 245752794 by 209.195.82.33 (talk)). The present address (URL) is a permanent link to this revision, which may differ significantly from the current revision.

For the Doctor Who novel named after the test, see The Turing Test (novel). For the opera named after the test, see under the composer, Julian Wagstaff.

The Turing test is a proposal for a test of a machine's ability to demonstrate intelligence. Described by Alan Turing in the 1950 paper "Computing Machinery and Intelligence," it proceeds as follows: a human judge engages in a natural language conversation with one human and one machine, each of which try to appear human; if the judge cannot reliably tell which is which, then the machine is said to pass the test. In order to test the machine's intelligence rather than its ability to render words into audio, the conversation is limited to a text-only channel such as a computer keyboard and screen (Turing originally suggested a teletype machine, one of the few text-only communication systems available in 1950).

The "standard interpretation" of the Turing Test, in which player C, the interrogator, is tasked with trying to determine which player - A or B - is a computer and which is a human. The interrogator is limited to only using the responses to written questions in order to make the determination

History

Philosophical background

While the field of artificial intelligence was founded in 1956,[1] its philosophical roots extend back considerably further. The question as to whether or not it is possible for machines to think has a long history, firmly entrenched in the distinction between dualist and materialist views of the mind. From the perspective of dualism, the mind is non-physical (or, at the very least, has non-physical properties[2]), and therefore cannot be explained in purely physical terms. The materialist perspective, on the other hand, argues that the mind can be explained physically, and thus leaves open the possibility of minds that are artificially produced.[3]

In 1936, philosopher A J Ayer considered the standard philosophical question of other minds: how do we know that other people have the same conscious experiences as we do? In his book Language, Truth and Logic 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'.[4] This suggestion is very similar to the Turing test. It is not certain that Ayer's popular philosophical classic was familiar to Turing.

Alan Turing

Researchers in Britain had been exploring "machine intelligence" for up to ten years prior to 1956. It was a common topic among the members of the Ratio Club, an informal group of British cybernetics and electronics researchers that included Alan Turing.[5]

Turing in particular had been tackling the notion of machine intelligence since at least 1941,[6] and one of the earliest known mentions of "computer intelligence" was made by Turing in 1947.[7] In Turing's report, "Intelligent Machinery", he investigated "the question of whether or not it is possible for machinery to show intelligent behaviour",[8] and as part of that investigation proposed what may be considered the forerunner to his later tests:

"It is not difficult to devise a paper machine which will play a not very bad game of chess. Now get three men as subjects for the experiment. A, B and C. 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 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."

— Turing 1948, p. 431

Thus by the time Turing published "Computing Machinery and Intelligence", he had been considering the possibility of machine intelligence for many years. This, however, was the first published paper[9] by Turing to focus exclusively on the notion.

Turing began his 1950 paper with the claim: "I propose to consider the question, 'Can machines think?'"[10] As Turing highlighted, the traditional approach to such a question is to start with definitions, defining both the terms machine and intelligence. Nevertheless, Turing chose not to do so. Instead he replaced the question with a new question, "which is closely related to it and is expressed in relatively unambiguous words".[10] In essence, Turing proposed to change the question from "Do machines think?" into "Can machines do what we (as thinking entities) can do?"[11] The advantage of the new question, Turing argued, was that it "drew a fairly sharp line between the physical and intellectual capacities of a man.[12]

To demonstrate this approach, Turing proposed a test that was inspired by a party game 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. Turing proposed recreating the imitation game as follows:

"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 think?'"

— Turing 1950, p. 434

Later in the paper he suggested an "equivalent" alternative formulation involving a judge conversing only with a computer and a man.[13]

While neither of these two formulations precisely match the version of the Turing Test that is more generally known today, a third version was proposed by Turing in 1952. In this version, which Turing discussed in a BBC radio broadcast, Turing proposes a jury which asks questions of a computer, and where the role of the computer is to make a significant proportion of the jury believe that it is really a man.[14]

Turing's paper considered nine common objections, which include all the major arguments against artificial intelligence that have been raised in the years since his paper was first published. (See Computing Machinery and Intelligence.)[15]

ELIZA, PARRY and the Chinese room

Blay Whitby lists four major turning points in the history of the Turing Test: the publication of "Computing Machinery and Intelligence" in 1950; the announcement of Joseph Weizenbaum's ELIZA in 1966; Kenneth Colby's creation of PARRY, which was first described in 1972; and the Turing Colloquium in 1990.[16]

ELIZA works by examining a user's typed comments for keywords. If a keyword is found, a rule is applied which transforms the user's comments and the resulting sentence is then returned. If a keyword is not found, ELIZA responds with either a generic response or by repeating one of the earlier comments.[17] In addition, Weizenbaum developed ELIZA to replicate the behavior of a Rogerian psychotherapist, allowing ELIZA to be "free to assume the pose of knowing almost nothing of the real world."[18] Due to 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 not human."[18] Thus ELIZA is claimed by many to be one of the programs (perhaps the first) that are able to pass the Turing Test.[19][18]

Colby's PARRY has been described as "ELIZA with attitude"[20] - it attempts to model the behavior of a paranoid schizophrenic, using a similar (if more advanced) approach to that employed by Weizenbaum. In order to help validate the work, PARRY was tested in the early 1970s using a variation of the Turing Test. A group of experienced psychiatrists analyzed a combination of real patients and computers running PARRY through teletype machines. 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.[21] The psychiatrists were only able to make the correct identification 48% of the time - a figure consistent with random guessing.[22]

While neither ELIZA nor PARRY were able to pass a strict Turing Test, they - and software like them - suggested that software might be written that was able to do so. More importantly, they suggested that such software might involve little more than databases and the application of simple rules. This led to John Searle's 1980 paper, "Minds, Brains, and Programs", in which he proposed an argument against the Turing Test. Searle described a thought experiment known as the Chinese room that highlighted what he saw as a fundamental misinterpretation of what the Turing Test could and could not prove: while software such as ELIZA might be able to pass the Turing Test, they might do so by simply manipulating symbols of which they have no understanding. And without understanding, they could not be described as "thinking" in the same sense people do. Searle concludes that the Turing Test can not prove that a machine can think, contrary to Turing's original proposal.[23]

Arguments such as that proposed by Searle and others working in the philosophy of mind sparked off a more intense debate about the nature of intelligence, the possibility of intelligent machines and the value of the Turing test that continued through the 1980s and 1990s.[24]

1990s and beyond

1990 was the 40th anniversary of the first publication of Turing's "Computing Machinery and Intelligence" paper, and thus saw renewed interest in the test. Two significant events occurred in that year. The first was the Turing Colloquium, which was held at the University of Sussex 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 significant event was the formation of the annual Loebner prize competition.

The Loebner prize was instigated by Hugh Loebner under the auspices of the Cambridge Center for Behavioral Studies of Massachusetts, United States, with the first competition held in November, 1991.[25] As Loebner describes it, the competition was created to advance the state of AI research, at least in part because while the Turing Test had been discussed for many years, "no one had taken steps to implement it."[26] The Loebner prize has three awards: the first prize of $100,000 and a gold medal, to be awarded to the first program that passes the "unrestricted" Turing test; the second prize of $25,000, to be awarded to the first program that passes the "restricted" version of the test; and a sum of $2000 (now $3000) to the "most human-like" program that was entered each year. As of 2008, neither the first nor second prizes have been awarded.

The running of the Loebner prize led to renewed discussion of both the viability of the Turing Test and the aim of developing artificial intelligences that could pass it. The Economist, in an article entitled "Artificial Stupidity", commented that the winning entry from the first Loebner prize won, at least in part, because it was able to "imitate human typing errors".[27] (Turing had considered the possibility that computers could be identified by their lack of errors, and had suggested that the computers should be programmed to add errors into their output, so as to be better "players" of the game).[28] The issue that The Economist raised was one that was already well established in the literature: perhaps we don't really need the types of computers that could pass the Turing Test, and perhaps trying to pass the Turing Test is nothing more than a distraction from more fruitful lines of research.[29] Equally, a second issue became apparent - by providing rules which restricted the abilities of the interrogators to ask questions, and by using comparatively "unsophisticated" interrogators, the Turing Test can be passed through the use of "trickery" rather than intelligence.[30]

Versions of the Turing test

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 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 wrong decision, while player B tries to help player C

There are at least three primary versions of the Turing test - two offered by Turing in "Computing Machinery and Intelligence" and one which Saul Traiger describes as the "Standard Interpretation".[31] While there is some debate as to whether or not the "Standard Interpretation" is described by Turing or is, instead, based on a misreading of his paper, these three versions are not regarded as being equivalent,[31] and are seen as having different strengths and weaknesses.

The imitation game

Turing described a simple party game which involves three players. Player A is a man, player B is a woman, and player C (who plays the role of the interrogator) can be of either gender. In the imitation game, player C - the interrogator - is unable to see either player A or player B, and can only communicate with them 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 of the two 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.[32]

In what Sterret refers to as the "Original Imitation Game Test",[33] Turing proposed that the role of player A be replaced with a computer. The computer's task is therefore to pretend to be a woman and to attempt to trick the interrogator into making an incorrect evaluation. The success of the computer is determined by comparing the outcome of the game when player A is a computer against the outcome when player A is a woman. If, as Turing puts it, "the interrogator decide[s] wrongly as often when the game is played [with the computer] as he does when the game is played between a man and a woman"[12], then it can be argued that the computer is intelligent.

The Original Imitation Game Test, in which the player A is replaced with a computer. The computer is now tasked with the role of pretending to be a woman, while player B continues to attempt to assist the interrogator

The second version comes later in Turing's 1950 paper. As with the Original Imitation Game Test, the role of player A is performed by a computer. The difference is that now the role of player B is to be performed by a man, rather than by a woman.

"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?"

— Turing 1950, p. 442

In this version both player A (the computer) and player B are trying to trick the interrogator into making an incorrect decision.[34]

The standard interpretation

A common understanding of the Turing test is that the purpose was not specifically to test if a computer is able to fool an interrogator into believing that it is a woman, but to test whether or not a computer could imitate a human.[34] While there is some dispute as to whether or not this interpretation was intended by Turing (for example, Sterrett believes that it was,[33] and thus conflates the second version with this one, while others, such as Traiger, do not[31]), this has nevertheless led to what can be viewed as the "standard interpretation". In this version, player A is a computer, and player B is a person of either gender. The role of the interrogator is not to determine which is male and which is female, but to determine which is a computer and which is a human.[35]

Imitation game vs. standard Turing test

There has been some controversy over which of the alternative formulations of the test Turing intended.[33] Sterret argues that two distinct tests can be extracted from Turing's 1950 paper, and that, pace Turing's remark, they are not equivalent. The test that employs the party game and compares frequencies of success in the game 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", noting that Sterret 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 its critics cite, but argues that, in contrast, the Original Imitation Game Test (OIG Test) so defined is immune to many of them, due to a crucial difference: the OIG Test, unlike the STT, does not make similarity to a human performance the criterion of the test, even though it employs a human performance in setting a criterion for machine intelligence. A man can fail the OIG Test, but it is argued that this is a virtue of a test of intelligence if failure indicates a lack of resourcefulness. It is argued that 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 nonverbal versions of imitation games.[36]

Still other writers[37] have interpreted Turing to be proposing that the imitation game itself is the test, without specifying how to take into account Turing's statement that the test he proposed using the party version of the imitation game is based upon a criterion of comparative frequency of success in that imitation game, rather than a capacity to succeed at one round of the game.

Should the interrogator know about the computer?

Turing never makes it clear as to whether or not the interrogator in his tests is aware that one of the participants is a computer. To return to the Original Imitation Game, Turing states only that Player A is to be replaced with a machine, not that player C is to be made aware of this replacement.[12] When Colby, Hilf, Weber and 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.[38] But, as Saygin and others highlight, this makes a big difference to the implementation and outcome of the test.[39]

Strengths of the test

Breadth of subject matter

The power of the Turing test derives from the fact that it is possible to talk about anything. Turing wrote "the question and answer method seems to be suitable for introducing almost any one of the fields of human endeavor that we wish to include."[40] John Haugeland adds that "understanding the words is not enough; you have to understand the topic as well."[41]

In order to pass a well designed Turing test, the machine would have to use natural language, to reason, to have knowledge and to learn. The test can be extended to include video input, as well as a "hatch" through which objects can be passed, and this would force the machine to demonstrate the skill of vision and robotics as well. Together these represent almost all the major problems of artificial intelligence.[42]

Weaknesses of the test

The test has been criticized on several grounds.

Human intelligence vs. intelligence in general

The test is explicitly anthropomorphic. It only tests if the subject resembles a human being, not whether the subject is generally "intelligent" or "sentient". The Turing test will fail to test for general intelligence in two ways:

  • Some human behavior is unintelligent. The Turing test requires that the machine be able to execute all human behaviors, regardless of whether they are intelligent or not. It even tests for behaviors that we may not consider intelligent all, such as the susceptibility to insults or the temptation to lie. If a machine can't imitate human conversation in detail, it will fail the test, regardless of how intelligent it may be.
  • Some intelligent behavior is inhuman. The Turing test does not test for highly intelligent behaviors such as the ability to solve difficult problems or come up with original insights. In fact, the Turing test practically requires deception on the part of the machine: If the machine quickly solves a computational problem that would be impossible for a human to solve, then it would by definition fail the test.

Stuart J. Russell and Peter Norvig argue that the anthropomorphism of the test prevents it from being truly useful for the task of engineering intelligent machines. They write: "Aeronautical engineering texts do not define the goal of their field as 'making machines that fly so exactly like pigeons that they can fool other pigeons.'"[43]

Real intelligence vs. simulated intelligence

The test is also explicitly behaviorist or functionalist: it only tests how the subject acts.

A machine passing the Turing test may be able to simulate human conversational behaviour but the machine might just follow some cleverly devised rules. Two famous examples of this line of argument against the Turing test are John Searle's Chinese room argument and Ned Block's Blockhead argument.

Even if the Turing test is a good operational definition of intelligence, it may not indicate that the machine has consciousness, or that it has intentionality. Perhaps intelligence and consciousness, for example, are such that neither one necessarily implies the other. In that case, the Turing test might fail to capture one of the key differences between intelligent machines and intelligent people.

Predictions and tests

Turing predicted that machines would eventually be able to pass the test. In fact, he estimated that by the year 2000, machines with 109 bits (about 119.2 MiB) of memory would be able to fool 30% of human judges during a 5-minute test. He also predicted that people would then no longer consider the phrase "thinking machine" contradictory. He further predicted that machine learning would be an important part of building powerful machines, a claim which is considered to be plausible by contemporary researchers in Artificial intelligence.

By extrapolating an exponential growth of technology over several decades, futurist Ray Kurzweil predicted that Turing-test-capable computers would be manufactured around the year 2020, roughly speaking.[44] See the Moore's Law article and the references therein for discussions of the plausibility of this argument.

As of 2008, no computer has passed the Turing test as such. Simple conversational programs such as ELIZA have fooled people into believing they are talking to another human being, such as in an informal experiment termed AOLiza. However, such "successes" are not the same as a Turing Test. Most obviously, the human party in the conversation has no reason to suspect they are talking to anything other than a human, whereas in a real Turing test the questioner is actively trying to determine the nature of the entity they are chatting with. Documented cases are usually in environments such as Internet Relay Chat where conversation is sometimes stilted and meaningless, and in which no understanding of a conversation is necessary. Additionally, many internet relay chat participants use English as a second or third language, thus making it even more likely that they would assume that an unintelligent comment by the conversational program is simply something they have misunderstood, and do not recognize the very non-human errors they make. See ELIZA effect.

The Loebner prize is an annual competition to determine the best Turing test competitors. Although they award an annual prize for the computer system that, in the judges' opinions, demonstrates the "most human" conversational behaviour (with learning AI Jabberwacky winning in 2005 and 2006, and A.L.I.C.E. before that), they have an additional prize for a system that in their opinion passes a Turing test. This second prize has not yet been awarded. The creators of Jabberwacky have proposed a personal Turing Test: the ability to pass the imitation test while attempting to specifically imitate the human player, with whom the AI will have conversed at length before the test.[45]

The directive for the competition is to stay as close as possible to Turing's original statements made in his 1950 paper, such that it can be ascertained if any machines are presently close to 'passing the test'. An academic meeting discussing the Turing Test, organised by the Society for the Study of Artificial Intelligence and the Simulation of Behaviour, is being held in parallel at the same venue.

Trying to pass the Turing test in its full generality is not, as of 2005, an active focus of much mainstream academic or commercial effort. Current research in AI-related fields is aimed at more modest and specific goals.

The first bet of the Long Bet Project is a $10,000 one between Mitch Kapor (pessimist) and Ray Kurzweil (optimist) about whether a computer will pass a Turing Test by the year 2029. The bet specifies the conditions in some detail.[46]

Variations of the Turing test

A modification of the Turing test, where the objective or one or more of the roles have been reversed between computers and humans, is termed a reverse Turing test.

Another variation of the Turing test is described as the Subject matter expert Turing test where a computer's response cannot be distinguished from an expert in a given field.

As brain and body scanning techniques improve it may also be possible to replicate the essential data elements of a person to a computer system.[citation needed] The Immortality test variation of the Turing test would determine if a person's essential character is reproduced with enough fidelity to make it impossible to distinguish a reproduction of a person from the original person.

The Minimum Intelligent Signal Test proposed by Chris McKinstry, is another variation of Turing's test, but where only binary responses are permitted. It is typically used to gather statistical data against which the performance of artificial intelligence programs may be measured.

Another variation of the reverse Turing test is implied in the work of psychoanalyst Wilfred Bion,[47] who was particularly fascinated by the "storm" that resulted from the encounter of one mind by another. Carrying this idea forward, R. D. Hinshelwood[48] described the mind as a "mind recognizing apparatus", noting that this might be some sort of "supplement" to the Turing test. To make this more explicit, 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 Turing was attempting to answer, but would, perhaps, be a high enough standard to define a machine that could "think" in a way we typically define as characteristically human.

Another variation is the Meta Turing test, in which the subject being tested (for example a computer) is classified as intelligent if it itself has created something that the subject itself wants to test for intelligence.

Practical applications

Stuart J. Russell and Peter Norvig note that "AI researchers have devoted little attention to passing the Turing Test"[49], since there are easier ways to test their programs: by giving them a task directly, rather than through the roundabout method of first posing a question in a chat room populated with machines and people. Alan Turing never intended his test to be used as a real, day-to-day measure of the intelligence of AI programs. He wanted to provide a clear and understandable example to help us discuss the philosophy of artificial intelligence.[50]

Real Turing tests, such as the Loebner prize, do not usually force programs to demonstrate the full range of intelligence and are reserved for testing chatterbot programs. However, even in this limited form these tests are still very rigorous. The 2008 Loebner prize however is sticking closely to Turing's original concepts - for example conversations will be for 5 minutes only.

CAPTCHA is a form of reverse Turing test. Before being allowed to do some action on a website, the user is presented with alphanumerical characters in a distorted graphic image and asked to recognise it. This is intended to prevent automated systems from abusing the site. The rationale is that software sufficiently sophisticated to read 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 being.

See also

Notes

  1. ^ Crevier 1993, pp. 47–49, Russell & Norvig 2003, p. 17 and Copeland 2003, p. 1
  2. ^ For an example of Property dualism, see Qualia.
  3. ^ Noting that materialism does not necessitate the possibility of artificial minds (for example, Roger Penrose), any more than dualism necessarily precludes the possibility (for example, Property dualism).
  4. ^ Language, Truth and Logic (p140), Penguin 2001
  5. ^ McCorduck 2004, p. 95
  6. ^ Copeland 2003, p. 1
  7. ^ Copeland 2003, p. 2
  8. ^ Turing 1948, p. 412
  9. ^ "Intelligent Machinery" was not published by Turing, and didn't see publication until 1968 in Evans, C. R. & Robertson, A. D. J. (1968) Cybernetics: Key Papers, University Park Press.
  10. ^ a b Turing 1950, p. 433
  11. ^ Harnad, p. 1
  12. ^ a b c Turing 1950, p. 434
  13. ^ Turing 1950, p. 446
  14. ^ Turing 1952, 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, while in the later it would be closer to current depictions of the test.
  15. ^ Turing 1950 and see Russell & Norvig 2003, 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."
  16. ^ Whitby 1996, p. 53
  17. ^ Weizenbaum 1966, p. 37
  18. ^ a b c Weizenbaum 1966, p. 42
  19. ^ Thomas 1995, p. 112
  20. ^ Bowden 2006, p. 370
  21. ^ Coby et al. 1972, p. 42
  22. ^ Saygin, Cicekli & Akman 2000, p. 501
  23. ^ Searle 1980
  24. ^ Saygin, Cicekli & Akman 2000, p. 479
  25. ^ Sundman 2003
  26. ^ Loebner 1994
  27. ^ "Artificial Stupidity" 1992
  28. ^ (Turing 1950, p. 448)
  29. ^ Shieber 1994, p. 77
  30. ^ Shapiro 1992, p. 10-11 and Shieber 1994, amongst others
  31. ^ a b c Traiger 2000
  32. ^ Turing 1950, p. 433-434
  33. ^ a b c Moor 2003 harvnb error: multiple targets (2×): CITEREFMoor2003 (help)
  34. ^ a b Saygin et al 2000, p. 252
  35. ^ Traiger 2000, p. 99
  36. ^ Sterrett 2000
  37. ^ Genova 1994, Hayes & Ford 1995, Heil 1998, Dreyfus 1979
  38. ^ Colby et al 1972
  39. ^ Saygin et al 2000, p. 60
  40. ^ Turing 1950 under "Critique of the New Problem"
  41. ^ Haugeland 1985, p. 8
  42. ^ Stuart J. Russell and Peter Norvig write "These six disciplines represent most of AI". Russell & Norvig 2003, p. 3
  43. ^ Russell & Norvig 2003, p. 3
  44. ^ Kurzweil 1990
  45. ^ See http://www.jabberwacky.com/s/PTT100605.pdf
  46. ^ Long Bets - By 2029 no computer - or "machine intelligence" - will have passed the Turing Test
  47. ^ Bion 1979
  48. ^ Hinshelwood 2001
  49. ^ Russell & Norvig 2003, p. 3
  50. ^ Turing 1950 under 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."

References

  • "Artificial Stupidity", The Economist, 324 (7770): 14, 1992-09-01{{citation}}: CS1 maint: date and year (link)
  • Bion, W.S. (1979), "Making the best of a bad job", Clinical Seminars and Four Papers, Abingdon: Fleetwood Press.
  • Bowden, Margaret A. (2006), Mind As Machine: A History of Cognitive Science, Oxford University Press, ISBN 9780199241446
  • Colby, K. M.; Hilf, F. D.; Weber, S.; Kraemer (1972), "Turing-like indistinguishability tests for the validation of a computer simulation of paranoid processes", Artificial Intelligence, 3: 199–221 {{citation}}: Unknown parameter |fisrt4= ignored (help)
  • Copeland, Jack (2003), Moor, James (ed.), "The Turing Test", The Turing Test: The Elusive Standard of Artificial Intelligence, Springer, ISBN 1-40-201205-5
  • Crevier, Daniel (1993), AI: The Tumultuous Search for Artificial Intelligence, New York, NY: BasicBooks, ISBN 0-465-02997-3
  • Dreyfus, Hubert (1979), What Computers Still Can't Do, New York: MIT Press, ISBN ISBN 0-06-090613-8 {{citation}}: Check |isbn= value: invalid character (help)
  • Genova, J. (1994), "Turing's Sexual Guessing Game", Social Epistemology, 8 (4): 314–326, ISSN 0269-1728
  • Harnad, Stevan (2004), "The Annotation Game: On Turing (1950) on Computing, Machinery, and Intelligence", in Epstein, Robert; Peters, Grace (eds.), The Turing Test Sourcebook: Philosophical and Methodological Issues in the Quest for the Thinking Computer, Klewer
  • Haugeland, John (1985), Artificial Intelligence: The Very Idea, MIT Press {{citation}}: Unknown parameter |publisher-place= ignored (help).
  • Hayes, Patrick; Ford, Kenneth (1995), "Turing Test Considered Harmful", Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence (IJCAI95-1), Montreal, Quebec, Canada.: 972–997
  • Heil, John (1998), Philosophy of Mind: A Contemporary Introduction, London and New York: Routledge, ISBN 0-415-13060-3
  • Hinshelwood, R.D. (2001), Group Mentality and Having a Mind: Reflections on Bion's work on groups and on psychosis
  • Kurzweil, Ray (1990), The Age of Intelligent Machines, ISBN 0-262-61079-5
  • Loebner, Hugh Gene (1994), "In response", Communications of the ACM, 37 (6): 79–82, retrieved 2008-03-22
  • Moor, James, ed. (2003), The Turing Test: The Elusive Standard of Artificial Intelligence, ISBN 1-4020-1205-5
  • Penrose, Roger (1989), The Emperor's New Mind: Concerning Computers, Minds, and The Laws of Physics, Oxford University Press, ISBN 0-14-014534-6
  • Russell, Stuart J.; Norvig, Peter (2003), Artificial Intelligence: A Modern Approach (2nd ed.), Upper Saddle River, NJ: Prentice Hall, ISBN 0-13-790395-2
  • Saygin, Ayse Pinar; Cicekli, Ilyas; Akman, Varol (2000), Turing Test: 50 Years Later in Moor, James, ed. (2003), The Turing Test: The Elusive Standard of Artificial Intelligence, Springer, ISBN 1-40-201205-5
  • Searle, John (1980), "Minds, Brains and Programs", Behavioral and Brain Sciences, 3 (3): 417–457. Page numbers above refer to a standard pdf print of the article. See also Searle's original draft.
  • Shapiro, Stuart C. (1992), "The Turing Test and the economist", ACM SIGART Bulletin, 3 (4): 10–11
  • Shieber, Stuart M. (1994), "Lessons from a Restricted Turing Test", Communications of the ACM, 37 (6): 70–78, retrieved 2008-03-25
  • Sterrett, S. G. (2000), "Turing's Two Test of Intelligence", Minds and Machines, 10 (4), ISSN 0924-6495 (reprinted in The Turing Test: The Elusive Standard of Artificial Intelligence edited by James H. Moor, Kluwer Academic 2003) ISBN 1-4020-1205-5
  • Sundman, John (February 26, 2003), "Artificial stupidity", Salon.com, retrieved 2008-03-22{{citation}}: CS1 maint: date and year (link)
  • Thomas, Peter J. (1995), The Social and Interactional Dimensions of Human-Computer Interfaces, Cambridge University Press, ISBN 052145302X
  • Traiger, Saul (2000), "Making the Right Identification in the Turing Test", Minds and Machines, 10 (4), ISSN 0924-6495 (reprinted in The Turing Test: The Elusive Standard of Artificial Intelligence edited by James H. Moor, Kluwer Academic 2003) ISBN 1-4020-1205-5
  • Turing, Alan (1948), "Machine Intelligence", in Copeland, B. Jack (ed.), The Essential Turing: The ideas that gave birth to the computer age, ISBN 0-19-825080-0
  • Turing, Alan (October 1950), "Computing Machinery and Intelligence", Mind, LIX (236): 433–460, doi:10.1093/mind/LIX.236.433, ISSN 0026-4423
  • Turing, Alan (1952), "Can Automatic Calculating Machines be Said to Think?", in Copeland, B. Jack (ed.), The Essential Turing: The ideas that gave birth to the computer age, ISBN 0-19-825080-0
  • Zylberberg, A.; Calot, E. (2007), "Optimizing Lies in State Oriented Domains based on Genetic Algorithms", Proceedings VI Ibero-American Symposium on Software Engineering: 11–18, ISBN 978-9972-2885-1-7
  • Weizenbaum, Joseph (January, 1966), "ELIZA - A Computer Program For the Study of Natural Language Communication Between Man And Machine", Communications of the ACM, 9 (1): 36–45 {{citation}}: Check date values in: |date= (help)CS1 maint: date and year (link)
  • Whitby, Blay (1996), "The Turing Test: AI's Biggest Blind Alley?", in Millican, Peter & Clark, Andy (ed.), Machines and Thought: The Legacy of Alan Turing, vol. 1, Oxford University Press, pp. 53–62, ISBN 0-19-823876-2{{citation}}: CS1 maint: multiple names: editors list (link)
  • Adams, Scott (2008), Dilbert {{citation}}: Unknown parameter |Distributed by= ignored (help)

Further reading

  • B. Jack Copeland, ed., The Essential Turing: The ideas that gave birth to the computer age (2004). ISBN 0-19-825080-0
  • Larry Gonick, The Cartoon Guide to the Computer (1983, originally The Cartoon Guide to Computer Science). ISBN 0-06-273097-5.
  • S. G. Sterrett "Nested Algorithms and the 'Original Imitation Game Test'," Minds and Machines (2002). ISSN 0924-6495
  • A.P. Saygin, I. Cicekli, and V Akman (2000), 'Turing Test: 50 Years Later', Minds and Machines 10(4): 463-518. (reprinted in The Turing Test: The Elusive Standard of Artificial Intelligence edited by James H. Moor, Kluwer Academic 2003) ISBN 1-4020-1205-5. (Thorough review. Online version at [1] )
  • Saygin, A.P. & Cicekli I (2002): Pragmatics in human-computer conversations (Abstract and links to pdf, if permitted), Journal of Pragmatics, Volume 34, Issue 3, March 2002, Pages 227-258.

External links

Retrieved from "https://en.wikipedia.org/w/index.php?title=Turing_test&oldid=245846639"