71:". The original Imitation game, that Turing described, is 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) can be of either sex. In the Imitation Game, player C is unable to see either player A or player B (and knows them only as X and Y), and can communicate with them only through written notes or any other form that does not give away any details about their gender. 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.
527:. The propositions would have various kinds of status, e.g., well-established facts, conjectures, mathematically proved theorems, statements given by an authority, expressions having the logical form of proposition but not belief-value. Certain propositions may be described as "imperatives." The machine should be so constructed that as soon as an imperative is classed as "well established" the appropriate action automatically takes place". Despite this built-in logic system the logical inference programmed in would not be one that is formal, rather it would be one that is more pragmatic. In addition the machine would build on its built-in logic system by a method of "scientific induction".
277:(acceptance speech for his 1948 award of Lister Medal) states that "not until a machine can write a sonnet or compose a concerto because of thoughts and emotions felt, and not by the chance fall of symbols, could we agree that machine equals brain." Turing replies by saying that we have no way of knowing that any individual other than ourselves experiences emotions, and that therefore we should accept the test. He adds, "I do not wish to give the impression that I think there is no mystery about consciousness ... ut I do not think these mysteries necessarily need to be solved before we can answer the question ." (This argument, that a computer can't have
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extended to a human mind and then to a machine. He concludes that such an analogy would indeed be suitable for the human mind with "There does seem to be one for the human mind. The majority of them seem to be "subcritical," i.e., to correspond in this analogy to piles of sub critical size. An idea presented to such a mind will on average give rise to less than one idea in reply. A smallish proportion are supercritical. An idea presented to such a mind that may give rise to a whole "theory" consisting of secondary, tertiary and more remote ideas". He finally asks if a machine could be made to be supercritical.
407:: This argument states that any system governed by laws will be predictable and therefore not truly intelligent. Turing replies by stating that this is confusing laws of behaviour with general rules of conduct, and that if on a broad enough scale (such as is evident in man) machine behaviour would become increasingly difficult to predict. He argues that, just because we can't immediately see what the laws are, does not mean that no such laws exist. He writes "we certainly know of no circumstances under which we could say, 'we have searched enough. There are no such laws.'". (
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understanding of the internal state of the machine at every moment during the computation. The machine will be seen to be doing things that we often cannot make sense of or something that we consider to be completely random. Turing mentions that this specific character bestows upon a machine a certain degree of what we consider to be intelligence, in that intelligent behaviour consists of a deviation from the complete determinism of conventional computation but only so long as the deviation does not give rise to pointless loops or random behaviour.
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The problem then is broken down into two parts, the programming of a child mind and its education process. He mentions that a child mind would not be expected as desired by the experimenter (programmer) at the first attempt. A learning process that involves a method of reward and punishment must be in place that will select desirable patterns in the mind. This whole process, Turing mentions, to a large extent is similar to that of evolution by natural selection where the similarities are:
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such that a systematic approach would investigate several unsatisfactory solutions to a problem before finding the optimal solution which would entail the systematic process inefficient. Turing also mentions that the process of evolution takes the path of random mutations in order to find solutions that benefit an organism but he also admits that in the case of evolution the systematic method of finding a solution would not be possible.
82:'. So the modified game becomes one that involves three participants in isolated rooms: a computer (which is being tested), a human, and a (human) judge. The human judge can converse with both the human and the computer by typing into a terminal. Both the computer and human try to convince the judge that they are the human. If the judge cannot consistently tell which is which, then the computer wins the game.
217:; therefore, a machine cannot think. "In attempting to construct such machines," wrote Turing, "we should not be irreverently usurping His power of creating souls, any more than we are in the procreation of children: rather we are, in either case, instruments of His will providing mansions for the souls that He creates."
54:
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Be kind, resourceful, beautiful, friendly, have initiative, have a sense of humour, tell right from wrong, make mistakes, fall in love, enjoy strawberries and cream, make someone fall in love with it, learn from experience, use words properly, be the subject of its own thought, have as much diversity
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Hence, Turing states that the focus is not on "whether all digital computers would do well in the game nor whether the computers that are presently available would do well, but whether there are imaginable computers which would do well". What is more important is to consider the advancements possible
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The importance of random behaviour: Though Turing cautions us of random behaviour he mentions that inculcating an element of randomness in a learning machine would be of value in a system. He mentions that this could be of value where there might be multiple correct answers or ones where it might be
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This allows the original question to be made even more specific. Turing now restates the original question as "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
44:
Turing's paper considers the question "Can machines think?" Turing says that since the words "think" and "machine" cannot be clearly defined, we should "replace the question by another, which is closely related to it and is expressed in relatively unambiguous words." To do this, he must first find a
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Given this process he asks whether it would be more appropriate to program a child's mind instead of an adult’s mind and then subject the child mind to a period of education. He likens the child to a newly bought notebook and speculates that due to its simplicity it would be more easily programmed.
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Turing concludes by speculating about a time when machines will compete with humans on numerous intellectual tasks and suggests tasks that could be used to make that start. Turing then suggests that abstract tasks such as playing chess could be a good place to start another method which he puts as
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Nature of inherent complexity: The child machine could either be one that is as simple as possible, merely maintaining consistency with general principles, or the machine could be one with a complete system of logical inference programmed into it. This more complex system is explained by Turing as
465:
Here Turing first returns to Lady
Lovelace's objection that the machine can only do what we tell it to do and he likens it to a situation where a man "injects" an idea into the machine to which the machine responds and then falls off into quiescence. He extends on this thought by an analogy to an
478:
Turing then mentions that the task of being able to create a machine that could play the imitation game is one of programming and he postulates that by the end of the century it will indeed be technologically possible to program a machine to play the game. He then mentions that in the process of
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Turing suggests that
Lovelace's objection can be reduced to the assertion that computers "can never take us by surprise" and argues that, to the contrary, computers could still surprise humans, in particular where the consequences of different facts are not immediately recognizable. Turing also
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of the pile were to be sufficiently large, then a neutron entering the pile would cause a disturbance that would continue to increase until the whole pile were destroyed, the pile would be supercritical. Turing then asks the question as to whether this analogy of a super critical pile could be
536:
Ignorance of the experimenter: An important feature of a learning machine that Turing points out is the ignorance of the teacher of the machines' internal state during the learning process. This is in contrast to a conventional discrete state machine where the objective is to have a clear
129:, are themselves controversial. Some have taken Turing's question to have been "Can a computer, communicating over a teleprinter, fool a person into believing it is human?" but it seems clear that Turing was not talking about fooling people but about generating human cognitive capacity.
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fire in an all-or-nothing pulse, both the exact timing of the pulse and the probability of the pulse occurring have analog components. Turing acknowledges this, but argues that any analog system can be simulated to a reasonable degree of accuracy given enough computing power.
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indistinguishably from the way a thinker acts. This question avoids the difficult philosophical problem of pre-defining the verb "to think" and focuses instead on the performance capacities that being able to think makes possible, and how a causal system can generate them.
78:"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?
151:, while man-made, would not provide a very interesting example. Turing suggested that we should focus on the capabilities of digital machinery—machines which manipulate the binary digits of 1 and 0, rewriting them into memory using simple rules. He gave two reasons.
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simple and unambiguous idea to replace the word "think", second he must explain exactly which "machines" he is considering, and finally, armed with these tools, he formulates a new question, related to the first, that he believes he can answer in the affirmative.
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Turing notes that "no support is usually offered for these statements," and that they depend on naive assumptions about how versatile machines may be in the future, or are "disguised forms of the argument from consciousness." He chooses to answer a few of them:
199:
Having clarified the question, Turing turned to answering it: he considered the following nine common objections, which include all the major arguments against artificial intelligence raised in the years since his paper was first published.
223:: "The consequences of machines thinking would be too dreadful. Let us hope and believe that they cannot do so." This thinking is popular among intellectual people, as they believe superiority derives from higher intelligence and
1000:, p. 948 where 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."
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researchers that included Alan Turing. 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.
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argues that Lady
Lovelace was hampered by the context from which she wrote, and if exposed to more contemporary scientific knowledge, it would become evident that the brain's storage is quite similar to that of a computer.
573:(though, this too is controversial) and the numerous computer chess games which can outplay most amateurs. As for the second suggestion Turing makes, it has been likened by some authors as a call to finding a
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would argue in 1972 that human reason and problem solving was not based on formal rules, but instead relied on instincts and awareness that would never be captured in rules. More recent AI research in
109:
notes, the question has become "Can machines do what we (as thinking entities) can do?" In other words, Turing is no longer asking whether a machine can "think"; he is asking whether a machine can
1936:
1147:
Scientific
Memoirs edited by Richard Taylor (1781–1858), Volume 3, Sketch of the Analytical Engine invented by Charles Babbage, Esq, Notes by the Translator, by Augusta Ada Lovelace. 1843
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227:(as machines have efficient memory capacities and processing speed, machines exceeding the learning and knowledge capabilities are highly probable). This objection is a fallacious
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of human cognitive development. Such attempts at finding the underlying algorithms by which children learn the features of the world around them are only beginning to be made.
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entering the pile from outside the pile; the neutron will cause a certain disturbance which eventually dies away. Turing then builds on that analogy and mentions that, if the
435:: In 1950, extra-sensory perception was an active area of research and Turing chooses to give ESP the benefit of the doubt, arguing that conditions could be created in which
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had proved that a digital computer can, in theory, simulate the behaviour of any other digital machine, given enough memory and time. (This is the essential insight of the
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can answer. Turing suggests that humans are too often wrong themselves and pleased at the fallibility of a machine. (This argument would be made again by philosopher
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trying to imitate an adult human mind it becomes important to consider the processes that lead to the adult mind being in its present state; which he summarizes as:
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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 (
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The "standard interpretation" of the Turing Test, in which the interrogator is tasked with trying to determine which player is a computer and which is a human
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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?"
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would not affect the test. Turing admitted to "overwhelming statistical evidence" for telepathy, likely referring to early 1940s experiments by
2019:
882:"A.I. experts say the Google researcher's claim that his chatbot became 'sentient' is ridiculous—but also highlights big problems in the field"
462:
In the final section of the paper Turing details his thoughts about the
Learning Machine that could play the imitation game successfully.
2014:
554:"..it is best to provide the machine with the best sense organs that money can buy, and then teach it to understand and speak English.".
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Since Turing introduced his test, it has been both highly influential and widely criticised, and has become an important concept in the
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attempts to find the complex rules that govern our "informal" and unconscious skills of perception, mobility and pattern matching. See
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Rather than trying to determine if a machine is thinking, Turing suggests we should ask if the machine can win a game, called the "
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1986:
360:: One of the most famous objections states that computers are incapable of originality. This is largely because, according to
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atomic pile of less than critical size, which is to be considered the machine, and an injected idea is to correspond to a
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1964:
1943:
1024:, pp. 949–950. Russell and Norvig identify Lucas and Penrose's arguments as being the same one answered by Turing.
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that has followed reveals that the learning machine did take the abstract path suggested by Turing as in the case of
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349:. He notes that, with enough storage capacity, a computer can behave in an astronomical number of different ways.
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in the state of our machines today regardless of whether we have the available resource to create one or not.
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sufficiently powerful digital machine can. Turing writes, "all digital computers are in a sense equivalent."
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Turing also notes that we need to determine which "machines" we wish to consider. He points out that a human
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to perform. It can follow analysis; but it has no power of anticipating any analytical relations or truths.
703:
The Turing Test
Sourcebook: Philosophical and Methodological Issues in the Quest for the Thinking Computer
1829:
Saygin, Ayse Pinar; Cicekli, Ilyas; Akman, Varol (1999). "An analysis and review of the next 50 years".
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program, can certainly be written. Turing asserts "a machine can undoubtably be its own subject matter."
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Parsing the Turing Test:Philosophical and
Methodological Issues in the Quest for the Thinking Computer
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First, there is no reason to speculate whether or not they can exist. They already did in 1950.
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Following this discussion Turing addresses certain specific aspects of the learning machine:
1981:
339:). A program which can report on its internal states and processes, in the simple sense of a
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1950:
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Mind over
Machine: The Power of Human Intuition and Expertise in the Era of the Computer
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Proceedings of the 2020 Federated
Conference on Computer Science and Information Systems
523:"..would be such that the machines store would be largely occupied with definitions and
68:
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1332:
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1108:
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949:
930:"The Turing Test Is Not A Trick: Turing Indistinguishability Is A Scientific Criterion"
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Wardrip-Fruin, Noah and Nick Montfort, ed (2003). The New Media Reader. The MIT Press.
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3. Other experience, not to be described as education, to which it has been subjected.
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1950 article by Alan Turing on artificial intelligence that introduced the Turing test
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This describes the simplest version of the test. For a more detailed discussion, see
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699:"The Annotation Game: On Turing (1950) on Computing, Machinery, and Intelligence"
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1137:, pp. 958–960, who identify Searle's argument with the one Turing answers.
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408:
398:
138:
33:
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231:, confusing what should not be with what can or cannot be (Wardrip-Fruin, 56).
2003:
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1374:
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1184:, pp. 51–52, who identify Dreyfus' argument with the one Turing answers.
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757:"Game AI Competitions: Motivation for the Imitation Game-Playing Competition"
718:"Minds, Machines, and Turing: The Indistinguishability of Indistinguishables"
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265:
257:
245:, to show that there are limits to what questions a computer system based on
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1648:
The Emperor's New Mind: Concerning Computers, Minds, and The Laws of Physics
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was not published by Turing, and did not see publication until 1968 in:
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336:
90:
1500:"First, Scale Up to the Robotic Turing Test, Then Worry About Feeling"
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would make this argument against "the biological assumption" in 1972.)
1059:
1034:
614:(Winter 2021 ed.), Metaphysics Research Lab, Stanford University
436:
254:
205:
157:
Second, digital machinery is "universal". Turing's research into the
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Turing proposes a variation of this game that involves the computer:
37:, was the first to introduce his concept of what is now known as the
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He notes it's easy to program a machine to appear to make a mistake.
412:
340:
89:) research in 1956. It was a common topic among the members of the
467:
148:
1678:(2nd ed.), Upper Saddle River, New Jersey: Prentice Hall,
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390:
1847:
1608:(1961), "Minds, Machines and Gödel", in Anderson, A.R. (ed.),
389:
research has shown that the brain is not digital. Even though
311:. These arguments all have the form "a computer will never do
929:
717:
246:
1282:. Learning, Development, and Conceptual Change. MIT Press.
214:
566:
1305:"Origins of theory of mind, cognition and communication"
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Saygin, A. P. (2000). "Turing Test: 50 years later".
1426:
AI: The Tumultuous Search for Artificial Intelligence
1242:
Epstein, Robert; Roberts, Gary; Beber, Grace (2008).
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The Analytical Engine has no pretensions whatever to
241:: This objection uses mathematical theorems, such as
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Structure of the child machine = hereditary material
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digital machine can "act like it is thinking", then
1241:
210:: This states that thinking is a function of man's
1828:
660:of 1956 are widely considered the "birth of AI". (
333:A machine cannot be the subject of its own thought
364:, machines are incapable of independent learning.
347:A machine cannot have much diversity of behaviour
2001:
1237:
1235:
1233:
510:Natural selection = judgment of the experimenter
488:2. The education to which it has been subjected,
485:1. The initial state of the mind, say at birth,
319:of behaviour as a man, do something really new.
1494:
1465:
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383:Argument from continuity in the nervous system
293:argument. Turing's reply is now known as the "
225:the possibility of being overtaken is a threat
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1181:
1134:
1021:
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2040:Works originally published in Mind (journal)
1597:Gödel, Escher, Bach: an Eternal Golden Braid
701:, in Epstein, Robert; Peters, Grace (eds.),
879:
1870:
1856:
1675:Artificial Intelligence: A Modern Approach
1590:
1017:
722:Journal of Logic, Language and Information
569:and one which defeated the world champion
405:Argument from the informality of behaviour
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1813:. "Lucasfilm's Habitat" pp. 663–677.
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188:
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852:"Online Love Seerkers Warned Flirt Bots"
849:
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565:, a chess playing computer developed by
507:Changes of the child machine = mutations
269:: This argument, suggested by Professor
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612:The Stanford Encyclopedia of Philosophy
285:, would be made in 1980 by philosopher
2002:
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1735:"Computing Machinery and Intelligence"
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1558:Artificial Intelligence: The Very Idea
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673:
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2020:Philosophy of artificial intelligence
1851:
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1572:The Role of Raw Power in Intelligence
1009:
766:. IEEE Publishing. pp. 155–160.
557:An examination of the development in
195:Philosophy of artificial intelligence
119:philosophy of artificial intelligence
1958:Computing Machinery and Intelligence
1074:Jefferson, Geoffrey (25 June 1949).
975:
960:
820:Withers, Steven (11 December 2007),
801:from the original on 26 January 2021
451:
423:). This rejoinder also includes the
21:Computing Machinery and Intelligence
1965:The Chemical Basis of Morphogenesis
1824:PDF with the full text of the paper
1504:Artificial Intelligence in Medicine
904:
832:from the original on 4 October 2017
680:Evans, A. D. J.; Robertson (1968),
309:Arguments from various disabilities
132:
13:
2015:History of artificial intelligence
1944:Systems of Logic Based on Ordinals
1312:Journal of Communication Disorders
1208:10.1093/oso/9780198747826.003.0042
1194:Leavitt, David (26 January 2017),
862:from the original on 24 April 2010
850:Williams, Ian (10 December 2007),
606:Oppy, Graham; Dowe, David (2021),
121:. Some of its criticisms, such as
31:. The paper, published in 1950 in
14:
2051:
1817:
892:from the original on 13 June 2022
754:
1801:and Nick Montfort, eds. (2003).
1020:, pp. 471–473, 476–477 and
48:
23:" is a seminal paper written by
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1386:Robotics and Autonomous Systems
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1163:
1151:
1140:
1124:
1067:
1027:
1003:
987:
921:
843:
813:
93:, an informal group of British
2025:Artificial intelligence papers
748:
709:
690:
674:"Intelligent Machinery" (1948)
667:
650:
637:
625:
599:
587:
445:Society for Psychical Research
327:Machines cannot make mistakes.
243:Gödel's incompleteness theorem
1:
1704:Behavioral and Brain Sciences
1560:, Cambridge, Mass.: MIT Press
1408:10.1016/S0921-8890(05)80025-9
1367:
1324:10.1016/S0021-9924(99)00009-X
1279:Words, thoughts, and theories
822:"Flirty Bot Passes for Human"
610:, in Zalta, Edward N. (ed.),
371:anything. It can do whatever
315:". Turing offers a selection:
221:'Heads in the Sand' Objection
2035:Cognitive science literature
1697:"Minds, Brains and Programs"
1526:10.1016/j.artmed.2008.08.008
1428:. New York, NY: BasicBooks.
1379:"Elephants Don't Play Chess"
1303:Meltzoff, Andrew N. (1999).
1076:"The Mind of Mechanical Man"
880:Jeremy Kahn (13 June 2022).
755:Swiechowski, Maciej (2020).
7:
1651:, Oxford University Press,
1202:, Oxford University Press,
1196:"Turing and the paranormal"
645:Versions of the Turing test
10:
2056:
1637:, Harvard University Press
1498:; Scherzer, Peter (2008),
1469:; Dreyfus, Stuart (1986),
1174:Dreyfus & Dreyfus 1986
455:
417:computational intelligence
299:Can a machine have a mind?
192:
159:foundations of computation
136:
60:
1974:
1928:
1885:
1716:10.1017/S0140525X00005756
1182:Russell & Norvig 2003
1135:Russell & Norvig 2003
1022:Russell & Norvig 2003
998:Russell & Norvig 2003
1805:. Cambridge: MIT Press.
1754:10.1093/mind/LIX.236.433
1248:. Springer. p. 65.
580:
432:Extra-sensory perception
167:universal Turing machine
1774:10.1023/A:1011288000451
1473:, Oxford, UK: Blackwell
1452:, New York: MIT Press,
1449:What Computers Can't Do
1092:10.1136/bmj.1.4616.1105
1080:British Medical Journal
928:Harnad, Stevan (1992),
734:10.1023/A:1008315308862
716:Harnad, Stevan (2001),
697:Harnad, Stevan (2008),
684:, University Park Press
682:Cybernetics: Key Papers
559:artificial intelligence
421:Dreyfus' critique of AI
373:we know how to order it
41:to the general public.
29:artificial intelligence
377:
321:
229:appeal to consequences
189:Nine common objections
58:
1982:Legacy of Alan Turing
1951:Intelligent Machinery
1937:On Computable Numbers
1489:, New York: MIT Press
946:10.1145/141420.141422
658:Dartmouth conferences
365:
316:
279:conscious experiences
56:
1803:The New Media Reader
163:Church–Turing thesis
143:Church–Turing thesis
1890:Turing completeness
1592:Hofstadter, Douglas
1274:Meltzoff, Andrew N.
1086:(4616): 1105–1110.
1051:1948Natur.162U.138.
1045:(4108): 138. 1948.
934:ACM SIGART Bulletin
1831:Minds and Machines
1799:Noah Wardrip-Fruin
1762:Minds and Machines
1666:Russell, Stuart J.
1611:Minds and Machines
1540:on 8 February 2012
443:, a member of the
271:Geoffrey Jefferson
59:
1997:
1996:
1658:978-0-14-014534-2
1618:on 19 August 2007
1459:978-0-06-011082-6
1255:978-1-4020-6710-5
1217:978-0-19-874782-6
783:978-83-955416-7-4
773:10.15439/2020F126
608:"The Turing Test"
452:Learning machines
297:reply". See also
169:.) Therefore, if
2047:
1915:Turing reduction
1872:
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1858:
1849:
1848:
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1795:
1785:
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1748:(236): 433–460,
1739:
1733:(October 1950),
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1614:, archived from
1600:
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1300:
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1200:The Turing Guide
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458:Machine learning
303:philosophy of AI
133:Digital machines
81:
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27:on the topic of
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2048:
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2044:
2000:
1999:
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1970:
1924:
1881:
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1840:10.1.1.157.1592
1820:
1737:
1699:
1686:
1659:
1621:
1619:
1582:
1580:
1579:on 3 March 2016
1554:Haugeland, John
1543:
1541:
1517:10.1.1.115.4269
1483:What Computers
1479:Dreyfus, Hubert
1467:Dreyfus, Hubert
1460:
1444:Dreyfus, Hubert
1436:
1422:Crevier, Daniel
1412:
1410:
1399:10.1.1.588.7539
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1035:"Announcements"
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5:
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2010:1950 documents
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1961:
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1910:Turing's proof
1907:
1905:Turing pattern
1902:
1900:Turing machine
1897:
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1875:
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1819:
1818:External links
1816:
1815:
1814:
1796:
1768:(4): 463–518.
1757:
1727:
1710:(3): 417–457,
1689:
1684:
1662:
1657:
1643:Penrose, Roger
1639:
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1563:
1550:
1496:Harnad, Stevan
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1375:Brooks, Rodney
1369:
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1318:(4): 251–269.
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1270:Gopnik, Alison
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571:Garry Kasparov
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409:Hubert Dreyfus
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399:Hubert Dreyfus
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275:Lister Oration
264:Argument From
261:
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139:Turing machine
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69:Imitation Game
61:Main article:
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1895:Turing degree
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1811:0-262-23227-8
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1685:0-13-790395-2
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1670:Norvig, Peter
1667:
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1635:Mind Children
1632:
1631:Moravec, Hans
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1160:, p. 156
1159:
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335:(or can't be
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283:understanding
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266:Consciousness
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258:Roger Penrose
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1929:Publications
1830:
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1731:Turing, Alan
1707:
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1693:Searle, John
1674:
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1616:the original
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1244:
1221:, retrieved
1199:
1189:
1178:Moravec 1988
1170:Dreyfus 1972
1165:
1158:Dreyfus 1979
1153:
1142:
1126:
1083:
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1069:
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1014:Penrose 1989
1005:
989:
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894:. Retrieved
885:
875:
864:, retrieved
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834:, retrieved
825:
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803:. Retrieved
763:
750:
725:
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711:
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692:
681:
669:
662:Crevier 1993
652:
639:
627:
616:, retrieved
611:
601:
589:
556:
552:
525:propositions
515:
496:
477:
464:
461:
437:mind-reading
430:
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387:neurological
382:
372:
368:
366:
362:Ada Lovelace
358:'s Objection
354:
346:
332:
326:
317:
312:
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291:Chinese room
282:
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273:in his 1949
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253:in 1961 and
237:Mathematical
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2030:Alan Turing
1920:Turing test
1879:Alan Turing
1783:11693/24987
1606:Lucas, John
1510:(2): 83–9,
1355:27 November
1131:Searle 1980
994:Turing 1950
982:Turing 1950
970:Turing 1950
940:(4): 9–10,
866:10 February
836:10 February
805:8 September
632:Turing 1950
594:Turing 1950
441:Samuel Soal
396:Philosopher
295:other minds
287:John Searle
123:John Searle
99:electronics
95:cybernetics
63:Turing test
39:Turing test
25:Alan Turing
2004:Categories
1622:2 December
1583:7 November
1368:References
1010:Lucas 1961
575:simulacrum
456:See also:
337:self-aware
251:John Lucas
193:See also:
137:See also:
91:Ratio Club
1987:namesakes
1835:CiteSeerX
1544:29 August
1512:CiteSeerX
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1394:CiteSeerX
1100:0007-1447
792:222296354
563:Deep Blue
427:argument.
385:: Modern
369:originate
260:in 1989.)
255:physicist
239:Objection
208:Objection
206:Religious
1967:" (1952)
1960:" (1950)
1953:" (1948)
1946:" (1939)
1939:" (1936)
1833:: 2000.
1724:55303721
1695:(1980),
1672:(2003),
1645:(1989),
1633:(1988),
1594:(1979),
1569:(1976),
1556:(1985),
1534:18930641
1487:Can't Do
1481:(1979),
1446:(1972),
1424:(1993).
1377:(1990),
1342:10466097
1276:(1997).
1118:18153422
954:36356326
890:Archived
860:archived
830:archived
796:Archived
705:, Kluwer
618:6 August
413:robotics
341:debugger
212:immortal
165:and the
1975:Related
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1223:23 July
1109:2050428
1047:Bibcode
896:13 June
886:Fortune
742:1911720
468:neutron
391:neurons
301:in the
289:in his
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950:S2CID
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581:Notes
247:logic
175:every
149:clone
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