Search results for 'TURING TEST' (try it on Scholar)

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  1. Turing Test (2004). The Ephemera. In Stuart M. Shieber (ed.), The Turing Test: Verbal Behavior as the Hallmark of Intelligence. Mit Press. 97.score: 540.0
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  2. M. H. A. Newman, Alan M. Turing, Geoffrey Jefferson, R. B. Braithwaite & S. Shieber (2004). Can Automatic Calculating Machines Be Said to Think? In Stuart M. Shieber (ed.), The Turing Test: Verbal Behavior as the Hallmark of Intelligence. Mit Press.score: 360.0
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  3. B. Jack Copeland (2000). The Turing Test. Minds and Machines 10 (4):519-539.score: 240.0
    Turing''s test has been much misunderstood. Recently unpublished material by Turing casts fresh light on his thinking and dispels a number of philosophical myths concerning the Turing test. Properly understood, the Turing test withstands objections that are popularly believed to be fatal.
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  4. William J. Rapaport (2000). How to Pass a Turing Test: Syntactic Semantics, Natural-Language Understanding, and First-Person Cognition. Journal of Logic, Language, and Information 9 (4):467-490.score: 240.0
    I advocate a theory of syntactic semantics as a way of understanding how computers can think (and how the Chinese-Room-Argument objection to the Turing Test can be overcome): (1) Semantics, considered as the study of relations between symbols and meanings, can be turned into syntax – a study of relations among symbols (including meanings) – and hence syntax (i.e., symbol manipulation) can suffice for the semantical enterprise (contra Searle). (2) Semantics, considered as the process of understanding one domain (...)
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  5. James H. Moor (2001). The Status and Future of the Turing Test. Minds and Machines 11 (1):77-93.score: 240.0
    The standard interpretation of the imitation game is defended over the rival gender interpretation though it is noted that Turing himself proposed several variations of his imitation game. The Turing test is then justified as an inductive test not as an operational definition as commonly suggested. Turing's famous prediction about his test being passed at the 70% level is disconfirmed by the results of the Loebner 2000 contest and the absence of (...)
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  6. Bruce Edmonds (2000). The Constructability of Artificial Intelligence (as Defined by the Turing Test). Journal of Logic Language and Information 9 (4):419-424.score: 240.0
    The Turing Test (TT), as originally specified, centres on theability to perform a social role. The TT can be seen as a test of anability to enter into normal human social dynamics. In this light itseems unlikely that such an entity can be wholly designed in anoff-line mode; rather a considerable period of training insitu would be required. The argument that since we can pass the TT,and our cognitive processes might be implemented as a (...) Machine(TM), that consequently a TM that could pass the TT could be built, isattacked on the grounds that not all TMs are constructible in a plannedway. This observation points towards the importance of developmentalprocesses that use random elements (e.g., evolution), but in these casesit becomes problematic to call the result artificial. This hasimplications for the means by which intelligent agents could bedeveloped. (shrink)
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  7. Stuart M. Shieber (ed.) (2004). The Turing Test: Verbal Behavior As the Hallmark of Intelligence. MIT Press.score: 240.0
    Stuart M. Shieber’s name is well known to computational linguists for his research and to computer scientists more generally for his debate on the Loebner Turing Test competition, which appeared a decade earlier in Communications of the ACM (Shieber 1994a, 1994b; Loebner 1994).1 With this collection, I expect it to become equally well known to philosophers.
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  8. Drew McDermott (2014). On the Claim That a Table-Lookup Program Could Pass the Turing Test. Minds and Machines 24 (2):143-188.score: 240.0
    The claim has often been made that passing the Turing Test would not be sufficient to prove that a computer program was intelligent because a trivial program could do it, namely, the “Humongous-Table (HT) Program”, which simply looks up in a table what to say next. This claim is examined in detail. Three ground rules are argued for: (1) That the HT program must be exhaustive, and not be based on some vaguely imagined set of tricks. (2) That (...)
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  9. Sean Zdenek (2001). Passing Loebner's Turing Test: A Case of Conflicting Discourse Functions. [REVIEW] Minds and Machines 11 (1):53-76.score: 240.0
    This paper argues that the Turing test is based on a fixed and de-contextualized view of communicative competence. According to this view, a machine that passes the test will be able to communicate effectively in a variety of other situations. But the de-contextualized view ignores the relationship between language and social context, or, to put it another way, the extent to which speakers respond dynamically to variations in discourse function, formality level, social distance/solidarity among participants, (...)
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  10. Ayse Pinar Saygin, Ilyas Cicekli & Varol Akman (2000). Turing Test: 50 Years Later. [REVIEW] Minds and Machines 10 (4):463-518.score: 240.0
    The Turing Test is one of the most disputed topics in artificial intelligence, philosophy of mind, and cognitive science. This paper is a review of the past 50 years of the Turing Test. Philosophical debates, practical developments and repercussions in related disciplines are all covered. We discuss Turing's ideas in detail and present the important comments that have been made on them. Within this context, behaviorism, consciousness, the `other minds' problem, and similar topics in philosophy (...)
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  11. B. Edmonds (2000). The Constructibility of Artificial Intelligence (as Defined by the Turing Test). Journal of Logic, Language and Information 9 (4):419-424.score: 240.0
    The Turing Test (TT), as originally specified, centres on theability to perform a social role. The TT can be seen as a test of anability to enter into normal human social dynamics. In this light itseems unlikely that such an entity can be wholly designed in an off-line mode; rather a considerable period of training insitu would be required. The argument that since we can pass the TT,and our cognitive processes might be implemented as a Turing (...)
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  12. Ondřej Beran (2014). Wittgensteinian Perspectives on the Turing Test. Studia Philosophica Estonica 7 (1):35-57.score: 240.0
    This paper discusses some difficulties in understanding the Turing test. It emphasizes the importance of distinguishing between conceptual and empirical perspectives and highlights the former as introducing more serious problems for the TT. Some objections against the Turingian framework stemming from the later Wittgenstein’s philosophy are exposed. The following serious problems are examined: 1) It considers a unique and exclusive criterion for thinking which amounts to their identification; 2) it misidentifies the relationship of speaking to thinking as that (...)
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  13. Paweł Łupkowski (2011). A Formal Approach to Exploring the Interrogator's Perspective in the Turing Test. Logic and Logical Philosophy 20 (1-2):139-158.score: 240.0
    My aim in this paper is to use a formal approach to the Turing test. This approach is based on a tool developed within Inferential Erotetic Logic, so called erotetic search scenarios. First, I reconstruct the setting of the Turing test proposed by A.M. Turing. On this basis, I build a model of the test using erotetic search scenarios framework. I use the model to investigate one of the most interesting issues of the TT (...)
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  14. Selmer Bringsjord (2000). Animals, Zombanimals, and the Total Turing Test: The Essence of Artificial Intelligence. Journal of Logic Language and Information 9 (4):397-418.score: 234.0
    Alan Turing devised his famous test (TT) through a slight modificationof the parlor game in which a judge tries to ascertain the gender of twopeople who are only linguistically accessible. Stevan Harnad hasintroduced the Total TT, in which the judge can look at thecontestants in an attempt to determine which is a robot and which aperson. But what if we confront the judge with an animal, and arobot striving to pass for one, and then challenge him to peg (...)
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  15. Jose Hernandez-Orallo (2000). Beyond the Turing Test. Journal of Logic, Language and Information 9 (4):447-466.score: 234.0
    The main factor of intelligence is defined as the ability tocomprehend, formalising this ability with the help of new constructsbased on descriptional complexity. The result is a comprehension <span class='Hi'>test</span>,or C-<span class='Hi'>test</span>, which is exclusively defined in computational terms. Due toits absolute and non-anthropomorphic character, it is equally applicableto both humans and non-humans. Moreover, it correlates with classicalpsychometric tests, thus establishing the first firm connection betweeninformation theoretical notions and traditional IQ tests. The TuringTest is compared with the C-<span (...)
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  16. Saul Traiger (2000). Making the Right Identification in the Turing Test. Minds and Machines 10 (4):561-572.score: 234.0
    The <span class='Hi'>test</span> Turing proposed for machine intelligence is usually understood to be a <span class='Hi'>test</span> of whether a computer can fool a human into thinking that the computer is a human. This standard interpretation is rejected in favor of a <span class='Hi'>test</span> based on the Imitation Game introduced by Turing at the beginning of "Computing Machinery and Intelligence.".
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  17. Stevan Harnad & Itiel Dror (2006). Distributed Cognition: Cognizing, Autonomy and the Turing Test. Pragmatics and Cognition 14 (2):14.score: 228.0
    Some of the papers in this special issue distribute cognition between what is going on inside individual cognizers' heads and their outside worlds; others distribute cognition among different individual cognizers. Turing's criterion for cognition was individual, autonomous input/output capacity. It is not clear that distributed cognition could pass the Turing Test.
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  18. Paul Schweizer (1998). The Truly Total Turing Test. Minds and Machines 8 (2):263-272.score: 228.0
    The paper examines the nature of the behavioral evidence underlying attributions of intelligence in the case of human beings, and how this might be extended to other kinds of cognitive system, in the spirit of the original Turing Test (TT). I consider Harnad's Total Turing Test (TTT), which involves successful performance of both linguistic and robotic behavior, and which is often thought to incorporate the very same range of empirical data that is available in (...)
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  19. Selmer Bringsjord, P. Bello & David A. Ferrucci (2001). Creativity, the Turing Test, and the (Better) Lovelace Test. Minds and Machines 11 (1):3-27.score: 210.0
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  20. Robert M. French (1990). Subcognition and the Limits of the Turing Test. Mind 99 (393):53-66.score: 210.0
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  21. Ayse P. Saygin, Ilyas Cicekli & Varol Akman (2000). Turing Test: 50 Years Later. [REVIEW] Minds and Machines 10 (4):463-518.score: 210.0
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  22. A. P. Saygin & I. Cicekli (2000). Turing Test: 50 Years Later. [REVIEW] Minds and Machines 10 (4):463-518.score: 210.0
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  23. Robert Sparrow (2004). The Turing Triage Test. Ethics and Information Technology 6 (4):203-213.score: 210.0
    If, as a number of writers have predicted, the computers of the future will possess intelligence and capacities that exceed our own then it seems as though they will be worthy of a moral respect at least equal to, and perhaps greater than, human beings. In this paper I propose a test to determine when we have reached that point. Inspired by Alan Turing’s (1950) original “Turing test”, which argued that we would be justified in conceding (...)
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  24. Adam Drozdek (1998). Human Intelligence and Turing Test. AI and Society 12 (4):315-321.score: 210.0
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  25. Adam Drozdek (2001). Descartes' Turing Test. Epistemologia 24 (1):5-29.score: 210.0
  26. Graham Oppy & D. Dowe, The Turing Test. Stanford Encyclopedia of Philosophy.score: 210.0
     
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  27. Blay Whitby (1996). The Turing Test: Ai's Biggest Blind Alley? In Peter Millican & A. Clark (eds.), Machines and Thought. Oxford University Press. 519-539.score: 210.0
     
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  28. Paul Schweizer (2012). The Externalist Foundations of a Truly Total Turing Test. Minds and Machines 22 (3):191-212.score: 208.0
    The paper begins by examining the original Turing Test (2T) and Searle’s antithetical Chinese Room Argument, which is intended to refute the 2T in particular, as well as any formal or abstract procedural theory of the mind in general. In the ensuing dispute between Searle and his own critics, I argue that Searle’s ‘internalist’ strategy is unable to deflect Dennett’s combined robotic-systems reply and the allied Total Turing Test (3T). Many would hold that the 3T marks (...)
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  29. Justin Leiber (1995). On Turing's Turing Test and Why the Matter Matters. Synthese 104 (1):59-69.score: 198.0
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  30. Benny Shanon (1989). A Simple Comment Regarding the Turing Test. Journal for the Theory of Social Behaviour 19 (June):249-56.score: 198.0
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  31. Robert M. French (1995). Refocusing the Debate on the Turing Test: A Response. Behavior and Philosophy 23 (1):59-60.score: 198.0
     
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  32. C. Waterman (1995). The Turing Test and the Argument From Analogy for Other Minds. Southwest Philosophy Review 11 (1):15-22.score: 198.0
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  33. Dale Jacquette (1993). Who's Afraid of the Turing Test? Behavior and Philosophy 20 (21):63-74.score: 192.0
    The Turing Test is a verbal-behavioral operational criterion of artificial intelligence. If a machine can participate in question–and–answer conversation adequately enough to deceive an intelligent interlocutor, then it has intelligent information processing abilities. Robert M. French has argued that recent discoveries in cognitive science about subcognitive processes involving associational primings prove that the Turing Test cannot provide a satisfactory criterion of machine intelligence, that Turing's prediction concerning the feasibility of building machines to play the imitation (...)
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  34. Robert French (2000). The Turing Test: The First Fifty Years. Trends in Cognitive Sciences 4 (3):115-121.score: 180.0
    The Turing Test, originally proposed as a simple operational definition of intelligence, has now been with us for exactly half a century. It is safe to say that no other single article in computer science, and few other articles in science in general, have generated so much discussion. The present article chronicles the comments and controversy surrounding Turing's classic article from its publication to the present. The changing perception of the Turing Test over (...)
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  35. L. Crockett (1994). The Turing Test and the Frame Problem: AI's Mistaken Understanding of Intelligence. Ablex.score: 180.0
    I have discussed the frame problem and the Turing test at length, but I have not attempted to spell out what I think the implications of the frame problem ...
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  36. Tyler Cowen & Michelle Dawson, What Does the Turing Test Really Mean? And How Many Human Beings (Including Turing) Could Pass?score: 180.0
    The so-called Turing test, as it is usually interpreted, sets a benchmark standard for determining when we might call a machine intelligent. We can call a machine intelligent if the following is satisfied: if a group of wise observers were conversing with a machine through an exchange of typed messages, those observers could not tell whether they were talking to a human being or to a machine. To pass the test, the machine has to be intelligent but (...)
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  37. Robert French (1996). The Inverted Turing Test: How a Mindless Program Could Pass It. Psycoloquy 7 (39).score: 180.0
    This commentary attempts to show that the inverted Turing Test (Watt 1996) could be simulated by a standard Turing test and, most importantly, claims that a very simple program with no intelligence whatsoever could be written that would pass the inverted Turing test. For this reason, the inverted Turing test in its present form must be rejected.
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  38. Robert M. French (2000). Peeking Behind the Screen: The Unsuspected Power of the Standard Turing Test. Journal of Experimental and Theoretical Artificial Intelligence 12 (3):331-340.score: 180.0
    No computer that had not experienced the world as we humans had could pass a rigorously administered standard Turing Test. We show that the use of “subcognitive” questions allows the standard Turing Test to indirectly probe the human subcognitive associative concept network built up over a lifetime of experience with the world. Not only can this probing reveal differences in cognitive abilities, but crucially, even differences in _physical aspects_ of the candidates can be detected. (...)
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  39. Stevan Harnad (1992). The Turing Test is Not a Trick: Turing Indistinguishability is a Scientific Criterion. Philosophical Explorations 3 (4):9-10.score: 180.0
    It is important to understand that the Turing Test (TT) is not, nor was it intended to be, a trick; how well one can fool someone is not a measure of scientific progress. The TT is an empirical criterion: It sets AI's empirical goal to be to generate human-scale performance capacity. This goal will be met when the candidate's performance is totally indistinguishable from a human's. Until then, the TT simply represents what it is that AI must (...)
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  40. William J. Rapaport, Review of The Turing Test: Verbal Behavior As the Hallmark of Intelligence. [REVIEW]score: 180.0
    Stuart M. Shieber’s name is well known to computational linguists for his research and to computer scientists more generally for his debate on the Loebner Turing Test competition, which appeared a decade earlier in Communications of the ACM (Shieber 1994a, 1994b; Loebner 1994).1 With this collection, I expect it to become equally well known to philosophers.
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  41. Michael Wheeler, Plastic Machines: Behavioural Diversity and the Turing Test.score: 180.0
    After proposing the Turing Test, Alan Turing himself considered a number of objections to the idea that a machine might eventually pass it. One of the objections discussed by Turing was that no machine will ever pass the Turing Test because no machine will ever “have as much diversity of behaviour as a man”. He responded as follows: the “criticism that a machine cannot have much diversity of behaviour is just a way of saying (...)
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  42. Peter Turney, Answering Subcognitive Turing Test Questions: A Reply to French.score: 180.0
    Robert French has argued that a disembodied computer is incapable of passing a Turing Test that includes subcognitive questions. Subcognitive questions are designed to probe the network of cultural and perceptual associations that humans naturally develop as we live, embodied and embedded in the world. In this paper, I show how it is possible for a disembodied computer to answer subcognitive questions appropriately, contrary to French’s claim. My approach to answering subcognitive questions is to use statistical information (...)
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  43. Robert S. Lockhart (2000). Modularity, Cognitive Penetrability and the Turing Test. Psycoloquy.score: 180.0
    The Turing Test blurs the distinction between a model and irrelevant) instantiation details. Modeling only functional modules is problematic if these are interconnected and cognitively penetrable.
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  44. Robert W. Mitchell & James R. Anderson (1998). Primate Theory of Mind is a Turing Test. Behavioral and Brain Sciences 21 (1):127-128.score: 180.0
    Heyes's literature review of deception, imitation, and self-recognition is inadequate, misleading, and erroneous. The anaesthetic artifact hypothesis of self-recognition is unsupported by the data she herself examines. Her proposed experiment is tantalizing, indicating that theory of mind is simply a Turing test.
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  45. Anthony Chemero, Ascribing Moral Value and the Embodied Turing Test.score: 180.0
    What would it take for an artificial agent to be treated as having moral value? As a first step toward answering this question, we ask what it would take for an artificial agent to be capable of the sort of autonomous, adaptive social behavior that is characteristic of the animals that humans interact with. We propose that this sort of capacity is best measured by what we call the Embodied Turing Test. The Embodied Turing test is (...)
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  46. S. Watt (1996). Naive Psychology and the Inverted Turing Test. Psycoloquy 7 (14).score: 180.0
    This target article argues that the Turing test implicitly rests on a "naive psychology," a naturally evolved psychological faculty which is used to predict and understand the behaviour of others in complex societies. This natural faculty is an important and implicit bias in the observer's tendency to ascribe mentality to the system in the test. The paper analyses the effects of this naive psychology on the Turing test, both from the side of (...)
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  47. Stuart M. Shieber (2007). The Turing Test as Interactive Proof. Noûs 41 (4):686–713.score: 180.0
    In 1950, Alan Turing proposed his eponymous test based on indistinguishability of verbal behavior as a replacement for the question "Can machines think?" Since then, two mutually contradictory but well-founded attitudes towards the Turing Test have arisen in the philosophical literature. On the one hand is the attitude that has become philosophical conventional wisdom, viz., that the Turing Test is hopelessly flawed as a sufficient condition for intelligence, while on the other hand is the (...)
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  48. Stuart M. Shieber (2014). There Can Be No Turing-Test-Passing Memorizing Machines. Philosophers' Imprint 14 (16).score: 180.0
    Anti-behaviorist arguments against the validity of the Turing Test as a sufficient condition for attributing intelligence are based on a memorizing machine, which has recorded within it responses to every possible Turing Test interaction of up to a fixed length. The mere possibility of such a machine is claimed to be enough to invalidate the Turing Test. I consider the nomological possibility of memorizing machines, and how long a Turing Test they can (...)
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  49. Santosh Putchala & Nikhil Agarwal (2011). Machine Vision: An Aid in Reverse Turing Test. [REVIEW] AI and Society 26 (1):95-101.score: 180.0
    Information security is perceived as an important and vital aspect for the survival of any business. Preserving user identity and limiting the access of web resources only to the humans and restricting ‘bots’ is an ever challenging area of study. With the increase in computing power and development of newer approaches towards circumvention and reverse-engineering, the recognition gap present between the machines and the humans is said to be decreasing. Turing test and its modified versions are in place (...)
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  50. Alan Mathison Turing (2012). Alan Turing's Systems of Logic: The Princeton Thesis. Princeton University Press.score: 180.0
     
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