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  1. Intelligence as a Social Concept: a Socio-Technological Interpretation of the Turing Test.Shlomo Danziger - 2022 - Philosophy and Technology 35 (3):1-26.
    Alan Turing’s 1950 imitation game has been widely understood as a means for testing if an entity is intelligent. Following a series of papers by Diane Proudfoot, I offer a socio-technological interpretation of Turing’s paper and present an alternative way of understanding both the imitation game and Turing’s concept of intelligence. Turing, I claim, saw intelligence as a social concept, meaning that possession of intelligence is a property determined by society’s attitude toward the entity. He realized that as long as (...)
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  • Imitation Versus Communication: Testing for Human-Like Intelligence.Jamie Cullen - 2009 - Minds and Machines 19 (2):237-254.
    Turing’s Imitation Game is often viewed as a test for theorised machines that could ‘think’ and/or demonstrate ‘intelligence’. However, contrary to Turing’s apparent intent, it can be shown that Turing’s Test is essentially a test for humans only. Such a test does not provide for theorised artificial intellects with human-like, but not human-exact, intellectual capabilities. As an attempt to bypass this limitation, I explore the notion of shifting the goal posts of the Turing Test, and related tests such as the (...)
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  • Turing's Two Tests for Intelligence.Susan G. Sterrett - 1999 - Minds and Machines 10 (4):541-559.
    On a literal reading of `Computing Machinery and Intelligence'', Alan Turing presented not one, but two, practical tests to replace the question `Can machines think?'' He presented them as equivalent. I show here that the first test described in that much-discussed paper is in fact not equivalent to the second one, which has since become known as `the Turing Test''. The two tests can yield different results; it is the first, neglected test that provides the more appropriate indication of intelligence. (...)
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  • The Turing Test: The First Fifty Years.Robert M. French - 2000 - Trends in Cognitive Sciences 4 (3):115-121.
    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 the last fifty years has paralleled the (...)
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  • Revisiting Turing and His Test: Comprehensiveness, Qualia, and the Real World.Vincent C. Müller & Aladdin Ayesh (eds.) - 2012 - AISB.
    Proceedings of the papers presented at the Symposium on "Revisiting Turing and his Test: Comprehensiveness, Qualia, and the Real World" at the 2012 AISB and IACAP Symposium that was held in the Turing year 2012, 2–6 July at the University of Birmingham, UK. Ten papers. - http://www.pt-ai.org/turing-test --- Daniel Devatman Hromada: From Taxonomy of Turing Test-Consistent Scenarios Towards Attribution of Legal Status to Meta-modular Artificial Autonomous Agents - Michael Zillich: My Robot is Smarter than Your Robot: On the Need for (...)
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  • Human Intelligence and Turing Test.Adam Drozdek - 1998 - AI and Society 12 (4):315-321.
  • Minimum Intelligent Signal Test as an Alternative to the Turing Test.Paweł Łupkowski & Patrycja Jurowska - 2019 - Diametros 59:35-47.
    The aim of this paper is to present and discuss the issue of the adequacy of the Minimum Intelligent Signal Test (MIST) as an alternative to the Turing Test. MIST has been proposed by Chris McKinstry as a better alternative to Turing’s original idea. Two of the main claims about MIST are that (1) MIST questions exploit commonsense knowledge and as a result are expected to be easy to answer for human beings and difficult for computer programs; and that (2) (...)
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  • Intelligence is Not Enough: On the Socialization of Talking Machines. [REVIEW]E. Ronald & Moshe Sipper - 2001 - Minds and Machines 11 (4):567-576.
    Since the introduction of the imitation game by Turing in 1950 there has been much debate as to its validity in ascertaining machine intelligence. We wish herein to consider a different issue altogether: granted that a computing machine passes the Turing Test, thereby earning the label of ``Turing Chatterbox'', would it then be of any use (to us humans)? From the examination of scenarios, we conclude that when machines begin to participate in social transactions, unresolved issues of trust and responsibility (...)
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  • Artificial Intelligences as Extended Minds. Why Not?Gianfranco Pellegrino & Mirko Daniel Garasic - 2020 - Rivista Internazionale di Filosofia e Psicologia 11 (2):150-168.
    : Artificial intelligences and robots increasingly mimic human mental powers and intelligent behaviour. However, many authors claim that ascribing human mental powers to them is both conceptually mistaken and morally dangerous. This article defends the view that artificial intelligences can have human-like mental powers, by claiming that both human and artificial minds can be seen as extended minds – along the lines of Chalmers and Clark’s view of mind and cognition. The main idea of this article is that the Extended (...)
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  • The Philosophising Machine – a Specification of the Turing Test.Arthur C. Schwaninger - 2022 - Philosophia 50 (3):1437-1453.
    Block’s, 5–43 1981) anti-behaviourist attack of the Turing Test not only illustrates that the test is a non-sufficient criterion for attributing thought; I suggest that it also exemplifies the limiting case of the more general concern that a machine which has access to enormous amounts of data can pass the Turing Test by simple symbol-manipulation techniques. If the answers to a human interrogator are entailed by the machines’ data, the Turing Test offers no clear criterion to distinguish between a thinking (...)
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  • Answering Subcognitive Turing Test Questions: A Reply to French.Peter Turney - 2001
    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 extracted from a (...)
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  • The Constructability of Artificial Intelligence.Bruce Edmonds - 2000 - Journal of Logic Language and Information 9 (4):419-424.
    The Turing Test, 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 Turing Machine, that consequently a TM that (...)
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  • The Turing Test.Graham Oppy & D. Dowe - 2003 - Stanford Encyclopedia of Philosophy.
    This paper provides a survey of philosophical discussion of the "the Turing Test". In particular, it provides a very careful and thorough discussion of the famous 1950 paper that was published in Mind.
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  • Dismantling the Chinese Room with linguistic tools: a framework for elucidating concept-application disputes.Lawrence Lengbeyer - forthcoming - AI and Society:1-19.
    Imagine advanced computers that could, by virtue merely of being programmed in the right ways, act, react, communicate, and otherwise behave like humans. Might such computers be capable of understanding, thinking, believing, and the like? The framework developed in this paper for tackling challenging questions of concept application answers in the affirmative, contrary to Searle’s famous ‘Chinese Room’ thought experiment, which purports to prove that ascribing such mental processes to computers like these would be necessarily incorrect. The paper begins by (...)
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  • The Turing Test as Interactive Proof.Stuart M. Shieber - 2007 - Noûs 41 (4):686–713.
    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 overwhelming sense that were a machine (...)
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  • The Embodied Cognition Research Programme.Larry Shapiro - 2007 - Philosophy Compass 2 (2):338–346.
  • Brain Simulation and Personhood: A Concern with the Human Brain Project.Daniel Lim - 2014 - Ethics and Information Technology 16 (2):77-89.
    The Human Brain Project (HBP) is a massive interdisciplinary project involving hundreds of researchers across more than eighty institutions that seeks to leverage cutting edge information and communication technologies to create a multi-level brain simulation platform (BSP). My worry is that some brain models running on the BSP will be persons. If this is right then not only will the in silico experiments the HBP envisions being carried on the BSP be unethical the mere termination of certain brain models running (...)
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  • On the Claim That a Table-Lookup Program Could Pass the Turing Test.Drew McDermott - 2014 - Minds and Machines 24 (2):143-188.
    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 the HT (...)
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  • The Turing Test.B. Jack Copeland - 2000 - Minds and Machines 10 (4):519-539.
    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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  • Philosophy of Mind Is (in Part) Philosophy of Computer Science.Darren Abramson - 2011 - Minds and Machines 21 (2):203-219.
    In this paper I argue that whether or not a computer can be built that passes the Turing test is a central question in the philosophy of mind. Then I show that the possibility of building such a computer depends on open questions in the philosophy of computer science: the physical Church-Turing thesis and the extended Church-Turing thesis. I use the link between the issues identified in philosophy of mind and philosophy of computer science to respond to a prominent argument (...)
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  • The Logic of Searle’s Chinese Room Argument.Robert I. Damper - 2006 - Minds and Machines 16 (2):163-183.
    John Searle’s Chinese room argument is a celebrated thought experiment designed to refute the hypothesis, popular among artificial intelligence scientists and philosophers of mind, that “the appropriately programmed computer really is a mind”. Since its publication in 1980, the CRA has evoked an enormous amount of debate about its implications for machine intelligence, the functionalist philosophy of mind, theories of consciousness, etc. Although the general consensus among commentators is that the CRA is flawed, and not withstanding the popularity of the (...)
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  • The Status and Future of the Turing Test.James H. Moor - 2001 - Minds and Machines 11 (1):77-93.
    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 any serious Turing test competitors from AI on the (...)
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  • Minds, Machines and Turing: The Indistinguishability of Indistinguishables.Stevan Harnad - 2000 - Journal of Logic, Language and Information 9 (4):425-445.
    Turing's celebrated 1950 paper proposes a very general methodological criterion for modelling mental function: total functional equivalence and indistinguishability. His criterion gives rise to a hierarchy of Turing Tests, from subtotal ("toy") fragments of our functions (t1), to total symbolic (pen-pal) function (T2 -- the standard Turing Test), to total external sensorimotor (robotic) function (T3), to total internal microfunction (T4), to total indistinguishability in every empirically discernible respect (T5). This is a "reverse-engineering" hierarchy of (decreasing) empirical underdetermination of the theory (...)
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  • Simulating Convesations: The Communion Game. [REVIEW]Stephen J. Cowley & Karl MacDorman - 1995 - AI and Society 9 (2-3):116-137.
    In their enthusiasm for programming, computational linguists have tended to lose sight of what humansdo. They have conceived of conversations as independent of sound and the bodies that produce it. Thus, implicit in their simulations is the assumption that the text is the essence of talk. In fact, unlike electronic mail, conversations are acoustic events. During everyday talk, human understanding depends both on the words spoken and on fine interpersonal vocal coordination. When utterances are analysed into sequences of word-based forms, (...)
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  • Turingův test: filozofické aspekty umělé inteligence.Filip Tvrdý - 2011 - Dissertation, Palacky University
    Disertační práce se zabývá problematikou připisování myšlení jiným entitám, a to pomocí imitační hry navržené v roce 1950 britským filosofem Alanem Turingem. Jeho kritérium, známé v dějinách filosofie jako Turingův test, je podrobeno detailní analýze. Práce popisuje nejen původní námitky samotného Turinga, ale především pozdější diskuse v druhé polovině 20. století. Největší pozornost je věnována těmto kritikám: Lucasova matematická námitka využívající Gödelovu větu o neúplnosti, Searlův argument čínského pokoje konstatující nedostatečnost syntaxe pro sémantiku, Blockův návrh na použití brutální síly pro (...)
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  • Imitation Game: Threshold or Watershed?Eric Neufeld & Sonje Finnestad - 2020 - Minds and Machines 30 (4):637-657.
    Showing remarkable insight into the relationship between language and thought, Alan Turing in 1950 proposed the Imitation Game as a proxy for the question “Can machines think?” and its meaning and practicality have been debated hotly ever since. The Imitation Game has come under criticism within the Computer Science and Artificial Intelligence communities with leading scientists proposing alternatives, revisions, or even that the Game be abandoned entirely. Yet Turing’s imagined conversational fragments between human and machine are rich with complex instances (...)
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  • AAAI: An Argument Against Artificial Intelligence.Sander Beckers - 2017 - In Vincent Müller (ed.), Philosophy and theory of artificial intelligence 2017. Berlin: Springer. pp. 235-247.
    The ethical concerns regarding the successful development of an Artificial Intelligence have received a lot of attention lately. The idea is that even if we have good reason to believe that it is very unlikely, the mere possibility of an AI causing extreme human suffering is important enough to warrant serious consideration. Others look at this problem from the opposite perspective, namely that of the AI itself. Here the idea is that even if we have good reason to believe that (...)
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  • Introduction to the Special Issue on Philosophical Foundations of Artificial Intelligence.Varol Akman - 2000 - Journal of Experimental and Theoretical Artificial Intelligence 12 (3):247-250.
    This is the guest editor's introduction to a JETAI special issue on philosophical foundations of AI.
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  • Universal Intelligence: A Definition of Machine Intelligence.Shane Legg & Marcus Hutter - 2007 - Minds and Machines 17 (4):391-444.
    A fundamental problem in artificial intelligence is that nobody really knows what intelligence is. The problem is especially acute when we need to consider artificial systems which are significantly different to humans. In this paper we approach this problem in the following way: we take a number of well known informal definitions of human intelligence that have been given by experts, and extract their essential features. These are then mathematically formalised to produce a general measure of intelligence for arbitrary machines. (...)
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  • The Uncanny Advantage of Using Androids in Cognitive and Social Science Research.Karl F. MacDorman & Hiroshi Ishiguro - 2006 - Interaction Studies. Social Behaviour and Communication in Biological and Artificial Systemsinteraction Studies / Social Behaviour and Communication in Biological and Artificial Systemsinteraction Studies 7 (3):297-337.
    The development of robots that closely resemble human beings can contribute to cognitive research. An android provides an experimental apparatus that has the potential to be controlled more precisely than any human actor. However, preliminary results indicate that only very humanlike devices can elicit the broad range of responses that people typically direct toward each other. Conversely, to build androids capable of emulating human behavior, it is necessary to investigate social activity in detail and to develop models of the cognitive (...)
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  • Refocusing the Debate on the Turing Test: A Reply to Jacquette.Robert M. French - 1995 - Behavior and Philosophy 23 (1):59 - 60.
  • If It Walks Like a Duck and Quacks Like a Duck... The Turing Test, Intelligence and Consciousness.R. French - 2009 - In Bayne Tim, Cleeremans Axel & Wilken Patrick (eds.), The Oxford Companion to Consciousness. Oxford University Press. pp. 461--463.
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  • Précis of Semantic Cognition: A Parallel Distributed Processing Approach.Timothy T. Rogers & James L. McClelland - 2008 - Behavioral and Brain Sciences 31 (6):689-714.
    In this prcis we focus on phenomena central to the reaction against similarity-based theories that arose in the 1980s and that subsequently motivated the approach to semantic knowledge. Specifically, we consider (1) how concepts differentiate in early development, (2) why some groupings of items seem to form or coherent categories while others do not, (3) why different properties seem central or important to different concepts, (4) why children and adults sometimes attest to beliefs that seem to contradict their direct experience, (...)
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  • A Formal Approach to Exploring the Interrogator's Perspective in the Turing Test.Paweł Łupkowski - 2011 - Logic and Logical Philosophy 20 (1-2):139-158.
    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 setting – the interrogator’s perspective and (...)
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  • The Social Embedding of Intelligence.Bruce Edmonds - manuscript
    I claim that in order to pass the Turing Test over any period of extended time, it will necessary to embed the entity into society. This chapter discusses why this is, and how it might be brought about. I start by arguing that intelligence is better characterised by tests of social interaction, especially in open-ended and extended situations. I then argue that learning is an essential component of intelligence and hence that a universal intelligence is impossible. These two arguments support (...)
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  • Learning, Social Intelligence and the Turing Test.Bruce Edmonds & Carlos Gershenson - 2012 - In S. Barry Cooper (ed.), How the World Computes. pp. 182--192.
  • Analogical Reminding and the Storage of Experience: The Paradox of Hofstadter-Sander.Stephen Robbins - 2017 - Phenomenology and the Cognitive Sciences 16 (3):355-385.
    In their exhaustive study of the cognitive operation of analogy, Hofstadter and Sander arrive at a paradox: the creative and inexhaustible production of analogies in our thought must derive from a “reminding” operation based upon the availability of the detailed totality of our experience. Yet the authors see no way that our experience can be stored in the brain in such detail nor do they see how such detail could be accessed or retrieved such that the innumerable analogical remindings we (...)
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  • Twenty Years Beyond the Turing Test: Moving Beyond the Human Judges Too.José Hernández-Orallo - 2020 - Minds and Machines 30 (4):533-562.
    In the last 20 years the Turing test has been left further behind by new developments in artificial intelligence. At the same time, however, these developments have revived some key elements of the Turing test: imitation and adversarialness. On the one hand, many generative models, such as generative adversarial networks, build imitators under an adversarial setting that strongly resembles the Turing test. The term “Turing learning” has been used for this kind of setting. On the other hand, AI benchmarks are (...)
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  • Moral Agency and Advancements in Artificial Intelligence.Arielle L. Zuckerberg - unknown
    The main trends underlying advancements in AI technology are increased autonomy, increased functionality, higher level social interaction and integration, and, many suggest, hard-wired ethical codes of conduct. These trends, along with the promises of engineers and scientists, give us ample reason to evaluate the agency of future AI machines.
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  • Meaning, Prototypes and the Future of Cognitive Science.Jaap van Brakel - 1991 - Minds and Machines 1 (3):233-57.
    In this paper I evaluate the soundness of the prototype paradigm, in particular its basic assumption that there are pan-human psychological essences or core meanings that refer to basic-level natural kinds, explaining why, on the whole, human communication and learning are successful. Instead I argue that there are no particular pan-human basic elements for thought, meaning and cognition, neither prototypes, nor otherwise. To illuminate my view I draw on examples from anthropology. More generally I argue that the prototype paradigm exemplifies (...)
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  • Semantic Redintegration: Ecological Invariance.Stephen E. Robbins - 2008 - Behavioral and Brain Sciences 31 (6):726-727.
    In proposing that their model can operate in the concrete, perceptual world, Rogers & McClelland (R&M) have not done justice to the complexities of the ecological sphere and its invariance laws. The structure of concrete events forces a different framework, both for retrieval of events and concepts defined across events, than that upon which the proposed model, rooted in essence in the verbal learning tradition, implicitly rests.
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  • Meaning, Prototypes and the Future of Cognitive Science.J. Brakel - 1991 - Minds and Machines 1 (3):233-257.
    In this paper I evaluate the soundness of the prototype paradigm, in particular its basic assumption that there are pan-human psychological essences or core meanings that refer to basic-level natural kinds, explaining why, on the whole, human communication and learning are successful. Instead I argue that there are no particular pan-human basic elements for thought, meaning and cognition, neither prototypes, nor otherwise. To illuminate my view I draw on examples from anthropology. More generally I argue that the prototype paradigm exemplifies (...)
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