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Diane Proudfoot
University of Canterbury
  1. Possible Worlds Semantics and Fiction.Diane Proudfoot - 2006 - Journal of Philosophical Logic 35:9-40.
    The canonical version of possible worlds semantics for story prefixes is due to David Lewis. This paper reassesses Lewis's theory and draws attention to some novel problems for his account.
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  2. Anthropomorphism: Opportunities and Challenges in Human-Robot Interaction.Diane Proudfoot, Jakub Zlotowski, Kumar Yogeeswaran & Christoph Bartneck - 2015 - International Journal of Social Robotics 7 (3):347-360.
    Anthropomorphism is a phenomenon that describes the human tendency to see human-like shapes in the environment. It has considerable consequences for people’s choices and beliefs. With the increased presence of robots, it is important to investigate the optimal design for this tech- nology. In this paper we discuss the potential benefits and challenges of building anthropomorphic robots, from both a philosophical perspective and from the viewpoint of empir- ical research in the fields of human–robot interaction and social psychology. We believe (...)
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  3.  39
    Rethinking Turing’s Test and the Philosophical Implications.Diane Proudfoot - 2020 - Minds and Machines 30 (4):487-512.
    In the 70 years since Alan Turing’s ‘Computing Machinery and Intelligence’ appeared in Mind, there have been two widely-accepted interpretations of the Turing test: the canonical behaviourist interpretation and the rival inductive or epistemic interpretation. These readings are based on Turing’s Mind paper; few seem aware that Turing described two other versions of the imitation game. I have argued that both readings are inconsistent with Turing’s 1948 and 1952 statements about intelligence, and fail to explain the design of his game. (...)
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  4.  64
    Deviant Encodings and Turing’s Analysis of Computability.B. Jack Copeland & Diane Proudfoot - 2010 - Studies in History and Philosophy of Science Part A 41 (3):247-252.
    Turing’s analysis of computability has recently been challenged; it is claimed that it is circular to analyse the intuitive concept of numerical computability in terms of the Turing machine. This claim threatens the view, canonical in mathematics and cognitive science, that the concept of a systematic procedure or algorithm is to be explicated by reference to the capacities of Turing machines. We defend Turing’s analysis against the challenge of ‘deviant encodings’.Keywords: Systematic procedure; Turing machine; Church–Turing thesis; Deviant encoding; Acceptable encoding; (...)
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  5.  67
    On Alan Turing's Anticipation of Connectionism.Diane Proudfoot & Jack Copeland - 1996 - Synthese 108:361-367.
    It is not widely realised that Turing was probably the first person to consider building computing machines out of simple, neuron-like elements connected together into networks in a largely random manner. Turing called his networks 'unorganised machines'. By the application of what he described as 'appropriate interference, mimicking education' an unorganised machine can be trained to perform any task that a Turing machine can carry out, provided the number of 'neurons' is sufficient. Turing proposed simulating both the behaviour of the (...)
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  6. Rethinking Turing’s Test.Diane Proudfoot - 2013 - Journal of Philosophy 110 (7):391-411.
  7. Turing and the First Electronic Brains: What the Papers Said.Diane Proudfoot & Jack Copeland - 2019 - In M. Colombo & M. Sprevak (eds.), Routledge Handbook of the Computational Mind. pp. 23-37.
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  8.  3
    Anthropomorphism and AI: Turingʼs Much Misunderstood Imitation Game.Diane Proudfoot - 2011 - Artificial Intelligence 175 (5-6):950-957.
    The widespread tendency, even within AI, to anthropomorphize machines makes it easier to convince us of their intelligence. How can any putative demonstration of intelligence in machines be trusted if the AI researcher readily succumbs to make-believe? This is (what I shall call) the forensic problem of anthropomorphism. I argue that the Turing test provides a solution. This paper illustrates the phenomenon of misplaced anthropomorphism and presents a new perspective on Turingʼs imitation game. It also examines the role of the (...)
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  9. Software Immortals—Science or Faith?Diane Proudfoot - 2013 - In A. Eden, J. Søraker, J. Moor & E. Steinhart (eds.), The Singularity Hypothesis—A Scientific and Philosophical Assessment. pp. 367-389.
    According to the early futurist Julian Huxley, human life as we know it is ‘a wretched makeshift, rooted in ignorance’. With modern science, however, ‘the present limitations and miserable frustrations of our existence could be in large measure surmounted’ and human life could be ‘transcended by a state of existence based on the illumination of knowledge’ (1957b, p. 16).
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  10. Artificial Intelligence.Diane Proudfoot & Jack Copeland - 2011 - In E. Margolis, R. Samuels & S. Stich (eds.), Oxford Handbook of Philosophy of Cognitive Science. pp. 147-182.
    In this article the central philosophical issues concerning human-level artificial intelligence (AI) are presented. AI largely changed direction in the 1980s and 1990s, concentrating on building domain-specific systems and on sub-goals such as self-organization, self-repair, and reliability. Computer scientists aimed to construct intelligence amplifiers for human beings, rather than imitation humans. Turing based his test on a computer-imitates-human game, describing three versions of this game in 1948, 1950, and 1952. The famous version appears in a 1950 article in Mind, ‘Computing (...)
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  11.  13
    Sylvan's Bottle and Other Problems.Diane Proudfoot - 2018 - Australasian Journal of Logic 15 (2):95-123.
    According to Richard Routley, a comprehensive theory of fiction is impossible, since almost anything is in principle imaginable. In my view, Routley is right: for any purported logic of fiction, there will be actual or imaginable fictions that successfully counterexample the logic. Using the example of ‘impossible’ fictions, I test this claim against theories proposed by Routley’s Meinongian contemporaries and also by Routley himself and his 21st century heirs. I argue that the phenomenon of impossible fictions challenges even today’s modal (...)
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  12. Alan Turing’s Forgotten Ideas in Computer Science.Diane Proudfoot & Jack Copeland - 1999 - Scientific American 280 (4):99-103.
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  13.  83
    Turing, Wittgenstein and the Science of the Mind.Diane Proudfoot & Jack Copeland - 1994 - Australasian Journal of Philosophy 72:497-519.
  14. Time to Reinspect the Foundations?Diane Proudfoot, Jack Copeland, Eli Dresner & Oron Shagrir - 2016 - Communications of the Acm 59 (11):34-38.
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  15. Turing’s Test: A Philosophical and Historical Guide.Diane Proudfoot & Jack Copeland - 2008 - In R. Epstein, G. Roberts & G. Beber (eds.), Parsing the Turing Test: Philosophical and Methodological Issues. pp. 119-138.
    We set the Turing Test in the historical context of the development of machine intelligence, describe the different forms of the test and its rationale, and counter common misinterpretations and objections. Recently published material by Turing casts fresh light on his thinking.
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  16. Can a Robot Smile? Wittgenstein on Facial Expression.Diane Proudfoot - 2013 - In T. P. Racine & K. L. Slaney (eds.), A Wittgensteinian Perspective on the Use of Conceptual Analysis in Psychology. pp. 172-194.
    Recent work in social robotics, which is aimed both at creating an artificial intelligence and providing a test-bed for psychological theories of human social development, involves building robots that can learn from ‘face-to-face’ interaction with human beings — as human infants do. The building-blocks of this interaction include the robot’s ‘expressive’ behaviours, for example, facial-expression and head-and-neck gesture. There is here an ideal opportunity to apply Wittgensteinian conceptual analysis to current theoretical and empirical work in the sciences. Wittgenstein’s philosophical psychology (...)
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  17. More Human Than Human: Does The Uncanny Curve Really Matter?Diane Proudfoot, Jakub Zlotowski & Christoph Bartneck - 2013 - In Proceedings of the HRI2013 Workshop on Design of Humanlikeness in HRI: from uncanny valley to minimal design. pp. 7-13.
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  18. How Human Can They Get? [REVIEW]Diane Proudfoot - 1999 - Science 248:745.
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  19. Turing and Free Will: A New Take on an Old Debate.Diane Proudfoot - 2017 - In Alisa Bokulich & Juliet Floyd (eds.), Philosophical Explorations of the Legacy of Alan Turing: Turing 100. Berlin: Springer Verlag. pp. 305-321.
    In 1948 Turing claimed that the concept of intelligence is an “emotional concept”. An emotional concept is a response-dependent concept and Turing’s remarks in his 1948 and 1952 papers suggest a response-dependence approach to the concept of intelligence. On this view, whether or not an object is intelligent is determined, as Turing said, “as much by our own state of mind and training as by the properties of the object”. His discussion of free will suggests a similar approach. Turing said, (...)
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  20. Child Machines.Diane Proudfoot - 2017 - In Jack Copeland, Jonathan P. Bowen, Mark Sprevak, Robin Wilson & Others (eds.), The Turing Guide. pp. 315-325.
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  21. The Turing Test -- From Every Angle.Diane Proudfoot - 2017 - In Jack Copeland, Jonathan P. Bowen, Mark Sprevak, Robin Wilson & Others (eds.), The Turing Guide. pp. 287-300.
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  22. Meaning and Mind: Wittgenstein’s Relevance for the “Does Language Shape Thought?” Debate.Diane Proudfoot - 2009 - New Ideas in Psychology 27:163-183.
    This paper explores the relevance of Wittgenstein’s philosophi- cal psychology for the two major contemporary approaches to the relation between language and cognition. As Pinker describes it, on the ‘Standard Social Science Model’ language is ‘an insidious shaper of thought’. According to Pinker’s own widely–shared alternative view, ‘Language is the magnificent faculty that we use to get thoughts from one head to another’. I investigate Wittgenstein’s powerful challenges to the hypothe- sis that language is a device for communicating independently constituted (...)
     
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  23. Mocking AI Panic.Diane Proudfoot - 2015 - IEEE Spectrum 52 (7):46-47.
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  24.  85
    AI’s New Promise: Our Posthuman Future.Jack Copeland & Diane Proudfoot - 2012 - The Philosophers' Magazine 57:73-78.
  25. Turing’s Three Senses of “Emotional”.Diane Proudfoot - 2014 - International Journal of Synthetic Emotions 5 (2):7-20.
    Turing used the expression “emotional” in three distinct ways: to state his philosophical theory of the concept of intelligence, to classify arguments for and against the possibility of machine intelligence, and to describe the education of a “child machine”. The remarks on emotion include several of the most important philosophical claims. This paper analyses these remarks and their significance for current research in Artificial Intelligence.
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  26.  78
    The Implications of an Externalist Theory of Rule-Following Behavior for Robot Cognition.Diane Proudfoot - 2004 - Minds and Machines 14 (3):283-308.
    Given (1) Wittgensteins externalist analysis of the distinction between following a rule and behaving in accordance with a rule, (2) prima facie connections between rule-following and psychological capacities, and (3) pragmatic issues about training, it follows that most, even all, future artificially intelligent computers and robots will not use language, possess concepts, or reason. This argument suggests that AIs traditional aim of building machines with minds, exemplified in current work on cognitive robotics, is in need of substantial revision.
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  27. Turing and the Computer.Diane Proudfoot & Jack Copeland - 2012 - In Jack Copeland & Others (eds.), Alan Turing’s Electronic Brain. Oxford and New York: pp. 107-148.
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  28. Wittgenstein’s Anticipation of the Chinese Room.Diane Proudfoot - 2002 - In J. Preston & M. Bishop (eds.), Views into the Chinese Room: New Essays on Searle and Artificial Intelligence. Oxford and New York: pp. 167-180.
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  29. Wittgenstein's Anticipation of the Chinese Room.Diane Proudfoot - 2002 - In John M. Preston & John Mark Bishop (eds.), Views Into the Chinese Room: New Essays on Searle and Artificial Intelligence. Oxford University Press.
  30. Alan Turing, Father of the Modern Computer.Diane Proudfoot & Jack Copeland - 2011 - Rutherford Journal: The New Zealand Journal for the History and Philosophy of Science and Technology 4.
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  31.  45
    Jakob Hohwy, The Predictive Mind. [REVIEW]Diane Proudfoot - 2014 - Australasian Journal of Philosophy 93 (1):207-208.
  32. Two Lectures on Religion by Karl Popper.Diane Proudfoot - 2011 - In C. Jones, B. Matthews & J. Clement (eds.), Treasures of the University Canterbury Library. pp. 173-177.
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  33. Artificial Intelligence: History, Foundations, and Philosophical Issues.Diane Proudfoot & Jack Copeland - 2006 - In P. Thagard (ed.), Handbook of the Philosophy of Psychology and Cognitive Science. pp. 429-482.
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  34. A New Interpretation of the Turing Test.Diane Proudfoot - 2005 - Rutherford Journal: The New Zealand Journal for the History and Philosophy of Science and Technology 1.
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  35. Alan Turing and Evil AI.Diane Proudfoot - 2018 - OUPBlog: Oxford University Press’s Academic Insights for the Thinking World.
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  36. Alan Turing: Codebreaker and Computer Pioneer.Diane Proudfoot & Jack Copeland - 2004 - History Today 54 (7):7.
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  37. Connectionism: Computing with Neurons.Diane Proudfoot & Jack Copeland - 2017 - In Jack Copeland, Jonathan P. Bowen, Mark Sprevak, Robin Wilson & Others (eds.), The Turing Guide. Oxford: pp. 309-314.
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  38. Design and Implementation of a New E-Learning Tool to Develop Self-Motivated Learning.Diane Proudfoot - 2011 - Journal of Adult Learning Aotearoa New Zealand 39 (1):98-103.
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  39. Diane Proudfoot on “What Does Philosophy of Religion Offer to the Modern University?”.Diane Proudfoot - 2016 - Philosophy of Religion: Big Question Philosophy for Scholars and Students.
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  40. Diane Proudfoot on “What is Philosophy of Religion?”.Diane Proudfoot - 2014 - Philosophy of Religion: Big Question Philosophy for Scholars and Students.
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  41. Enigma Variations. [REVIEW]Diane Proudfoot & Jack Copeland - 1998 - Times Literary Supplement 4970:6.
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  42. Facts About Artificial Intelligence.Diane Proudfoot - 1999 - Science 285:835.
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  43. Fictional Entities.Diane Proudfoot - 2009 - In S. Davies, K. M. Higgins, R. Hopkins, R. Stecker & D. E. Cooper (eds.), A Companion to Aesthetics. pp. 284-287.
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  44. Fictional Entities.Diane Proudfoot - 2009 - In S. Davies, K. M. Higgins, R. Hopkins, R. Stecker & D. E. Cooper (eds.), A Companion to Aesthetics. pp. 284-287.
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  45. ‘Intelligent Machinery’: Foreword to Christof Teuscher, Turing’s Connectionism: An Investigation of Neural Network Architectures (Vii-Xiii).Diane Proudfoot & Jack Copeland - 2002 - In Turing’s Connectionism: An Investigation of Neural Network Architectures.
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  46. Robots and Rule-Following.Diane Proudfoot - 2004 - In C. Teuscher (ed.), Alan Turing: Life and Legacy of a Great Thinker. Berlin, German: pp. 359-379.
    Turing was probably the first person to advocate the pursuit of robotics as a route to Artificial Intelligence and Wittgenstein the first to argue that, without the appropriate history, no machine could be intelligent. Wittgenstein anticipated much recent theorizing about the mind, including aspects of connectionist theo- ries of mind and the situated cognition approach in AI. Turing and Wittgenstein had a wary respect for each other and there is significant overlap in their work, in both the philosophy of mathematics (...)
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  47. Turing’s Concept of Intelligence.Diane Proudfoot - 2017 - In Jack Copeland, Jonathan P. Bowen, Mark Sprevak, Robin Wilson & Others (eds.), The Turing Guide. pp. 301-307.
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  48. Two Lectures on Religion by Karl Popper.Diane Proudfoot - 2011 - In C. Jones, B. Matthews & J. Clement (eds.), Treasures of the University Canterbury Library. pp. 173-177.
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  49. The Legacy of Alan Turing. [REVIEW]Diane Proudfoot & Jack Copeland - 1998 - Mind 108:187-195.
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  50. Turing’s Mystery Machine.Diane Proudfoot & Jack Copeland - 2019 - American Philosophical Association Newsletter for Philosophy and Computers 18 (2):1-6.
    This is a detective story. The starting-point is a philosophical discussion in 1949, where Alan Turing mentioned a machine whose program, he said, would in practice be “impossible to find.” Turing used his unbreakable machine example to defeat an argument against the possibility of artificial intelligence. Yet he gave few clues as to how the program worked. What was its structure such that it could defy analysis for (he said) “a thousand years”? Our suggestion is that the program simulated a (...)
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