About this topic
Summary This category is about whether or not computers, robots, and software agents can literally be said to think.  Humans think, chimps think, dogs think, cats and birds think. But do computers?  Is your computer thinking now?  Perhaps only specially programmed computers think?  Or perhaps only computers with special hardware can think -- hardware that resembles the neurons of the brain, for example. If computers can be made to think, then does that mean that humans are a kind of robot and their brains a kind of computer -- a neurocomputer, say?  One of the deeper issues here is that the term "thinking" is ambiguous in at least two ways: It can include being conscious of one's environment (surroundings), one's personal feelings and thoughts, etc., or it can mean cogitate, learn, plan, and solve problems, where these latter terms pick out mental events that may or may not be conscious.   
Key works The idea that machines could think occurred to the very first computer builders and programmers.  See, e.g., Alan Turing's great paper Turing 1950.  The term "artificial intelligence" (AI) goes back to a summer conference in held 1956 at Dartmouth College in New Hampshire.  Many AI pioneers took it for granted that within a decade or two computers would be as intelligent as humans.  A central paper from this time is McCarthy & Hayes 1969.  Another crucial paper is Putnam's Putnam 1960.  But the optimism proved to be unjustified.  The decades came and went without machines achieving human-level intelligence.  Soon several philosophers and other researchers argued that computers would never think and that human brains and minds were completely different from computers.  The most important paper in this push-back was John Searle's famous paper: Searle 1980, where he argues that machines cannot think at all because they lack the proper semantical connection to the world.  Summaries and replies to Searle's paper accompany it in the same journal issue (Searle 1980).  Also, a summary of Searle's anti-AI argument and many replies to it can be found in Dietrich 1994.  Another form of attack on AI came from Lucas 1961, who argued that Godel's famous Incompleteness Theorems showed that machines could not think.  This theme was reinvigorated by Roger Penrose in his well-known book Penrose 1989.  Yet another form of attack on AI came from Fodor 1987.  All of these attacks on AI spawned a large literature trying to refute them, agreeing with them, or amending them. To this day, it is not known whether or not machines (computers) can think, nor if humans are machines.  Nevertheless, the effort to build intelligent machines continues, and this is probably the best way to answer the question.
Introductions See Searle 1980 and the associated replies for a good introduction to the issues surrounding Searle's attack on AI. For some good history of AI, which raises many important issues, see Pamela McCorduck's McCorduck 2004 and Daniel Crevier's AI: The Tumultuous Search for Artificial Intelligence (1993).  
Related categories

1974 found
Order:
1 — 50 / 1974
Material to categorize
  1. Philosophy and Theory of Artificial Intelligence 2017.Vincent C. Müller (ed.) - 2017 - Berlin: Springer.
    This book reports on the results of the third edition of the premier conference in the field of philosophy of artificial intelligence, PT-AI 2017, held on November 4 - 5, 2017 at the University of Leeds, UK. It covers: advanced knowledge on key AI concepts, including complexity, computation, creativity, embodiment, representation and superintelligence; cutting-edge ethical issues, such as the AI impact on human dignity and society, responsibilities and rights of machines, as well as AI threats to humanity and AI safety; (...)
  2. Should Machines Be Tools or Tool-Users? Clarifying Motivations and Assumptions in the Quest for Superintelligence.Dan J. Bruiger - manuscript
    Much of the basic non-technical vocabulary of artificial intelligence is surprisingly ambiguous. Some key terms with unclear meanings include intelligence, embodiment, simulation, mind, consciousness, perception, value, goal, agent, knowledge, belief, optimality, friendliness, containment, machine and thinking. Much of this vocabulary is naively borrowed from the realm of conscious human experience to apply to a theoretical notion of “mind-in-general” based on computation. However, if there is indeed a threshold between mechanical tool and autonomous agent (and a tipping point for singularity), projecting (...)
  3. Super-Intelligence and Consciousness.Steve Torrance - 2012 - International Journal of Machine Consciousness 4 (2):483-501.
  4. Consciousness: A Philosophic Study of Minds and Machines.J. R. Lucas & Kenneth M. Sayre - 1972 - Philosophical Review 81 (2):241.
  5. Computers and Classroom Culture.Janet Ward Schofield - 1995 - Cambridge University Press.
    As important as it is to realize the potential of computer technology to improve education, it is just as important to understand how the social organization of schools and classrooms influences the use of computers, and in turn is effected by that technology in unanticipated ways. In Computers and Classroom Culture, first published in 1996, Janet Schofield observes the fascinating dynamics of the computer-age classroom. Among her many discoveries, Schofield describes how the use of an artificially-intelligent tutor in a geometry (...)
  6. Computers for Everyone.Fiorella Battaglia - 2016 - Metascience 25 (2):279-280.
  7. Computational Reflection, Machines and Minds.Gaetano Aurelio Lanzarone - 2009 - Dialogue and Universalism 19 (1-2):9-30.
    The purpose of this paper is to argue that, in order for the debate in Computing and philosophy to move forward with respect to its current state, the advances of Computer Science and Artificial Intelligence of the last decades must be taken into account. Computational reflection, one of these advances, is presented in detail and its philosophical implications are discussed, in contrast with old-fashioned views of computational systems such as those presented by Lucas’ papers on Minds and Machines.
  8. Can a Turing Machine Know That the Gödel Sentence is True?Storrs McCall - 1999 - Journal of Philosophy 96 (10):525-532.
  9. Report: Computers and the Medievalist.Vern L. Bullough, Serge Lusignan & Thomas H. Ohlgren - 1974 - Speculum 49 (2):392-402.
  10. God-Made and Machine-Made.John Gray - 1924 - New Blackfriars 5 (56):451-457.
  11. Perceptual Tests of “General Intelligence” for Inter-Racial Use.Meyer Fortes & H. A. Reyburn - 1932 - Transactions of the Royal Society of South Africa 20 (3):281-299.
  12. Machines and Intelligence: A Critique of Arguments Against the Possibility of Artificial Intelligence. Stuart Goldkind.Jay David Bolter - 1987 - Isis 78 (4):597-597.
  13. Intelligence Tests of Immigrant Groups.C. C. Brigham - 1930 - Psychological Review 37 (2):158-165.
  14. The Intelligence Examination and Evaluation: A Study of the Child's Mind Part II.J. Victor Haberman - 1916 - Psychological Review 23 (6):484-500.
  15. The Intelligence Examination and Evaluation: A Study of the Child's Mind :Part I.J. Victor Haberman - 1916 - Psychological Review 23 (5):352-379.
  16. Intelligence and Behavior.A. A. Roback - 1922 - Psychological Review 29 (1):54-62.
  17. Is Lack of Intelligence the Chief Cause of Delinquency?Curt Rosenow - 1920 - Psychological Review 27 (2):147-157.
  18. A Reply to " The Nature of Animal Intelligence and the Methods of Investigating It".Edward Thorndike - 1899 - Psychological Review 6 (4):412-420.
  19. The Nature of Animal Intelligence and the Methods of Investigating It.Wesley Mills - 1899 - Psychological Review 6 (3):262-274.
  20. Machines and Thought: The Legacy of Alan Turing, Volume 1.P. J. R. Millican & A. Clark (eds.) - 1996 - Oxford University Press UK.
    This is the first of two volumes of essays in commemoration of Alan Turing, whose pioneering work in the theory of artificial intelligence and computer science continues to be widely discussed today. A group of prominent academics from a wide range of disciplines focus on three questions famously raised by Turing: What, if any, are the limits on machine `thinking'? Could a machine be genuinely intelligent? Might we ourselves be biological machines, whose thought consists essentially in nothing more than the (...)
  21. Genes, Affect, and Reason: Why Autonomous Robot Intelligence Will Be Nothing Like Human Intelligence.Henry Moss - 2016 - Techné: Research in Philosophy and Technology 20 (1):1-15.
    Abstract: Many believe that, in addition to cognitive capacities, autonomous robots need something similar to affect. As in humans, affect, including specific emotions, would filter robot experience based on a set of goals, values, and interests. This narrows behavioral options and avoids combinatorial explosion or regress problems that challenge purely cognitive assessments in a continuously changing experiential field. Adding human-like affect to robots is not straightforward, however. Affect in organisms is an aspect of evolved biological systems, from the taxes of (...)
  22. Rethinking Machines: Artificial Intelligence Beyond the Philosophy of Mind.Daniel Estrada - unknown
    Recent philosophy of mind has increasingly focused on the role of technology in shaping, influencing, and extending our mental faculties. Technology extends the mind in two basic ways: through the creative design of artifacts and the purposive use of instruments. If the meaningful activity of technological artifacts were exhaustively described in these mind-dependent terms, then a philosophy of technology would depend entirely on our theory of mind. In this dissertation, I argue that a mind-dependent approach to technology is mistaken. Instead, (...)
  23. Enumeration of Recursive Sets By Turing Machine.E. K. Blum - 1965 - Zeitschrift fur mathematische Logik und Grundlagen der Mathematik 11 (3):197-201.
  24. Organization of Addressless Computers Working in Parenthesis Notation.Zdzisław Pawlar - 1963 - Zeitschrift fur mathematische Logik und Grundlagen der Mathematik 9 (16-17):243-249.
  25. Incentives and an Intelligence Tests.Henry H. Ferguson - 1937 - Australasian Journal of Psychology and Philosophy 15 (1):39-53.
  26. Intelligence Tests of Blind Subjects with the Modified Bridges Point Scale.W. E. Black - 1928 - Australasian Journal of Psychology and Philosophy 6 (1):64-66.
  27. The Application of Intelligence Tests to Personnel in a Retail Store.Winifred Taylor - 1925 - Australasian Journal of Psychology and Philosophy 3 (3):211-218.
  28. Utopias, Dolphins and Computers: Problems in Philosophical Plumbing.Mary Midgley - 1996 - Routledge.
    Why do the big philosophical questions so often strike us as far-fetched and little to with everyday life? Mary Midgley shows that it need not be that way; she shows that there is a need for philosophy in the real world. Her popularity as one of our foremost philosophers is based on a no-nonsense, down-to-earth approach to fundamental human problems, philosphical or otherwise. In _Utopias, Dolphins and Computers_ she makes her case for philosophy as a difficult but necessary tool for (...)
  29. Future Progress in Artificial Intelligence: A Poll Among Experts.Vincent C. Müller & Nick Bostrom - 2014 - AI Matters 1 (1):9-11.
    [This is the short version of: Müller, Vincent C. and Bostrom, Nick (forthcoming 2016), ‘Future progress in artificial intelligence: A survey of expert opinion’, in Vincent C. Müller (ed.), Fundamental Issues of Artificial Intelligence (Synthese Library 377; Berlin: Springer).] - - - In some quarters, there is intense concern about high–level machine intelligence and superintelligent AI coming up in a few dec- ades, bringing with it significant risks for human- ity; in other quarters, these issues are ignored or considered science (...)
  30. Future Progress in Artificial Intelligence: A Survey of Expert Opinion.Vincent C. Müller & Nick Bostrom - 2016 - In Fundamental Issues of Artificial Intelligence. Springer. pp. 553-571.
    There is, in some quarters, concern about high–level machine intelligence and superintelligent AI coming up in a few decades, bringing with it significant risks for humanity. In other quarters, these issues are ignored or considered science fiction. We wanted to clarify what the distribution of opinions actually is, what probability the best experts currently assign to high–level machine intelligence coming up within a particular time–frame, which risks they see with that development, and how fast they see these developing. We thus (...)
  31. Challenges for Artificial Cognitive Systems.Antoni Gomila & Vincent C. Müller - 2012 - Journal of Cognitive Science 13 (4):452-469.
    The declared goal of this paper is to fill this gap: “... cognitive systems research needs questions or challenges that define progress. The challenges are not (yet more) predictions of the future, but a guideline to what are the aims and what would constitute progress.” – the quotation being from the project description of EUCogII, the project for the European Network for Cognitive Systems within which this formulation of the ‘challenges’ was originally developed (http://www.eucognition.org). So, we stick out our neck (...)
  32. Philosophy and Theory of Artificial Intelligence, 3–4 October (Report on PT-AI 2011).Vincent C. Müller - 2011 - The Reasoner 5 (11):192-193.
    Report for "The Reasoner" on the conference "Philosophy and Theory of Artificial Intelligence", 3 & 4 October 2011, Thessaloniki, Anatolia College/ACT, http://www.pt-ai.org. --- Organization: Vincent C. Müller, Professor of Philosophy at ACT & James Martin Fellow, Oxford http://www.sophia.de --- Sponsors: EUCogII, Oxford-FutureTech, AAAI, ACM-SIGART, IACAP, ECCAI.
  33. How Do We Read a Dictionary (as Machines and as Humans)? Kinds of Information in Dictionaries Constructed and Reconstructed.Vincent C. Müller - 2000 - In Evangelos Dermatas (ed.), Proceedings of COMLEX2000: Computational lexicography. Patras University Press. pp. 141-144.
    Two large lexicological projects for the Center for the Greek Language, Thessaloniki, were to be published in print and on the WWW, which meant that two conversions were needed: a near-database file had to be converted to fully formatted file for printing and a fully formatted file had to be converted to a database for WWW access. As it turned out, both conversions could make use of existing clues that indicated the kinds of information contained in each particular piece of (...)
  34. Computability and Human Symbolic Output.Jason Megill & Tim Melvin - 2014 - Logic and Logical Philosophy.
    This paper concerns “human symbolic output,” or strings of characters produced by humans in our various symbolic systems; e.g., sentences in a natural language, mathematical propositions, and so on. One can form a set that consists of all of the strings of characters that have been produced by at least one human up to any given moment in human history. We argue that at any particular moment in human history, even at moments in the distant future, this set is finite. (...)
  35. Trouble with Medical Computers.Ian E. Bush - 1979 - Perspectives in Biology and Medicine 22 (4):600-620.
  36. Computers and Medical Discoveries.F. M. Berger & Harry P. Kroitor - 1967 - Perspectives in Biology and Medicine 11 (1):63-70.
  37. Artificial Intelligence and Human Reason: A Teleological Critique.J. R. Rychlak - 1991 - Cambridge University Press.
  38. Machines Cannot Think.Robert George Gell - unknown
    This paper is a critical essay on the question "Can machines think?", with particular attention paid to the articles appearing in an anthology Minds and Machines, A. R. Anderson editor. The general conclusion of this paper is that those arguments which have been advanced to show that machines can think are inconclusive. I begin by examining rather closely a paper by Hilary Putnam called "Minds and Machines" in which he argues that the traditional mind-body problem can arise with a complex (...)
  39. Editorial for Minds and Machines Special Issue on Philosophy of Colour.M. Chirimuuta - 2015 - Minds and Machines 25 (2):123-132.
  40. 20. What Computers Can’T Do: A Critique of Artificial Reason.Hubert L. Dreyfus - 2016 - In Bernard Williams (ed.), Essays and Reviews: 1959-2002. Princeton University Press. pp. 90-100.
  41. How to Talk to Each Other Via Computers: Semantic Interoperability as Conceptual Imitation.Werner Kuhn & Simon Scheider - 2015 - In Peter Gärdenfors & Frank Zenker (eds.), Applications of Conceptual Spaces. Springer Verlag.
  42. Medienphilosophie Des Computers.Lutz Ellrich - 2005 - In Ludwig Nagl & Mike Sandbothe (eds.), Systematische Medienphilosophie. De Gruyter. pp. 343-358.
  43. Response [to Whitmer's "Intentionality, Artificial Intelligence and the Causal Powers of the Brain"].Thomas Eudaly - unknown
  44. Artificial Intelligence in Simulation.Iván Futó & T. Gergely - 1990
  45. Logics for Artificial Intelligence.Raymond Turner - 1984
  46. The Convergence of Machine and Human Nature a Critique of the Computer Metaphor of Mind and Artificial Intelligence.A. E. Mcclintock - 1995
  47. Philosophie Contre Intelligence Artificielle.Jacques Bolo - 1996
    This essay replies to some representative authors, canonic indeed, of the opposition to artificial intelligence (AI) : Hubert L. DREYFUS, with his study, systematic enough in its time, What Computers can't do. His phenomenological critic meets a numerous audience, even among computer scientists. Joseph WEIZENBAUM, research worker in artificial intelligence himself, gone over to the opposition with his book Computer Power and Human Reason. His objections are classically moral and anti-techno-scientific. The philosopher John R. SEARLE, whose book Mind, Brain and (...)
  48. The Framing of Artificial Intelligence a Whodunit Problem.Toni-lou Marlow - 1989
  49. Criticism and Artificial Intelligence Evaluating the Arguments.Stephen Weber - 1991
  50. Animal Intelligence.George John Romanes - 1882
1 — 50 / 1974