3 - Philosophical challenges
Published online by Cambridge University Press: 05 July 2014
Summary
Descartes (1637/1931, p. 116) held that our reason was a “universal instrument.” Since he believed that any mechanism has to have some special purpose, and that no collection of special purpose mechanisms could be large enough to encompass all that reason can do, he concluded that no mechanism could instantiate human reason. Aquinas (1265–72, I, Q.75, a. 2) also argued that intellect was not provided by a material organ. He believed that a disease-induced bitter humor could interfere with our tasting sweetness, or any taste different from bitter. Analogously, he thought that if our intellects were material, they would be prevented from knowing material things of different natures.
Most contemporary philosophers would accept that our intelligence is provided by our material brains, and thus would be disinclined to challenge the possibility of artificially intelligent devices on the ground of their materiality. The questions and problems about artificial intelligence that remain can be divided into those that are largely independent of particular approaches to AI, and those that are prompted by more specific ideas about artificially realizable cognitive architectures. We shall begin with the more general issues.
Keywords
Information
- Type
- Chapter
- Information
- The Cambridge Handbook of Artificial Intelligence , pp. 64 - 86Publisher: Cambridge University PressPrint publication year: 2014
References
(2007). Minds and Computers: An Introduction to the Philosophy of Artificial Intelligence. Edinburgh University Press. Introduces basic concepts in philosophy of mind and the computational theory of mind, which is defended.Google Scholar
and (Repeatedly updated.) “Philosophy of Artificial Intelligence,” . A comprehensive bibliography of papers, organized by many sections and subsections covering all aspects under its title.
(2004, rev. 2009). The Chinese Room argument, in (ed.), The Stanford Encyclopedia of Philosophy, . Explains the argument and the replies to it, and makes connections to larger philosophical issues.
(1997, rev. 2010). Connectionism, in (ed.), The Stanford Encyclopedia of Philosophy, . Explanation of connectionist devices, strengths and weaknesses, and issues between connectionism and classical approaches to AI.
(2003, rev. 2009). The computational theory of mind, in (ed.), The Stanford Encyclopedia of Philosophy, . Explains why the mind has been regarded as a computer, and reviews criticisms of that view.
(1265–72/1945). Summa Theologica, in (tr.), Basic Writings of St. Thomas Aquinas. New York: Random House.Google Scholar
(1954). Freedom and necessity, in , Philosophical Essays (pp. 271–84). London and Basingstoke: Macmillan.Google Scholar
(1998). Representation and cognitive explanations: Assessing the dynamicist’s challenge in cognitive science, Cognitive Science 22: 295–318.CrossRefGoogle Scholar
(1991). Intelligence without representation, Artificial Intelligence 47: 139–59.CrossRefGoogle Scholar
(1993). Connectionism and compositionality: Why Fodor and Pylyshyn were wrong, Philosophical Psychology 6: 305–19.CrossRefGoogle Scholar
. (1996). Does a rock implement every finite-state automaton?, Synthese 108: 309–33.CrossRefGoogle Scholar
(1993). Associative Engines: Connectionism, Concepts, and Representational Change. Cambridge, MA: MIT Press.Google Scholar
(1973). Mechanism and responsibility, in (ed.), Essays on Freedom of Action (pp. 157–84). London: Routledge and Kegan Paul. Reprinted in Dennett, D. C. (1978) Brainstorms (pp. 233–55). Cambridge, MA: Bradford Books.Google Scholar
(1637/1931). Discourse on the Method of Rightly Conducting the Reason and Seeking for Truth in the Sciences, in and (trs.), The Philosophical Works of Descartes, vol 1. Cambridge University Press.Google Scholar
(1985). Connectionist models and their applications: Introduction, Cognitive Science 9: 1–2.Google Scholar
and (1988). Connectionism and cognitive architecture: A critical analysis, in and (eds.), Connections and Symbols (pp. 3–71). Cambridge, MA: MIT Press.Google Scholar
(1931). Über formal unentscheidbare Sätze der Principia Mathematica und verwandter Systeme I, Monatshefte für Mathematik und Physik 38: 173–98.CrossRefGoogle Scholar
(1997). The architecture of representation, Philosophical Psychology 10: 5–23.CrossRefGoogle Scholar
(ed.) (1981). Mind Design. Montgomery, VT: Bradford Books.
(1748). An Enquiry Concerning Human Understanding. Full text available online at .CrossRefGoogle Scholar
, , and (1996). Reinforcement learning: A survey, Journal of Artificial Intelligence Research 4: 237–85.Google Scholar
and (2002a). ‘Words or Rules’ cannot exploit the regularity in exceptions: A reply to Pinker and Ullman, Trends in Cognitive Science 6: 464–65.CrossRefGoogle ScholarPubMed
and . (2002b). Rules or connections in past-tense inflections: What does the evidence rule out?, Trends in Cognitive Science 6: 465–72.CrossRefGoogle ScholarPubMed
(1976). Artificial intelligence meets natural stupidity, SIGART Newsletter, no. 57: 4–9.CrossRefGoogle Scholar
and (2000). Evolutionary Robotics: The Biology, Intelligence and Technology of Self-Organizing Machines. Cambridge, MA: MIT Press.Google Scholar
(2010). Computation in physical systems, in (ed.), The Stanford Encyclopedia of Philosophy (Fall 2010 edn.), .Google Scholar
and (1988). On language and connectionism: Analysis of a parallel distributed model of language acquisition, in and (eds.), Connections and Symbols (pp. 73–193). Cambridge, MA: MIT Press.Google Scholar
and (2002a). The past and future of the past tense, Trends in Cognitive Science 6: 456–63.CrossRefGoogle ScholarPubMed
and . (2002b). Combination and structure, not gradedness, is the issue: Reply to McClelland and Patterson, Trends in Cognitive Science 6: 472–4.CrossRefGoogle ScholarPubMed
(1988). Recursive auto-associative memory: Devising compositional distributed representations, Proceedings of the 10th Annual Conference of the Cognitive Science Society. Mahwah, NJ: L. Erlbaum.Google Scholar
. (1990). Recursive distributed representations, Artificial Intelligence 46: 77–105.CrossRefGoogle Scholar
and (2005). Reinforcement learning for agents with many sensors and actuators acting in categorizable environments, Journal of Artificial Intelligence Research 23: 79–122.
(1960). Review of Nagel and Newman, Gödel’s Proof, Philosophy of Science 27: 205–7.CrossRefGoogle Scholar
, , and (1990). Connectionism, eliminativism and the future of folk psychology, in (ed.), Philosophical Perspectives 4: 499–533.CrossRefGoogle Scholar
. (1995). Mild realism, causation, and folk psychology, Philosophical Psychology 8: 167–87.CrossRefGoogle Scholar
. (1996). Review of Roger Penrose, Shadows of the Mind, Philosophical Psychology 9: 119–22.Google Scholar
and (1986). On learning the past tenses of English verbs, in , , and the PDP Research Group, Parallel Distributed Processing: Explorations in the Microstructure of Cognition, vol. 2 (pp. 216–71). Cambridge, MA: MIT Press.Google Scholar
(1980). Minds, brains, and programs, The Behavioral and Brain Sciences 3: 417–24.CrossRefGoogle Scholar
(1995). Constituent structure and explanation in an integrated connectionist/symbolic cognitive architecture, in and (eds.), Connectionism: Debates on Psychological Explanation (pp. 223–90). Oxford: Blackwell.Google Scholar
. (1997). Dynamics and cognition, in (ed.), Mind Design II (pp. 421–50). Cambridge, MA: MIT Press.Google Scholar
Accessibility standard: Unknown
Why this information is here
This section outlines the accessibility features of this content - including support for screen readers, full keyboard navigation and high-contrast display options. This may not be relevant for you.Accessibility Information
Accessibility compliance for the PDF of this chapter is currently unknown and may be updated in the future.