The Philosophy of Artificial Intelligence

Is "artificial intelligence" a contradiction in terms? Could computers (in principle) be made to model every aspect of the mind, including logic, language, and emotion? This interdisciplinary collection of classical and contemporary readings provides a clear and comprehensive guide to the many hotly-debated philosophical issues at the heart of artificial intelligence. The editor includes an informative introduction and reading list.

Is `artificial intelligence' a contradiction in terms? Could computers (in principle) model every aspect of the mind, including logic, language, and emotion? What of the more brain-like, connectionist computers: could they really understand, even if digital computers cannot? This collection of classic and contemporary readings (which includes an editor's introduction and an up-to-date reading list) provides a clearly signposted pathway into hotly disputed philosophical issues at the heart of artificial intelligence.

Introduction; Warren S. McCulloch and Walter H. Pitts: A Logical Calculus of Nervous Activity; Alan M. Turing: Computing Machinery and Intelligence; John R. Searle: Minds, Brains, and Programs; Margaret A. Boden: Escaping from the Chinese Room; Allen Newell and Herbert A. Simon: Computer Science as Empirical Enquiry: Symbols and Search; David C. Marr: Artificial Intelligence: A Personal View; Daniel C. Dennett: Cognitive Wheels: The Frame Problem of AI; Patrick J. Hayes: The Naive Physics Manifesto; Drew McDermott: A Critique of Pure Reason; Aaron Sloman: Motives, Mechanisms, and Emotions; Geoffrey E. Hinton, James L. McClelland, and David E. Rumelhart: Distributed Representations; Andy Clark: Connectionism, Competence, and Explanation; Hubert L. Dreyfus and Stewart E. Dreyfus: Making a Mind Versus Modelling the Brain; Paul M. Churchland: Some Reductive Strategies in Cognitive Neurobiology; Adrian Cussins: The Connectionist Construction of Concepts