Description
The essential reader on the philosophical foundations and implications of artificial intelligence, now comprehensively updated for the twenty-first century.
In the quarter century since the publication of John Haugeland’s Mind Design II, computer scientists have hit many of their objectives for successful artificial intelligence. Computers beat chess grandmasters, driverless cars navigate streets, autonomous robots vacuum our homes, and ChatGPT answers existential queries in iambic pentameter on command. Engineering has made incredible strides. But have we made progress in understanding and building minds? Comprehensively updated by Carl Craver and Colin Klein to reflect the astonishing ubiquity of machine learning in modern life, Mind Design III offers an essential collection of classic and contemporary essays on the philosophical foundations and implications of artificial intelligence. Contributions from a diverse range of philosophers and computer scientists address the nature of computation, the nature of thought, and the question of whether computers can be made to think. With extensive new material reflecting the explosive growth and diversification of AI approaches, this classic reader equips students to assess the possibility of, and progress toward, building minds out of computers.
New edition highlights:
- New chapters on advances in deep neural networks, reinforcement learning, and causal learning
- New material on the complementary intersection of neuroscience and AI
- Organized thematically rather than chronologically
- Brand new introductions to each section that include suggestions for coursework and further reading
Table of Contents
1 Introduction to Mind Design III 1
Carl F. Craver and Colin Klein
PART I COMPUTERS, COMPUTING, AND COMPUTATION 5
2 What Is Mind Design? 11
John Haugeland
3 Computer Science as Empirical Inquiry: Symbols and Search 35
Allen Newell and Herbert A. Simon
4 Vision 59
David Marr
5 The Analog Alternative 71
Corey J. Maley
PART II WHAT IS INTELLIGENCE? 93
6 Computing Machinery and Intelligence 101
Alan M. Turing
7 On Our Best Behaviour 125
Hector J. Levesque
8 Rationality and Intelligence 139
Stuart J. Russell
9 Central Systems 159
Jerry A. Fodor
10 Why AI Is Harder than We Think 175
Melanie Mitchell
PART III INTENTIONALITY AND UNDERSTANDING 189
11 True Believers: The Intentional Strategy and Why It Works 197
Daniel C. Dennett
12 Minds, Brains, and Programs 217
John R. Searle
13 Escaping from the Chinese Room 235
Margaret Boden
14 Computation and Content 249
Frances Egan
PART IV MODELING THE WORLD 267
15 Transformational Abstraction in Deep Neural Networks 275
Cameron Buckner
16 The Evaluative Mind 295
Julia Haas
17 Whatever Next? Predictive Brains, Situated Agents, and the Future of Cognitive Science 315
Andy Clark
18 Theoretical Impediments to Machine Learning with Seven Sparks from the Causal Revolution 343
Judea Pearl
PART V CONTRIBUTIONS FROM COGNITIVE NEUROSCIENCE 353
19 The Architecture of Mind: A Connectionist Approach 361
David E. Rumelhart
20 The Computational Brain 385
Patricia Churchland and Terrence Sejnowski
21 The Mind Is Not (Just) a System of Modules Shaped (Just) by Natural Selection 409
Fiona Cowie and James Woodward
PART VI BODY AND WORLD 431
22 Mind Embodied and Embedded 439
John Haugeland
23 Intelligence without Representation 465
Rodney A. Brooks
24 What Does Biorobotics Offer Philosophy? A Tale of Two Navigation Systems 487
Barbara Webb
Acknowledgments 501
Bibliography 507
