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To the researchers, the visionaries, and the critics. ARTIFICIAL INTELLIGENCE: Mirrors for the Mind Copyright © 2007 by Harry Henderson All rights reserved. No part of this book may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, or by any information storage or retrieval systems, without permission in writing from the publisher. For information contact: Chelsea House An imprint of Infobase Publishing 132 West 31st Street New York NY 10001 ISBN-10: 0-8160-5749-4 ISBN-13: 978-0-8160-5749-8 Library of Congress Cataloging-in-Publication Data Henderson, Harry. Artificial intelligence : mirrors for the mind / Harry Henderson. p. cm. — (Milestones in discovery and invention) Includes bibliographical references and index. ISBN 0-8160-5749-4 1. Artificial intelligence. I. Title. II. Series. Q335.H455 2007 006.3.—dc22 2006016639 Chelsea House books are available at special discounts when purchased in bulk quantities for businesses, associations, institutions, or sales promotions. Please call our Special Sales Department in New York at (212) 967-8800 or (800) 322-8755. You can find Chelsea House on the World Wide Web at http://www.chelseahouse.com Text design by James Scotto-Lavino Cover design by Dorothy M. Preston Illustrations by Sholto Ainslie and Melissa Ericksen Printed in the United States of America MP FOF 10 9 8 7 6 5 4 3 2 1 This book is printed on acid-free paper.
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eCONTENTS PREFACE ix ACKNOWLEDGMENTS xiii INTRODUCTION xv 1 BEYOND CALCULATION: ALAN TURING AND THE BIRTH OF ARTIFICIAL INTELLIGENCE 1 Science and Friendship 1 Does It Compute? 3 From Symbols to Codes 4 Riddling the Enigma 5 Designing Electronic Computers 8 Toward AI 9 The “Turing Test” 10 Turing and Objections to AI 12 Issues: Is the Turing Test a Dead End? 14 The Final Enigma 15 Chronology 16 Further Reading 17 2 MIND IN A BOX: ALLEN NEWELL AND HERBERT SIMON EXPLORE REASONING AND DECISION MAKING 19 A Vigorous Mind 20 Looking for Interesting Problems 21 Simulating Organizations 22 Meeting of the Minds 22 Simon Sets His Course 23 Simon and Newell’s Opening Moves 25 I Was There: Unexpected Results 28 A Logic Machine 28 The General Problem Solver 30
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Parallels: Chess and Mathematical Proofs 32 I Was There: The Birth of AI 33 Expanding the Artificial Mind 34 A General Theory of Thinking 34 Getting to “Good Enough” 35 A Rich Legacy 36 Chronology 37 Further Reading 38 3 I HAVE A LITTLE LIST: JOHN MCCARTHY CREATES TOOLS FOR AI 41 Radical Roots 41 A Possible Machine 42 Dartmouth and the “Birth” of AI 43 Lisp 45 Framing the Question 47 Connections: SHRDLU and the “Blocks World” 48 Reflections and Rewards 51 McCarthy on the Future of AI 52 Chronology 54 Further Reading 55 4 SIMULATED BRAINS: MARVIN MINSKY’S JOURNEY FROM NEURAL NETWORKS TO MULTIPLE MINDS 56 Experiencing Science at Harvard 57 Hunting the SNARC 58 Perceptrons and Neural Networks 59 Emergence of AI Research 60 Steps toward AI 60 Other Scientists: Seymour Papert (1928– ) 61 Solving Problems: Basic AI Strategies 62 Frames to Organize Knowledge 63 Many Minds 65 Still Going Strong 66 Solving Problems: Improving or Copying the Brain? 67 The Emotion Machine 68 Issues: Minsky on AI Research and the Nature of Consciousness 69 Chronology 71 Further Reading 72
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5 HARNESSING KNOWLEDGE: EDWARD FEIGENBAUM AND EXPERT SYSTEMS 74 A “Practical” Career 75 Meeting the “Thinking Machine” 76 From Deduction to Induction 76 An Automated Chemist 78 The Priority of Knowledge 79 Building an Expert System 80 The “Expert Company” 82 Connections: Prolog, the Logic Programming Language 83 Issues: The “AI Winter” 84 What Comes Next? 84 Parallels: Japan’s “Fifth Generation” 87 Chronology 88 Further Reading 88 6 THE COMMONSENSE COMPUTER: DOUGLAS LENAT AND THE CYC PROJECT 90 Saved by Science 91 A Commonsense Approach 92 The Automated Mathematician 93 The Need for Knowledge 94 Cyc: An Encyclopedia for Machines 95 Building Cyc 96 Using Cyc 98 Achievements and Criticisms 100 Connections: More Uses for Cyc 100 Chronology 103 Further Reading 104 7 AT YOUR SERVICE: PATTIE MAES AND THE NEW BREED OF INTELLIGENT AGENTS 105 A New Kind of Program 106 Solving Problems: How Agent Programs Work 108 Commercial Applications 110 Future Agents 110 Turning “Things” into Agents? 111 “What Would They Think?” 112 Other Scientists: Stacy Marsella, David Pynadath, and PsychSim 113
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Visionary and “Download Diva” 114 Social Impact: Can Software Agents Be Harmful? 115 Chronology 116 Further Reading 116 8 ANSWERING ELIZA: JOSEPH WEIZENBAUM AND THE SOCIAL RESPONSIBILITY OF AI 118 Working with Computers 118 Ask ELIZA 119 I Was There: Passing the Turing Test? 122 Becoming a Critic of Computers 124 A Social Critique 125 Trends: “Chatterbots” 126 Against Oppressive Technology 127 Later Years 130 Chronology 131 Further Reading 132 9 A PHILOSOPHER’S CHALLENGE: HUBERT DREYFUS AND THE ASSUMPTIONS OF AI 134 The Philosopher and the Robots 136 Against the “Alchemists” 137 The AI Community Responds 139 “What Computers Can’t Do” 139 Connections: What about the “Other” AI? 140 Taking On the Internet 141 Issues: Differing Views of Computers and Humans 142 Chronology 144 Further Reading 144 10 WHEN EVERYTHING CHANGES: RAY KURZWEIL AND THE TECHNOLOGICAL SINGULARITY 146 “I Have Got a Secret” 146 Learning about AI 147 The Reading Machine 148 The Universal Instrument 149 I Was There: The Old Engineer’s Trick 150 Trends: Kurzweil’s Predictions for 2009 152 From Entrepreneur to Visionary 154 The “Technological Singularity” 155
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Other Writers: David Brin (1950– ) 156 “Live Long Enough to Live Forever” 159 Issues: Kurzweil and the AI Critics 160 Chronology 161 Further Reading 162 CHRONOLOGY 165 GLOSSARY 170 FURTHER RESOURCES 177 INDEX 183
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ePREFACE The Milestones in Discovery and Invention set is based on a simple but powerful idea—that science and technology are not separate from people’s daily lives. Rather, they are part of seeking to understand and reshape the world, an activity that virtually defines being human. More than a million years ago, the ancestors of modern humans began to shape stones into tools that helped them compete with the specialized predators around them. Starting about 35,000 years ago, the modern type of human, Homo sapiens, also created elabo- rate cave paintings and finely crafted art objects, showing that tech- nology had been joined with imagination and language to compose a new and vibrant world of culture. Humans were not only shaping their world but representing it in art and thinking about its nature and meaning. Technology is a basic part of that culture. The mythologies of many peoples include a trickster figure, who upsets the settled order of things and brings forth new creative and destructive pos- sibilities. In many myths, for instance, a trickster such as the Native Americans’ Coyote or Raven steals fire from the gods and gives it to human beings. All technology, whether it harnesses fire, electric- ity, or the energy locked in the heart of atoms or genes, partakes of the double-edged gift of the trickster, providing power to both hurt and heal. An inventor of technology is often inspired by the discoveries of scientists. Science as we know it today is younger than technology, dating back about 500 years to a period called the Renaissance. During the Renaissance, artists and thinkers began to explore nature systematically, and the first modern scientists, such as Leonardo da Vinci (1452–1519) and Galileo Galilei (1564–1642), ix
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x Artificial Intelligence used instruments and experiments to develop and test ideas about how objects in the universe behaved. A succession of revolutions followed, often introduced by individual geniuses: Isaac Newton (1643–1727) in mechanics and mathematics, Charles Darwin (1809–1882) in biological evolution, Albert Einstein (1879–1955) in relativity and quantum physics, James Watson (1928– ) and Francis Crick (1916–2004) in modern genetics. Today’s emerg- ing fields of science and technology, such as genetic engineering, nanotechnology, and artificial intelligence, have their own inspir- ing leaders. The fact that particular names such as Newton, Darwin, and Einstein can be so easily associated with these revolutions suggests the importance of the individual in modern science and technology. Each book in this set thus focuses on the lives and achievements of eight to 10 individuals who together have revolutionized an aspect of science or technology. Each book presents a different field: marine science, genetics, astronomy and space science, forensic sci- ence, communications technology, robotics, artificial intelligence, and mathematical simulation. Although early pioneers are included where appropriate, the emphasis is generally on researchers who worked in the 20th century or are still working today. The biographies in each volume are placed in an order that reflects the flow of the individuals’ major achievements, but these life sto- ries are often intertwined. The achievements of particular men and women cannot be understood without some knowledge of the times they lived in, the people they worked with, and developments that preceded their research. Newton famously remarked, “If I have seen further [than others], it is by standing on the shoulders of giants.” Each scientist or inventor builds upon—or wrestles with—the work that has come before. Individual scientists and inventors also inter- act with others in their own laboratories and elsewhere, sometimes even partaking in vast collective efforts, such as the government and private projects that raced at the end of the 20th century to com- plete the description of the human genome. Scientists and inventors affect, and are affected by, economic, political, and social forces as well. The relationship between scientific and technical creativity and developments in social institutions is another important facet of this series.
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PREFACE xi A number of additional features provide further context for the biographies in these books. Each chapter includes a chronology and suggestions for further reading. In addition, a glossary and a general bibliography (including organizations and Web resources) appear at the end of each book. Several types of sidebars are also used in the text to explore particular aspects of the profiled scientists’ and inventors’ work: Connections Describes the relationship between the featured work and other scientific or technical developments. I Was There Presents first-hand accounts of discoveries or inventions. Issues Discusses scientific or ethical issues raised by the discovery or invention. Other Scientists (or Inventors) Describes other individuals who played an important part in the work being discussed. Parallels Shows parallel or related discoveries. Social Impact Suggests how the discovery or invention affects or might affect society and daily life. Solving Problems Explains how a scientist or inventor dealt with a particular technical problem or challenge. Trends Presents data or statistics showing how developments in a field changed over time. Our hope is that readers will be intrigued and inspired by these stories of the human quest for understanding, exploration, and innovation. We have tried to provide the context and tools to enable readers to forge their own connections and to further pursue their fields of interest.
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eACKNOWLEDGMENTS Iwould like to acknowledge the researchers and staff who helped me obtain photographs of the artificial intelligence pioneers featured in this book, as well as of their work. I would also like to express my continuing appreciation for the ongoing help of Frank K. Darmstadt, my editor. xiii
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eINTRODUCTION “Artificial Intelligence.” Just putting the two words together is like issuing a challenge. When the chart of the animal king- dom was first laid out by naturalists, humans reserved for them- selves the exalted name Homo sapiens. The ancient Greeks saw the rational faculties as distinguishing humans from other creatures. Many religious thinkers added to this the notion of the soul, a permanent and essential identity infused into people by their divine creator. The birth of modern science in the 17th and 18th centuries and the work of thinkers such as René Descartes, Isaac Newton, and Gottfried Leibniz brought a new question into play. If the Universe was really a sort of huge, complex machine subject only to the laws of nature, then perhaps people, too, were really machines. But what was the role of the mind in the human machine? This question arose naturally from dualism, or the split between mind on the one hand and body on the other. The brain was part of the body, but how was it connected to the structures of thought, perception, and imagination? As the 20th century progressed many new views and explana- tions would be heard. Alan Turing, the first person profiled in this volume, developed a mathematical proof that said that some kinds of problems could not be solved through computation. On the other hand, all possible computations can be done by a hypothetical machine, a “universal computer.” When actual computing machines came along in the 1940s, Turing went on to ask key questions that would continue to preoccupy artificial intelligence (AI) researchers for almost six decades and counting: Can what the mind does be expressed as computation? Can a computer be so advanced people cannot tell that it is a computer? Before his tragically early death, xv
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xvi Artificial Intelligence Turing predicted that by the end of the century people would find the idea of intelligent computers to be at least plausible. The first generation of electronic digital computers grew steadily in power, and the 1950s saw the establishment of AI as a dis- tinct field of research. One of the pioneers in this volume, John McCarthy, coined the term artificial intelligence and organized the 1956 conference at Dartmouth that displayed the field’s first fruits and suggested its future agenda. Two other featured AI researchers, Allen Newell and Herbert Simon, created programs that could apply the rules of logic, form hypotheses, and solve problems—all things that most people would consider to be signs of intelligence. Meanwhile, the course of AI research had split into two cur- rents. Researchers such as McCarthy, Newell, and Simon focused on programming logical structures and ways to manipulate sym- bols and understand language. They focused on computation. The other current, found in early work with neural networks, suggested that the road to AI was to be found in creating complex webs of connections similar to those found in the neurons in the brain, and to develop simple but powerful ways of reinforcing such connections. This would allow the network to learn how, for example, to recognize a letter or a shape. Another featured scientist, Marvin Minsky, developed these ideas and added a new theory of the mind—that it consisted of many layers of different “agents” that dealt with different aspects of knowledge and coop- erated as a “society of mind” from which our intelligence and consciousness emerged. By the 1970s, considerable progress had been made in both of these currents of AI. However, the hoped-for breakthrough to a general-purpose artificial intelligence that could understand natu- ral human language and deal with a wide variety of problems still seemed rather far away. The next two featured researchers, Edward Feigenbaum and Douglas Lenat, shared with many earlier col- leagues a belief that a major obstacle to versatile AI was that com- puter programs lacked common sense. That is, they did not have the broad base of knowledge about how the world works that a human six year old already possesses. Marvin Minsky had begun to address this lack through the devel- opment of frames, or structured descriptions of facts or situations in
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INTRODUCTION xvii daily life. Feigenbaum developed a way to create a “knowledge base” of assertions about a particular field of expertise, and a program called an “inference engine” that could search the knowledge base for applicable rules and logically construct an answer to the user’s question. By the end of the 1980s “expert systems” using these tech- niques were doing everything from diagnosing infectious diseases and car trouble to figuring out the best way for an airline to deploy its planes efficiently. Meanwhile, Douglas Lenat has embarked on a decades-long project called Cyc (short for encyclopedia) that con- tinues to this day, compiling millions of facts and relationships and developing sophisticated tools to deal with them. Historically AI researchers have tended to make bold, confident predictions that such goals as language understanding, robust problem solving, and commonsense reasoning would be achieved in a matter of only a few years. Actual progress has always been much slower. After all, there is not even a single widely accepted theory about what intelligence actually consists of. Nevertheless, AI research and the related field of cognitive science—the study of thinking in brain and machine—have shed much light on each oth- er’s concerns. To the extent researchers learn about the brain, they can create computer simulations that seek to capture its processing. To the extent they try out new ideas about cognition with comput- ers, they might learn more about the brain in turn. The AI field has also been the subject of vigorous (and often heated) debate. This volume features three final people who bring quite different perspectives to the field. Joseph Weizenbaum created a deceptively simple program called ELIZA in the mid-1960s. The program echoed back the user’s statements in a way similar to that of certain modern psychotherapists. Alarmed at how readily people confided in the machine, Weizenbaum undertook a critique of the use and misuse of computer power. He suggested that people both overestimated the prowess of the machines and misused them to serve military and other purposes contrary to humane values. Philosopher Hubert Dreyfus also criticized the use of computers, but his major critique involved his assertion that the human mind is not like a computer at all. The brain is part of a body, and the body is deeply and intricately connected to the living environment. As a follower of “phenomenological” philosophy, Dreyfus has attempted
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xviii Artificial Intelligence with only partial success to carry on a dialogue or dispute with AI researchers over the years. Finally, the volume ends with the ultimate question: is a true artificial intelligence possible—and if it is, what will it do to us flesh-and-blood humans? This question has been addressed head-on by our last subject (and one of our most interesting), Ray Kurzweil. A prolific inventor who brought the world a reading machine for the blind, scanners, and music synthesizers, Kurzweil has focused in recent years on trying to answer the big questions about AI. His answer is that the explosive growth of computing power and the ability to scan the brain with greater and greater resolution will, in a few decades, lead to AI that equals and then surpasses human capa- bilities. People will also be able to enhance their capabilities using this technology. Response to Kurzweil has ranged from exhilaration to dismay at the possibility of technology getting out of control and perhaps resulting in the extinction of the human species. Wherever the future may lead, the history of AI and the people who made it are fascinating. Their work continues to shape many of the products in use today, from navigation systems to online financial planning tools. In the end, though, AI is most fascinating because it asks us how much we understand about ourselves and challenges us to imagine and perhaps face the nearly unimaginable.
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1 BEYOND CALCULATION ALAN TURING AND THE BIRTH OF ARTIFICIAL INTELLIGENCE At the dawn of the computer age Alan Turing’s startling range of original thought led to the creation of many branches of computer science ranging from the fundamental theory of com- putability to the question of what might constitute true artificial intelligence. Alan Turing was born in London on June 23, 1912. His father worked in the Indian (colonial) Civil Service, while his mother came from a family that had produced a number of distinguished scientists. Because his parents were often away Turing was raised mainly by relatives until he was of school age. As quoted in a letter in Andrew Hodges’s biography of Turing, the boy’s nanny noted that The thing that stands out most in my mind was his integrity and his intelligence for a child so young as he then was, also you couldn’t camouflage anything from him. I remember one day Alan and I play- ing together. I played so that he should win, but he spotted it. There was commotion for a few minutes . . . Science and Friendship Young Turing then went as a boarding student to various private schools, finally attending Sherborne School, a college preparatory 1
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