Pamela McCorduck is the author or coauthor of eight published books, two of them novels. Among her books are
Machines Who Think, a history of artificial intelligence;
The Universal Machine, a study of the worldwide impact of the computer; and
Aaron’s Code, an inquiry into the future of art and artificial intelligence. Her work has been translated into all the major European and Asian languages. A recent book, coauthored with Nancy Ramsey, is
The Futures of Women (Addison-Wesley, 1996; Time-Warner paperback, 1997), containing four scenarios for women worldwide in the year 2015.
Ms. McCorduck has been an active member of PEN American Center, the author organization in New York City, serving on its executive board and as vice president for several years. In addition, she founded and chaired PEN’s Readers and Writers Program, which sends authors and their books to newly literate adults all over the country. She has been a board member and treasurer of the New Mexico Committee of the National Museum of Women in the Arts, and currently serves on its advisory committee. Ms. McCorduck also works as a consultant, constructing future scenarios for firms in the transportation, financial, and high-tech sectors.
The review you are reading was written by a human, not a machine. This fact would no doubt disappoint some of the pioneers of artificial intelligence, who would have thought that by the 21st century a computer would be able to read a book, consider it in the context of other knowledge and express some thoughtful opinions about it. On the other hand, the human who wrote this review was aided in researching and preparing it by telecommunications and computer networks, including the Internet, that owe a big part of their existence —and even more of their smooth functioning—to theories and concepts that arose from artificial-intelligence research. The enormous, if stealthy, influence of AI bears out many of the wonders foretold 25 years ago in Machines Who Think, Pamela McCorduck’s groundbreaking survey of the history and prospects of the field. A novelist at the time (she has since gone on to write and consult widely on the intellectual impact of computing), McCorduck got to the founders of the field while they were still feeling their way into a new science. Her novelist’s eye for detail and ear for style formed a book that this magazine’s review of the first edition described as "delicious." When Machines Who Think was first published in 1979, it was an up-to-the-moment history. But in a digital world, that moment was an eternity ago, so McCorduck has appended a 30,000-word afterword to bring the reader up-to-date. The original text has been wisely left unaltered (including a few passages that now seem quaint, such as the explanation of the difference between hardware and software). Her story begins long before the advent of computing, in ancient thinking about the human need to make something in our own image. McCorduck sees AI research as the continuation of a long tradition of thought, encompassing everything from the Ten Commandments’ prohibition against idols to Mary Shelley and her Frankenstein monster. But the book, like the field, really doesn’t begin to take off until computing machines—mechanical at first, then eventually digital—enter the picture. McCorduck details the thoughts of theorists such as Alan Turing (who believed machine intelligence was possible) and John von Neumann (who didn’t) and devotes considerable space to work on chess- and checkers-playing machines, which was the early public face of AI. She notes seminal events, particularly the Dartmouth Conference, a 1956 workshop where much of the groundwork for future research was laid by such men as Marvin Minsky, John McCarthy and two upstarts who would be hugely influential, Alan Newell and Herbert Simon. Newell and Simon were in large part responsible for a shift in thinking away from the idea that machine intelligence must mimic the brain physically, an approach that drew parallels between neurons and digital devices, and toward the view that it should simulate human thought processes—what became known as the information-processing model. McCorduck shows how this idea developed over the years, how problems that were first seen as "impossibly nonmechanical" were solved and how these solutions "slowly began to be brought into the domain of ordinary computational processes." That slow infusion of AI into everyday computing picked up speed after 1979, and in the afterword McCorduck gives a taste of these advances and of recent research in robotics, natural-language processing and other fields that are, in essence, AI spin-offs. This part of the book feels sketchy, and the author acknowledges that it is not meant as a definitive survey of the field’s past 25 years. But the reader is left wanting more. Still, taken together, the original and the afterword form a rich and fascinating history. Along the way, McCorduck introduces us to some interesting characters, not the least of whom are the naysayers. She devotes a chapter to Hubert Dreyfus, the philosopher who in the 1960s became a thorn in the side of researchers with his public pronouncements about the futility of their work (they had the last laugh, however, when a machine beat him at chess). And she writes about those thinkers, most recently the technologist Bill Joy, for whom the great hopes of AI have been replaced by great fears, of machines that might rule rather than rival humans. The book is described as a "personal inquiry," and now, as then, McCorduck leaves little doubt as to where her personal allegiance lies. From the title to the very last sentence, she is a believer in what she calls a "heroic enterprise." She may admit that researchers have a long way to go, but she dismisses the doubters as well: AI, she writes, is "neither the field of dreams nor the field of nightmares portrayed." Were she to produce a 50th-anniversary edition in 2029, she might be somewhat surprised, but surely very pleased, to see it reviewed by a machine who thinks.
Henry Fountain is a writer and editor at the New York Times, specializing in science and technology.