Machines Who Think: A Personal Inquiry into the History and Prospects of Artificial Intelligence

by Pamela McCorduck

This book is a history of artificial intelligence, that audacious effort to duplicate in an artifact what we consider to be our most important property―our intelligence. It is an invitation for anybody with an interest in the future of the human race to participate in the inquiry.

Genres: Science, Artificial Intelligence, History, Philosophy, Nonfiction, Computers, Technology

598 pages, Paperback

First published September 1, 1979

Reviews

[Ben Peters · Rating 1 out of 5]

Review of the first edition only: This book may be useful as a parading of the cast of artificial intelligence (AI) characters in 1980, when it was first written but it does not do much for me today. Exuberant, hopeful, bright--sure, but so what? The material seems insensitive to the deep philosophical stakes of its surface skim of Turing's hardy question: machines be considered intelligent, and how and why? Maybe that's the later engineers' fault, not McCorduck's. (This edition can't tell us the difference.) Still there's some useful material gathered here--names, chronologies, testimonies, interviews, etc., and the fact that so many of the themes are right on--information and entropy; Turing and binary difference; Simon and processing; von Neumann, IBM, and games, etc., etc.--suggests that this volume, however breezy, registers the currents of thought in the 1980s that continue to trickle down into the popular understanding of AI. Again, the revised version might redeem its barely bearable lightness, but this edition seems like it should only interest the relatively few historians who want to document the popular imagination of AI in the 1980s.

[Metageek · Rating 3 out of 5]

This is a book written in the late 1970s about the early history of the field of Artificial Intelligence. The book reflects a considerable bias towards the part of this field that came out of the Dartmouth conference (McCarthy, Simon, Newell, Misky, etc). The first 2/3 of the book are good as historical context, though the book misses some things (eg at this time it was not yet known about Alan Turing's work with computers during the world war II). The book is, however, rather biased by the Dartmouth crowd. for example, there is little attention paid to the perceptron. Yet, all in all I would have given 4* to the book if it had stopped at 2/3, if nothing else because it is a good read. The last part is difficult to read. Twice I started this book, and twice I stopped before page 400. So overall it gets 3*

[Robert · Rating 4 out of 5]

Loved this book.

One of my first introductions to the history of AI.

[Aaron Thiel · Rating 4 out of 5]

Very long but always interesting throughout. A different but needed perspective on the topic for me.

[Corbin Routier · Rating 3 out of 5]

Page xii - The desire to write the book, "It's the desire to show that science is above all a human endeavor... Science is people by humans, and not by a solitary, abstract Truth... Here I address my fellow humanists more than anyone else, because so many of them are convinced that science is somehow alien to the humanities. I want them to see that it is not."

The author covers the works of major Artificial Intelligence researchers up until 1979. The language used to describe "advanced" computing is an interesting phenomenon when read in 2025. The language used to describe the non-linear exploration of possibilities is also a very sobering experience. Scientists don't know where they are going.

Unfortunately, the author takes advantage of this unknown future to mischaracterize much of the successes and failures in the field. It is important to fact check her overexuberance.

This book does not discuss math, algorithms, or theorems. This book discusses people, organized chaos, and the natural path of science.

Page 120 - Alan Newell - "I see science as a thing which is full of bets but not full of moral imperatives. All that happens is that I'll be consigned to the dustbin if I go pick up the wrong thing to worry about, and that's a risk I'm willing to take."

Page 129 - "To move from speculation in science to the more solid tasks of theorizing, modeling, and verification is always a major step."

Page247 - Everyone, "long since learned to be embarrassed when they make wrong guesses publicly... Too bad for us. We close ourselves off from learning except under the most private circumstances, missing not only the joy of mutual human activity, but the acceleration it lends to individual learning."

[Rob Mason · Rating 5 out of 5]

I found the book enjoyable an interesting from a historical perspective. I found the groupings of the research into topics/movements to work better than a strictly linear approach. Of course, it is a bit dated but that makes it interesting to look back and see where the field was compared to where it is now. The early chapter(s) of the ancient history/philosophy was a bit tough and probably could have been skipped but I guess offers a long term perspective.

[ACRL]

Read by ACRL Member of the Week Elizabeth Dupuis. Learn more about Elizabeth on the ACRL Insider Blog.