Put as broadly as I can manage, the problem with artificial intelligence (A.I.) systems is that, one way or another, they take their training too literally. Human beings grow up in some socio-cultural context. When we are taught to do something potentially dangerous—for example, driving a car—and then face a road situation we did not encounter in our training, our cultural context informs our ability to improvise appropriately in most (though not all) cases. This is precisely what computers cannot do and that is why society faces often unanticipated dangers when it gives machines autonomous control over potentially harmful activities.
Mr. Christian, a seasoned author on the subject, provides a comprehensive review of the history of A.I. development in this book. The review illustrates not only how a particular effect was achieved but also what went wrong in early attempts and how those issues were corrected—often but not always with complete success. The author carries us forward historically in both determinate (playing chess, go, or any game in which there is a specifiable outcome), partially determinate (safely operating a car, boat, or aircraft), and indeterminate (morality) domains.
In my career, I first encountered A.I. in the form of “expert systems” developed in the late 1970s and early 1980s to help energy companies find oil. I lost track of the field after that until the development of facial recognition systems and ChatGPT. Christian’s book filled in the gaps from the early 1980s and today. He has given me a sense of how much has been accomplished and in how many different ways, how much there is left to do, and intractable issues about which we cannot instruct machines because we do not know how to resolve them ourselves. Well written, great read!
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