Artificial Intelligence: The Very Idea. By JOHN HAUGELAND. The MIT Press, Cambridge, MA, 1985. xii + 290 pp. $14.95. ISBN 0-262-08153-9. A Bradford Book.

Alas, John Haugeland has got the Very Idea wrong and made a few other important errors. Nevertheless, this is an excellent book because of the number of things he has got right, his fair-mindedness and his excellent explanations of the connections between AI and older philosophical issues.

His first error is regarding AI as a branch of biology, whereas it’s really a branch of computer science—somewhat related to a branch of biology. As a branch of computer science, AI concerns how a machine should decide how to achieve goals under certain conditions of information and computational resources. In this respect it’s like linear programming. Indeed if achieving goals always amounted to finding the maximum of a linear function given a collection of linear inequality constraints, then AI would be included in linear programming. However, the problems we want machines to solve are often quite different.

The key question in describing AI is characterizing the problems that require intelligence to solve and the methods available for solving them. For example, the roles of pattern matching, search and learning from experience need to be discussed. Haugeland doesn’t attempt any general discussion of this, although many of his examples are relevant.

Haugeland’s second mistake is to omit discussing mathematical logic as a way of representing the machine’s information about the world and the consequences of action in the world. Using logic is what gives AI a chance to match the modularity of human representation of information, e.g. the fact that we can receive information with provided by someone long since dead who had no idea how it was going to be used.

The third mistake is to omit discussing expert systems. AI has resulted in a certain technology that has both capabilities and limitations that represent the current state of AI as a science. He justifies this omission by remarking that expert systems have no pyschological pretensions. I suppose this dismissal is a consequence of regarding AI as biology rather than computer science.

Moreover, it seems to me that GOFAI (his abbreviation of “good old-fashioned AI”) doesn’t rest on the theory that intelligence is computation, an assertion whose vagueness makes me nervous. The theory is that intelligent behavior can be realized computationally. The extent to which human intelligence is realized digitally is a matter for psychologists and physiologists. For example, hormones may intervene in human thought processes in an analog way and may have chemical roles beyond communication, e.g. the same substance may digest food and signal that a person is full.

Here are some of the things he has got right.

First of all, Haugeland has got right the polarization between the scoffers and the boosters of AI—the self-assurance of both sides about the main philosophical issue. The scoffers say it’s ridiculous—“like imagining that your car (really) hates you” vs. the view that it’s only a matter of time until we understand intelligence well enough to program it. This reviewer is a booster and accepts Haugeland’s characterization subject to some qualifications not important enough to mention.

Second he’s right about the abstractness of the AI approach to intelligence. We consider it inessential whether the intelligence is implemented by electronics or by neurochemical mechanisms or even by a person manipulating pieces of paper according to rules he can follow but whose purpose he doesn’t understand.

The discussion of the relation between arguments about the possibility of AI and philosophical arguments going back to Aristotle, Hobbes, Descartes and Leibniz and Hume is perhaps the main content of the book. It shows that many issues raised by these philosophers are alive today in an entirely different technological context. However, it’s hard to trace any influence of this philosophy on present AI thought or even to argue that reading Hobbes would be helpful. What people are trying to do today is almost entirely determined by their experience with modern computing facilities rather than by old arguments however inspired.

Haugeland doesn’t discuss very much the influence of AI on philosophical thought except to acknowledge its existence. There is much more about that in Aaron Sloman’s The Computer Revolution in Philosophy, although Sloman’s arguments don’t seem to convince many of his former colleagues in philosophy.