What Are Intelligence? And Why? 1996 AAAI Presidential Address

Randall Davis

Abstract


This article, derived from the 1996 Association for the Advancement of Artificial Intelligence Presidential Address, explores the notion of intelligence from a variety of perspectives and finds that it "are" many things. It has, for example, been interpreted in a variety of ways even within our own field, ranging from the logical view (intelligence as part of mathematical logic) to the psychological view (intelligence as an empirical phenomenon of the natural world) to a variety of others. One goal of this article is to go back to basics, reviewing the things that we, individually and collectively, have taken as given, in part because we have taken multiple different and sometimes inconsistent things for granted. I believe it will prove useful to expose the tacit assumptions, models, and metaphors that we carry around as a way of understanding both what we're about and why we sometimes seem to be at odds with one another. Intelligence are also many things in the sense that is a product of evolution. Our physical bodies are in many ways overdetermined, unnecessarily complex, and inefficiently designed, that is, the predictable product of the blind search that is evolution. What's manifestly true of our anatomy is also likely true of our cognitive architecture. Natural intelligence is unlikely to be limited by principles of parsimony and is likely to be overdetermined, unnecessarily complex, and inefficiently designed. In this sense, intelligence are many things because is composed of the many elements that have been thrown together over evolutionary timescales. I suggest that in the face of that, searching for minimalism and elegance may be a diversion, for it simply may not be there. Somewhat more crudely put: The human mind is a 400,000-year-old legacy application -- and you expected to find structured programming? I end with a number of speculations, suggesting that there are some niches in the design space of intelligences that are currently underexplored. One example is the view that thinking is in part visual, and hence it might prove useful to develop representations and reasoning mechanisms that reason with diagrams (not just about them) and that take seriously their visual nature. I speculate as well that thinking may be a form of reliving, that re-acting out what we have experienced is one powerful way to think about and solve problems in the world. In this view, thinking is not simply the decontextualized manipulation of abstract symbols, powerful though that may be. Instead, some significant part of our thinking may be the reuse or simulation of our experiences in the environment. In keeping with this, I suggest that it may prove useful to marry the concreteness of reasoning in a model with the power that arises from reasoning abstractly.

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DOI: http://dx.doi.org/10.1609/aimag.v19i1.1356

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