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ABSTRACT :

The notion of representation lies at the crossroads of questions about the nature of belief and knowledge, meaning, and intentionality. But there is some hope that it might be simpler than all those. If we could understand it clearly, it might then help to explicate those more difficult notions. In this paper, my central aim is to find a principled criterion, along lines that make biological sense, for deciding just when it becomes theoretically plausible to ascribe to some process or state a representational role. I shall be especially concerned with some differences, in this regard, between classical and connectionist models.

The relation between "standard" artificial intelligence and connectionism turns out to illustrate a "first in, last out" principle: What we most easily understand (and so can program) is what we have most recently invented; tasks we ourselves perform best, by contrast, are a lot harder to understand. Classical AI has modeled the former; connectionism tries to tackle the latter.

I end with some speculations about the possible implications of these considerations for our understanding of understanding.

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