Anyone who is familiar with computational theories of mind (or brain), according to which the mind (or brain) is (analogous to) a computer, should agree that this is a good question (cf. John Searle, The Rediscovery of Mind, 1992, p. 205). For computational theories of mind to be formulated in a precise and testable manner, it must be made clear what it takes for something to be a computer. Yet there is little consensus on what a computer is.
Searle, for one, thinks that everything is a computer, because computational descriptions are very much like unconstrained series of labels, which may be freely applied to anything we wish. Because of this, Searle argues that the computational theory of mind is empty: It doesn’t tell us anything substantive about the mind.
Searle’s computational nihilism aside, a number of other issues in the foundations of computational theories of mind require an adequate account of what counts as a computer, and more specifically, what counts as a certain kind of computer. For instance, is the brain a digital or analog computer? Is the mind a serial or parallel computer? These questions have been debated ad nauseam. But without some precise criteria for what counts as a computer of a certain kind (digital vs. analog, serial vs. parallel, etc.), these debates remain unresolved.
In one of my papers, entitled “Computers,” I investigate the notion of computer systematically, grounding my account in the practices of computability theorists and computer scientists. I begin by rejecting the contention that everything is a computer. Then, I explain what distinguishes computers from calculators in terms of their functional properties and consequent computing power. I also offer a systematic taxonomy of kinds of computer, including general purpose vs. special purpose computers, analog vs. digital, and serial vs. parallel, with relatively explicit criteria for each. My account is mechanistic: which class a system belongs in, and which functions are computable by which system, depends on the system’s mechanistic properties. Finally, I briefly discuss some implications of my account for how to understand computational theories of mind. There are some surprises; for instance, the view that the brain is not a serial computer because it’s parallel turns out to be confused. For first, there are different notions of parallel computation; and second, the same computer can be both serial and parallel, in several senses.
As far as I know, my paper contains the most general, comprehensive, and systematic discussion of computers and their properties to date. I’m hoping it will help clarify some of the above debates about computational theories of mind and their testability. (I’m also hoping it will help researchers in other areas—e.g., historians and philosophers of computing—but that is less germane to this blog.)
My paper will appear in Pacific Philosophical Quarterly. As I prepare my final revision, I would greatly appreciate any comments. (You can access the paper from my webpage by clicking on “works” and then “Computers”.)