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right and the vitalists were wrong: living things (a fortiori, brains, democracies, economies) are really nothing over and above the sum of their parts—there is no vital spark, and no ghost in the machine, and no invisible hand. The progress of science seems to have born this out, and in a sense it has: in looking for (say) living things to behave in ways that were not determined by the behavior of their cells and genes, vitalists were chasing ghosts. Still, in the last few decades cracks have begun to appear in the hegemonic analytic approach: cracks that suggest not that the insights garnered by that approach were wrong, but that they were incomplete. This is where complexity theory enters our story.

As an example, consider the highly computational theory of mind that’s been developed by some cognitive psychologists and philosophers of mind[1]. On this account, psychology as a scientific practice is, in a very real sense, predicated on a very large misunderstanding: according to the most radical computationalists, what we take to be “psychological states” are really nothing more than formal computational operations being carried out by the firing of one or another set of neurons in our brain. It’s worth emphasizing that this is a stronger thesis than the standard “metaphysical reduction” that’s rather more common in the philosophy of mind literature, and it is certainly a stronger thesis than a generally physicalist view of psychology (where psychological states in some sense are realized by or depend on the action of neurons). The strongest adherents of computational neuroscience argue that not only do mental states depend on brain states, but that (as a methodological dictum) we ought to focus our scientific efforts on mapping neuronal firings only. That is, it’s not just necessary to understand the brain in order to get a grip on psychology—understanding how neurons work just is understanding

  1. See, for instance, Pinker (2000). This position is also there at times in the work of Paul and Patricia Churchland, though it is also moderated at times when compared to the fairly hard-line computationalism of Pinker.