Daniel Dennett in Edge.org:
I'm trying to undo a mistake I made some years ago, and rethink the idea that the way to understand the mind is to take it apart into simpler minds and then take those apart into still simpler minds until you get down to minds that can be replaced by a machine. This is called homuncular functionalism, because you take the whole person. You break the whole person down into two or three or four or seven sub persons that are basically agents. They're homunculi, and this looks like a regress, but it's only a finite regress, because you take each of those in turn and you break it down into a group of stupider, more specialized homunculi, and you keep going until you arrive at parts that you can replace with a machine, and that's a great way of thinking about cognitive science. It's what good old-fashioned AI tried to do and still trying to do.
The idea is basically right, but when I first conceived of it, I made a big mistake. I was at that point enamored of the McCulloch-Pitts logical neuron. McCulloch and Pitts had put together the idea of a very simple artificial neuron, a computational neuron, which had multiple inputs and a single branching output and a threshold for firing, and the inputs were either inhibitory or excitatory. They proved that in principle a neural net made of these logical neurons could compute anything you wanted to compute. So this was very exciting. It meant that basically you could treat the brain as a computer and treat the neuron as a sort of basic switching element in the computer, and that was certainly an inspiring over-simplification. Everybody knew is was an over-simplification, but people didn't realize how much, and more recently it's become clear to me that it's a dramatic over-simplification, because each neuron, far from being a simple logical switch, is a little agent with an agenda, and they are much more autonomous and much more interesting than any switch.