http://www.edge.org/conversation/normal-well-tempered-mind
"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 in the 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.
The question is, what happens to your ideas about computational architecture when you think of individual neurons not as dutiful slaves or as simple machines but as agents that have to be kept in line and that have to be properly rewarded and that can form coalitions and cabals and organizations and alliances? This vision of the brain as a sort of social arena of politically warring forces seems like sort of an amusing fantasy at first, but is now becoming something that I take more and more seriously, and it's fed by a lot of different currents.
Evolutionary biologist David Haig has some lovely papers on intrapersonal conflicts where he's talking about how even at the level of the genetics, even at the level of the conflict between the genes you get from your mother and the genes you get from your father, the so-called madumnal and padumnal genes, those are in opponent relations and if they get out of whack, serious imbalances can happen that show up as particular psychological anomalies.
We're beginning to come to grips with the idea that your brain is not this well-organized hierarchical control system where everything is in order, a very dramatic vision of bureaucracy. In fact, it's much more like anarchy with some elements of democracy. Sometimes you can achieve stability and mutual aid and a sort of calm united front, and then everything is hunky-dory, but then it's always possible for things to get out of whack and for one alliance or another to gain control, and then you get obsessions and delusions and so forth. You begin to think about the normal well-tempered mind, in effect, the well-organized mind, as an achievement, not as the base state, something that is only achieved when all is going well, but still, in the general realm of humanity, most of us are pretty well put together most of the time. This gives a very different vision of what the architecture is like, and I'm just trying to get my head around how to think about that. What we're seeing right now in cognitive science is something that I've been anticipating for years, and now it's happening, and it's happening so fast I can't keep up with it. We're now drowning in data, and we're also happily drowning in bright young people who have grown up with this stuff and for whom it's just second nature to think in these quite abstract computational terms, and it simply wasn't possible even for experts to get their heads around all these different topics 30 years ago. Now a suitably motivated kid can arrive at college already primed to go on these issues. It's very exciting, and they're just going to run away from us, and it's going to be fun to watch.
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