Ari N. Schulman had an interesting piece in the New Atlantis recently on Why Minds Are Not Like Computers. Very briefly his view is that the aims of the strong AI project have quietly become less ambitious over time. In particular, from aiming to find the algorithms which directly generate high-level consciousness in one fell swoop, researchers have turned to simulating lower level mechanisms and modules; in some cases they’ve gone to a further level and are attempting to simulate the brain at neuronal level. Who knows, they might end up trying to do it at molecular or subatomic level, he says, but the point is that at these low levels the game is already lost; even if the simulation runs, we still won’t understand what’s happening on the higher levels. If we have to go to the level of simulating individual neurons, the original claim that the brain works the way a computer does has implicitly been abandoned.
Schulman thinks that a misleading application of an analogy between computers and the mind is key to the problem. In computers we have the well-established set of layers which goes from high-level languages through machine code all the way down to physical transistors; researchers assumed, he thinks, that they would in effect be able to reverse engineer the source code of the brain and come up with high-level scripts which explicated the mechanisms of consciousness; and that they would be able to do it simply by ensuring that the input-output relationships were reproduced without having to worry about whether the hidden inner mechanisms of their version were actually the same as those of nature. But it never happened, and as time goes by it seems less and less likely that those algorithms will ever be found; it looks as if the mind just isn’t like that after all.
Although there’s something recognisable about that, I’m not sure whether this is a completely accurate account historically. It is certainly true that the misplaced early optimism of Good Old Fashioned Artificial Intelligence is a thing of the past – but that’s hardly breaking news. I’m not sure that even in the most upbeat period people thought that they could do the entire mind in one go: even then they surely looked to start with simplified tasks and build single modules. It’s just that they thought these modules and tasks would be dealt with more quickly and easily than they really were. The recent emergence of projects like the Blue Brain, seeking to simulate the neuronal level working of the brain, are also less a sign of lack of confidence in AI and more a sign of growing confidence in the number-crunching power of the computers now available. I don’t think such projects are exactly typical of where things are at these days in any case.
Still, plausible claims? Of course, working out the high-level code, or even recognising the general drift of a program, from looking only at the machine-code level is not at all an easy business, so the fact that looking at neurons for many years has not yet led us to a general theory of consciousness is not necessarily a sign that it never will. Schulman does not, like Searle (whose views he discusses), take the view that something about the physical stuff of brains is essential; his objection to functionalism seems merely to be that it hasn’t worked yet. Perhaps we just need more patience.
We also need to be a little careful about the diagnosis. There are actually different ways of dividing the whole business into levels; one is the programmer-facing way which Schulman mainly focuses on; another is the user-facing one. Here the bottom level is made up of meaningless symbols; somewhere in the middle is organised data; and at the top is meaningful information. Surely it’s here that the aim of AI researchers has been focussed; they expected consciousness, not as high-level program code, but as outputs which mean something to a human being, or which ‘make sense’ in the context of a task. Ultimately, for consciousness, the outputs have to make sense to the machine itself. If some form of computationalism can deliver these results, I don’t think the absence of a high-level theory in the other sense would indicate philosophical failure.
Even if we do ultimately have to go beyond a narrow functionalist view, we need not abandon the overall quest. We should perhaps hang on to the distinction between consciousness as computation and consciousness as computable. The idea that the mind actually is just the programs running in the brain may look less plausible than it did; the idea that programs running somewhere might sustain a mind might yet be getting a second wind. It might be too narrow a view of clocks to say that they are nothing more than cogs, springs, and other pieces of mechanism; the works don’t tell us what the essence of a clock is. But the ironmongery is all we need to make a clock, and perhaps we could make one that worked before we fully understood the principle of the escapement mechanism…?