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But beyond the question of subjective flavoring, there remains the problem of whether Darwin has explained enough. Is it not possible that there remains an as-yet unarticulated idea that explains aspects of achievement and creativity that Darwin does not?

For instance, is Darwinian-styled explanation sufficient to understand the process of rational thought? There are a plethora of recent theories in which the brain is said to produce random distributions of subconscious ideas that compete with one another until only the best one has survived, but do these theories really fit with what people do?

In nature, evolution appears to be brilliant at optimizing, but stupid at strategizing. (The mathematical image that expresses this idea is that "blind" evolution has enourmous trouble getting unstuck from a local minima in an energy landscape.) The classic question would be: How could evolution have made such marvelous feet, claws, fins, and paws, but have missed the wheel? There are plenty of environments in which creatures would benefit from wheels, so why haven't any appeared? Not even once? (A great long term art project for some rebellious kid in school now: Genetically engineer an animal with wheels! See if DNA can be made to do it.)

People came up with the wheel and numerous other useful inventions that seem to have eluded evolution. It is possible that the explanation is simply that hands had access to a different set of inventions than DNA, even though both were guided by similar processes. But it seems to me premature to treat such an interpretation as a certainty. Is it not possible that in rational thought the brain does some as yet unarticulated thing that might have originated in a Darwinian process, but that cannot be explained by it?

The first two or three generations of artificial intelligence researchers took it as a given that blind evolution in itself couldn't be the whole of the story, and assumed that there were elements that distinguished human mentation from other Earthly processes. For instance, humans were thought by many to build abstract representations of the world in their minds, while the process of evolution needn't do that. Furthermore, these representations seemed to possess extraordinary qualities like the fearsome and perpetually elusive "common sense". After decades of failed attempts to build similar abstractions in computers, the field of AI gave up, but without admitting it. Surrender was couched as merely a series of tactical retreats. AI these days is often conceived as more of a craft than a branch of science or engineering. A great many practitioners I've spoken with lately hope to see software evolve that does various things but seem to have sunk to an almost "post-modern", or cynical lack of concern with understanding how these gizmos might actually work.

It is important to remember that craft-based cultures can come up with plenty of useful technologies, and that the motivation for our predecessors to embrace the Enlightenment and the ascent of rationality was not just to make more technologies more quickly. There was also the idea of Humanism, and a belief in the goodness of rational thinking and understanding. Are we really ready to abandon that?

Finally, there is an empirical point to be made: There has now been over a decade of work worldwide in Darwinian approaches to generating software, and while there have been some fascinating and impressive isolated results, and indeed I enjoy participating in such research, nothing has arisen from the work that would make software in general any better- as I'll ddescribe in the next section.

So, while I love Darwin, I won't count on him to write code.

Belief #5: That qualitative as well as quantitative aspects of information systems will be accelerated by Moore's Law.

The hardware side of computers keeps on getting better and cheaper at an exponential rate known by the moniker "Moore's Law". Every year and a half or so computation gets roughly twice as fast for a given cost. The implications of this are dizzying and so profound that they induce vertigo on first apprehension. What could a computer that was a million times faster than the one I am writing this text on be able to do? Would such a computer really be incapable of doing whatever it is my human brain does? The quantity of a "million" is not only too large to grasp intuitively, it is not even accessible experimentally for present purposes, so speculation is not irrational. What is stunning is to realize that many of us will find out the answer in our lifetimes, for such a computer might be a cheap consumer product in about, say 30 years.

This breathtaking vista must be starkly contrasted with the Great Shame of computer science, which is that we don't seem to be able to write software much better as computers get much faster. Computer software continues to disappoint. How I hated UNIX back in the seventies - that devilish accumulator of data trash, obscurer of function, enemy of the user! If anyone had told me back then that getting back to embarrassingly primitive UNIX would be the great hope and investment obsession of the year 2000, merely because it's name was changed to LINUX and its source code was opened up again, I never would have had the stomach or the heart to continue in computer science.