ROD BROOKS: Every nine years or so I change what I'm doing scientifically. Last year, 2001, I moved away from building humanoid robots to worry about what the difference is between living matter and non-living matter. You have an organization of molecules over here and it's a living cell; you have an organization of molecules over here and it's just matter. What is it that makes something alive? Humberto Maturana was interested in this question, as was the late Francisco Varela in his work on autopoesis. More recently, Stuart Kauffman has talked about what it is that makes something living, how it is a self-perpetuating structure of interrelationships.

We have all become computation-centric over the last few years. We've tended to think that computation explains everything. When I was a kid, I had a book which described the brain as a telephone-switching network. Earlier books described it as a hydrodynamic system or a steam engine. Then in the '60s it became a digital computer. In the '80s it became a massively parallel digital computer. I bet there's now a kid's book out there somewhere which says that the brain is just like the World Wide Web because of all of its associations. We're always taking the best technology that we have and using that as the metaphor for the most complex things—the brain and living systems. And we've done that with computation.

But maybe there's more to us than computation. Maybe there's something beyond computation in the sense that we don't understand and we can't describe what's going on inside living systems using computation only. When we build computational models of living systems—such as a self-evolving system or an artificial immunology system—they're not as robust or rich as real living systems. Maybe we're missing something, but what could that something be?

You could hypothesize that what's missing might be some aspect of physics that we don't yet understand. David Chalmers has certainly used that notion when he tries to explain consciousness. Roger Penrose uses that notion to a certain extent when he says that it's got to be the quantum effects in the microtubules. He's looking for some physics that we already understand but are just not describing well enough.

If we look back at how people tried to understand the solar system in the time of Kepler and Copernicus, we notice that they had their observations, geometry, and a. They could describe what was happening in those terms, but it wasn't until they had calculus that they were really able to make predictions and have a really good model of what was happening. My working hypothesis is that in our understanding of complexity and of how lots of pieces interact we're stuck at that algebra-geometry stage. There's some other tool—some organizational principle—that we need to understand in order to really describe what's going on.

And maybe that tool doesn't have to be disruptive. If we look at what happened in the late 19th century through the middle of the 20th, there were a couple of very disruptive things that happened in physics: quantum mechanics and relativity. The whole world changed. But computation also came along in that time period—around the 1930s—and that wasn't disruptive. If you were to take a 19th century mathematician and sit him down in front of a chalk board, you could explain the ideas of computation to him in a few days. He wouldn't be saying, "My God, that can't be true!" But if we took a 19th century physicist (or for that matter, an ordinary person in the 21st century) and tried to explain quantum mechanics to him, he would say, "That can't be true. It's too disruptive." It's a completely different way of thinking. Using computation to look at physical systems is not disruptive to the extent that it needs its own special physics or chemistry; it's just a way of looking at organization.