Complexity: The Emerging Science at the Edge of Order and Chaos

by M. Mitchell Waldrop

Was Darwin “unscientific” because he couldn’t predict what species will evolve in the next million years? Are geologists unscientific because they can’t predict precisely where the next earthquake will come, or where the next mountain range will rise? Are astronomers unscientific because they can’t predict precisely where the next star will be born? Not at all. Predictions are nice, if you can make them. But the essence of science lies in explanation, laying bare the fundamental mechanisms of nature.

Those zillions of molecules have collectively acquired a property, liquidity, that none of them possesses alone. In fact, unless you know precisely where and how to look for it, there’s nothing in those well-understood equations of atomic physics that even hints at such a property. The liquidity is “

Neither phase transition would have any meaning for one molecule alone.

In that case, it wouldn’t matter how much investment got poured into the country. “If all you do is produce bananas, nothing will happen except that you produce more bananas.” But if a country ever managed to diversify and increase its complexity above the critical point, then you would expect it to undergo an explosive increase in growth and innovation—what some economists have called an “economic takeoff.

“The point is that the phase transitions may be lawful, but the specific details are not. So maybe we have the starts of models of historical, unfolding processes for such things as the Industrial Revolution, for example, or the Renaissance as a cultural transformation, and

self-reproduction, once considered to be an exclusive characteristic of living things, could indeed be achieved by machines.

Its credo is that life is not a property of matter per se, but the organization of that matter.

But the answer lies with a second great insight, which could be heard at the workshop again and again: living systems are machines, all right, but machines with a very different kind of organization from the ones we’re used to. Instead of being designed from the top down, the way a human engineer would do it, living systems always seem to emerge from the bottom up, from a population of much simpler systems. A cell consists of proteins, DNA, and other biomolecules. A brain consists of neurons. An embryo consists of interacting cells. An ant colony consists of ants. And for that matter, an economy consists of firms and individuals.

“The most surprising lesson we have learned from simulating complex physical systems on computers is that complex behavior need not have complex roots,”

Try doing that with a single set of top-level rules, said Langton. The system would be impossibly cumbersome and complicated, with the rules telling each boid precisely what to do in every conceivable situation. In fact, he had seen simulations like that; they usually ended up looking jerky and unnatural, more like an animated cartoon than like animated life. And besides, he said, since it’s effectively impossible to cover every conceivable situation, top-down systems are forever running into combinations of events they don’t know how to handle.

Furthermore, he said, suppose that you could create life. Then suddenly you would be involved in something a lot bigger than some technical definition of living versus nonliving. Very quickly, in fact, you would find yourself engaged in a kind of empirical theology. Having created a living creature, for example, would you then have the right to demand that it worship you and make sacrifices to you? Would you have the right to act as its god? Would you have the right to destroy it if it didn’t behave the way you wanted it to?