Chapter 20


"Order for Free"

Brian Goodwin: Stuart is primarily interested in the emergence of order in evolutionary systems. That's his fix. It's exactly the same as mine, in terms of the orientation towards biology, but he uses a very different approach. Our approaches are complementary with respect to the same problem: How do you understand emergent novelty in evolution? Emergent order? Stuart's great contributions are there.


STUART KAUFFMAN is a biologist; professor of biochemistry at the University of Pennsylvania and a professor at the Santa Fe Institute; author of Origins of Order: Self Organization and Selection in Evolution (1993), and coauthor with George Johnson of At Home in the Universe (1995).

Stuart Kauffman: What kinds of complex systems can evolve by accumulation of successive useful variations? Does selection by itself achieve complex systems able to adapt? Are there lawful properties characterizing such complex systems? The overall answer may be that complex systems constructed so that they're on the boundary between order and chaos are those best able to adapt by mutation and selection.

Chaos is a subset of complexity. It's an analysis of the behavior of continuous dynamical systems — like hydrodynamic systems, or the weather — or discrete systems that show recurrences of features and high sensitivity to initial conditions, such that very small changes in the initial conditions can lead a system to behave in very different ways. A good example of this is the so called butterfly effect: the idea is that a butterfly in Rio can change the weather in Chicago. An infinitesimal change in initial conditions leads to divergent pathways in the evolution of the system. Those pathways are called trajectories. The enormous puzzle is the following: in order for life to have evolved, it can't possibly be the case that trajectories are always diverging. Biological systems can't work if divergence is all that's going on. You have to ask what kinds of complex systems can accumulate useful variation.

We've discovered the fact that in the evolution of life very complex systems can have convergent flow and not divergent flow. Divergent flow is sensitivity to initial conditions. Convergent flow means that even different starting places that are far apart come closer together. That's the fundamental principle of homeostasis, or stability to perturbation, and it's a natural feature of many complex systems. We haven't known that until now. That's what I found out twenty-five years ago, looking at what are now called Kauffman models — random networks exhibiting what I call "order for free."

Complex systems have evolved which may have learned to balance divergence and convergence, so that they're poised between chaos and order. Chris Langton has made this point, too. It's precisely those systems that can simultaneously perform the most complex tasks and evolve, in the sense that they can accumulate successive useful variations. The very ability to adapt is itself, I believe, the consequence of evolution. You have to be a certain kind of complex system to adapt, and you have to be a certain kind of complex system to coevolve with other complex systems. We have to understand what it means for complex systems to come to know one another — in the sense that when complex systems coevolve, each sets the conditions of success for the others. I suspect that there are emergent laws about how such complex systems work, so that, in a global, Gaia- like way, complex coevolving systems mutually get themselves to the edge of chaos, where they're poised in a balanced state. It's a very pretty idea. It may be right, too.

My approach to the coevolution of complex systems is my order-for-free theory. If you have a hundred thousand genes and you know that genes turn one another on and off, then there's some kind of circuitry among the hundred thousand genes. Each gene has regulatory inputs from other genes that turn it on and off. This was the puzzle: What kind of a system could have a hundred thousand genes turning one another on and off, yet evolve by creating new genes, new logic, and new connections?

Suppose we don't know much about such circuitry. Suppose all we know are such things as the number of genes, the number of genes that regulate each gene, the connectivity of the system, and something about the kind of rules by which genes turn one another on and off. My question was the following: Can you get something good and biology-like to happen even in randomly built networks with some sort of statistical connectivity properties? It can't be the case that it has to be very precise in order to work — I hoped, I bet, I intuited, I believed, on no good grounds whatsoever — but the research program tried to figure out if that might be true. The impulse was to find order for free. As it happens, I found it. And it's profound.

One reason it's profound is that if the dynamical systems that underlie life were inherently chaotic, then for cells and organisms to work at all there'd have to be an extraordinary amount of selection to get things to behave with reliability and regularity. It's not clear that natural selection could ever have gotten started without some preexisting order. You have to have a certain amount of order to select for improved variants.

Think of a wiring diagram that has ten thousand light bulbs, each of which has inputs from two other light bulbs. That's all I'm going to tell you. You pick the inputs to each bulb at random, and put connecting wires between them, and then assign one of the possible switching rules to each of the light bulbs at random. One rule might be that a light bulb turns on at the next moment if both of its inputs are on at the previous moment. Or it might turn on if both of its inputs are off.

If you go with your intuition, or if you ask outstanding physicists, you'll reach the conclusion that such a system will behave chaotically. You're dealing with a random wiring diagram, with random logic — a massively complex, disordered, parallel- processing network. You'd think that in order to get such a system to do something orderly you'd have to build it in a precise way. That intuition is fundamentally wrong. The fact that it's wrong is what I call "order for free."

There are other epistemological considerations regarding "order for free." In the next few years, I plan to ask, "What do complex systems have to be so that they can know their worlds?" By "know" I don't mean to imply consciousness; but a complex system like the E. coli bacterium clearly knows its world. It exchanges molecular variables with its world, and swims upstream in a glucose gradient. In some sense, it has an internal representation of that world. It's also true that IBM in some sense knows its world. I have a hunch that there's some deep way in which IBM and E. coli know their worlds in the same way. I suspect that there's no one person at IBM who knows IBM's world, but the organization gets a grip on its economic environment. What's the logic of the structure of these systems and the worlds that they come to mutually live in, so that entities that are complex and ordered in this way can successfully cope with one another? There must be some deep principles.

For example, IBM is an organization that knows itself, but I'm not quite talking about Darwinian natural selection operating as an outside force. Although Darwin presented natural selection as an external force, what we're thinking of is organisms living in an environment that consists mostly of other organisms. That means that for the past four billion years, evolution has brought forth organisms that successfully coevolved with one another. Undoubtedly natural selection is part of the motor, but it's also true that there is spontaneous order.

By spontaneous order, or order for free, I mean this penchant that complex systems have for exhibiting convergent rather than divergent flow, so that they show an inherent homeostasis, and then, too, the possibility that natural selection can mold the structure of systems so that they're poised between these two flows, poised between order and chaos. It's precisely systems of this kind that will provide us with a macroscopic law that defines ecosystems, and I suspect it may define economic systems as well.

While it may sound as if "order for free" is a serious challenge to Darwinian evolution, it's not so much that I want to challenge Darwinism and say that Darwin was wrong. I don't think he was wrong at all. I have no doubt that natural selection is an overriding, brilliant idea and a major force in evolution, but there are parts of it that Darwin couldn't have gotten right. One is that if there is order for free — if you have complex systems with powerfully ordered properties — you have to ask a question that evolutionary theories have never asked: Granting that selection is operating all the time, how do we build a theory that combines self-organization of complex systems — that is, this order for free — and natural selection? There's no body of theory in science that does this. There's nothing in physics that does this, because there's no natural selection in physics — there's self organization. Biology hasn't done it, because although we have a theory of selection, we've never married it to ideas of self-organization. One thing we have to do is broaden evolutionary theory to describe what happens when selection acts on systems that already have robust self-organizing properties. This body of theory simply does not exist.

There are a couple of parallels concerning order for free. We've believed since Darwin that the only source of order in organisms is selection. This is inherent in the French biologist François Jacob's phrase that organisms are "tinkered-together contraptions." The idea is that evolution is an opportunist that tinkers together these widgets that work, and the order you see in an organism has, as its source, essentially only selection, which manages to craft something that will work. But if there's order for free, then some of the order you see in organisms is not due to selection. It's due to something somehow inherent in the building blocks. If that's right, it's a profound shift, in a variety of ways.

The origin of life might be another example of order for free. If you have complex-enough systems of polymers capable of catalytic action, they'll self-organize into an autocatalytic system and, essentially, simply be alive. Life may not be as hard to come by as we think it is.

There are some immediate possibilities for the practical application of these theories, particularly in the area of applied molecular evolution. In l985, Marc Ballivet and I applied for a patent based on the idea of generating very, very large numbers of partly or completely random DNA sequences, and therefrom RNA sequences, and from that proteins, to learn how to evolve biopolymers for use as drugs, vaccines, enzymes, and so forth. By "very large" I mean numbers on the order of billions, maybe trillions of genes — new genes, ones that have never before existed in biology. Build random genes, or partly random genes. Put them into an organism. Make partly random RNA molecules; from that make partly random proteins, and learn from that how to make drugs or vaccines. Within five years, I hope we'll be able to make vaccines to treat almost any disease you want, and do it rapidly. We're going to be able to make hundreds of new drugs.

A related area is that probably a hundred million molecules would suffice as a roughed-in universal toolbox, to catalyze any possible reaction. If you want to catalyze a specific reaction, you go to the toolbox, you pull out a roughed-in enzyme, you tune it up by some mutations, and you catalyze any reaction you want. This will transform biotechnology. It will transform chemistry.

There are also connections to be made between evolutionary theory and economics. One of the fundamental problems in economics is that of bounded rationality. The question in bounded rationality is, How can agents who aren't infinitely rational and don't have infinite computational resources get along in their worlds? There's an optimizing principle about precisely how intelligent such agents ought to be. If they're either too intelligent or too stupid, the system doesn't evolve well.

Economist colleagues and I are discussing the evolution of a technological web, in which new goods and services come into existence and in which one can see bounded rationality in a nonequilibrium theory of price formation. It's the next step toward understanding what it means for complex systems to have maps of their world and to undertake actions for their own benefit which are optimally complex or optimally intelligent — boundedly rational. It's also part of the attempt to understand how complex systems come to know their world.

Brian Goodwin: Stuart is primarily interested in the emergence of order in evolutionary systems. That's his fix. It's exactly the same as mine, in terms of the orientation toward biology, but he uses a very different approach. Our approaches are complementary with respect to the same problem: How do you understand emergent novelty in evolution? Emergent order? Stuart's great contributions are there.

The notion of life at the edge of chaos is absolutely germane to Stuart's work. He didn't discover that phrase, but his work has always been concerned with precisely that notion, of how you have an immensely complex system with patterns of interaction that don't obviously lead anywhere, and suddenly out pops order.

That's what he discovered when he was a medical student in the sixties messing about with computers. He worked with François Jacob's and Jacques Monod's ideas about controls. He implemented those on his computer, and he looked at neural networks. It's the same thing that inspired me, but we went in different directions. I went in the direction of the organism as a dynamic organization, and he was much closer to Warren McCulloch and the notion of logical networks and applying it to gene networks. Stuart and I have always had this complementary approach to things, and yet we come to exactly the same conclusions about the emergence of order out of chaotic dynamics. Stuart has the fastest flow of interesting new ideas of anybody I've ever met. I've learned a lot from him.

W. Daniel Hillis: Stuart Kauffman is a strange creature, because he's a theoretical biologist, which is almost an oxymoron. In physics, there are the theoretical types and the experimental types, and there's a good understanding of what the relationship is between them. There's a tremendous respect for the theoreticians. In physics, the theory is almost the real stuff, and the experiments are just an approximation to test the theory. If you get something a little bit wrong, then it's probably an experimental error. The theory is the thing of perfection, unless you find an experiment that shows that you need to shift to another theory. When Eddington went off during a solar eclipse to measure the bending of starlight by the sun and thus to test Einstein's general relativity theory, somebody asked Einstein what he would think if Eddington's measurements failed to support his theory, and Einstein's comment was, "Then I would have felt sorry for the dear Lord. The theory is correct."

In biology, however, this is reversed. The experimental is on top, and the theory is considered poor stuff. Everything in biology is data. The way to acquire respect is to spend hours in the lab, and have your students and postdocs spend hours in the lab, getting data. In some sense, you're not licensed to theorize unless you get the data. And you're allowed to theorize only about your own data — or at the very least you need to have collected data before you get the right to theorize about other data.

Stuart is of the rare breed that generates theories without being an experimentalist. He takes the trouble to understand things, such as dynamical-systems theory, and tries to connect those into biology, so he becomes a conduit of ideas that are coming out of physics, from the theorists in physics, into biology.

Daniel C. Dennett: Stuart Kauffman and his colleague Brian Goodwin are particularly eager to discredit the powerful image first made popular by the great French biologists Jacques Monod and François Jacob — the image of Mother Nature as a tinkerer engaged in the opportunistic handiwork that the French call bricolage. Kauffman wants to stress that the biological world is much more a world of Newtonian discoveries than of Shakespearean creations. He's certainly found some excellent demonstrations to back up this claim. Kauffman is a meta-engineer. I fear that his attack on the metaphor of the tinkerer feeds the yearning of those who don't appreciate Darwin's dangerous idea. It gives them a false hope that they're seeing not the forced hand of the tinkerer but the divine hand of God in the workings of nature. Kauffman gets that from Brian Goodwin. John Maynard Smith has been pulling Kauffman in the other direction — very wisely so, in my opinion.

Stephen Jay Gould: Stuart Kauffman is very similar to Brian Goodwin, in that they are both trying to explore the relevance of the grand structuralist tradition, which Darwinian functionalism never paid a whole lot of attention to. Stuart is different from Brian, in that Brian focuses upon the morphology of organisms. Stuart's main interests are in questions of the origin of life, the origins of molecular organization, which I don't understand very well. I'm not as quantitative as he is, so I don't follow all the arguments in his book. He's trying to understand what aspects of organic order follow from the physical principles of matter, and the mathematical structure of nature, and need not be seen as Darwinian optimalities produced by natural selection.

He's following in the structuralist tradition, which should not be seen as contrary to Darwin but as helpful to Darwin. Structural principles set constraints, and natural selection must work within them. His "order for free" is an outcome of sets of constraints; it shows that a great deal of order can be produced just from the physical attributes of matter and the structural principles of organization. You don't need a special Darwinian argument; that's what he means by "order for free." It's a very good phrase, because a strict Darwinian thinks that all sensible order has to come from natural selection. That's not true.

J. Doyne Farmer: Stuart Kauffman was in a theoretical-biology group at the University of Chicago, run by Jack Cowan, that included people like Arthur Winfree, Leon Glass, and several others who have become some of the most famous theoretical biologists. The fact that any of these guys are still employed as scientists is a tribute to their ability; most of the biology establishment hates theoreticians and surviving as a theoretical biologist is difficult. Stuart survived, in part, by doing experiments as well, but I think his real passion has always been for theoretical biology.

Francisco Varela: Stuart has taken the notion of seeing emerging levels in biological organizations into explicit forms and mechanisms. In his early work on genetic networks, he did some very fundamental things. He took something that was vague and made it into a concrete example that was workable.

I have a little harder time with his last book. The monster, The Origins of Order. Although many of the pieces in there have a flavor of something quite interesting, it doesn't seem to me that the book hangs together as a whole. There's too much of "Let's assume this, and let's assume that, and if this were right, then...." But the basic idea is that we're back to the notion of evolution having intrinsic factors, and in this regard it has to be right. It's like Nick Humphrey's book. Although the smell is the right one, I'm not so sure I can buy the actual theory that he's trying to stitch together.

Stuart is one of the most competent people we have around when it comes to dealing with molecular biological networks. He's one of the great people, in that he has put some important bricks in that edifice, but that edifice has been built by many other people as well: Gould, Eldredge, Margulis, Goodwin. If there's a slight criticism I would make of Stuart, it's that sometimes he's not so clear in acknowledging that. What's happening here is that there's an evolution — or revolution — in biology, which is going beyond Darwin. But this revolution is not reducible to Stuart's own way of expressing it.

Niles Eldredge: Stuart is amazing. He had me on the floor of a cab, doubled up in laughter, the first time I met him. He was imitating all of the variant accents of the Oxford dons in philosophy. He's an amazingly funny guy, very likable guy, and extremely bright, of course. He takes what I used to call a transformationalist approach to evolution.

The standard way of looking at evolution is that evolution is a matter of transforming the physical properties of organisms. Stuart's got models jumping around from adaptive peak to adaptive peak, to explain the early Cambrian explosion. There's so much missing between the way he's thinking about things and the way I'm thinking about things that we've never really connected. We've talked, and I've put him together with other people who use computers to simulate evolutionary patterns, but there's just too much of a gap in our approach to things for there to be much useful dialog between us.

Nicholas Humphrey: Kauffman is less radical than Goodwin, at least nowadays. Kauffman originally would have said that natural selection doesn't play a very important role, but he's been persuaded that even if the possibilities that biology has to play with are determined by the properties of complex systems, nonetheless the ones we see in nature are those that have been selected. The world throws up possibilities, and then natural selection gets to work and ensures that just certain ones survive.

Kauffman is doing wonderful work, and he's certainly put the cat among the pigeons for old fashioned neo-Darwinism. He's forced people to recognize that selection may not be the only designing force in nature. But he's not claiming to be the new Darwin. We don't need a new Darwin

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Excerpted from The Third Culture: Beyond the Scientific Revolution by John Brockman (Simon & Schuster, 1995) . Copyright 1995 by John Brockman. All rights reserved.