Arms races in human technology are easier to study than their biological equivalents because they are so much faster. We can actually see them going on, from year to year. In the case of a biological arms race, on the other hand, we can usually see only the end-products. Very rarely a dead animal or plant fossilizes, and it is then sometimes possible to see progressive stages in an animal arms race a little more directly. One of the most interesting examples of this concerns the electronic arms race, as shown in the brain sizes of fossil animals.
Brains themselves do not fossilize but skulls do, and the cavity in which the brain was housed — the braincase — if interpreted with care, can give a good indication of brain size. I said ‘if interpreted with care’, and the qualification is an important one. Among the many problems is the following. Big animals tend to have big brains partly just because they are big, but this doesn’t necessarily mean that they are, in any interesting sense, ‘cleverer’. Elephants have bigger brains than humans but, probably with some justice, we like to think that we are cleverer than elephants and that our brains are ‘really’ bigger if you make allowance for the fact that we are much smaller animals. Certainly our brains occupy a much larger proportion of our body than elephants’ brains do, as is evident from the bulging shape of our skulls. This is not just species vanity. Presumably a substantial fraction of any brain is needed to perform routine caretaking operations around the body, and a big body automatically needs a big brain for this. We must find some way of ‘taking out’ of our calculations that fraction of brain that can be attributed simply to body size, so that we can compare what is left over as the true ‘braininess’ of animals. This is another way of saying that we need some good way of defining exactly what we mean by true braininess. Different people are at liberty to come up with different methods of doing the calculations, but probably the most authoritative index is the ‘encephalization quotient’ or EQ used by Harry Jerison, a leading American authority on brain history.
The EQ is actually calculated in a somewhat complicated way, taking logarithms of brain weight and body weight, and standardizing against the average figures for a major group such as the mammals as a whole. Just as the ‘intelligence quotient’ or IQ used (or it may be misused) by human psychologists is standardized against the average for a whole population, the EQ is standardized against, say, the whole of the mammals. Just as an IQ of 100 means, by definition, an IQ identical to the average for a whole population, so an EQ of 1 means, by definition, an EQ identical to the average for, say, mammals of that size. The details of the mathematical technique don’t matter. In words, the EQ of a given species such as a rhino or a cat, is a measure of how much bigger (or smaller) the animal’s brain is than we should expect it to be, given the animal’s body size. How that expectation is calculated is certainly open to debate and criticism. The fact that humans have an EQ of 7 and hippos an EQ of 0.3 may not literally mean that humans are 23 times as clever as hippos! But the EQ as measured is probably telling us something about how much ‘computing power’ an animal has in its head, over and above the irreducible minimum of computing power needed for the routine running of its large or small body.
Measured EQs among modern mammals are very varied. Rats have an EQ of about 0.8, slightly below the average for all mammals. Squirrels are somewhat higher, about 1.5. Perhaps the threedimensional world of trees demands extra computing power for controlling precision leaps, and even more for thinking about efficient paths through a maze of branches that may or may not connect farther on. Monkeys are well above average, and apes (especially ourselves) even higher. Within the monkeys it turns out that some types have higher EQs than others and that, interestingly, there is some connection with how they make their living: insect-eating and fruit-eating monkeys have bigger brains, for their size, than leaf-eating monkeys. It makes some sense to argue that an animal needs less computing power to find leaves, which are abundant all around, than to find fruit, which may have to be searched for, or to catch insects, which take active steps to get away. Unfortunately, it is now looking as though the true story is more complicated, and that other variables, such as metabolic rate, may be more important. In the mammals as a whole, carnivores typically have a slightly higher EQ than the herbivores upon which they prey. The reader will probably have some ideas about why this might be, but it is hard to test such ideas. Anyway, whatever the reason, it seems to be a fact.
So much for modern animals. What Jerison has done is to reconstruct the probable EQs of extinct animals that now exist only as fossils. He has to estimate brain size by making plaster casts of the insides of braincases. Quite a lot of guesswork and estimation has to go into this, but the margins of error are not so great as to nullify the whole enterprise. The methods of taking plaster casts can, after all, be checked for their accuracy, using modern animals. We make-believe that the dried skull is all that we have from a modern animal, use a plaster cast to estimate how big its brain was from the skull alone, and then check with the real brain to see how accurate our estimate was. These checks on modern skulls encourage confidence in Jerison’s estimates of long-dead brains. His conclusion is, firstly, that there is a tendency for brains to become bigger as the millions of years go by. At any given time, the current herbivores tended to have smaller brains than the contemporary carnivores that preyed on them. But later herbivores tended to have larger brains than earlier herbivores, and later carnivores larger brains than earlier carnivores. We seem to be seeing, in the fossils, an arms race, or rather a series of restarting arms races, between carnivores and herbivores. This is a particularly pleasing parallel with human armament races, since the brain is the on-board computer used by both carnivores and herbivores, and electronics is probably the most rapidly advancing element in human weapons technology today.
How do arms races end? Sometimes they may end with one side going extinct, in which case the other side presumably stops evolving in that particular progressive direction, and indeed it will probably even ‘regress’ for economic reasons soon to be discussed. In other cases, economic pressures may impose a stable halt to an arms race, stable even though one side in the race is, in a sense, permanently ahead. Take running speed, for instance. There must be an ultimate limit to the speed at which a cheetah or a gazelle can run, a limit imposed by the laws of physics. But neither cheetahs nor gazelles have reached that limit. Both have pushed up against a lower limit which is, I believe, economic in character. High-speed technology is not cheap. It demands long leg bones, powerful muscles, capacious lungs. These things can be had by any animal that really needs to run fast, but they must be bought. They are bought at a steeply increasing price. The price is measured as what economists call ‘opportunity cost’. The opportunity cost of something is measured as the sum of all the other things that you have to forgo in order to have that something. The cost of sending a child to a private, fee-paying school is all the things that you can’t afford to buy as a result: the new car that you can’t afford, the holidays in the sun that you can’t afford (if you’re so rich that you can afford all these things easily, the opportunity cost, to you, of sending your child to a private school may be next to nothing). The price, to a cheetah, of growing larger leg muscles is all the other things that the cheetah could have done with the materials and energy used to make the leg muscles, for instance make more milk for cubs.
There is no suggestion, of course, that cheetahs do cost-accounting sums in their heads! It is all done automatically by ordinary natural selection. A rival cheetah that doesn’t have such big leg muscles may not run quite so fast, but it has resources to spare for making an extra lot of milk and therefore perhaps rearing another cub. More cubs will be reared by cheetahs whose genes equip them with the optimum compromise between running speed, milk production and all the other calls on their budget. It isn’t obvious what the optimum trade-off is between, say, milk production and running speed. It will certainly be different for different species, and it may fluctuate within each s
pecies. All that is certain is that trade-offs of this kind will be inevitable. When both cheetahs and gazelles reach the maximum running speed that they can ‘afford’, in their own internal economies, the arms race between them will come to an end.
Their respective economic stopping points may not leave them exactly equally matched. Prey animals may end up spending relatively more of their budget on defensive weaponry than predators do on offensive weaponry. One reason for this is summarized in the Aesopian moral: The rabbit runs faster than the fox, because the rabbit is running for his life, while the fox is only running for his dinner. In economic terms, this means that individual foxes that shift resources into other projects can do better than individual foxes that spend virtually all their resources on hunting technology. In the rabbit population, on the other hand, the balance of economic advantage is shifted towards those individual rabbits that are big spenders on equipment for running fast. The upshot of these economically balanced budgets within species is that arms races between species tend to come to a mutually stable end, with one side ahead.
We are unlikely to witness arms races in dynamic progress, because they are unlikely to be running at any particular ‘moment’ of geological time, such as our time. But the animals that are to be seen in our time can be interpreted as the end-products of an arms race that was run in the past.
To summarize the message of this chapter, genes are selected, not for their intrinsic qualities, but by virtue of their interactions with their environments. An especially important component of a gene’s environment is other genes. The general reason why this is such an important component is that other genes also change, as generations go by in evolution. This has two main kinds of consequences.
First, it has meant that those genes are favoured that have the property of ‘cooperating’ with those other genes that they are likely to meet in circumstances that favour cooperation. This is especially, though not exclusively, true of genes within the same species, because genes within one species frequently share cells with one another. It has led to the evolution of large gangs of cooperating genes, and ultimately to the evolution of bodies themselves, as the products of their cooperative enterprise. An individual body is a large vehicle or ‘survival machine’ built by a gene cooperative, for the preservation of copies of each member of that cooperative. They cooperate because they all stand to gain from the same outcome — the survival and reproduction of the communal body — and because they constitute an important part of the environment in which natural selection works on each other.
Second, circumstances don’t always favour cooperation. In their march down geological time, genes also encounter one another in circumstances that favour antagonism. This is especially, though not exclusively, true of genes in different species. The point about different species is that their genes don’t mix — because members of different species can’t mate with one another. When selected genes in one species provide the environment in which genes in another species are selected, the result is often an evolutionary arms race. Each new genetic improvement selected on one side of the arms race — say predators — changes the environment for selection of genes on the other side of the arms race — prey. It is arms races of this kind that have been mainly responsible for the apparently progressive quality of evolution, for the evolution of ever-improved running speed, flying skill, acuity of eyesight, keenness of hearing, and so on. These arms races don’t go on forever, but stabilize when, for instance, further improvements become too economically costly to the individual animals concerned.
This has been a difficult chapter, but it had to go into the book. Without it, we would have been left with the feeling that natural selection is only a destructive process, or at best a process of weeding-out. We have seen two ways in which natural selection can be a constructive force. One way concerns cooperative relationships between genes within species. Our fundamental assumption must be that genes are ‘selfish’ entities, working for their own propagation in the gene pool of the species. But because the environment of a gene consists, to such a salient degree, of other genes also being selected in the same gene pool, genes will be favoured if they are good at cooperating with other genes in the same gene pool. This is why large bodies of cells, working coherently towards the same cooperative ends, have evolved. This is why bodies exist, rather than separate replicators still battling it out in the primordial soup.
Bodies evolve integrated and coherent purposefulness because genes are selected in the environment provided by other genes within the same species. But because genes are also selected in the environment provided by other genes in different species, arms races develop. And arms races constitute the other great force propelling evolution in directions that we recognize as ‘progressive’, complex ‘design’. Arms races have an inherently unstable ‘runaway’ feel to them. They careen off into the future in a way that is, in one sense, pointless and futile, in another sense progressive and endlessly fascinating to us, the observers. The next chapter takes up a particular, rather special case of explosive, runaway evolution, the case that Darwin called sexual selection.
CHAPTER 8
Explosions and spirals
The human mind is an inveterate analogizer. We are compulsively drawn to see meaning in slight similarities between very different processes. I spent much of a day in Panama watching two teeming colonies of leaf-cutter ants fighting, and my mind irresistibly compared the limb-strewn battlefield to pictures I had seen of Passchendaele. I could almost hear the guns and smell the smoke. Shortly after my first book, The Selfish Gene, was published, I was independently approached by two clergymen, who both had arrived at the same analogy between ideas in the book and the doctrine of original sin. Darwin applied the idea of evolution in a discriminating way to living organisms changing in body form over countless generations. His successors have been tempted to see evolution in everything; in the changing form of the universe, in developmental ‘stages’ of human civilizations, in fashions in skirt lengths. Sometimes such analogies can be immensely fruitful, but it is easy to push analogies too far, and get overexcited by analogies that are so tenuous as to be unhelpful or even downright harmful. I have become accustomed to receiving my share of crank mail, and have learned that one of the hallmarks of futile crankiness is overenthusiastic analogizing.
On the other hand, some of the greatest advances in science have come about because some clever person spotted an analogy between a subject that was already understood, and another still mysterious subject. The trick is to strike a balance between too much indiscriminate analogizing on the one hand, and a sterile blindness to fruitful analogies on the other. The successful scientist and the raving crank are separated by the quality of their inspirations. But I suspect that this amounts, in practice, to a difference, not so much in ability to notice analogies as in ability to reject foolish analogies and pursue helpful ones. Passing over the fact that we have here yet another analogy, which may be foolish or may be fruitful (and is certainly not original), between scientific progress and Darwinian evolutionary selection, let me now come to the point that is relevant to this chapter. This is that I am about to embark on two interwoven analogies which I find inspiring but which can be taken too far if we are not careful. The first is an analogy between various processes that are united by their resemblance to explosions. The second is an analogy between true Darwinian evolution and what has been called cultural evolution. I think that these analogies may be fruitful — obviously, or I would not devote a chapter to them. But the reader is warned.
The property of explosions that is relevant is the one known to engineers as ‘positive feedback’. Positive feedback is best understood by comparison with its opposite, negative feedback. Negative feedback is the basis of most automatic control and regulation, and one of its neatest and best-known examples is the Watt steam governor. A useful engine should deliver rotational power at a constant rate, the right rate for the job in hand, milling, weaving, pumping or wh
atever it happens to be. Before Watt, the problem was that the rate of turning depended upon the steam pressure. Stoke the boiler and you speed up the engine, not a satisfactory state of affairs for a mill or loom that requires uniform drive for its machines. Watt’s governor was an automatic valve regulating the flow of steam to the piston.
The clever trick was to link the valve to the rotary motion produced by the engine, in such a way that the faster the engine ran the more the valve shut down the steam. Conversely, when the engine was running slowly, the valve opened up. Therefore an engine going too slowly soon speeded up, and an engine going too fast soon slowed down. The precise means by which the governor measured the speed was simple but effective, and the principle is still used today. A pair of balls on hinged arms spin round, driven by the engine. When they are spinning fast, the balls rise up on their hinges, by centrifugal force. When they are spinning slowly, they hang down. The hinged arms are directly linked to the steam throttle. With suitable fine-tuning, the Watt governor can keep a steam engine turning at an almost constant rate, in the face of considerable fluctuations in the firebox.
The underlying principle of the Watt governor is negative feedback. The output of the engine (rotary motion in this case) is fed back into the engine (via the steam valve). The feedback is negative because high output (fast rotation of the balls) has a negative effect upon the input (steam supply). Conversely, low output (slow rotation of the balls) boosts the input (of steam), again reversing the sign. But I introduced the idea of negative feedback only in order to contrast it with positive feedback. Let us take a Watt-governed steam engine, and make one crucial change in it. We reverse the sign of the relationship between the centrifugal ball apparatus and the steam valve. Now when the balls spin fast, the valve, instead of closing as Watt had it, opens. Conversely, when the balls spin slowly, the valve, instead of increasing the flow of steam, reduces it. In a normal, Watt-governed engine, an engine that started to slow down would soon correct this tendency and speed up again to the desired speed. But our doctored engine does just the opposite. If it starts to slow down, this makes it slow down even more. It soon throttles itself down to a halt. If, on the other hand, such a doctored engine happens to speed up a little, instead of the tendency being corrected as it would in a proper Watt engine, the tendency is increased. The slight speeding up is reinforced by the inverted governor, and the engine accelerates. The acceleration feeds back positively, and the engine accelerates even more. This continues until either the engine breaks up under the strain and the runaway flywheel careens through the factory wall, or no more steam pressure is available and a maximum speed is imposed.
The Blind Watchmaker Page 26
