The Selfish Gene

by Richard Dawkins

To a Darwinian, a successful strategy is one that has become numerous in the population of strategies. For a strategy to remain successful, it must do well specifically when it is numerous, that is in a climate dominated by copies of itself.

Axelrod did, as a matter of fact, run a third round of his tournament as natural selection might have run it, looking for an ESS.

Axelrod took the 63 strategies and threw them again into the computer to make ‘generation 1’ of an evolutionary succession. In ‘generation 1’, therefore, the ‘climate’ consisted of an equal representation of all 63 strategies. At the end of generation 1, winnings to each strategy were paid out, not as ‘money’ or ‘points’, but as offspring, identical to their (asexual) parents. As generations went by, some strategies became scarcer and eventually went extinct. Other strategies became more numerous. As the proportions changed, so, consequently, did the ‘climate’ in which future moves of the game took place. Eventually, after about 1,000 generations, there were no further changes in proportions, no further changes in climate. Stability was reached.

Of the nasty strategies, one or two of them began by increasing in frequency, but their prosperity, like that of cheat in my simulation, was short-lived. The only nasty strategy to survive beyond generation 200 was one called Harrington. Harrington’s fortunes rose steeply for about the first 150 generations. Thereafter it declined rather gradually, approaching extinction around generation 1,000. Harrington did well temporarily for the same reason as my original cheat did. It exploited softies like Tit for Two Tats (too forgiving) while these were still around. Then, as the softies were driven extinct, Harrington followed them, having no easy prey left. The field was free for ‘nice’ but ‘provocable’ strategies like Tit for Tat.

When all the nasties had been driven extinct, there was no way in which any of the nice strategies could be distinguished from Tit for Tat or from each other, because they all, being nice, simply played cooperate against each other.

Suspicious Tit for Tat is technically nasty, but it is not very nasty. It behaves just like Tit for Tat itself after the first move, but—this is what makes it technically nasty—it does defect on the very first move of the game. In a climate entirely dominated by Tit for Tat, Suspicious Tit for Tat does not prosper, because its initial defection triggers an unbroken run of mutual recrimination. When it meets a Tit for Two Tats player, on the other hand, Tit for Two Tats’s greater forgivingness nips this recrimination in the bud. Both players end the game with at least the ‘benchmark’, all C, score and with Suspicious Tit for Tat scoring a bonus for its initial defection. Boyd and Lorberbaum showed that a population of Tit for Tat could be invaded, evolutionarily speaking, by a mixture of Tit for Two Tats and Suspicious Tit for Tat, the two prospering in each other’s company. This combination is almost certainly not the only combination that could invade in this kind of way. There are probably lots of mixtures of slightly nasty strategies with nice and very forgiving strategies that are together capable of invading.

As in the case of true ESSs, it is possible for more than one strategy to be collectively stable at the same time. And again, it is a matter of luck which one comes to dominate a population. Always Defect is also stable, as well as Tit for Tat. In a population that has already come to be dominated by Always Defect, no other strategy does better. We can treat the system as bistable, with Always Defect being one of the stable points, Tit for Tat (or some mixture of mostly nice, retaliatory strategies) the other stable point. Whichever stable point comes to dominate the population first will tend to stay dominant.

It obviously matters, therefore, on which side of the knife-edge a population happens to start. And we need to know how it might happen that a population could occasionally cross from one side of the knife-edge to the other.

We can try to think of practical ways in which a minority of Tit for Tat individuals might happen to increase to the critical mass. This amounts to a quest for possible ways in which Tit for Tat individuals might happen to cluster together in sufficient numbers that they can all benefit at the banker’s expense.

In a local area, Tit for Tat individuals may meet each other often enough to prosper from mutual cooperation, even though calculations that take into account only the global frequency in the total population might suggest that they are below the ‘knife-edge’ critical frequency. If this happens, Tit for Tat individuals, cooperating with one another in cosy little local enclaves, may prosper so well that they grow from small local clusters into larger local clusters. These local clusters may grow so large that they spread out into other areas, areas that had hitherto been dominated, numerically, by individuals playing Always Defect.

Unlike Tit for Tat, Always Defect, though a true ESS, cannot use local clustering to cross the knife-edge. On the contrary. Local clusters of Always Defect individuals, far from prospering by each other’s presence, do especially badly in each other’s presence. Far from quietly helping one another at the expense of the banker, they do one another down. Always Defect, then, unlike Tit for Tat, gets no help from kinship or viscosity in the population.

Tit for Tat is also ‘not envious’. To be envious, in Axelrod’s terminology, means to strive for more money than the other player, rather than for an absolutely large quantity of the banker’s money. To be non-envious means to be quite happy if the other player wins just as much money as you do, so long as you both thereby win more from the banker. Tit for Tat never actually ‘wins’ a game. Think about it and you’ll see that it cannot score more than its ‘opponent’ in any particular game because it never defects except in retaliation. The most it can do is draw with its opponent. But it tends to achieve each draw with a high, shared score.

Sadly, however, when psychologists set up games of Iterated Prisoner’s Dilemma between real humans, nearly all players succumb to envy and therefore do relatively poorly in terms of money. It seems that many people, perhaps without even thinking about it, would rather do down the other player than cooperate with the other player to do down the banker.

A zero sum game is one in which a win for one player is a loss for the other. Chess is zero sum, because the aim of each player is to win, and this means to make the other player lose. Prisoner’s Dilemma, however, is a nonzero sum game. There is a banker paying out money, and it is possible for the two players to link arms and laugh all the way to the bank.

Lawyers must accept only one member of a couple as a client. The other person is turned from the door, and either has no legal advice at all or is forced to go to another lawyer. And that is when the fun begins. In separate chambers but with one voice, the two lawyers immediately start referring to ‘us’ and ‘them’. ‘Us’, you understand, doesn’t mean me and my wife; it means me and my lawyer against her and her lawyer. When the case comes to court, it is actually listed as ‘Smith versus Smith’! It is assumed to be adversarial, whether the couple feel adversarial or not, whether or not they have specifically agreed that they want to be sensibly amicable. And who benefits from treating it as an ‘I win, you lose’ tussle? The chances are, only the lawyers. The hapless couple have been dragged into a zero sum game. For the lawyers, however, the case of Smith v. Smith is a nice fat nonzero sum game, with the Smiths providing the pay-offs and the two professionals milking their clients’ joint account in elaborately coded cooperation. One way in which they cooperate is to make proposals that they both know the other side will not accept. This prompts a counter proposal that, again, both know is unacceptable. And so it goes on. Every letter, every telephone call exchanged between the cooperating ‘adversaries’ adds another wad to the bill.

Do we assume, in real life as well as in psychological experiments, that we are playing a zero sum game when we are not?

Many situations in real life are, as a matter of fact, equivalent to nonzero sum games. Nature often plays the role of ‘banker’, and individuals can therefore benefit from one another’s success.

nice guys may finish first. But none of this works unless the game is iterated.

But how long must it be? It can’t be infinitely long. From a theoretical point of view it doesn’t matter how long the game is; the important thing is that neither player should know when the game is going to end.

Each player can be expected to behave as if he possessed a continuously updated estimate of how long the game is likely to go on. The longer his estimate, the more he will play according to the mathematician’s expectations for the true iterated game: in other words, the nicer, more forgiving, less envious he will be. The shorter his estimate of the future of the game, the more he will be inclined to play according to the mathematician’s expectations for the one-off game: the nastier, and less forgiving will he be.

I was having tea with A company when we heard a lot of shouting and went to investigate. We found our men and the Germans standing on their respective parapets. Suddenly a salvo arrived but did no damage. Naturally both sides got down and our men started swearing at the Germans, when all at once a brave German got on to his parapet and shouted out ‘We are very sorry about that; we hope no one was hurt. It is not our fault, it is that damned Prussian artillery.’ Axelrod comments that this apology ‘goes well beyond a merely instrumental effort to prevent retaliation. It reflects moral regret for having violated a situation of trust, and it shows concern that someone might have been hurt.’ Certainly an admirable and very brave German.

The live-and-let-live system could have been worked out by verbal negotiation, by conscious strategists bargaining round a table. In fact it was not. It grew up as a series of local conventions, through people responding to one another’s behaviour; the individual soldiers were probably hardly aware that the growing up was going on.

A computer program can behave in a strategic manner, without being aware of its strategy or, indeed, of anything at all. We are, of course, entirely familiar with the idea of unconscious strategists, or at least of strategists whose consciousness, if any, is irrelevant. Unconscious strategists abound in the pages of this book. Axelrod’s programs are an excellent model for the way we, throughout the book, have been thinking of animals and plants, and indeed of genes. So it is natural to ask whether his optimistic conclusions—about the success of non-envious, forgiving niceness—also apply in the world of nature. The answer is yes, of course they do. The only conditions are that nature should sometimes set up games of Prisoner’s Dilemma, that the shadow of the future should be long, and that the games should be nonzero sum games. These conditions are certainly met, all round the living kingdoms.

normally harmless or beneficial bacteria can turn nasty, even causing lethal sepsis, in a person who is injured. A doctor might say that the person’s ‘natural resistance’ is lowered by the injury. But perhaps the real reason is to do with games of Prisoner’s Dilemma. Do the bacteria, perhaps, have something to gain, but usually keep themselves in check? In the game between human and bacteria, the ‘shadow of the future’ is normally long since a typical human can be expected to live for years from any given starting-point. A seriously wounded human, on the other hand, may present a potentially much shorter shadow of the future to his bacterial guests. The ‘temptation to defect’ correspondingly starts to look like a more attractive option than the ‘reward for mutual cooperation’. Needless to say, there is no suggestion that the bacteria work all this out in their nasty little heads! Selection on generations of bacteria has presumably built into them an unconscious rule of thumb which works by purely biochemical means.

Throughout this book we have been alert to the possibility of individual organisms ‘cheating’ in subtle ways against their social companions. Here we are talking about single genes cheating against the other genes with which they share a body.

we are nevertheless, paradoxically, less impressed than we would be by equivalent achievements in animals closer to ourselves. Just imagine the banner headlines if a marine biologist were to discover a species of dolphin that wove large, intricately meshed fishing nets, twenty dolphin-lengths in diameter! Yet we take a spider web for granted, as a nuisance in the house rather than as one of the wonders of the world.

parasitic castration! Crabs are parasitized by a creature called Sacculina.

among the first organs that it attacks are the crab’s testicles or ovaries; it spares the organs that the crab needs to survive—as opposed to reproduce—till later. The crab is effectively castrated by the parasite. Like a fattened bullock, the castrated crab diverts energy and resources away from reproduction and into its own body—rich pickings for the parasite at the expense of the crab’s reproduction.

Genes, then, reach outside their ‘own’ body to influence phenotypes in other bodies.

Our own genes cooperate with one another, not because they are our own but because they share the same outlet—sperm or egg—into the future. If any genes of an organism, such as a human, could discover a way of spreading themselves that did not depend on the conventional sperm or egg route, they would take it and be less cooperative.

What is harder to understand is the behaviour of foster parents later in the season, towards young cuckoos that are almost fledged. The cuckoo is usually much larger, in some cases grotesquely larger, than its ‘parent’. I am looking at a photograph of an adult dunnock, so small in comparison to its monstrous foster child that it has to perch on its back in order to feed it. Here we feel less sympathy for the host. We marvel at its stupidity, its gullibility. Surely any fool should be able to see that there is something wrong with a child like that. I think that cuckoo nestlings must be doing rather more than just ‘fooling’ their hosts, more than just pretending to be something that they aren’t. They seem to act on the host’s nervous system in rather the same way as an addictive drug. This is not so hard to sympathize with, even for those with no experience of addictive drugs. A man can be aroused, even to erection, by a printed photograph of a woman’s body. He is not ‘fooled’ into thinking that the pattern of printing ink really is a woman. He knows that he is only looking at ink on paper, yet his nervous system responds to it in the same kind of way as it might respond to a real woman. We may find the attractions of a particular member of the opposite sex irresistible, even though the better judgment of our better self tells us that a liaison with that person is not in anyone’s long-term interests. The same can be true of the irresistible attractions of unhealthy food. Th...

‘The rabbit runs faster than the fox, because the rabbit is running for his life while the fox is only running for his dinner.’ My colleague John Krebs and I have dubbed this the ‘life/dinner principle’. Because of the life/dinner principle, animals might at times behave in ways that are not in their own best interests, manipulated by some other animal. Actually, in a sense they are acting in their own best interests: the whole point of the life/dinner principle is that they theoretically could resist manipulation but it would be too costly to do so. Perhaps to resist manipulation by a cuckoo you need bigger eyes or a bigger brain, which would have overhead costs. Rivals with a genetic tendency to resist manipulation would actually be less successful in passing on genes, because of the economic costs of resisting.

In the world of the extended phenotype, ask not how an animal’s behaviour benefits its genes; ask instead whose genes it is benefiting.

all cases in which natural selection has favoured genes for manipulation, it is legitimate to speak of those same genes as having (extended phenotypic) effects on the body of the manipulated organism.

The fundamental units of natural selection, the basic things that survive or fail to survive, that form lineages of identical copies with occasional random mutations, are called replicators. DNA molecules are replicators. They generally, for reasons that we shall come to, gang together into large communal survival machines or ‘vehicles’. The vehicles that we know best are individual bodies like our own. A body, then, is not a replicator; it is a vehicle. I must emphasize this, since the point has been misunderstood. Vehicles don’t replicate themselves; they work to propagate their replicators. Replicators don’t behave, don’t perceive the world, don’t catch prey or run away from predators; they make vehicles that do all those things. For many purposes it is convenient for biologists to focus their attention at the level of the vehicle. For other purposes it is convenient for them to focus their attention at the level of the replicator. Gene and individual organism are not rivals for the same starring role in the Darwinian drama. They are cast in different, complementary, and in many respects equally important roles, the role of replicator and the role of vehicle.

The group of organisms—the flock of birds, the pack of wolves—does not merge into a single vehicle, precisely because the genes in the flock or the pack do not share a common method of leaving the present vehicle.

Many-celled bodies outgrow the microscope. They can even become elephants or whales. Being big is not necessarily a good thing: most organisms are bacteria and very few are elephants. But when the ways of making a living that are open to small organisms have all been filled, there are still prosperous livings to be made by larger organisms. Large organisms can eat smaller ones, for instance, and can avoid being eaten by them.

what do I mean by bottlenecked? No matter how many cells there may be in the body of an elephant, the elephant began life as a single cell, a fertilized egg. The fertilized egg is a narrow bottleneck which, during embryonic development, widens out into the trillions of cells of an adult elephant.

The complicated organs of an advanced animal like a human or a woodlouse have evolved by gradual degrees from the simpler organs of ancestors. But the ancestral organs did not literally change themselves into the descendant organs, like swords being beaten into ploughshares. Not only did they not. The point I want to make is that in most cases they could not. There is only a limited amount of change that can be achieved by direct transformation in the ‘swords to ploughshares’ manner. Really radical change can be achieved only by going ‘back to the drawing board’, throwing away the previous design and starting afresh. When engineers go back to the drawing board and create a new design, they do not necessarily throw away the ideas from the old design. But they don’t literally try to deform the old physical object into the new one. The old object is too weighed down with the clutter of history. Maybe you can beat a sword into a ploughshare, but try ‘beating’ a propellor engine into a jet engine! You can’t do it. You have to discard the propellor engine and go back to the drawing board.

One important thing about a ‘bottlenecked’ life cycle is that it makes possible the equivalent of going back to the drawing board.

To sum up, we have seen three reasons why a bottlenecked life history tends to foster the evolution of the organism as a discrete and unitary vehicle. The three may be labelled, respectively, ‘back to the drawing board’, ‘orderly timing-cycle’, and ‘cellular uniformity’.

Let me end with a brief manifesto, a summary of the entire selfish gene/extended phenotype view of life. It is a view, I maintain, that applies to living things everywhere in the universe. The fundamental unit, the prime mover of all life, is the replicator. A replicator is anything in the universe of which copies are made. Replicators come into existence, in the first place, by chance, by the random jostling of smaller particles. Once a replicator has come into existence it is capable of generating an indefinitely large set of copies of itself. No copying process is perfect, however, and the population of replicators comes to include varieties that differ from one another. Some of these varieties turn out to have lost the power of self-replication, and their kind ceases to exist when they themselves cease to exist. Others can still replicate, but less effectively. Yet other varieties happen to find themselves in possession of new tricks: they turn out to be even better self-replicators than their predecessors and contemporaries. It is their descendants that come to dominate the population. As time goes by, the world becomes filled with the most powerful and ingenious replicators. Gradually, more and more elaborate ways of being a good replicator are discovered. Replicators survive, not only by virtue of their own intrinsic properties, but by virtue of their consequences on the world. These consequences can be quite indirect. All that is necessary is that eventually the co...

Scientists, unlike politicians, can take pleasure in being wrong. A politician who changes his mind is accused of ‘flip-flopping’. Tony Blair boasted that he had ‘not got a reverse gear’. Scientists on the whole prefer to see their ideas vindicated, but an occasional reversal gains respect, especially when graciously acknowledged. I have never heard of a scientist being maligned as a flip-flopper.

The Cooperative Gene would have been an equally appropriate title for this book, and the book itself would not have changed at all. I suspect that a whole lot of mistaken criticisms could have been avoided. Another good title would have been The Immortal Gene. As well as being more poetic than ‘selfish’, ‘immortal’ captures a key part of the book’s argument.

All of us, regardless of where in the world we live, are not only cousins of each other. We are cousins in hundreds of different ways.

A sufficiently knowledgeable geneticist should be able to read out, from the genome of an animal, the environments in which its ancestors survived.