The Selfish Gene

by

Richard Dawkins

The Selfish Gene: Chapter 5 Summary & Analysis

Summary
Analysis
Dawkins thinks that aggressive behavior has been largely misunderstood. He is going to describe these behaviors from the gene’s eye view in order to clear up some of these misunderstandings. The first thing one should realize is that every individual is a “selfish machine,” programmed by its genes to make the best use of its environment in order to survive. This “environment” includes other individuals. Survival machines of different species might compete for resources. They can be predators, prey, parasites, or hosts. Survival machines of the same species interact even more often. For example, they also compete for mates. 
Many group selectionists argue that aggression in the animal world is much less hostile than it needs to be. A lot of animals hold back from fighting as hard as they can, so they think this implies evidence of altruism in nature. Dawkins disagrees, and he wants to convince the reader that he’s right by describing a series of aggressive behaviors in nature from the gene’s eye view, to show that genetic programming is never altruistic.  
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It might be logical to assume that a survival machine who competes for mates would do best by murdering its rivals (and maybe also eating them for food). Murder and cannibalism do happen in nature, but nowhere near as often as one might think. Lorenz, for example, talks a lot about the “restrained” way in which many animals fight. Lorenz says many animals fight to scare off others in their species, but not to kill them. On the surface, this looks like a form of altruism, but Dawkins disagrees.
Lorenz, a group selectionist, considers the fact that animals don’t murder, fight, and eat each other as much as they could as evidence for altruism in nature. Dawkins will counteract this claim by showing that these behaviors are avoided when they keep genes alive, which is a selfish rather than altruistic cause.  
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Indiscriminately killing every rival that crosses an individual’s path won’t always be the best survival strategy. This comes down to a simple “cost-benefit analysis.” Imagine that one face two rivals (B and C). If one meets B first and kills him, one will be spending energy to do that, and then one also has to deal with C. But if one lets B live, he might fight with C and leave one to use one’s energy in better ways.  
Dawkins needs a way to measure altruism and selfishness in nature. His example here shows that it’s not enough to look on the surface of the action—the overall benefit or cost of that action to the actor in the course of their lifetime also needs to be considered.   
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Dawkins thinks that Maynard Smith has a good way of explaining behavior strategies in animals from an evolutionary perspective. Maynard Smith uses the term evolutionarily stable strategy (ESS) to describe behavior that best increases the chance of survival, relative to the way others in the environment behave.
An evolutionarily stable strategy or state is achieved when the same ratio of replicators persists in the gene pool from generation to generation. It’s a way of measuring behavior that factors in the response from others in the environment, and calculates the overall chances of the gene for that behavior being passed on in the long run.
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Imagine there are two kinds of fighting strategies in a society. “Hawk” is an aggressive strategy, because hawks fight hard, but they tend to win. “Dove” is a less aggressive strategy, because doves only threaten, but don’t actually fight.
Dawkins uses the hawk and dove behavior strategies to explain that nice (dove-like, or less aggressive) behavior only exists when it keeps the genes causing that behavior in the gene pool in the long run. 
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In a society where all the creatures use the dove strategy, nobody gets hurt. But if one creature mutates and starts acting more aggressive (or hawk-like), it will win all the fights, get food and territory, and mate the most. So, the next generation would contain more aggressive individuals, who are more likely to fight and injure themselves. This means that individuals who act less aggressively (or act dove-like) would then end up less likely to become injured, and therefore survive to reproduce.
Evolutionary unstable strategies arise when a mutation causes a new behavior that takes over the gene pool for a while, but eventually dies out (or nearly dies out) when it becomes too numerous. It implies a bit of evolution almost happened, but failed.
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Each generation goes back and forth in aggressiveness like a “pendulum” until a particular balance of more and less aggressive behaviors become “stable,” meaning they stay relatively consistent from generation to generation. This is called an evolutionarily stable strategy.  One can also think of an evolutionarily stable strategy as a situation in which the number of hawk-genes and dove-genes stays consistent from generation to generation. Put another way, this means the ratio of hawk-genes to dove-genes stays stable in the gene pool.
The proportion of act-calm genes (dove genes) and act-aggressive genes (hawk genes) swings back and forth—with one gene taking over each generation by winning the mating game—until a happy medium (or evolutionarily stable strategy) is reached, and the ratio stays consistent over time. A stable ratio enables a gene to guarantee its survival over many generations. 
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Many perplexing animal behaviors start to make sense when one realizes they are the result of evolutionarily stable strategies. These include behaviors like “gloved fist” aggression, meaning threatening but not always fighting, or the “poker face,” meaning bluffing. 
On the surface, it looks like some animals act less hostile (potentially altruistic), while others are aggressive (selfish).  Really, however, their genes just settled on a balance (evolutionarily stable strategy) that won’t cause those genes to be nearly wiped out every other generation. What looks like altruism in the short run is actually selfishness in the long run, as it facilitates gene survival in the large-scale picture of evolutionary time.
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Maynard Smith says there are three factors affecting behaviors that will become evolutionarily stable strategies. The first is differences in size and strength. For example, large animals are more likely to benefit from being aggressive than small animals. The second factor is age differences. An older bird (who has already mated) has less to lose from fighting than a young one who has yet to mate. The third factor is chance: happening to be in the right place at the right time.
The actual genes that do persist in a gene pool over time depends largely on environmental factors, but Dawkins thinks altruism is never responsible. Aggressive genes persist when the survival machine is large or strong, or when they program risky behavior to kick in only after reproduction has already occurred and clone-genes have already spread. Sometimes, a risk just pays off by chance.
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Many scientists assume that dominance hierarchies arise in groups to make the group overall less aggressive, which seems beneficial for the group overall, even if those lower in the hierarchy suffer. But Dawkins thinks that dominance hierarchies are just another example of an evolutionarily stable strategy.
Dawkins thinks group selectionists are wrong to think that dominance hierarchies exist because some animals are naturally altruistic and let other animals dominate them for the sake of peace in the group overall. He thinks a combination of calm and aggressive temperaments persist in a group because the ratio of calm to aggressive genes is stable in the gene pool, and therefore keeps those genes alive, meaning there is no altruism involved.
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R. D. Alexander conducted an experiment showing that crickets act less aggressively if they remember losing fights in the past. Dawkins thinks this means that animals who tend to win fights act more aggressive over time, enabling them to assert dominance. Meanwhile, animals that tend to lose fights act less aggressively over time, keeping the aggressive animals in charge. That’s how dominance hierarchies come about.
Dawkins wants to provide explanations for behavior that don’t rely on altruism, to support his core argument that altruism does not exist in nature. He uses Alexander to show that less aggressive animals don’t hold back to be nice, but play it safe and avoid fights they might lose.
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Many scientists also assume that animals tend to avoid cannibalism because of some inherent altruism toward others in their species. Dawkins thinks that this is wrong. He thinks many behaviors that look altruistic exist because they happen to be evolutionarily stable strategies.   
Dawkins also thinks cannibalism doesn’t happen because of animals being kind to each other. He would rather say that the gene fails to persist in the gene pool in the long-term.
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For example, lions eat antelopes, but they don’t eat other lions. Dawkins thinks it’s not an evolutionarily stable strategy for lions to be cannibals. If a lion eats all the other lions who are its rivals for mates, it will be able to mate more and pass on its cannibalistic trait more widely. Then more cannibalistic lions would be born, but they’d be more likely to be eaten by each other, causing the trait to eventually die out in lions.
The lion example shows that cannibalistic lions might win out over a single generation, but the gene for cannibalism would ultimately fail to maintain a stable (and therefore ongoing) presence in the gene pool over time. It’s not altruism that stops animals from eating each other. The cannibal gene just doesn’t survive evolutionary processes. 
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Similarly, an antelope that decides to fight back when attacked by a lion is more likely to be eaten (simply because the lion is stronger), so it fails to survive and reproduce. Dawkins thinks the general tendency for lions to chase antelopes and for antelopes to run away is evolutionarily stable. In the long run, this combination of behavior strategies keeps enough antelopes and lions alive for these respective traits to be passed on.
Similarly, genes for aggression in antelopes don’t survive natural selection because those survival machines fail in an environment with strong predators. Antelopes aren’t altruistic, the ones that run away are just better at staying alive and keeping those genes in the pool.
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Dawkins believes that explaining behavior in terms of evolutionarily stable strategies is going to be one of the “most important advances to evolutionary theory since Darwin.” Dawkins thinks this type of explanation is important because it shows how a group of selfish organisms can resemble “a single organized whole” that appears to be cooperating for the good of their species.
Dawkins believes that thinking in terms of evolutionarily stable strategies poses a profound challenge to group selectionists. They believe that some animals (who are naturally altruistic) sacrifice themselves and others (who are naturally selfish) don’t, but overall the species as a whole evolves. Evolutionarily stable strategies show animals are never purely altruistic. Differences between selfish and altruistic individuals in a group are accounted for by the ratio of genes for those temperaments in the gene pool. The ratio only persists for selfish reasons: it keeps those genes in the gene pool for many generations.
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The evolutionarily stable strategy concept is also useful for explaining why genes appear to “cooperate.” Dawkins revisits the oarsmen metaphor to explain genetic cooperation. Imagine the coach is mixing up candidates at random to see which ones work best as a rowing team. If, by chance, one of those teams is made up of four left-handed rowers and four right-handed rowers, they’ll tend to perform better. Dawkins thinks it might look like the coach picked them as a unit, but in actual fact, they came together by chance.
Dawkins believes that evolutionarily stable strategies explain competition among genes within a survival machine as well. Once again, Dawkins intends to show that there’s no altruism going on here. Genes that work well together tend to stay in stable ratios over generations of reproduction (in the same way that oarsmen who happen to row well together tend to be put together on an ongoing basis).
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In general, it’s hard for a new oarsman to infiltrate a well performing team. For example, replacing one of the right-handed rowers with a left-handed one will throw the team off balance and undermine their overall performance. Similarly, it’s hard for genes to infiltrate a survival machine that is already a fine-tuned mixture of genes that cooperate well. This is why most new mutated genes getting shuffled into the gene pool do not survive to reproduce. They throw off the balance that has prevailed from generation to generation, and most likely cause their survival machines to perform more poorly in their environments.
A new gene will destabilize the balance of genes in a gene pool until a new stable ratio is achieved. Dawkins shows that the oarsmen analogy explains this because new candidates for a team usually throw off the way the team is used to working and don’t get picked to replace an existing team member if the team is already working well. The oarsmen stay intact as a team over time because the team wins, and not because of any altruism among team members who want to stick together for the sake of it.  
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Once in a while, a new gene will make a survival machine work better. There will be a transition period of instability, which tests how the enhanced survival machine functions in its environment relative to other organisms. If the environment overall finds a new balance, it becomes stable under these new terms, and a new evolutionarily stable state is reached. This means “a little bit of evolution has occurred.”
Dawkins explains that evolution happens to genes, and not individuals or groups by describing a moment of evolution from the gene’s eye view as the achievement of a new evolutionarily stable state.  Crucially, a “little bit of evolution” only happens when a gene is able to persist in the gene pool. It keeps replicating in multiple survival machines over multiple generations. When that happens, a different ratio of genes has become stable.
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So far, it has made sense to think of each organism as a single “selfish machine” but this model runs into problems for family members, because relatives are often unselfish toward each other. Dawkins thinks that selfless behavior within families actually makes perfect sense, because relatives share genes.       
While group selectionists believe that kindness between family members proves that altruism exists and species are the things evolving, Dawkins believes that kindness in families only happens when it increases the total number of clone-genes in the pool, regardless of which survival machine they come from. Once again, this is a self-preserving (and not altruistic) behavior.
Themes
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