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Tag Archives: Richard Dawkins

Competition, Cooperation, and the Selfish Gene

Richard Dawkins has one of the best-selling books of all time for a serious piece of scientific writing.

Often labeled “pop science”, The Selfish Gene pulls together the “gene-centered” view of evolution: It is not really individuals being selected for in the competition for life, but their genes. The individual bodies (phenotypes) are simply carrying out the instructions of the genes. This leads most people to a very “competition focused” view of life. But is that all?


More than 100 years before The Selfish Gene, Charles Darwin had famously outlined his Theory of Natural Selection in The Origin of Species.

We’re all hopefully familiar with this concept: Species evolve over long periods time through a process of heredity, variation, competition, and differential survival.

The mechanism of heredity was invisible to Darwin, but a series of scientists, not without a little argument, had figured it out by the 1970’s: Strands of the protein DNA (“genes”) encoded instructions for the building of physical structures. These genes were passed on to offspring in a particular way – the process of heredity. Advantageous genes were propagated in greater numbers. Disadvantageous genes, vice versa.

The Selfish Gene makes a particular kind of case: Specific gene variants grow in proportion to a gene pool by, on average, creating advantaged physical bodies and brains. The genes do their work through “phenotypes” – the physical representation of their information. As Helena Cronin would put in her book The Ant and the Peacock, “It is the net selective value of a gene's phenotypic effect that determines the fate of the gene.”

This take of the evolutionary process became influential because of the range of hard-to-explain behavior that it illuminated.

Why do we see altruistic behavior? Because copies of genes are present throughout a population, not just in single individuals, and altruism can cause great advantages in those gene variants surviving and thriving. (In other words, genes that cause individuals to sacrifice themselves for other copies of those same genes will tend to thrive.)

Why do we see more altruistic behavior among family members? Because they are closely related, and share more genes!

Many problems seemed to be solved here, and the Selfish Gene model became one for all-time, worth having in your head.

However, buried in the logic of the gene-centered view of evolution is a statistical argument. Gene variants rapidly grow in proportion to the rest of the gene pool because they provide survival advantages in the average environment that the gene will experience over its existence. Thus, advantageous genes “selfishly” dominate their environment before long. It's all about gene competition.

This has led many people, some biologists especially, to view evolution solely through the lens of competition. Unsurprisingly, this also led to some false paradigms about a strictly “dog eat dog” world where unrestricted and ruthless individual competition is deemed “natural”.

But what about cooperation?


The complex systems researcher Yaneer Bar-Yam argues that not only is the Selfish Gene a limiting concept biologically and possibly wrong mathematically (too complex to address here, but if you want to read about it, check out these pieces), but that there are more nuanced ways to understand the way competition and cooperation comfortably coexist. Not only that, but Bar-Yam argues that this has implications for optimal team formation.

In his book Making Things Work, Bar-Yam lays out a basic message: Even in the biological world, competition is a limited lens through which to see evolution. There’s always a counterbalance of cooperation.

Counter to the traditional perspective, the basic message of this and the following chapter is that competition and cooperation always coexist. People see them as opposing and incompatible forces. I think that this is a result of an outdated and one-sided understanding of evolution…This is extremely useful in describing nature and society; the basic insight that “what works, works” still holds. It turns out, however, that what works is a combination of competition and cooperation.

Bar-Yam uses the analogy of a sports team which exists in context of a sports league – let’s say the NBA. Through this lens we can see why players, teams, and leagues compete and cooperate. (The obvious analogy is that genes, individuals, and groups compete and cooperate in the biological world.)

In general, when we think about the conflict between cooperation and completion in team sports, we tend to think about the relationships between the players on a team. We care deeply about their willingness to cooperate and we distinguish cooperative “team players” from selfish non-team players, complaining about the latter even when their individual skill is formidable.

The reason we want players to cooperate is so that they can compete better as a team. Cooperation at the level of the individual enables effective competition at the level of the group, and conversely, the competition between teams motivates cooperation between players. There is a constructive relationship between cooperation and competition when they operate at different levels of organization.

The interplay between levels is a kind of evolutionary process where competition at the team level improves the cooperation between players. Just as in biological evolution, in organized team sports there is a process of selection of winners through competition of teams. Over time, the teams will change how they behave; the less successful teams will emulate strategies of teams that are doing well.

At every level then, there is an interplay between cooperation and competition. Players compete for playing time, and yet must be intensively cooperative on the court to compete with other teams. At the next level up, teams compete with each other for victories, and yet must cooperate intensively to sustain a league at all.

They create agreed upon rules, schedule times to play, negotiate television contracts, and so on. This allows the league itself to compete with other leagues for scarce attention from sports fans. And so on, up and down the ladder.

Competition among players, teams, and leagues is certainly a crucial dynamic. But it isn’t all that’s going on: They’re cooperating intensely at every level, because a group of selfish individuals loses to a group of cooperative ones.

And it is the same among biological species. Genes are competing with each other, as are individuals, tribes, and species. Yet at every level, they are also cooperating. The success of the human species is clearly due to its ability to cooperate in large numbers; and yet any student of war can attest to its deadly competitive nature. Similar dynamics are at play with ants, rats, and chimpanzees, among other species of insect and animal. It’s a yin and yang world.

Bar-Yam thinks this has great implications for how to build successful teams.

Teams will improve naturally – in any organization – when they are involved in a competition that is structured to select those teams that are better at cooperation. Winners of a competition become successful models of behavior for less successful teams, who emulate their success by learning their strategies and by selecting and trading team members.

For a business, a society, or any other complex system made up of many individuals, this means that improvement will come when the system’s structure involves a completion that rewards successful groups. The idea here is not a cutthroat competition of teams (or individuals) but a competition with rules that incorporate some cooperative activity with a mutual goal.

The dictum that “politics is the art of marshaling hatreds” would seem to reflect this notion: A non-violent way for competition of cooperative groups for dominance. As would the incentive systems of majorly successful corporations like Nucor and the best hospital systems, like the Mayo Clinic. Even modern business books are picking up on it.

Individual competition is important and drives excellence. Yet, as Bar-Yam points out, it’s ultimately not a complete formula. Having teams compete is more effective: You need to harness competition and cooperation at every level. You want groups pulling together, creating emerging effects where the whole is greater than the sum of the parts (a recurrent theme throughout nature).

You should read his book for more details on both this idea and the concept of complex systems in general. Bar-Yam also elaborated on his sports analogy in a white-paper here. If you're interested in complex systems, check out this post on frozen accidents. Also, for more on creating better groups, check out how Steve Jobs did it.

What Can Chain Letters Teach us about Natural Selection?

“It is important to understand that none of these replicating entities is consciously interested in getting itself duplicated. But it will just happen that the world becomes filled with replicators that are more efficient.”


In 1859, Charles Darwin first described his theory of evolution through natural selection in The Origin of Species. Here we are, 157 years later, and although it has become an established fact in the field of biology, its beauty is still not that well understood among the populace. I think that's because it's slightly counter-intuitive. Unlike string theory or quantum mechanics, the theory of evolution through natural selection is pretty easily obtainable by most.

So, is there a way we can help ourselves understand the theory in an intuitive way, so we can better go on applying it to other domains? I think so, and it comes from an interesting little volume released in 1995 by the biologist Richard Dawkins called River Out of Eden. But first, let's briefly head back to the Origin of Species, so we're clear on what we're trying to understand.


In the fourth chapter of the book, entitled “Natural Selection,” Darwin describes a somewhat cold and mechanistic process for the development of species: If species had heritable traits and variation within their population, they would survive in different numbers, and those most adapted to survival would thrive and pass on those traits to successive generations. Eventually, new species would arise, slowly, as enough variation and differential reproduction acted on the population to create a de facto branch in the family tree.

Here's the original description.

Let it be borne in mind how infinitely complex and close-fitting are the mutual relations of all organic beings to each other and to their physical conditions of life. Can it, then, be thought improbable, seeing that variations useful to man have undoubtedly occurred, that other variations useful in some way to each being in the great and complex battle of life, should sometimes occur in the course of thousands of generations? If such do occur, can we doubt (remembering that many more individuals are born than can possibly survive) that individuals having any advantage, however slight, over others, would have the best chance of surviving and of procreating their kind? On the other hand, we may feel sure that any variation in the least degree injurious would be rigidly destroyed. This preservation of favourable variations and the rejection of injurious variations, I call Natural Selection.


In such case, every slight modification, which in the course of ages chanced to arise, and which in any way favored the individuals of any species, by better adapting them to their altered conditions, would tend to be preserved; and natural selection would thus have free scope for the work of improvement.


It may be said that natural selection is daily and hourly scrutinizing, throughout the world, every variation, even the slightest; rejection that which is bad, preserving and adding up all that is good; silently and insensibly working, whenever and wherever opportunity offers, at the improvement of each organic being in relation to its organic and inorganic conditions of life. 

The beauty of the theory is in its simplicity. The mechanism of evolution is, at root, a simple one. An unguided one. Better descendants outperform lesser ones in a competitive world and are more successful at replicating. Traits that improve the survival of their holder in its current environment tend to be preserved and amplified over time. This is hard to see in real time, although some examples are helpful in understanding the concept, e.g. antibiotic resistance.

Darwin's idea didn't take as quickly as we might like to think. In The Reluctant Mr. Darwin, David Quammen talks about the period after the release of the groundbreaking work, in which the world had trouble coming to grips with Darwin's theory. It was not the case, as it might seem today, that the world simply threw up its hands and accepted Darwin as a genius. This is a lesson in and of itself. It was quite the contrary:

By the 1890s, natural selection as Darwin had defined it–that is, differential reproductive success resulting from small, undirected variations and serving as the chief mechanism of adaption and divergence–was considered by many evolutionary biologists to have been a wrong guess.

It wasn't until Gregor Mendel's peas showed how heritability worked that Darwin's ideas were truly vindicated against his rivals'. So if we have trouble coming to terms with evolution by natural selection in the modern age, we're not alone: So did Darwin's peers.


What's this all got to do with chain letters? Well, in Dawkins' River Out of Eden, he provides an analogy for the process of evolution through natural selection that is quite intuitive, and helpful in understanding the simple power of the idea. How would a certain type of chain letter come to dominate the population of all chain letters? It would work the same way.

A simple example is the so-called chain letter. You receive in the mail a postcard on which is written: “Make six copies of this card and send them to six friends within a week. If you do not do this, a spell will be cast upon you and you will die in horrible agony within a month.” If you are sensible you will throw it away. But a good percentage of people are not sensible; they are vaguely intrigued, or intimidated by the threat, and send six copies of it to other people. Of these six, perhaps two will be persuaded to send it on to six other people. If, on average, 1/3 of the people who receive the card obey the instructions written on it, the number of cards in circulation will double every week. In theory, this means that the number of cards in circulation after one year will be 2 to the power of 52, or about four thousand trillion. Enough post cards to smother every man, woman, and child in the world.

Exponential growth, if not checked by the lack of resources, always leads to startlingly large-scale results in a surprisingly short time. In practice, resources are limited and other factors, too, serve to limit exponential growth. In our hypothetical example, individuals will probably start to balk when the same chain letter comes around to them for the second time. In the competition for resources, variants of the same replicator may arise that happen to be more efficient at getting themselves duplicated. These more efficient replicators will tend to displace their less efficient rivals. It is important to understand that none of these replicating entities is consciously interested in getting itself duplicated. But it will just happen that the world becomes filled with replicators that are more efficient.

In the case of the chain letter, being efficient may consist in accumulating a better collection of words on the paper. Instead of the somewhat implausible statement that “if you don't obey the words on the card you will die in horrible agony within a month,” the message might change to “Please, I beg of you, to save your soul and mine, don't take the risk: if you have the slightest doubt, obey the instructions and send the letter to six more people.”

Such “mutations” happen again and again, and the result will eventually be a heterogenous population of messages all in circulation, all descended from the same original ancestor but differing in detailed wording and in the strength and nature of the blandishments they employ. The variants that are more successful will increase in frequency at the expense of less successful rivals. Success is simply synonymous with frequency in circulation. 

The chain letter contains all of the elements of biological natural selection except one: Someone had to write the first chain letter. The first replicating biological entity, on the other hand, seems to have sprung up from an early chemical brew.

Consider this analogy an intermediate mental “step” towards the final goal. Because we know and appreciate the power of reasoning by analogy and metaphor, we can deduce that finding an appropriate analogy is one of the best ways to pound an idea into your head–assuming it is a correct idea that should be pounded in.

And because evolution through natural selection is one of the more powerful ideas a human being has ever had, it seems worth our time to pound this one in for good and start applying it elsewhere if possible. (For example, Munger has talked about how business evolves in a manner such that competitive results are frequently similar to biological outcomes.)

Read Dawkins' book in full for a deeper look at his views on replication and natural selection. It's shorter than some of his other works, but worth the time.

The Seven Books Bill Gates Thinks You Should Read This Summer

Bill gates
Bill Gates is out with his annual summer reading list and, while longer than last year’s, it's a great place to kick off your summer reading.

“Each of these books,” Gates writes, “made me think or laugh or, in some cases, do both. I hope you find something to your liking here.”

Hyperbole and a Half, by Allie Brosh.

The book, based on Brosh’s wildly popular website, consists of brief vignettes and comic drawings about her young life. The adventures she recounts are mostly inside her head, where we hear and see the kind of inner thoughts most of us are too timid to let out in public. You will rip through it in three hours, tops. But you’ll wish it went on longer, because it’s funny and smart as hell. I must have interrupted Melinda a dozen times to read to her passages that made me laugh out loud.

The Magic of Reality, by Richard Dawkins.

Dawkins, an evolutionary biologist at Oxford, has a gift for making science enjoyable. This book is as accessible as the TV series Cosmos is for younger audiences—and as relevant for older audiences. It’s an engaging, well-illustrated science textbook offering compelling answers to big questions, like “how did the universe form?” and “what causes earthquakes?” It’s also a plea for readers of all ages to approach mysteries with rigor and curiosity. Dawkins’s antagonistic (and, to me, overzealous) view of religion has earned him a lot of angry critics, but I consider him to be one of the great scientific writer/explainers of all time.

What If?, by Randall Munroe.

The subtitle of the book is “Serious Scientific Answers to Absurd Hypothetical Questions,” and that’s exactly what it is. People write Munroe with questions that range over all fields of science: physics, chemistry, biology. Questions like, “From what height would you need to drop a steak for it to be cooked when it hit the ground?” (The answer, it turns out, is “high enough that it would disintegrate before it hit the ground.”) Munroe’s explanations are funny, but the science underpinning his answers is very accurate. It’s an entertaining read, and you’ll also learn a bit about things like ballistics, DNA, the oceans, the atmosphere, and lightning along the way.

XKCD, by Randall Munroe.

A collection of posts from Munroe’s blog XKCD, which is made up of cartoons he draws making fun of things—mostly scientists and computers, but lots of other things too. There’s one about scientists holding a press conference to reveal their discovery that life is arsenic-based. They research press conferences and find out that sometimes it’s good to serve food that’s related to the subject of the conference. The last panel is all the reporters dead on the floor because they ate arsenic. It’s that kind of humor, which not everybody loves, but I do.

On Immunity, by Eula Biss.

When I stumbled across this book on the Internet, I thought it might be a worthwhile read. I had no idea what a pleasure reading it would be. Biss, an essayist and university lecturer, examines what lies behind people’s fears of vaccinating their children. Like many of us, she concludes that vaccines are safe, effective, and almost miraculous tools for protecting children against needless suffering. But she is not out to demonize anyone who holds opposing views. This is a thoughtful and beautifully written book about a very important topic.

How to Lie With Statistics, by Darrell Huff.

I picked up this short, easy-to-read book after seeing it on a Wall Street Journal list of good books for investors. I enjoyed it so much that it was one of a handful of books I recommended to everyone at TED this year. It was first published in 1954, but aside from a few anachronistic examples (it has been a long time since bread cost 5 cents a loaf in the United States), it doesn’t feel dated. One chapter shows you how visuals can be used to exaggerate trends and give distorted comparisons—a timely reminder, given how often infographics show up in your Facebook and Twitter feeds these days. A useful introduction to the use of statistics, and a helpful refresher for anyone who is already well versed in it.

Should We Eat Meat?, by Vaclav Smil.

The richer the world gets, the more meat it eats. And the more meat it eats, the bigger the threat to the planet. How do we square this circle? Vaclav Smil takes his usual clear-eyed view of the whole landscape, from meat’s role in human evolution to hard questions about animal cruelty. While it would be great if people wanted to eat less meat, I don’t think we can expect large numbers of people to make drastic reductions. I’m betting on innovation, including higher agricultural productivity and the development of meat substitutes, to help the world meet its need for meat. A timely book, though probably the least beach-friendly one on this list.

Here is the video gates showed explaining the reads:

Claude Shannon: The Man Who Turned Paper Into Pixels

"The fundamental problem of communication is that of reproducing at one point either exactly or approximately a message selected at another point. Frequently the messages have meaning."— Claude Shannon (1948)
“The fundamental problem of communication is that of reproducing at one point either exactly or approximately a message selected at another point. Frequently the messages have meaning.”— Claude Shannon (1948)

Claude Shannon is the most important man you've probably never heard of. If Alan Turing is to be considered the father of modern computing, then the American mathematician Claude Shannon is the architect of the Information Age.

The video, created by the British filmmaker Adam Westbrook, echoes the thoughts of Nassim Taleb that boosting the signal does not mean you remove the noise, in fact, just the opposite: you amplify it.

Any time you try to send a message from one place to another something always gets in the way. The original signal is always distorted. Where ever there is signal there is also noise.

So what do you do? Well, the best anyone could do back then was to boost the signal. But then all you do is boost the noise.

Thing is we were thinking about information all wrong. We were obsessed with what a message meant.

A Renoir and a receipt? They’re different, right? Was there a way to think of them in the same way? Like so many breakthroughs the answer came from an unexpected place. A brilliant mathematician with a flair for blackjack.


The transistor was invented in 1948, at Bell Telephone Laboratories. This remarkable achievement, however, “was only the second most significant development of that year,” writes James Gleick in his fascinating book: The Information: A History, a Theory, a Flood. The most important development of 1948 and what still underscores modern technology is the bit.

An invention even more profound and more fundamental came in a monograph spread across seventy-nine pages of The Bell System Technical Journal in July and October. No one bothered with a press release. It carried a title both simple and grand “A Mathematical Theory of Communication” and the message was hard to summarize. But it was a fulcrum around which the world began to turn. Like the transistor, this development also involved a neologism: the word bit, chosen in this case not by committee but by the lone author, a thirty-two-year -old named Claude Shannon. The bit now joined the inch, the pound, the quart, and the minute as a determinate quantity— a fundamental unit of measure.

But measuring what? “A unit for measuring information,” Shannon wrote, as though there were such a thing, measurable and quantifiable, as information.


Shannon’s theory made a bridge between information and uncertainty; between information and entropy; and between information and chaos. It led to compact discs and fax machines, computers and cyberspace, Moore’s law and all the world’s Silicon Alleys. Information processing was born, along with information storage and information retrieval. People began to name a successor to the Iron Age and the Steam Age.

Gleick also recounts the relationship between Turing and Shannon:

In 1943 the English mathematician and code breaker Alan Turing visited Bell Labs on a cryptographic mission and met Shannon sometimes over lunch, where they traded speculation on the future of artificial thinking machines. (“ Shannon wants to feed not just data to a Brain, but cultural things!” Turing exclaimed. “He wants to play music to it!”)

Commenting on vitality of information, Gleick writes:

(Information) pervades the sciences from top to bottom, transforming every branch of knowledge. Information theory began as a bridge from mathematics to electrical engineering and from there to computing. … Now even biology has become an information science, a subject of messages, instructions, and code. Genes encapsulate information and enable procedures for reading it in and writing it out. Life spreads by networking. The body itself is an information processor. Memory resides not just in brains but in every cell. No wonder genetics bloomed along with information theory. DNA is the quintessential information molecule, the most advanced message processor at the cellular level— an alphabet and a code, 6 billion bits to form a human being. “What lies at the heart of every living thing is not a fire, not warm breath, not a ‘spark of life,’” declares the evolutionary theorist Richard Dawkins. “It is information, words, instructions.… If you want to understand life, don’t think about vibrant, throbbing gels and oozes, think about information technology.” The cells of an organism are nodes in a richly interwoven communications network, transmitting and receiving, coding and decoding. Evolution itself embodies an ongoing exchange of information between organism and environment.

The bit is the very core of the information age.

The bit is a fundamental particle of a different sort: not just tiny but abstract— a binary digit, a flip-flop, a yes-or-no. It is insubstantial, yet as scientists finally come to understand information, they wonder whether it may be primary: more fundamental than matter itself. They suggest that the bit is the irreducible kernel and that information forms the very core of existence.

In the words of John Archibald Wheeler, the last surviving collaborator of both Einstein and Bohr, information gives rise to “every it— every particle, every field of force, even the spacetime continuum itself.”

This is another way of fathoming the paradox of the observer: that the outcome of an experiment is affected, or even determined, when it is observed. Not only is the observer observing, she is asking questions and making statements that must ultimately be expressed in discrete bits. “What we call reality,” Wheeler wrote coyly, “arises in the last analysis from the posing of yes-no questions.” He added: “All things physical are information-theoretic in origin, and this is a participatory universe.” The whole universe is thus seen as a computer —a cosmic information-processing machine.

The greatest gift of Prometheus to humanity was not fire after all: “Numbers, too, chiefest of sciences, I invented for them, and the combining of letters, creative mother of the Muses’ arts, with which to hold all things in memory .”

Information technologies are both relative in the time they were created and absolute in terms of the significance. Gleick writes:

The alphabet was a founding technology of information. The telephone, the fax machine, the calculator, and, ultimately, the computer are only the latest innovations devised for saving, manipulating, and communicating knowledge. Our culture has absorbed a working vocabulary for these useful inventions. We speak of compressing data, aware that this is quite different from compressing a gas. We know about streaming information, parsing it, sorting it, matching it, and filtering it. Our furniture includes iPods and plasma displays, our skills include texting and Googling, we are endowed, we are expert, so we see information in the foreground. But it has always been there. It pervaded our ancestors’ world, too, taking forms from solid to ethereal, granite gravestones and the whispers of courtiers. The punched card, the cash register, the nineteenth-century Difference Engine, the wires of telegraphy all played their parts in weaving the spiderweb of information to which we cling. Each new information technology, in its own time, set off blooms in storage and transmission. From the printing press came new species of information organizers: dictionaries, cyclopaedias, almanacs— compendiums of words, classifiers of facts, trees of knowledge. Hardly any information technology goes obsolete. Each new one throws its predecessors into relief. Thus Thomas Hobbes, in the seventeenth century, resisted his era’s new-media hype: “The invention of printing, though ingenious, compared with the invention of letters is no great matter.” Up to a point, he was right. Every new medium transforms the nature of human thought. In the long run, history is the story of information becoming aware of itself.

The Information: A History, a Theory, a Flood is a fascinating read.

(image source)

The False Allure of Group Selection.

From Steven Pinker's edge.org article The False Allure of Group Selection.

Pinker argues that the more carefully you think about group selection, the less sense it makes, and the more poorly it fits the facts of human psychology and history.

Human Psychology and Bees?

So for the time being we can ask, is human psychology really similar to the psychology of bees? When a bee suicidally stings an invader, presumably she does so as a primary motive, as natural as feeding on nectar or seeking a comfortable temperature. But do humans instinctively volunteer to blow themselves up or advance into machine-gun fire, as they would if they had been selected with group-beneficial adaptations? My reading of the study of cooperation by psychologists and anthropologists, and of the study of group competition by historians and political scientists, suggest that in fact human are nothing like bees.

The huge literature on the evolution of cooperation in humans has done quite well by applying the two gene-level explanations for altruism from evolutionary biology, nepotism and reciprocity, each with a few twists entailed by the complexity of human cognition.

Nepotistic altruism in humans consists of feelings of warmth, solidarity, and tolerance toward those who are likely to be one's kin. It evolved because any genes that encouraged such feelings toward genetic relatives would be benefiting copies of themselves inside those relatives. (This does not, contrary to a common understanding, mean that people love their relatives because of an unconscious desire to perpetuate their genes.) A vast amount of human altruism can be explained in this way. Compared to the way people treat nonrelatives, they are far more likely to feed their relatives, nurture them, do them favors, live near them, take risks to protect them, avoid hurting them, back away from fights with them, donate organs to them, and leave them inheritances.[5]

The cognitive twist is that the recognition of kin among humans depends on environmental cues that other humans can manipulate.[6] Thus people are also altruistic toward their adoptive relatives, and toward a variety of fictive kin such as brothers in arms, fraternities and sororities, occupational and religious brotherhoods, crime families, fatherlands, and mother countries. These faux-families may be created by metaphors, simulacra of family experiences, myths of common descent or common flesh, and other illusions of kinship. None of this wasteful ritualizing and mythologizing would be necessary if “the group” were an elementary cognitive intuition which triggered instinctive loyalty. Instead that loyalty is instinctively triggered by those with whom we are likely to share genes, and extended to others through various manipulations.

The other classic form of altruism is reciprocity: initiating and maintaining relationships in which two agents trade favors, each benefiting the other as long as each protects himself from being exploited. Once again, a vast amount of human cooperation is elegantly explained by this theory.[7] People are “nice,” both in the everyday sense and the technical sense from game theory, in that they willingly confer a large benefit to a stranger at a small cost to themselves, because that has some probability of initiating a mutually beneficial long-term relationship. (It's a common misunderstanding that reciprocal altruists never help anyone unless they are soliciting or returning a favor; the theory in fact predicts that they will sympathize with the needy.) People recognize other individuals and remember how they have treated and been treated by them. They feel gratitude to those who have helped them, anger to those who have exploited them, and contrition to those whom they have exploited if they depend on them for future cooperation.

One cognitive twist on this formula is that humans are language-using creatures who need not discriminate reciprocators from exploiters only by direct personal experience, but can also ask around and find out their reputation for reciprocating with or exploiting others. This in turn creates incentives to establish and exaggerate one's reputation (a feature of human psychology that has been extensively documented by social psychologists), and to attempt to see through such exaggerations in others.[8] And one way to credibly establish one's reputation as an altruist in the probing eyes of skeptics to be an altruist, that is, to commit oneself to altruism (and, indirectly, its potential returns in the long run, at the expense of personal sacrifices in the short run).[9] A third twist is that reciprocity, like nepotism, is driven not by infallible knowledge but by probabilistic cues. This means that people may extend favors to other people with whom they will never in fact interact with again, as long as the situation is representative of ones in which they may interact with them again.[10] Because of these twists, it's a fallacy to think that the theory of reciprocal altruism implies that generosity is a sham, and that people are nice to one another only when each one cynically calculates what's in it for him.

Group selection, in contrast, fails to predict that human altruism should be driven by moralistic emotions and reputation management, since these may benefit of individuals who inflate their reputations relative to their actual contributions and thus subtract from the welfare of the group. Nor is there any reason to believe that ants, bees, or termites have moralistic emotions such as sympathy, anger, and gratitude, or a motive to monitor the reputations of other bees or manage their own reputations. Group welfare would seem to work according to the rule “From each according to his ability, to each according to his need.” Ironically, Wilson himself, before he came out as a group selectionist, rejected the idea that human altruism could be explained by going to the ants, and delivered this verdict on the Marxist maxim: “Wonderful theory; wrong species.” Haidt, too, until recently was content to explain the moral emotions with standard theories of nepotistic and reciprocal altruism.


People punish those that are most likely to exploit them, choose to interact with partners who are least likely to free-ride, and cooperate and punish more, and free-ride less, when their reputations are on the line.

Tribal Warfare

In tribal warfare among non-state societies, men do not regularly take on high lethal risks for the good of the group. Their pitched battles are noisy spectacles with few casualties, while the real combat is done in sneaky raids and ambushes in which the attackers assume the minimum risks to themselves.[14] When attacks do involve lethal risks, men are apt to desert, stay in the rear, and find excuses to avoid fighting, unless they are mercilessly shamed or physically punished for such cowardice.

Early Empires

What about early states? States and empires are the epitome of large-scale coordinated behavior and are often touted as examples of naturally selected groups. Yet the first complex states depended not on spontaneous cooperation but on brutal coercion. They regularly engaged in slavery, human sacrifice, sadistic punishments for victimless crimes, despotic leadership in which kings and emperors could kill with impunity, and the accumulation of large harems, with the mathematically necessity that large number of men were deprived of wives and families.

Nor has competition among modern states been an impetus for altruistic cooperation. Until the Military Revolution of the 16th century, European states tended to fill their armies with marauding thugs, pardoned criminals, and paid mercenaries, while Islamic states often had military slave castes.[17] The historically recent phenomenon of standing national armies was made possible by the ability of increasingly bureaucratized governments to impose conscription, indoctrination, and brutal discipline on their powerless young men. Even in historical instances in which men enthusiastically volunteered for military service (as they did in World War I), they were usually victims of positive illusions which led them to expect a quick victory and a low risk of dying in combat.[18] Once the illusion of quick victory was shattered, the soldiers were ordered into battle by callous commanders and goaded on by “file closers” (soldiers ordered to shoot any comrade who failed to advance) and by the threat of execution for desertion, carried out by the thousands. In no way did they act like soldier ants, willingly marching off to doom for the benefit of the group.

To be sure, the annals of war contain tales of true heroism—the proverbial soldier falling on the live grenade to save his brothers in arms. But note the metaphor. Studies of the mindset of soldierly duty shows that the psychology is one of fictive kinship and reciprocal obligation within a small coalition of individual men, far more than loyalty to the superordinate group they are nominally fighting for. The writer William Manchester, reminiscing about his service as a Marine in World War II, wrote of his platoonmates, “Those men on the line were my family, my home. … They had never let me down, and I couldn't do it to them. . . . Men, I now knew, do not fight for flag or country, for the Marine Corps or glory of any other abstraction. They fight for one another.”

What about the ultimate in individual sacrifice, suicide attacks? Military history would have unfolded very differently if this was a readily available tactic, and studies of contemporary suicide terrorists have shown that special circumstances have to be engineered to entice men into it. Scott Atran, Larry Sugiyama, Valerie Hudson, Jessica Stern, and Bradley Thayer have documented that suicide terrorists are generally recruited from the ranks of men with poor reproductive prospects, and they are attracted and egged on by some combination of peer pressure, kinship illusions, material and reputational incentives to blood relatives, and indoctrination into the theory of eternal rewards in an afterlife (the proverbial seventy-two virgins).[19] These manipulations are necessary to overcome a strong inclination not to commit suicide for the benefit of the group.

The historical importance of compensation, coercion, and indoctrination in group-against-group competition should not come as a surprise, because the very idea that group combat selects for individual altruism deserves a closer look. Wilson's dictum that groups of altruistic individuals beat groups of selfish individuals is true only if one classifies slaves, serfs, conscripts, and mercenaries as “altruistic.” It's more accurate to say that groups of individuals that are organized beat groups of selfish individuals. And effective organization for group conflict is more likely to consist of more powerful individuals incentivizing and manipulating the rest of their groups than of spontaneous individual self-sacrifice.

The Argument

Now, no one “owns” the concept of natural selection, nor can anyone police the use of the term. But its explanatory power, it seems to me, is so distinctive and important that it should not be diluted by metaphorical, poetic, fuzzy, or allusive extensions that only serve to obscure how profound the genuine version of the mechanism really is.

Still curious? Read E.O. Wilson's NYTimes article supporting multilevel selection. Also, check out some comments by Richard Dawkins and his take.

Richard Dawkins on Pascal’s Wager

Richard Dawkins's wide-ranging interview with Playboy Magazine.

PLAYBOY: So you aren’t taking Pascal up on his wager. He was the 17th century philosopher who argued it’s a smarter bet to believe in God, because if you’re wrong——

DAWKINS: The cost of failure is very high. But what if you choose the wrong god to believe in? What if you get up there and it’s not Jehovah but Baal? [laughs] And even if you pick the right god, why should God be so obsessive about you believing in him? Plus, any god worth its salt is going to realize you’re feigning. The odds are extremely low, but nevertheless it’s worth it because the reward is extremely high. But you may also be wasting your life. You go to church every Sunday, you do penance, you wear sackcloth and ashes. You have a horrible life, and then you die and that’s it.


PLAYBOY: What will happen when you die?

DAWKINS: Well, I shall either be buried or be cremated.

PLAYBOY: Funny. But without faith in an afterlife, in what do you take comfort in times of despair?

DAWKINS: Human love and companionship. But in more thoughtful, cerebral moments, I take—comfort is not quite the right word, but I draw strength from reflecting on what a privilege it is to be alive and what a privilege it is to have a brain that’s capable in its limited way of understanding why I exist and of reveling in the beauty of the world and the beauty of the products of evolution. The magnificence of the universe and the sense of smallness that gives us in space and in geologically deep time is humbling but in a strangely comforting way. It’s nice to feel you’re part of a hugely bigger picture.

America is split into halves:

PLAYBOY: Do you get discouraged by the continuing attacks on reason?

DAWKINS: No. I go on the internet quite a lot and read what young people are saying. I see a great upsurge of good sense, rationality, irreverence. America is split into halves. There’s the Sarah Palin know-nothing idiots on the one hand, and then there’s a huge number of intellectual, intelligent, educated people on the other. I find it hard to believe that the Stone Age types are going to win in the end. An awful lot of people who call themselves religious simply don’t know there’s any alternative. If you probe what they believe, it turns out to be pretty much the same—we all have a sense of wonder and reverence at the majesty of the universe.

What makes us human?

DAWKINS: We are a unique ape. We have language. Other animals have systems of communication that fall far short of that. They don’t have the same ability to communicate complicated conditionals and what-ifs and talk about things that are not present. These are all unique manifestations of our evolved ape brain, which some evidence suggests came about through a rather limited number of mutations.