The Altruism Equation

Lee Alan Dugatkin’s new book The Altruism Equation: Seven Scientists Search for the Origins of Goodness was sitting on my doorstep a few days ago (too big to fit in the mailbox). Dugatkin is a biologist at the University of Louisville. That evening I sat down to read the first chapter, and ended up polishing off half the book. It’s quite an engaging read.

Dugatkin recounts the history of various attempts to solve the problem of altruism in evolutionary biology. In this context “altruism” should be viewed as a technical term referring to behavior that benefits others but incurs some personal risk. Superficially such behavior is a challenge for the idea of evolution by natural selection. Since selection only understands immediate reproductive advantage, altruistic behavior should be ruthlessly unselected. Yet many instances of altruistic behavior can be found in nature.

Dugatkin traces the history of attempts to solve this problem from Darwin to the present. Darwin himself weighed in on the subject, describing it as potentially a serious problem for his theory. His main solution was to argue that selection could operate at the level of a whole family, and not just at the level of the individual. He did not attempt to develop this into a full-blooded theory, but his ideas mesh very well with modern thinking on the subject.

Next up are Thomas Huxley and Petr Kropotkin. Not for nothing was Huxley known as Darwin’s bulldog. Huxley endorsed Darwin’s thinking on this subject, and argued that altruism in nature was largely illusory. He emphasized the important role of family relatedness in explaining apparent altruism. Dugatkin quotes him as follows:

From the point of view of the moralist, the animal world is on about the same level as a gladiator’s show. The creatures are fairly well treated, and set to fight; whereby the strongest, the swiftest and the cunningest live to fight another day. The spectator has no need to turn his thumb’s down, as no quarter is given…The weakest and the stupidest went to the wall, while the toughest and the shrewdest, those who were best fitted to cope with their circumstances, but not the best in any other sense, survived. Life was a continual free fight, and beyond the limited and temporary relations of the family, the Hobbesian war of each against all was the normal state of existence. (p. 12)

This sort of thinking was repugnant to Kropotikin, who emphasized cooperation and selflessness as the general rule in nature. His classic book on this subject is Mutual Aid, which provides numerous examples to back up his view of nature. Dugatkin makes an interesting point about how the environments in which Huxley and Kropotikin lived likely affected their view of this issue:

When Darwin published the Origin, Russia made up one-sixth of the earth’s dry land mass, with Siberia alone being forty times larger than Great Britain and Ireland combined. Yet this vast expanse was inhabited by a mere 82 million people (as compared with the 35 million inhabitants of the British Isles), in part owing to the very harsh weather, in which vast sections of the country would “stay frozen eight months out of ten…while the rivers freeze all the way to the black Sea.” In such a world, underpopulation, not overpopulation, was the most pressing problem. And Darwin’s direct competition did not stem from underpopulation; hence, instead of evolution via overpopulation leading to nature’s cycle of slaughter as per Malthus and then Huxley, underpopulation opened the door to altruism and cooperation for Russian scientists like Kropotkin. And underpopulation allowed the Russians to take evolutionary processes proposed by Darwin and derive altruism from them. (p. 22)

Warder Clyde Allee was next. He tended to see things in a fashion similar to Kropotkin, and his work tried to document examples of altruism that was not related to kinship. He also emphasized group selection as a possible solution to this problem. Number five on Dugatkin’s list is JBS Haldane, who contributed the first serious ideas for constructing a mathematical model for the relationship between kinship and altruism. Rounding out the list are William Hamilton, who ran with Haldane’s vague suggestion and developed the first, full-blooded, testable, mathematical model for the altruism problem, and George Price, who brought still further mathematical sophistication in the form of covariance analysis and game theory. Actually, I’m only pretty sure they are the seven scientists in question, since more than seven people receive serious discussion in the book.

Dugatkin also discusses some of the field experiments that have largely confirmed Hamilton’s thinking on this subject. There is also a chapter discussing the importance of books like Richard Dawkins’ The Selfish Gene and E.O. Wilson’s Sociobiology in spreading the word about Hamilton’s ideas. The relationship between altruism and kinship is now firmly entrenched in modern biology.

Speaking as someone who frequently argues with creationists, one thing that impresses me about this is the strong match between theory and reality. Hamilton’s mathematical models are based entirely on the cold, hard logic of natural selection. Likewise for Price’s application of game theory to ethology. The success of these models in predicting the results of field experiments strikes at two common creationist shibboleths. First, it is strong evidence that the behaviors being studied really were formed by natural selection, thereby providing yet another line of evidence in support of evolution. Second, the difficult field work that has been done to test these models illustrates the nonsense of claiming that scientists just assume evolution as an axiom. After all, Hamilton’s and Price’s logic was impeccable. If scientists were the dogmatists creationists say they are, one wonders why they bothered to test the models at all.

Dugatkin has a pleasant writing style, and at a mere 150 pages the book is a fast read. It is more of a history of science book than a science book. Indeed, my one criticism is that I would have preferred a bit more technical detail in the discussion of Hamilton’s work. Since this is a popular level book, I suspect one of Dugatkin’s editors warned him of the perils of including toomuch mathematics. I notice that he has written other books on animal behavior, and I suspect he covered the more technincal aspects of the subject there.

At any rate, I heartily recommend the book both as an interesting look into the history of an important question, and for a window into the real world of professional evolutionary biology. It looks nothing like the caricature you get from the creationists or ID folks.

Comments

  1. #1 somnilista, FCD
    September 19, 2006

    Maybe you could buy an extra copy and mail it to Francis Collins.

  2. #2 Jake
    September 19, 2006

    To me it seems that altruism simply grows out of social behavior, which is a survival mechanism. The decisions linked to true altruism would become something that is beyond group survival, especially if one species is helping another. That transition would be the thing worth studying. I suppose this is where this book would begin.

  3. #3 Gerard Harbison
    September 19, 2006

    There are really two very different categories of altruism; kin preference, and reciprocal altruism, where the expectation of future advantage through reciprocity outweighs short term disadvantage. Does the book cover the latter at all, or merely the former?

  4. #4 coturnix
    September 19, 2006

    Is there a chapter on Sober and Wilson’s “Unto Others” – the hypothesis I like the best?

    In my Lysenko post I also compared Western Europe to Russia, but not in terms of human population – in terms of natural environments instead – to argue that the competitive vs. cooperative ideas were derived from what they could see in nature when they walked outside of their homes. Also, most of the pioneers of evlutionary theory – Darinw, Wallace, Bates – got their ideas while travelling in the tropics where competition is much more obvious than in the taiga.

  5. #5 Mike Elzinga
    September 19, 2006

    Another interesting exploration of this topic is Robert Axelrod?s ?The Evolution of Cooperation? written way back in 1984. This has been a pretty hot field for some time, and the computer models find that stable configurations of cooperative behavior emerge even from a number of players who initially begin interactions with each other using varying strategies.

  6. #6 Brian
    September 20, 2006

    Anyone care to comment on how this book compares to Matt Ridley’s “The Origins of Virtue”, which seems to cover much the same territory?

  7. #7 Christensen
    September 20, 2006

    Just so.

  8. #8 Jason Rosenhouse
    September 20, 2006

    The book focuses mostly on kin selection. The final (short) chapter gives some discussion of reciprocal altruism and Robert Axelrod. There’s no serious discussion of Wilson and Sober’s work, though they are mentioned briefly. As I mentioned, this should really be viewed as a history of science book focusing on seven especially important figures. It’s hardly an exahustive or rigorous discussion of the problem of altruism in evolution.

  9. #9 AJS
    September 21, 2006

    I have to take issue with the premise that “selection only understands immediate survival advantage”. That might be the case in a race where each organism produced offspring once per lifetime and then died. However, many animals that live in packs live to see several generations. It is thus possible that behaviour which is deleterious but not catastrophic might be modified when the next litter are born — in other words, learning from non-fatal mistakes.

    If altruistic behaviour were detrimental to the survival of a species as a whole, surely Nature would select against that species?

    I think game theory provides some explanation for altruism within the context of pack animals. To keep things simple I will limit discussion to two game types: Rock, Paper, Scissors, and the Prisoner’s Dilemma.

    In Rock, Paper, Scissors each player picks, unbeknownst to the other, one of the available options; and both reveal their selections to each other simultaneously. Rock scores 2 against scissors (for sharpening), 1 against rock (for a draw) and 0 against paper; Paper scores 0 against scissors, 1 against paper and 2 against rock (for wrapping); Scissors score 0 against rock, 2 against paper (for cutting) and 1 against scissors.

    The Prisoner’s Dilemma is a game with only two moves, again revealed simultaneously, which I will label “nice” and “nasty”. As I am presenting it here, if both players play “nice” then they each score 2. If both players play “nasty” then they each score 1. If one player plays “nice” and the other plays “nasty”, the “nasty” player scores 3 and the “nice” player scores 0.

    (Unfortunately, the blog prevents me from presenting these scoring matrices in a tabular form. Please use your imagination!)

    The important distinction is this. Rock, Paper, Scissors is an even-scoring game. The same total number of points are distributed in each round. If played completely randomly for several rounds, the final result should be a draw. (Note that the scoring would not be affected if we eliminate one of the materials altogether: if we just play “rock and paper” the game might become very boring, but neither player is favoured. However, if you know that your opponent is never going to play scissors, you cannot lose by playing paper. The game then favours one player, although the scoring is still even.)

    The Prisoner’s Dilemma is not an even-scoring game. Depending on the moves played by each player, the sum of points awarded to both players in a single round may be 4, 3 or 2. Repeated random play will not tend to prodce the same scores every time. The best aggregate score results from both players playing “nice”. A “nasty” move has a greater effect on your opponent’s score than on your own score. Over several rounds, the best strategy with this matrix is “tit-for-tat retaliation”: play nice every time unless your opponent played nasty in the immediately-preceding round: then play nasty just once, and immediately revert to playing nice.

    Note that the Prisoner’s Dilemma scoring matrix described above is not absolutely representative of every P.D. situation; it is only an example. There may well be real-life situations with a different scoring matrix, including some which always favour one player.

    We can apply game theory to social interactions between members of a pack, and between a member of a pack and an outsider, where the points awarded represent the probability of survival. Within a pack, all players’ scores are added together to produce the pack’s aggregate score, which relates directly to the viability of the pack as a whole. Social interactions within the pack which resemble rock, paper, scissors will not affect the pack’s total score; but interactions which resemble the Prisoner’s Dilemma will affect the overall score. Any interaction between a pack member and an outsider, whether R.P.S. or P.D., will affect the pack’s overall score.

    Consider a wolf catching a sheep. This is a simple Prisoner’s Dilemma situation: his “nice” move is to alert the other members of the pack to the presence of food (and get both a reasonable meal and improved status within the pack if the other members play “nice”, but risk losing it all if the others play “nasty”); his “nasty” move is to try to scoff the lot there and then (and have already eaten something even if the other wolves do find out about it and steal his prize). However, any of the meat which exceeds the finder’s appetite will be wasted if it is not shared by the whole pack; so not sharing is less beneficial to the pack’s survival than sharing.

    However, if a wolf encroaches on another pack’s territory, it might be more beneficial to the defenders to be “nasty” to the invader (since the outcome from nasty vs. nasty is still preferable to nice vs. nasty, even although it is not as good as nice vs. nice; beside which, the points awarded to the invader will not necessarily stay within the pack. If the interloper accepts an invitation to join the pack — “nice” vs. “nice” — the maximum points do stay within the pack).

    Tendencies towards behaviour which actively jeopardises the survival of the pack obviously will be selected against: in the limiting case, there will be no members of the pack left in a fit state to reproduce. Nature will select for pack-neutral and pack-beneficial behaviour tendencies.

    What is being selected for is actually the ability to weigh up the scoring matrix in any given “Prisoner’s Dilemma” situation, evaluate accordingly and make the best move. And it just so happens that the highest scoring moves are altruistic. Therefore, Nature will select altruistic behaviour over selfishness.

  10. #10 David Harmon
    September 21, 2006

    AJS: ‘I have to take issue with the premise that “selection only understands immediate survival advantage”. ‘

    Indeed, that’s just wrong. Selection represents, not immediate, but ultimate survival advantage, where “survival” represents lineages, rather than individuals. There is no “scoring system”, the results are the score, and the “advantage” is measured exactly by it’s success.

    With regard to games theory, remember that the other side of the Prisoner’s Dilemma is the “Temptation” payoff. Thus, while cooperation evolves repeatedly, so does cheating, and (in turn) attempts to detect and punish such cheaters.

    What I find most interesting about evolution is that it smashes “meta levels” with impunity. It doesn’t really care if a given advantage came from a directly improved function (Say, a better claw), a happy accident of circumstance (white fur in winter), a subtle side-effect (becoming poisonous by eating a particular insect), or even an epiphenomenon of group interactions (pecking orders reduce intragroup conflict). Whatever succeeds, proceeds!

  11. #11 AJS
    September 21, 2006

    With regard to games theory, remember that the other side of the Prisoner’s Dilemma is the “Temptation” payoff. Thus, while cooperation evolves repeatedly, so does cheating, and (in turn) attempts to detect and punish such cheaters.

    I’m not really contradicting that. I’m saying that in the case of interaction within a pack, the aggregate score of all pack members is important in its own right. (On further thought, it probably isn’t quite as simple as just adding up the scores; but I do think that the outcomes of Prisoner’s Dilemma-type situations between members of a pack have an effect on the viability of the pack as a unit, and it is the extent of this effect that defines the pack.) It’s true that if you cheat, you will not be beaten as soundly as if you play fair and are cheated; but if you play fair, you contribute more towards the viability of the entire pack — even if you lose.

    Also, there is only so far that a winning strategy can evolve (it’s perfect when you win every time) and there is only so far that a cheating strategy can evolve (it’s perfect when you win as often as you can while never getting caught). But there’s still a big jump from “good enough to work” to perfect, and the Law of Diminishing Returns sets in. Minor improvements to an established species have little survival advantage, and so are not so strongly selected. But once a population is more or less stable, a sudden catastrophic event can impose special requirements, “raising the bar” and selecting for changes that might have been of little benefit previously; and the population will expand again with the latest changes incorporated.

    What I find most interesting about evolution is that it smashes “meta levels” with impunity. It doesn’t really care if a given advantage came from a directly improved function (Say, a better claw), a happy accident of circumstance (white fur in winter), a subtle side-effect (becoming poisonous by eating a particular insect), or even an epiphenomenon of group interactions (pecking orders reduce intragroup conflict). Whatever succeeds, proceeds!

    That’s a good demonstration of the Principle of Equivalence. Nature is lazy like that :) Why bother to discriminate between means, if they all lead to the same end?

  12. #12 Jason Rosenhouse
    September 21, 2006

    Immediate…Ultimate. To-MAY-to…To-MAH-to.

    Point taken. Thanks for the correction.

  13. #13 Davis
    September 23, 2006

    As a fellow mathematician, could you recommend something that *does* get into the mathematics left out here? It’s enjoyable reading books like The Selfish Gene, but they always seem to cut out the math so as not to scare away most readers. However, my issue is that I don’t know the *biology* — the math is not a problem.

  14. #14 Morgan-LynnGriggs Lamberth
    March 17, 2008

    Si, Ayn Rand was a crank1

  15. #15 okey oyna
    January 24, 2009

    thanks

  16. #16 Timothy Allen
    July 30, 2010

    How about pairing the principle of “survival of the fittest” with that of “thriving of the most cooperative” and leave altruism to follow?

The site is undergoing maintenance presently. Commenting has been disabled. Please check back later!