In a 1945 paper, George Stigler, the 1982 winner of the Nobel Memorial Prize in Economic Sciences, examined what would be the cheapest way in which a 154 pound man could meet his National Research Council recommended dietary requirements of 3000 calories a day, including 70 grams of protein and a range of other vitamins and minerals.

Using 1939 prices, Stigler found that an annual diet consisting of 370 pounds of wheat flour, 57 cans of evaporated milk, 111 pounds of cabbage, 23 pounds of spinach and 285 pounds of navy beans would meet the requirements. A nice vegetarian diet. Using 1945 prices, the evaporated milk and beans are substituted out for pancake flour and pork liver (leading to over 700 pounds of wheat and pancake flour to be consumed annually). Each diet costs roughly $600 a year in 2012 dollar terms.

One interesting element of the diet, and the NRC recommendation, is the low protein content. The protein leverage hypothesis (which I have blogged about previously), suggests that we have evolved a stronger propensity to regulate protein content than non-protein calories. As a result, around 14 per cent of the diet should be protein to allow one to feel full and prevent overeating. Given that less than 10 per cent of the Stigler diet is protein, the Stigler diet will leave someone permanently hungry – unless they want to splash out on some extra wheat and pancake flour.

A few minutes of googling did not turn up someone’s “year on the Stigler diet”.

Around ten years ago, I was rummaging through books in a bargain bookshop under Sydney’s Central Station when I came across a $2 copy of Geoffrey Miller’s The Mating Mind. It turned out to be a good use of my $2, as The Mating Mind is one of the most important books in shaping my thinking, and it was one of the first books I put on my economics and evolutionary biology reading list.

Miller’s basic argument was that sexual selection shaped the human mind. Whether through runaway selection or the brain acting as a fitness indicator, female choice led to increasing mental capacity and shaped our propensity to be humorous, create art or engage in other displays of mental fitness.

As I read the Mating Mind, it occurred to me that the growing mental capability and tendency to display it would have direct economic effects. It would be possible to argue that sexual selection shapes economic growth. Ten years after that idea, my latest working paper (co-authored with my supervisors Boris Baer and Juerg Weber) seeks to flesh out one element of it. The working paper provides a theoretical model for the hypothesis that sexual selection and the resulting propensity to engage in conspicuous consumption has economic effects, and in particular, the desire to engage in conspicuous consumption is one of the pillars underlying the emergence of modern economic growth.

The concept behind the hypothesis is relatively simple. Men who signal their quality through conspicuous consumption have higher reproductive success, as the conspicuous consumption provides a reliable signal of their quality to potential mates. To engage in conspicuous consumption takes effort by the men – whether in the form of art, humour or entering the labour force to acquire resources to consume conspicuously. As the prevalence of males who conspicuously consume increases, the total level of these activities also increases. The increased participation in productive activities results in a scale effect, whereby the greater number of people involved in creative and productive activities results in increased technological progress, which underlies economic growth.

The evolutionary part of the model is more interesting than the economic as there is minimal feedback from the economy back into the evolutionary dynamics. The lack of feedback also means that it is not very representative of modern society, as conspicuous consumption in modern societies is of limited threat to survival. Still, the model provides a starting point and I have a few ideas to take it further.

I have been introducing my talks on the paper with an example from Robert Frank’s Luxury Fever, in which Frank held up Patek Philippe’s Calibre 89 watch as an example of conspicuous consumption. Only four were made, with the first selling for $2.5 million and the latest auction price being over $5 million. Frank mocks the watch for its need for a tourbillon, a mechanism to account for the earth’s rotation, when his cheap quartz watch does not require such a mechanism, as gravity does not affect the vibrations of the crystal.

Now consider the innovation and thought that went into the Patek Philippe watch, including that tourbillon. This watch has 1728 components, gives you the date of Easter each year, and unlike most mechanical watches, will not record the years 2100, 2200 and 2300 as leap years while still recording 2400 as one (as per the order of Pope Gregory XIII in 1582). If you look at Patek Philippe’s list of patents, you get a feel for the innovation involved in making watches for what is largely conspicuous consumption.

When you also consider the innovation undertaken by the potential buyers as they seek to amass the wealth necessary to obtain such a watch, the positive angle to conspicuous consumption grows. As a result, curbing conspicuous consumption may have costs (although, I still prefer taxing consumption to income). If nothing else, we should appreciate the historical role of conspicuous consumption – competition for sexual partners is a driving force for many productive activities, and one generation’s conspicuous consumption is another generation’s day-to-day tool.

*I foreshadowed this paper a couple of months ago with a poster that I presented at the Consilience Conference.

At the Consilience Conference earlier this year, I saw Peter Turchin’s presentation on cliodynamics – the mathematical modelling of historical dynamics. I was relatively sceptical of what I saw, and a new Nature news piece by Laura Spinney on Turchin’s work captures some of this scepticism. Spinney describes cliodynamics as follows:

In their analysis of long-term social trends, advocates of cliodynamics focus on four main variables: population numbers, social structure, state strength and political instability. Each variable is measured in several ways. Social structure, for example, relies on factors such as health inequality — measured using proxies including quantitative data on life expectancies — and wealth inequality, measured by the ratio of the largest fortune to the median wage. Choosing appropriate proxies can be a challenge, because relevant data are often hard to find. No proxy is perfect, the researchers concede. But they try to minimize the problem by choosing at least two proxies for each variable.

Then, drawing on all the sources they can find — historical databases, newspaper archives, ethnographic studies — Turchin and his colleagues plot these proxies over time and look for trends, hoping to identify historical patterns and markers of future events. For example, it seems that indicators of corruption increase and political cooperation unravels when a period of instability or violence is imminent. Such analysis also allows the researchers to track the order in which the changes occur, so that they can tease out useful correlations that might lead to cause–effect explanations.

Some of the ideas behind cliodynamics are interesting, particularly the data collection, use of agent based models and nonlinear mathematics, but I am sceptical of the “chartist” approach of Turchin and others who extend their search of patterns and causation to identifying cycles. In particular, Turchin and colleagues have identified two historical cycles:

The first, which they call the secular cycle, extends over two to three centuries. It starts with a relatively egalitarian society, in which supply and demand for labour roughly balance out. In time, the population grows, labour supply outstrips demand, elites form and the living standards of the poorest fall. At a certain point, the society becomes top-heavy with elites, who start fighting for power. Political instability ensues and leads to collapse, and the cycle begins again.

Superimposed on that secular trend, the researchers observe a shorter cycle that spans 50 years — roughly two generations. Turchin calls this the fathers-and-sons cycle: the father responds violently to a perceived social injustice; the son lives with the miserable legacy of the resulting conflict and abstains; the third generation begins again. Turchin likens this cycle to a forest fire that ignites and burns out, until a sufficient amount of underbrush accumulates and the cycle recommences.

This conclusion is difficult to reconcile with a view of history as the outcome of a complex system, where what seem to be repeated cycles may be transitory and long periods of apparent calm may end with sudden shifts. Black swan events (even relatively small) can have large effects. Turchin appears to be aware of complexity theory from what I have read of his writings and he adopts many of the tools that has emerged from it, so I find his focus on cycles surprising.

The focus on cycles also appears to give a low weight to the strong trends underlying them, such as the general decline in violence or massive gains in wealth since the Industrial Revolution. That is where cliodynamics could add some real value. What caused these changes to what extent are the changes permanent and stable?

This is not to say, however, that cliodynamics can’t produce something interesting – the modelling and mass collection of data could be highly valuable. Herb Gintis captures some of my optimism:

Herbert Gintis, a retired economist who is still actively researching the evolution of social complexity at the University of Massachusetts Amherst, also doubts that cliodynamics can predict specific historical events. But he thinks that the patterns and causal connections that it reveals can teach policy-makers valuable lessons about pitfalls to avoid, and actions that might forestall trouble. He offers the analogy of aviation: “You certainly can’t predict when a plane is going to crash, but engineers recover the black box. They study it carefully, they find out why the plane crashed, and that’s why so many fewer planes crash today than used to.”

Comments on my research often approach the edge of debates about race and IQ, so despite my general lack of interest in going there, I keep a rough watch on what is happening in the area. A couple of weeks ago, Ron Unz made a solid entry into the debate by ploughing through a mountain of data on race, income and IQ to come to the following conclusion:

The central thesis of Lynn and Vanhanen’s work might be called the “Strong IQ Hypothesis,” namely that IQ accurately reflects intelligence, that IQ is overwhelmingly determined by genetics, and that IQ is subject to little or no significant cultural or economic influence after we adjust for the universal Flynn Effect. …

Yet an objective review of the Lynn/Vanhanen data almost completely discredits the Lynn/Vanhanen “Strong IQ Hypothesis.” If so many genetically-indistinguishable European populations—of roughly similar cultural and historical background and without severe nutritional difficulties—can display such huge variances in tested IQ across different decades and locations, we should be extremely cautious about assuming that other ethnic IQ differences are innate rather than environmental, especially since these may involve populations separated by far wider cultural or nutritional gaps.

We cannot rule out the possibility that different European peoples might have relatively small differences in innate intelligence or IQ—after all, these populations often differ in height and numerous other phenotypic traits. But this residual genetic element would explain merely a small fraction of the huge 10–15 point IQ disparities discussed above. Such a view might be characterized as the “Weak IQ Hypothesis”: huge IQ differences between large populations may be overwhelmingly due to cultural or socio-economic factors, but a residual component might indeed be genetic in origin.

Regardless of the merits of Unz’s argument – among other things, he ignores the potential for measurement error, and while he notes persistently high east Asian IQ, he does not ask how this fits with his picture – the weak IQ hypothesis does not necessarily rule out IQ as a major cause of cross-country income differences. If slightly higher IQ has a positive effect on economic growth, this may in turn then allow IQ improvements through improved nutrition, which would then allow for further economic growth. A virtuous cycle would begin. Small changes in initial conditions can have a substantial effect on final outcomes. We can of course come to a similar argument with no genetic basis to IQ if there was a shock that temporarily lifted income to allow the IQ increase and trigger the growth-IQ feedback loop.

Unz’s approach raises one other interesting question, which Unz himself asks:

We are now faced with a mystery arguably greater than that of IQ itself. Given the powerful ammunition that Lynn and Vanhanen have provided to those opposing their own “Strong IQ Hypothesis,” we must wonder why this has never attracted the attention of either of the warring camps in the endless, bitter IQ dispute, despite their alleged familiarity with the work of these two prominent scholars. In effect, I would suggest that the heralded 300-page work by Lynn and Vanhanen constituted a game-ending own-goal against their IQ-determinist side, but that neither of the competing ideological teams ever noticed.

Presumably, human psychology is the underlying explanation for this mysterious and even amusing silence. Given that Lynn and Vanhanen rank as titans of the racial-difference camp, perhaps their ideological opponents, who often come from less quantitative backgrounds, are reluctant even to open the pages of their books, fearful lest the vast quantity of data within prove that the racialist analysis is factually correct after all. Meanwhile, the pro-racialist elements may simply skim over the hundreds of pages of dry and detailed quantitative evidence and skip to the summary text, which claims that the data demonstrate IQ is genetically fixed and determines which nations will be rich and which will be poor.

The whole piece by Unz is worth the read, as is Richard Lynn’s response.

In my recent review of Paul Ormerod’s Why Most Things Fail, I asked if Ormerod’s comparison between the extinction of species and the death of firms was the right analogy. One reason for my question was that species are typically defined due to their reproductive isolation, preventing gene transfer between species. In contrast, the unit of selection for firms, business plan modules (the name used by Eric Beinhocker), can spread freely spread between firms.

Interestingly, I have just picked up Kevin Kelly’s What Technology Wants, 18 months after my post speculating on Kelly’s approach, where he raises a similar issue. Kelly notes that whereas the passage of biological traits is limited to the passing of traits to offspring, technology transmission can occur horizontally. He writes:

[N]ature can’t plan ahead. It does not hoard innovations for later use. If a variation in nature does not provide an immediate survival advantage, it is too costly to maintain and so over time it disappears. But sometimes a trait advantageous for one problem will turn out to be advantageous for a second, unanticipated problem. … These inadvertent anticipatory inventions are called exaptations in biology. We don’t know how common exaptations are in nature, but they are routine in the technium. The technium is nothing but exaptations, since innovations can be easily borrowed across lines of origin or moved across time and repurposed.

Niles Eldredge is the cofounder (with Stephen Jay Gould) of the theory of punctuated, stepwise evolution. … Once Eldredge applied his professional taxonomic methods to his collection of 500 cornets, some dating back to 1825. He selected 17 traits that varied among his instruments—the shape of their horns, the placement of the valves, the length and diameter of their tubes—very similar to the kinds of metrics he applies to trilobites. When he mapped the evolution of cornets using techniques similar to those he applies to ancient arthropods, he found that the pattern of the lineages were very similar in many ways to those of living organisms. As one example, the evolution of cornets showed a stepwise progress, much like trilobites. But the evolution of musical instruments was also very distinctive. The key difference between the evolution of multicellular life and the evolution of the technium is that in life most blending of traits happens “vertically” in time. Innovations are passed from living parents down (vertically) through offspring. In the technium, on the other hand, most blending of traits happens laterally across time—even from “extinct” species and across lineages from nonparents. Eldredge discovered that the pattern of evolution in the technium is not the repeated forking of branches we associate with the tree of life, but rather a spreading, recursive network of pathways that often double back to “dead” ideas and resurrect “lost” traits.

Kelly goes as far as suggesting that no species of technology ever goes extinct. I’m not sure that calling a technology a species is the right approach – is the species the horn and the feature of the horn the unit of selection? – but the general point has some significant consequences for the biology-technology analogy. Similarly, the firm-species analogy is not a perfect fit due to this horizontal transfer of business plan modules, and possibility that individual modules never go extinct. In the case of Ormerod’s analysis however, I’m not yet sure what the consequences of that difference is.

The article by Tëmkin and Eldredge that charts the evolution of cornets can be found in Current Anthropology (ungated version here).

After sitting on my reading list for a few years, I have finally read Paul Ormerod’s Why Most Things Fail. Ormerod’s basic argument is that failure is all around us and given the complexity of the world, there are limits to how much corporations can control their fate or governments can control the success of their policies. Governments, firms and households lack complete information. They do not have the cognitive power to process the available information to determine the optimal choice. As a result, when you look at their success, the outcomes look more like the result of chance than of rational strategic decisions.

Ormerod’s argument is built upon some interesting work done by himself and others in which he examined the extinction rate of United States firms (and ultimately a wider suite of global firms). Firm death tends to follow a power law distribution, and when mapped against the historical extinction of species, which we know is built upon chance events, the pattern looks similar. In models of firm extinction involving networks of interconnected firms, if firms are given much more than 10 per cent of the available information about their relationships with other firms and are able to affect those relationships, the patterns of firm death cease to mirror those which we see. This suggests that firms act with little control over their success or failure.

While this is an interesting and important observation, is the mapping of firms to species the right mapping for the analogy? For example, a species is defined (roughly) as a group of organisms that are capable of interbreeding and producing viable offspring. Thus, the units of selection, the genes, are limited to within that species. In the case of a firm, if we consider the unit of selection to be a strategy, these are able to spread to any firm. All firms are capable of interbreeding and producing fertile offspring. So are firms more akin to members of a species than to each being a species on their own? And if so, what implications does this have for the model? If individual organisms within species have similar patterns of death without reproduction to that observed for the extinction of species (which I expect is roughly the case), then the implications may be small. However, without exploring these types of questions, Ormerod has not convinced that his comparison is the right one.

Ormerod takes some time to build to his exploration of firm extinction and some detours of varying interest along the way. One of his building blocks is an exploration of Schelling’s models of segregation, which Ormerod uses to show that simple rules can result in surprising and complex phenomena. This example forms ones of the pillars of Ormerod’s case about the complexity of the world, but I wondered at times if this was the most convincing example available. Despite the complex behaviour in Schelling’s models and the difficulty of predicting which person will end up living where, the model does allow some prediction at the macro level. It is also the case for other models explored in this area, whether that being the first-order difference equations investigated by Robert May or Brian Arthur’s El Farol bar. Predicting specific results is near impossible, but picking the pattern and the effect of parameter changes on that pattern is possible.

The detours also includes some bashing of the neoclassical economics straw man. Ormerod’s choice of supporting evidence is interesting, but the omissions are often obvious. Take his quoting of Vernon Smith on the flaws with existing models of the operation of markets, but no mention of Smith’s experimental work which suggests how well markets seem to find an equilibrium despite the knowledge shortfalls and bounded rationality. Similarly, when discussing bounded rationality, Ormerod does not explore the success or failure of heuristics (Also strange was the crediting of bounded rationality to Akerlof and Stiglitz with no mention of Herbert Simon). Ormerod could still have made his case with a more in-depth discussion, and then it might have felt more convincing.

Once Ormerod has established that companies have little control over their fate, and that the world is too complicated for governments to make decisions (both arguments I am sympathetic to), he dedicates little space to ask what this means. In the company case, it comes with a call to innovation and flexibility. But given that strategic choice has little to no effect on the probability of firm survival, why will that particular approach work?

When it comes to government, again the questions left unanswered are more interesting than those addressed. If governments are likely to achieve success only by chance and cannot possibly achieve success through detailed planning, what should they do? We have a host of government interventions ranging from legislation to enable joint stock companies to protection of property rights, each arguably important for our wellbeing. How would these be facilitated in a world where we otherwise throw up our hands in despair? Ormerod’s hints at some ideas but instead of exploring them, he sticks to denouncements of governments acting as though Soviet Russia was a success. Fair enough, but I sense the book sells Ormerod’s thoughts on this question short.

From a new paper in PLOS Genetics:

[R]efined analyses of modern human genomic data have changed our view of evolutionary forces acting on our genome. While most people assumed that the out-of-Africa expansion had been characterized by a series of adaptations to new environments leading to recurrent selective sweeps, our genome actually contains little trace of recent complete sweeps and the genetic differentiation of human population has been very progressive over time, probably without major adaptive episodes

John Hawks draws a different conclusion:

[I]n fact, we have abundant signs of recent positive selection in the genome, but those signs are nearly all very recent partial sweeps in different human populations. Complete sweeps and near-complete sweeps are indeed few, suggesting that there was relatively little directional adaptive evolution associated with the “origin of modern humans.” Measuring by genetic change, agriculture was many times more important than the appearance of modern humans throughout the world.

It is obvious in some ways, but if we wish to link economic growth with genetic changes since the appearance of agriculture, those genetic changes may look very different across populations, even comparing two populations that have similar long histories of agricultural life.

In outing Irving Fisher as a Social Darwinist, Bryan Caplan writes on how Fisher reconciled eugenics and economics. First, Caplan quotes Fisher:

The core of the problem of immigration is, however, one of race and eugenics. If we could leave out of account the question of race and eugenics I should, as an economist, be inclined to the view that unrestricted immigration, although injurious to some classes, is economically advantageous to a country as a whole, and still more to the world as a whole. But such a view would ignore the supremely important factors… Our problem is to make the most of this inheritance [of the 8,000 immigrants who arrived before 1741]. We can not do so if that racial stock is overwhelmed by the inferior stock which “assisted” immigration has recently brought. (“Impending Problems of Eugenics” [1921])

Caplan considers that the two approaches diverge due to the inherent misanthropy of eugenics:

Economics doesn’t point to people and say, “Look what they can’t do.” Economics instead asks, “Well, what can they do?” If the answer is “something productive,” then the Law of the Comparative Advantage implies gains to trade. Economics, known for its hard-headed methods, culminates in an optimistic and humane conclusion: Regardless of their Darwinian “fitness,” the existence of people – even those well below average – makes the world a better place.

I would argue that the difference is more subtle than Caplan suggests, as Fisher and many other eugenicists were well aware of comparative advantage. Rather, they had different goals, particularly about the distribution of benefits, and they often came to a different conclusion about how someone’s negative externalities balance with the “something productive” that one can offer. At the limit, we regularly put people in prison for those externalities. The question is where the line gets drawn – Fisher would likely put more people into the negative externality basket than Caplan.

Further, eugenicists often understood that the poor had a comparative advantage (although I’d suggest they did not fully understand the full implications of this) when framing their policy preferences. Thomas Leonard writes:

Progressive economists, like their neoclassical critics, believed that binding minimum wages would cause job losses. However, the progressive economists also believed that the job loss induced by minimum wages was a social benefit, as it performed the eugenic service ridding the labor force of the “unemployable.” Sidney and Beatrice Webb (1897 [1920], p. 785) put it plainly: “With regard to certain sections of the population [the “unemployable”], this unemployment is not a mark of social disease, but actually of social health.” “[O]f all ways of dealing with these unfortunate parasites,” Sidney Webb (1912, p. 992) opined in the Journal of Political Economy,  “the most ruinous to the community is to allow them to unrestrainedly compete as wage earners.” A minimum wage was seen to operate eugenically through two channels: by deterring prospective immigrants (Henderson, 1900) and also by removing from employment the “unemployable,” who, thus identified, could be, for example, segregated in rural communities or sterilised. …

Worthy wage-earners, Seager (1913a, p. 12) argued, need protection from the “wearing competition of the casual worker and the drifter” and from the other “unemployable” who unfairly drag down the wages of more deserving workers (1913b, pp. 82–83). The minimum wage protects deserving workers from the competition of the unfit by making it illegal to work for less. Seager (1913a, p. 9) wrote: “The operation of the minimum wage requirement would merely extend the definition of defectives to embrace all individuals, who even after having received special training, remain incapable of adequate self-support.” Seager (p. 10) made clear what should happen to those who, even after remedial training, could not earn the legal minimum: “If we are to maintain a race that is to be made of up of capable, efficient and independent individuals and family groups we must courageously cut off lines of heredity that have been proved to be undesirable by isolation or sterilization . . . .”

These paragraphs also indicate the often missed difference between eugenics and Social Darwinism. Social Darwinists tend to be much more rosy about the effects of competition on the human race, while eugenicists would prefer to give it a push in their preferred direction.

In my last post on group selection, I described how multilevel selection differed from more traditional (and popular) concepts of group selection. One difference is that the multilevel selection framework defines groups as any subset of interacting individuals, such as a cooperating pair or family unit, rather than restricting the definition to population size groups.

There are few tangible examples available on how a multilevel selection framework works, so below is an attempt to offer an illustration of how the definition of group in a multilevel selection framework is used. It also serves as a test of how well I understand the concept myself. This numerical example also illustrates why it is generally the less intuitive approach, which is also the reason I consider that inclusive fitness – the sum of direct and indirect (kin) fitness – has proven to be the more fruitful approach in evolutionary biology. At the end, I place the discussion in an economic context to draw out my point.

This numerical example is loosely based on the approach David Sloan Wilson used in his 1975 and 1977 papers, which might be seen as the beginning of modern multilevel selection theory. The maths in the multilevel selection debate has moved on since this time, but this illustration works for the point I want to make.

Suppose there are 200 agents in a population, of which half are cooperators and half are defectors. Cooperators always seek to cooperate and engage in a mutual trade (say, making an alert sound or entering into a transaction), while the defector will always shirk.

Agents live for one generation during which they are randomly paired with another agent. From a multilevel selection perspective, we will describe these pairs as groups. This gives us 100 groups, each comprising two agents. From random pairing, we expect that 50 of the cooperators will be paired with other cooperators, and the other 50 will be paired with defectors. Similarly, 50 of the defectors are paired with other defectors, and 50 with cooperators.

A cooperator will seek to cooperate with whoever they are paired, generating a benefit of one fitness unit for themselves, but donating two fitness units to whoever they cooperate with. Thus, if a cooperator meets another cooperator, they both cooperate and generate a surplus, from which they each get a pay-off of three fitness units (one from their own action and two from their partner). If a cooperator pairs with a defector, the group still generates a surplus through the efforts of the cooperator, but the cooperator only receives one fitness unit while the defector receives two. Finally, if a defector is paired with another defector, there is no cooperation or surplus generated, so both defectors receive zero.

Within the groups of all cooperators and all defectors, both agents get the same pay-off (three or zero), so there is no individual level selection. Within mixed groups of cooperators and defectors, the defectors get double the fitness units of the cooperator, so there is individual level selection against the cooperators. Therefore, on average, there is individual selection against cooperators within groups. Within the group, the cooperator’s action appears to be an altruistic act. David Sloan Wilson has called this situation where an agent’s absolute fitness increases but their relative fitness is decreased within a group “weak altruism”.

Now for the competition between groups. The groups of cooperators get a total pay-off of six, mixed groups both get a total pay-off of three, while the groups of all defectors receive a pay-off of zero. There is selection for groups comprising solely of cooperators relative to the other two groups, and selection for mixed groups relative to groups of defectors. Group success increases with the proportion of cooperators.

Group and individual selection are operating in different directions – individual selection favours defectors while group level selection favours cooperators. Which one wins? Across all cooperators, they receive an average of two fitness units each, while defectors receive an average of one fitness unit each. Competition between groups is the dominant force and cooperators increase in prevalence despite being selected against within groups. Wilson showed in his papers that all it requires in this case of random assortment is that the cooperator have positive absolute fitness – then the group selection will overcome the relative fitness disadvantage within groups.

Now, let’s reframe this from an inclusive fitness perspective. An cooperator’s action gives them a pay-off of one, and a pay-off of two to whomever they are paired with. If we ignore kin for a moment, that pay-off of two to their partner represents an average fitness increase of 0.01 for the rest of the population (two fitness units across a population of 199). One is more than 0.01, so the cooperator’s relative fitness in the population is increased due to the transaction (the transaction also increases cooperators fitness relative to 198 of the 199 others in the population). It is in the cooperators self-interest to conduct a transaction with their partner, no matter who the partner is.

Factoring in kin, the random assortment means that the two donated fitness units will on average increase the fitness of receiving defectors (non-kin) or cooperators (their kin) by an equal amount, so the effect of that donation nets out to zero instead of 0.01. Thus, the mere fact that the cooperator receives a positive pay-off is sufficient for them to increase in prevalence. Further, if there is any assortment by type, the cooperators’ pay-off can even be negative as their kin are even more likely to benefit from their cooperative acts.

The benefit of the inclusive fitness approach is that we are not left asking why someone enters a transaction when their partner obtains a fitness advantage relative to them. The reason is that this partner is not the relevant benchmark. Rather, it is the broader population. When looked at from the population level, the situation described above involves no altruism in the ordinary sense that we define it – it is pure self-interest or benefit to kin. So what if your particular partner does well from dealing with you? The deal still makes sense. The label of weak altruism appears out of place.

If we frame this example in an economic context, the inclusive fitness approach appears even more intuitive. In economics, there is a concept known as consumer and producer surplus, which is the benefit one receives from a transaction. In the case of a consumer, if you value a good at $2 but only have to pay $1, then your consumer surplus is $1. Similarly, if a producer is willing to sell a good for $1 but receives $2 for it, there is $1 of producer surplus. Every economic transaction involves a distribution of surplus between the two parties.

Now, imagine we have a population of economic agents, some of whom are cooperators and others are defectors. When two cooperators get together, a transaction occurs and each receives $3 of consumer or producer surplus. If a cooperator meets a defector, the defector rips them off, but not so much that the transaction does not occur. A defecting producer might use sub-standard materials, while a defecting consumer might try to shortchange the purchaser. The net result is that the defector walks away from the transaction with $2 of surplus, while the cooperator receives $1. If two defectors meet, their mutual attempts to get the better of the transaction results in it collapsing and no surplus is gained by either party.

Obviously, this is just a slightly different framing of my earlier example. If we treat each consumer-producer pair as a group, there is within group selection against cooperators, but group selection for cooperators. The net effect is that cooperators prosper. Similarly, if looked at from an inclusive fitness perspective, the cooperators will end up better off as their fitness gain is higher than that for the rest of the population.

Now, an economist looking at these exchanges would say they are obviously beneficial, regardless of any group framing. This is partly a consequence of the economic focus on absolute and not relative gains, but it also reflects the general fact that the majority of transactions do not have a perfectly equal division of the surplus. If you limit your group to the two people conducting the transaction, there is almost always “weak altruism” within the group. But is the cooperator being altruistic in any ordinary sense? No. Of course the altruist would enter into the transaction, even if the relative share of the benefits is not perfectly equal. We enter into transactions of this type every day because we benefit from the exchange. Ask yourself how often you consider yourself to be altruistic when you enter into an economic exchange. The only time we would not agree to enter such an exchange is spite, which Alan Grafen noted when he said that “a self interested refusal to be spiteful” was a far better description than “weak altruism” of what is occurring when we do transact.

The above is a simple example, but it captures a fundamental issue with the multilevel selection approach. The groupings are often less intuitive and, in my opinion (and I suspect most biologists’ opinion), less insightful than simply looking at the issue from an inclusive fitness angle to begin with. Group selection tends to be a more intuitive concept when the groups are population size groups. But then we find ourselves back in the old group selection debate and discussing factors such as the degree of migration between groups and whether intergroup competition can override the spread of cheaters within them. But to be realistic, that is where much of the popular debate about human altruism is anyhow.

Herbert Simon’s autobiography is probably not the best introduction to his work (I would suggest other starting points), but below are two paragraphs that caught my eye.

First, describing Chapter 15 of Models of Man:

Bracketing satisficing with Darwinian may appear contradictory, for evolutionists sometimes talk about survival of the fittest. But in fact, natural selection only predicts that survivors will be fit enough, that is, fitter than their losing competitors; it postulates satisficing, not optimizing. The paper showed how relatively simple choice mechanisms could enable an organism, searching through its life maze, to survive in an uncertain environment in which several incommensurable needs had to be met. It depicted a procedural rationality for organisms that was squarely based on satisficing rather than optimizing.

On whether the natural sciences are exact sciences:

As soon as they have to cope with the messiness of real world problems, as contrasted with the sometimes neat and simple laboratory problems, they become at least as inexact as the social sciences (which only rarely can retreat to the laboratory). I no longer have any patience with natural scientists who imagine that they have some kind of patent on exactness which they have not licensed to their social science brethren. …

The true line is not between “hard” natural science and “soft” social sciences, but between precise science limited to highly abstract and simple phenomena in the laboratory and inexact science and technology dealing with complex problems in the real world.