Proceedings B just published an interesting article by theoretical biologists McNally and Jackson called "Cooperation creates selection for tactical deception". The authors analyzed a simple mathematical model and reviewed comparative data on cooperation and decepton across the order Primates to argue...well...exactly what their title says. Irrelevant side note: the Jackson author's first name is Andrew. That is, he shares a name with one of the most badass, cantankerous, and dare I say murderous of American Presidents.

Anyway, the mathematical analysis reveals that, if cooperation evolutionarily prevails over "honest" cheating (where cheaters don't try to hide their cheating), then a new strategy can invade that tactically deceives cooperators (by hiding or misrepresenting their behavior). But this can only happen if cooperators aren't good at recognizing rare cheaters. In that case, you'd expect a mixed population of cooperators and deceptive cheaters. The equilibrium ratio of cooperators to deceptive cheaters depends on how difficult it is to deceive relative to how good cooperators are at recognizing both cheaters and deception. The more difficult deception is and the easier recognizing it is, the greater the ratio of cooperators to deceptive cheaters.


What's really interesting about the mathematical result is that if cooperators are terrible at catching cheaters, then "honest" cheaters can invade the mixed population of cooperators and deceivers because they don't pay the cost of deception that deceivers do, but they still reap all the benefits of cheating. In that case, cooperation prevails. Hurray. But if cooperators are good at catching cheaters, it pays to deceive ... at least for rare deceptive cheaters. I'm pretty sure that these mathematical results make sense and you might guess at them without doing any calculus. That's not a mark against the models. Instead, it's helpful when a mathematical model with explicit, formal assumptions confirms our intuition, which derives from implicit assumptions and informal logic.


The authors argue that their mathematical model implies a positive correlation between the number of cooperative strategies and the number of deceptive strategies in a species. Actually, their model implies that, under some very specific circumstances, we'd expect a positive correlation between the frequency of cooperators and the frequency of defectors. That said, it's not too much of a logical leap.

To examine this prediction, the authors did a comparative analysis of species in the order Primates (to which we belong). The data compiled the presence or absence of different types of cooperative and deceptive behaviors. They used a method called independent contrasts to examine the relationship between cooperativeness and deception, controlling for the phylogenetic relationships among species and for the research effort into a particular species (because more research yields more observations of different types of behaviors). Here is are scatterplots of the independent contrasts with best fitting lines through the points.
The left plot includes only primates in the wild (because behavior in the wild is more relevant than behavior in captivity). The right plot includes both free-ranging and captive individuals. In both cases, the positive correlation between cooperativeness and deception rate is statistically significant, if a bit weak in the case of the full data set. 

What's fascinating about the empirical results is that there is no statistically significant relationship between neocortex size (a measure of cognitive capacity) and deception rate when controlling for cooperativeness. This goes against the grain of the Machiavellian intelligence hypothesis, which argues that there should be a positive correlation between deception rate and neocortex size. 

But is the non-significance of neocortex size simply due to a collinearity problem? A collinearity problem happens when you fit a regression in which two of the predictor variables are highly correlated. The effect of collinearity is that it inflates the confidence intervals of your regression coefficients (which measure the relationship between the outcome variable and the predictors). Wider confidence intervals mean larger p-values and lower statistical significance. The number of cooperative behaviors in a species and its neocortex size might be correlated. Indeed, R.I.M. Dunbar's classic study found that group size is correlated with neocortex size in primates, and group size is a problematic but still useful proxy for social complexity.

And this is why journals need to allow more room for the methods section: because we should never penalize scientists for doing collinearity diagnostics.
 
 
Why are humans so egalitarian. Wait, a second. Are we egalitarian? Have we ever been? If so, why?

To address these questions, Sergey Gavrilets recently published an article in PNAS about the "egalitarian syndrome" among humans. That is the tendency of humans to exhibit a psychological bias toward fairness, even toward others. Gavrilets asserts that one manifestation of the egalitarian syndrome is a tendency to interfere in conflicts between bullies and victims, siding with the victim. 

Gavrilets argues that the standard evolutionary explanations for the emergence of cooperation - e.g., punishment, reciprocity, kinship, and group selection - "do not apply to the emergence of egalitarian behavior in hierarchically organized groups that characterized the social life of our ancestors" (from the abstract). 

He then builds and extends a model similar to the famous hawk-dove game to allow for differences in strength between bullies and victims. He also allows individuals to make mistakes when deciding whether to escalate a bully-victim contest due to imperfect information about the strength of opponents.

Gavrilets then shows that, if fitness increases quickly with each additional unit of goodies that it accumulates through bullying or defending its current bag of goodies, individuals have incentive to take action toward making the distribution of resources across fellow group members more equal. He then asserts that, among primates like chimpanzees and humans that live in hierarchically ranked societies, fitness indeed increases quickly with the amount of goodies you have in your bag. 

With this brief and vague justification in hand, Gavrilets then assumes that our ancestors had incentive to equalize the distribution of resources across their fellow group members, while at the same time maximizing their own share of group resources. One way to equalize resource distribution is to side with the victim in bully-victim conflicts. Therefore, selection would favor a psychological propensity toward forming coalitions with victims against bullies.

So let's review:

  1. Individuals have the opportunity to act as bullies or victims in dyadic interactions over their life course.
  2. Bullies rob victims of their goodies and so have more goodies in their bag.
  3. The more goodies you have in your bag, the greater your reproductive success.
  4. If your reproductive success increase rapidly (say, to the power of some number greater than one) with each additional goody you have in your bag, then you have incentive to equalize distribution across your fellow group members, but also to grab as many goodies as you can for your own bag.
  5. One way to drive resource distribution to become more egalitarian is to side with victims against bullies.
  6. Apparently, (4) is a foregone conclusion for organisms living in hierarchically structured societies, like humans and...well...lot's of other things.


Now, points (4) and (6) might stand out like a sore thumb to you if you are a critical thinker. With point (4), you might ask, "Why does being in a hierarchically structured society make reproductive success increase rapidly with the amount of goodies you accumulate?" The answer is, it doesn't. Gavrilets skipped a step in his paper, and probably because he is smarter than you. But let's flesh this out a bit so that his model makes more sense.

Reproductive success increases rapidly with the amount of goodies in your bag because there is positive feedback between the amount of goodies in your bag and your strength (or, as behavioral ecologists call it, your resource holding potential; but it could also be your resource stealing potential in this model!). The more goodies you have in your bag, the more you can consume. The more you consume, the heavier and stronger you are. Individuals who are innately stronger than their cohort are born with an advantage that is likely to stay with them over their life course, creating a stable hierarchy.

Now for point (6), you might be asking, "Okay. So if hierarchically structured animal societies create an incentive for individuals to have an egalitarian bias, why isn't there an egalitarian syndrome among chimpanzees or baboons or, I dunno, dogs?" The answer is that difference between other animals and humans in this case is probably not one of kind as much as it is of degree.

See, in Gavrilets' model of third party interference in bully-victim conflicts, there are two very important parameters: the reliability of assessing the strength of an opponent (which we've already discussed), and the efficiency of coalition formation (i.e., how much more likely you are to win against a bully the more people you have in your posse?). Gavrilets argues convincingly that the reliability of strength assessment, and the efficiency of coalition formation may have increased as a result of preadaptations for making weaponry and coordinated attacks for cooperative big game hunting, which also entailed increased cognitive ability. The more reliable are a coalition's assessment of an opponent's strength, and the greater the efficiency of coalition formation, the lower the cost-to-benefit ratio for forming coalitions.

But Gavrilets commits one error of omission that I hope my research on hawkish cooperation will one day rectify. In his discussion, Gavrilets argues that one overlooked factor that would favor the emergence of the egalitarian syndrome is differing group fitness, assuming that group fitness decreases with the amount of within-group conflict. 

My hawkish cooperation research asks, "But why should we assume that group fitness strictly decreases with the amount of within-group conflict?" What if groups composed of individuals who have more experience either bullying or facing bullies are more prepared for conflict with other groups? Being better prepared for between-group conflicts might provide both an individual and group level incentive for a level of within-group competition above that which we would predict based on Gavrilets' model.

More interestingly, there may be some kind of complex balancing act going on between the egalitarian syndrome and the hawkish cooperation syndrome. Between the needs of the individual and the needs of the group. Between the will and the wiles of the strong, and compassion for the weak.
 
 

Did you know that there is a website called Whale.fm where you can do your part to help marine biologists decipher the eerily beautiful language of whales?

There are all sorts of similar research projects out there tapping into the wisdom of the crowd to deal with difficult problems and large datasets. It's been called crowd science or citizen science. Thanks to the Internet, humans are inventing new ways of thinking that aggregate our grey matter.

Someday I'll have a genealogy or some other dataset large enough so that the time investment in developing a citizen science platform would be worthwhile. For now, I'm thinking about embarking on what I will call open source noodling. And I want you to tell me whether or not this is a really bad idea.

Open source noodling puts together two terms, "open source" and "noodling". Open source, of course, refers to a mode of production that involves free access to and distribution of an end product's design. Many argue that open source bolsters innovation and levels the playing field. Scholars in many disciplines, including my own, are debating a shift to open access peer review from the corporate, for-profit peer-reviewed journal model. Open access is very similar to the open source philosophy.

Noodling is a term I first heard in conversation with Richard McElreath, an anthropologist at UC Davis who studies cultural transmission and lots of other stuff. Basically, it's the use of abstract mathematical models to answer concrete questions like, "Why are humans so reliant on social learning?" or..well..anything really, if you build the model properly.

If you put open source and noodling together you get the development of a mathematical model to answer a question, which is built collaboratively using a system that allows open distribution and free access to information.

What I want to do is take a mathematical model I've been working on, and which is basically finished, write a draft manuscript, and post it in a medium that allows for open discussion and possibly even open editing. This sounds like a terrible idea but I'm playing with it, and want you to come and play with it, too.

The benefits of open source are manifold. I could tap into a huge knowledge base to solve a problem that I think is really interesting. It bypasses the slow process of peer review while also potentially improving a manuscript in preparation for the peer review format. Yet open source also poses new problems about who gets credit for the research, how to filter information, and how to aggregate the wisdom of the crowd into a singular product.

How would you set something like this up? I encourage open (heh) discussion about it. Or contact me personally, whatever. It's an idea I'd like to develop into a systematic method of producing and distribution knowledge.

I'd also appreciate it if you told me if I was reinventing the wheel, and if there are already venues out there where open source noodling can be done in a way that maximizes the benefits but minimizes the costs.

Anyway, here's an example of something I'd like to submit to open source noodling. I have other things, too, but here's one for starters

In between genealogical interviews with key informants and preparation for the rest of my field surveys, I'm working on some side projects to pass the down time.

The one I'm focusing on now is part of a project I'm calling "the tragedy of hawkish altruism". The tragedy of hawkish altruism is this:

If individuals who are aggressive to members of their own group make that group better prepared for competition with other groups, it may drive the evolution of aggressive behavior that leads to more conflict within groups. In this scenario, hawkish bastards are also tragic heroes because they risk their necks training for and maneuvering on the evolutionary battlefield against other groups. 

Think about warriors risking severe injury to realistically train for battle. Think about office intrigue and backstabbing that prepares people for the rigors of negotiation with other firms.

The tragedy of hawkish altruism ties into a broader debate in evolutionary biology about the strength of natural selection among groups versus individuals. Natural selection needs variation in order to happen. When individuals move freely between groups, it causes all groups to be more similar to one another and for most variation to exist among individuals. For this and other reasons, evolutionary biologists have traditionally considered individual selection to be stronger than group selection.

Yet a few evolutionary biologists argue that group selection may still be an important force in some cases. For example, the tendency of humans to conform to the customs most common in their current group may allow variation among groups to increase relative to variation among individuals, causing group selection to overpower individual selection. 

Researchers have used this reasoning to support a hypothesis for why humans are an especially cooperative species, even in large groups of unrelated individuals, and even when cooperation requires altruism, which would be selected against among individuals but favored among groups (that characterization of humanity, by the way, is itself a hypothesis that I don't think has been adequately tested; at least not the part where cooperation is assumed to be altruistic). 

Anyway, this so-called cultural group selection explanation for the cooperativeness of humans is contentious for many but compelling for some. Unfortunately, some people I've spoken to during academic conferences and after-school happy hours have clearly misinterpreted the argument as meaning that group selection leads inexorably to socially desirable outcomes.

Um. No. In fact, some research suggests (though not without substantial controversy) that group selection could potentially explain warfare if warfare entails individually costly contributions toward common defense or offensive raids that benefit a group. Hard to argue that warfare between groups is socially desirable.

Back to the tragedy of hawkish altruism. I've developed a mathematical model showing that group selection cannot only explain conflict BETWEEN groups. It might also explain conflict WITHIN them.

Where the crowd science and open source noodling comes in is that I want to post an early version of my manuscript and hold an open discussion about it before I submit it for publication. Hell, maybe the discussion might result in a collaboration. Scientists share their unpublished manuscripts all the time with their colleagues. And there are many many many scientists out there who could be my virtual colleagues. Why limit it to the people I know personally?

My ultimate goal with this tragedy of hawkish altruism stuff is to develop several quantitative models of increasing complexity while amassing a large, cross-cultural dataset to test the assumptions and qualitative predictions of those models. In fact, one of my post-PhD plans is to apply for a Harry Guggenheim Research Grant (they fund research on dominance and violence) to do this research.

Anyway, I'm looking for suggestions on how and if to do this kind of open source noodling in a way that maximizes the coolness and soundness of the science while minimizing the possibility for unforeseen bad stuff to happen. So how about it?