An incomplete area of study in philosophy and science is the hows and whys of social cooperation. We can easily assume that social organisms gain benefits in terms of the propagation of genes by speculating about the consequences of social interactions versus individual ones, but translating that speculation into deep insights has remained a continuing research program. The consequences couldn’t be more significant because we immediately gain traction on the Naturalistic Fallacy and build a bridge towards a clearer understanding of human motivation in arguing for a type of Moral Naturalism that embodies much of the best we know and hope for from human history.
So worth tracking are continued efforts to understand how competition can be outdone by cooperation in the most elementary and mathematical sense. The superlatively named Freeman Dyson (who doesn’t want to be a free man?) cast a cloud of doubt on the ability of cooperation to be a working strategy when he and colleague William Press analyzed the payoff matrixes of iterated prisoner’s dilemma games and discovered a class of play strategies called “Zero-Determinant” strategies that always pay-off regardless of the opponent’s strategies. Hence, the concern that there is a large corner in the adaptive topology where strong-arming always wins. And evolutionary search must seek out that corner and winners must accumulate there, thus ruling out cooperation as a prominent feature of evolutionary success.
But that can’t reflect the reality we think we see, where cooperation in primates and other eusocial organisms seems to be the precursor to the kinds of virtues that are reflected in moral, religious, and ethical traditions. So what might be missing in this analysis? Christophe Adami and Arend Hintze at Michigan State may have some of the answers in their paper, Evolutionary instability of zero-determinant strategies demonstrates that winning is not everything. The reasons for instability are several, but one key one is that in the matrixed encounters between individual players, geography interferes with the capacity for one player to exploit any other players; the mathematics breaks down because of the inability of individuals to recognize one another. Interestingly, though, a method for improving recognition memory or by “tagging” the other players for enhanced recognition becomes subject to an evolutionary arms race. And this is a Red Queen effect, running forever to stay in place through development and counter-strategies.
Expanding towards a consideration of the ethical and moral consequences of cooperation brings us to the Red Queen of Hearts.
Fukuyama’s suggestion is intriguing but needs further development and empirical support before it can be considered more than a hypothesis. To be mildly repetitive, ideology derived from scientific theories should be subject to even more scrutiny than religious-political ideologies if for no other reason than it can be. But in order to drill down into the questions surrounding how reciprocal altruism might enable the evolution of linguistic and mental abstractions, we need to simplify the problems down to basics, then work outward.
So let’s start with reciprocal altruism as a mere mathematical game. The iterated prisoner’s dilemma is a case study: you and a compatriot are accused of a heinous crime and put in separate rooms. If you deny involvement and so does your friend you will each get 3 years prison. If you admit to the crime and so does your friend you will both get 1 year (cooperation behavior). But if you or your co-conspirator deny involvement while fingering the other, one gets to walk free while the other gets 6 years (defection strategy). Joint fingering is equivalent to two denials at 3 years since the evidence is equivocal. What does one do as a “rational actor” in order to minimize penalization? The only solution is to betray your friend while denying involvement (deny, deny, deny): you get either 3 years (assuming he also denies involvement), or you walk (he denies), or he fingers you also which is the same as dual denials at 3 years each. The average years served are 1/3*3 + 1/3*0 + 1/3*3 = 3 years versus 1/2*1 + 1/2*6 = 3.5 years for admitting to the crime.
In other words it doesn’t pay to cooperate.
But that isn’t the “iterated” version of the game. In the iterated prisoner’s dilemma the game is played over and over again. What strategy is best then? An initial empirical result showed that “tit for tat” worked impressively well between two actors. In tit-for-tat you don’t need much memory about your co-conspirator’s past behavior. It suffices for you to simply do in the current round what they just did in the last round. If they defected, you defect to punish them. If they cooperated, you cooperate.
But this is just two actors and robust payoff matrixes. What if we expand the game to include hundreds of interacting agents who are all competing for mating privileges and access to resources? Fukuyama’s claim is being applied to human prehistory, after all. How does a more complex competitive-cooperative landscape change these simple games and lead to an upward trajectory of abstraction, induction, abduction, or other mechanisms that feed into cognitive processes and then into linguistic ones? We can bound the problem in the following way: the actors need at least as many bits as there are interacting actors to be able to track their defection rates to the last interaction. And, since there are observable limitations to identifying defection (cheating) with regard to mating opportunities or other complex human behaviors, we can expand the bits requirement to floating point representations that cast past behavior in terms of an estimate of their likelihood of future defections. Next, you have to maintain individual statistical models of each participant to better estimate their likelihood of defection versus cooperation (hundreds of estimates and variables). You also need a vast array of predictive neural structures that are tuned to various social cues (Did he just flirt with my girlfriend? Did he just suck-up to the head man?)
We do seem to end up with big brains, just like Vonnegut predicted and lamented in Galapagos, though contra-Vonnegut whether those big brains translate into species-wide destruction is less about prediction and more about policy choices. Still, Fukuyama is better than most historians in that he neither succumbs to atheoretical reporting (ODTAA: history is just “one damn thing after another”) nor to fixating on the support of a central theory that forces the interpretation of the historical record (OMEX: “one more example of X”).