Why do humans have such big brains? Partly because we’re primates, and primates in general have big brains – not just big brains but an exceptional density of neurons, especially in big primates. But a recent article by González-Forero and Gardner offers some more specific ideas.
Before getting down to the article, a general reflection on statistics and methodology:
In many areas of science, you’ve got a lot of data and you want to sort out cause and effect. This happens in evolutionary biology, for example, when you want to determine what selective pressures have caused brains to evolve to different sizes. And it happens in medicine, when you want to find out what lifestyle choices generate what health problems. It also happens in social science and public policy, when you want to find out what programs generate what social outcomes. A common method in these cases is to use multivariate regression, looking for the strongest correlates of your dependent variable. This has its limits however. You often find that a lot of your variables are correlated with one another, and it’s hard to figure out what is cause and what’s effect.
So there’s been a lot of interest lately in a different approach, where you start out at the beginning with an explicit model of cause-and-effect pathways and use your data to estimate the strength of causal connections. An excellent popular introduction to this rapidly developing field comes from Judea Pearl, in The Book of Why: The New Science of Cause and Effect. Pearl makes the case here that statistics needs to move beyond pattern recognition, to testing causal models and counterfactual reasoning. Pearl sees counterfactual reasoning in particular as a human specialty, One Weird Trick that distinguishes humans from other creatures, and he is skeptical about current work in Artificial Intelligence, impressive as it is, that is mainly about pattern recognition.
Richard McElreath, commenting on González-Forero and Gardner, puts it this way:
“Automobile engineering can provide an analogy for studying this type of system. It would be difficult to understand racing-car design through regression analysis of how engine size varies depending on changes in other features, such as the mass and shape of the car. Instead, a model is needed that uses physical laws to predict optimal combinations of the variables under different criteria. Understanding brain evolution poses a similar challenge in that an organism’s features co-evolve under biological constraints.”
So turning to the article itself, what the authors do is to test an explicit model in which a developing organism has to allocate energy to growing a brain, growing a body, and reproducing. They ask what sorts of evolutionary challenges would lead to the particular combination of brain size, body size, and reproductive life history that we see in Homo sapiens. The challenges might be ecological (e.g. securing more food). They might be social (outwitting competitors). They might be solitary or cooperative (working with others to secure more food, or banding with others to defeat rival bands). Their conclusion: the best fit to their model comes when they assume that the evolution of big brains is 60% a result of individual ecological adaptation, 30% a result of cooperative ecological adaptation, and 10% a result of group-versus-group social adaptation. More specifically, what mostly drives the evolution of brain size in their model is that marginal returns to investing in ecological skills don’t decline as quickly for humans as for our close relatives. Spending extra years learning stuff continues to have a payoff for us, maybe because culture and language mean that there are a lot more useful tricks floating around to learn.
These results have to be considered pretty tentative at this point. Note however that they count strongly against the view that human brain evolution is mostly about being Machiavellian and outsmarting the other guys, although they do allow a modest role for inter-group competition. And they count against the view, advocated by Geoffrey Miller, that the human mind evolved as a sexual display, like the peacock’s tail. So it may be true that “sexual love … lays claim to half the powers and thoughts of the youngest portion of mankind” (Schopenhauer). But (at least according to González-Forero and Gardner), whatever the claims of love on our hearts, we owe our big brains to our work.