Machiavellian strategist or cultural learner? Mentalizing and learning over development in a resource-sharing game

What Makes Us Smart?

How did humans become clever enough to live in nearly every major ecosystem on earth, create vaccines against deadly plagues, explore the oceans depths, and routinely traverse the globe at 30,000 feet in aluminum tubes while nibbling on roasted almonds? Drawing on recent developments in our understanding of human evolution, we consider what makes us distinctively smarter than other animals. Contrary to conventional wisdom, human brilliance emerges not from our innate brainpower or raw computational capacities, but from the sharing of information in communities and networks over generations. We review how larger, more diverse, and more optimally interconnected networks of minds give rise to faster innovation and how the cognitive products of this cumulative cultural evolutionary process feedback to make us individually "smarter"-in the sense of being better at meeting the challenges and problems posed by our societies and socioecologies. Here, we consider not only how cultural evolution supplies us with "thinking tools" (like counting systems and fractions) but also how it has shaped our ontologies (e.g., do germs and witches exist?) and epistemologies, including our notions of what constitutes a "good reason" or "good evidence" (e.g., are dreams a source of evidence?). Building on this, we consider how cultural evolution has organized and distributed cultural knowledge and cognitive tasks among subpopulations, effectively shifting both thinking and production to the level of the community, population, or network, resulting in collective information processing and group decisions. Cultural evolution can turn mindless mobs into wise crowds by facilitating and constraining cognition through a wide variety of epistemic institutions-political, legal, and scientific. These institutions process information and aid better decision-making by suppressing or encouraging the use of different cultural epistemologies and ontologies.

The Evolution of Cognitive Biases in Human Learning

Cognitive biases like underinference, the hard-easy effect, and recurrently non-monotonic confidence are evolutionarily puzzling when viewed as persistent flaws in how people learn from environmental feedback. To explain these empirically robust cognitive biases from an evolutionary perspective, we propose a model of ancestral human learning based on the cultural-evolutionary-theoretic hypothesis that the primary selection pressure acting on ancestral human cognition pertained not to learning individually from environmental feedback, but to socially learning task-specific knowledge. In our model-which is inspired by classical Bayesian models-an ancestral human learner (the student) attempts to learn task-specific knowledge from a role model, with the option of switching between different tasks and role models. Suppose that the student's method of learning from their role model is a priori uncertain-in that it can either be successful imitation learning or de facto innovation learning-and the ecological fitness costs of meaningfully retaining environmental feedback are high. Then, the student's fitness-maximizing strategy does not retain their environmental feedback and-depending on the choice of model parameters-can be characterized by all of the aforementioned cognitive biases. Specifically, in order for the evolutionarily optimal estimate of confidence in this learning environment to be recurrently non-monotonic, it is necessary (as long as the environment's marginal payoff function satisfies a plausible quantitative condition) that a positive proportion of ancestral humans' attempted imitation learning was unknowingly implemented as de facto innovation learning. Moreover, an ecologically rational strategy of selective social learning can plausibly cause the evolutionarily optimal estimate of confidence to be recurrently non-monotonic in the empirically documented way: general increase with an intermediate period of decrease.