The evolution of similarity-biased social learning

Humans often learn preferentially from ingroup members who share a social identity affiliation, while ignoring or rejecting information when it comes from someone perceived to be from an outgroup. This sort of bias has well-known negative consequences - exacerbating cultural divides, polarization, and conflict - while reducing the information available to learners. Why does it persist? Using evolutionary simulations, we demonstrate that similarity-biased social learning (also called parochial social learning) is adaptive when (1) individual learning is error-prone and (2) sufficient diversity inhibits the efficacy of social learning that ignores identity signals, as long as (3) those signals are sufficiently reliable indicators of adaptive behaviour. We further show that our results are robust to considerations of other social learning strategies, focusing on conformist and pay-off-biased transmission. We conclude by discussing the consequences of our analyses for understanding diversity in the modern world. Why do we often prefer to learn from people who are similar to us and ignore people we view as different? We present a cultural evolutionary model that demonstrates how, in diverse populations, parochial social learning can be adaptive whereas other social learning strategies - like learning from successful individuals or averaging over many observations - can fail. We discuss implications for stereotypes and polarization.