Social Learning Strategies for Diverse and Unequal Worlds

Paul E. Smaldino (University of California, Merced)

May 21, 2024, 11:30–12:30


Room Auditorium 4 (First floor - TSE Building)

IAST General Seminar


Research on cultural evolution and social learning have identified optimal strategies for learning from others under a variety of conditions prevalent in our deep cultural past, including those based on individual markers of success and those based on aggregated information from many sources (e.g., conformity). However, models have tended to assume that within a given environment, the adaptive value of behavioral strategies did not vary between individuals. This assumption was perhaps valid in small egalitarian societies, but does not always hold within the diverse, unequal societies prevalent today. I will present several new models on the evolution of social learning focusing on (1) sources of uncertainty, (2) identity diversity, and (3) on inequality and risk. I will show that optimal social learning strategies can vary dramatically in such worlds. This work provides explanations and new predictions related to polarization, conformity, and the persistence of poverty traps.