FROMANNUAL REVIEWS

CogSci 2025

•

August 02, 2025

•

San Francisco, United States

keywords:

social cognition

computational modeling

decision making

learning

psychology

Research on individual decision-making often finds a positivity bias, where people weight positive outcomes more strongly than negative ones during learning. This can be beneficial when rewards are rare, by amplifying relative value differences. Yet, we know very little about learning rate biases in social settings, where a key advantage is being able to vicariously learn from the negative experiences of others. This would imply a benefit for focusing on negative outcomes when learning socially, but is at odds with the seemingly inflexible positivity bias found in individual learning. Here, we examine learning rate biases across both individual and social settings, testing for adaptivity versus generally stable biases. Overall, participants appear more flexible in their learning rate biases when learning socially than when learning individually. This implies that human social learning may be more flexible and closer to normatively optimal behavior than individual learning.

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