Reputation for Competence: Social Learning Mechanisms Create an Incentive to Help Others

Abstract

Research on social learning has identified mechanisms that learners use to decide from whom to learn. Several of these mechanisms indicate that learners prefer to learn from more competent people over less competent people. This requires learners to measure the competence of other people. We use this article to analyze the incentives that this measure of competence creates. Learners measure the competence of models, people they would consider learning from, and share these judgments with other learners. This gives each model a reputation for competence within a community. Each model has a biological incentive to increase the magnitude of that reputation; at the very least, increasing the magnitude should make the model more attractive to potential mates. In this article, we present logic that indicates that one way for the model to increase the magnitude of that reputation is for the model to help people who think the model is competent. This reveals a novel evolutionary incentive for humans to help other humans.