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Algorithm-mediated social learning

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  • UserWilliam Brady (Northwestern University)
  • ClockWednesday 25 February 2026, 15:00-16:00
  • HouseOnline.

If you have a question about this talk, please contact Yara Kyrychenko .

Social information is the currency of human culture, and it is increasingly encountered in online social networks where information flow is controlled by algorithms. In practice, this has generated a significant problem: social information encountered online is often highly unrepresentative of all the people in a given social network. Focusing on the context of politics, I argue that the problem of unrepresentativeness is best explained as an emergent phenomenon that arises when humans and social media algorithms learn from one another (‘algorithm-mediated social learning’). I will present a series of experiments in the lab and in a large field experiment that find social media algorithms exploit human social learning biases toward PRestigious, Ingroup, Moral and Emotional information, or PRIME information) in ways that distort our understanding of social norms. This work also examines consequences of algorithm-mediated social learning for intergroup relations, and test newly designed algorithms that mitigate unrepresentativeness, offering possible paths toward healthier online information environments.

This talk is part of the Social Psychology Seminar Series (SPSS) series.

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