Interview-Based AI Agents Predict Individual Survey Responses More Accurately
Stanford professor Michael Bernstein argues that AI agents built from detailed accounts of real people could help decision-makers test how people might respond to products, policies, or organizational changes before acting. But convincing behavior is not the same as accurate prediction: Bernstein says simulations are more useful for surfacing plausible scenarios and guiding further tests than for settling consequential questions on their own. Their reliability depends on the quality of the information behind the agents and on how well the simulated environment reflects real conditions.
Stanford Online·Sep 29, 2026·16 min read