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Watch a 35-minute Simons Institute symposium talk where UC Berkeley researcher Nika Haghtalab explores the design principles behind truthful calibration measures in forecasting systems. Delve into the challenges and solutions for creating reliable calibration mechanisms that encourage honest predictions while preventing manipulation. Learn about the intersection of machine learning, game theory, and forecasting as part of the joint IFML/MPG Symposium series, gaining insights into how to evaluate and ensure the accuracy of predictive models.
