Michael Kearns: Algorithmic Fairness, Privacy & Ethics | Lex Fridman Podcast #50

University of Pennsylvania professor Michael Kearns explores the ethical boundaries of algorithmic systems in his book *An Ethical Algorithm*, highlighting the mathematical impossibility of simultaneously satisfying all fairness metrics while advocating for Pareto curves to let policymakers visualize accuracy versus bias trade-offs. Kearns distinguishes between the rigorous mathematical guarantees of differential privacy and the flawed nature of traditional anonymization, arguing that privacy must be preserved through calibrated noise rather than data masking. Furthermore, he applies algorithmic game theory to explain how optimization for engagement on social platforms inadvertently drives societal polarization, urging a shift where human values are explicitly injected into objective functions rather than left to autonomous systems.