Michael Kearns: Algorithmic Fairness, Bias, Privacy, and Ethics in Machine Learning

Lex Fridman Podcast

This podcast episode touches upon the intersection of literature, philosophy, and algorithmic approaches to fairness and privacy. It explores the ethical implications of technology and the importance of considering humanistic perspectives in the development of algorithms, highlighting the complexities of measuring ethics and biases in algorithms. The conversation also delves into the challenges of balancing fairness and error, the impact of social media platforms, and the evolution of differential privacy for data protection.

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