Machine Learning and Social Norms - Balancing Fairness and Accuracy

Explore the intersection of machine learning and social norms in this thought-provoking Santa Fe Institute Community Lecture by Michael Kearns. Delve into the increasing role of algorithms in making consequential decisions about individuals' lives across various domains, including advertising, credit, employment, education, and criminal sentencing. Examine the growing concerns over potential erosions of privacy, fairness, transparency, and accountability in algorithmic decision-making. Learn about recent research in machine learning that aims to quantify the extent to which social norms can be embedded in algorithms and the resulting tradeoffs with predictive accuracy and other utility measures. Gain insights into what it means for machine learning to be "fair" and the challenges associated with implementing ethical considerations in algorithmic systems. Benefit from the expertise of Michael Kearns, a distinguished professor in Computer and Information Science at the University of Pennsylvania, as he shares his knowledge on this critical topic at the intersection of technology and society.