Michael Kearns

Michael Kearns, a professor at the University of Pennsylvania and co-author of 'Ethical Algorithms,' dives into the fascinating world of algorithmic fairness and bias. He discusses the interplay between ethics and technology, and how social norms influence perceptions of fairness. Kearns explores the ethical dilemmas of engaging users versus ensuring fairness in algorithms, the role of differential privacy in safeguarding data, and the dynamic relationship between game theory and machine learning. A thought-provoking conversation on balancing human values with technological advancement!

Michael Kearns, a professor at the University of Pennsylvania and Amazon scholar, dives into the new challenges of responsible AI in the generative era. He discusses the evolution of service card metrics and their limitations in evaluating AI performance. Kearns also tackles the complexities of evaluating large language models and introduces the concept of clean rooms in machine learning, emphasizing privacy through differential techniques. With insights from his work at AWS, he advocates for collaboration between AI developers and stakeholders to enhance ethical practices.

In a fascinating discussion, Michael Kearns, a UPenn professor and Amazon Scholar, delves into the vital topics of AI governance and fairness. He describes the innovative service cards introduced at Amazon, emphasizing their holistic approach compared to traditional model cards. Kearns also tackles the ongoing debate surrounding algorithmic versus dataset bias, reflecting on current challenges in fairness within large language models. His insights shed light on the importance of responsibly addressing these issues in AI development.