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AI Ethics#Generative AI📝 BlogAnalyzed: Dec 29, 2025 07:28

Responsible AI in the Generative Era with Michael Kearns - #662

Published:Dec 22, 2023 01:37
1 min read
Practical AI

Analysis

This podcast episode from Practical AI features Michael Kearns, a professor at the University of Pennsylvania and an Amazon scholar, discussing responsible AI in the generative AI era. The conversation covers various challenges and solutions, including service card metrics, privacy, hallucinations, RLHF, and LLM evaluation benchmarks. The episode also highlights Clean Rooms ML, a secure environment utilizing differential privacy for secure data handling. The discussion bridges Kearns' experience at AWS and his academic work, offering insights into practical applications and theoretical considerations of responsible AI development.
Reference

The episode covers a diverse range of topics under this banner, including service card metrics, privacy, hallucinations, RLHF, and LLM evaluation benchmarks.

Research#llm📝 BlogAnalyzed: Dec 29, 2025 07:38

Service Cards and ML Governance with Michael Kearns - #610

Published:Jan 2, 2023 17:05
1 min read
Practical AI

Analysis

This article summarizes a podcast episode from Practical AI featuring Michael Kearns, a professor and Amazon Scholar. The discussion centers on responsible AI, ML governance, and the announcement of service cards. The episode explores service cards as a holistic approach to model documentation, contrasting them with individual model cards. It delves into the information included and excluded from these cards, and touches upon the ongoing debate of algorithmic bias versus dataset bias, particularly in the context of large language models. The episode aims to provide insights into fairness research in AI.
Reference

The article doesn't contain a direct quote.

Research#AI Ethics📝 BlogAnalyzed: Dec 29, 2025 17:44

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

Published:Nov 19, 2019 17:52
1 min read
Lex Fridman Podcast

Analysis

This article summarizes a podcast episode featuring Michael Kearns, a professor at the University of Pennsylvania, discussing algorithmic fairness, bias, privacy, and ethics in machine learning. The conversation, part of the Artificial Intelligence podcast, delves into Kearns's work, including his book "Ethical Algorithm." The episode covers various aspects of ethical considerations in AI, such as fairness trade-offs and the role of social networks like Facebook. The article also mentions other fields Kearns is involved in, like learning theory, game theory, and computational social science, highlighting the breadth of his expertise. The podcast provides timestamps for different discussion points.
Reference

Michael Kearns is a professor at University of Pennsylvania and a co-author of the new book Ethical Algorithm that is the focus of much of our conversation, including algorithmic fairness, bias, privacy, and ethics in general.