Tanner Lecture: AI and Human Values with Seth Lazar
The 2022-2023 Tanner Lecture will be a special event entitled the "Tanner Lectures on AI and Human Values." The lectures will be given by Seth Lazar.
Lazar is professor of philosophy at the Australian National University, an Australian Research Council (ARC) Future fellow, and a Distinguished Research Fellow of the University of Oxford Institute for Ethics in AI.
At ANU, he was founding lead of the Humanising Machine Intelligence project, and recently launched the Machine Intelligence and Normative Theory (MINT) Lab, where he directs research projects on the moral and political philosophy of AI, funded by the ARC, the Templeton World Charity Foundation, and Insurance Australia Group. He is general co-chair for the ACM Fairness, Accountability, and Transparency conference 2022, was program co-chair for the ACM/AAAI AI, Ethics and Society conference in 2021, and is one of the authors of a study by the U.S. National Academies of Science, Engineering and Medicine, reporting to Congress on the ethics and governance of responsible computing research.
Lazar has given the Mala and Solomon Kamm Lecture in Ethics at Harvard University, and has published articles and books with the world’s leading journals and presses on the ethics of war, the ethics of risk, and the moral and political philosophy of data and AI.
The title for Professor Lazar's talk is "Algorithmic Governance and Political Philosophy." Lecture 1, entitled "Governing the Algorithmic City," will take place on Tuesday, Jan. 24, 2023. Lecture 2, entitled "Communicative Justice and the Political Philosophy of Attention," will take place on Wednesday, Jan. 25, 2023. A discussion seminar that focuses on both lectures takes place on Thursday, Jan. 26, 2023.
This Tanner Lecture is hosted by the McCoy Family Center for Ethics in Society and co-sponsored by the Office of the President and the Stanford Institute for Human-Centered Artificial Intelligence.
More details about how to join will be posted to this HAI events page preceding the event.
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