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Ilia Shumailov
Google DeepMind
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SCHOLARLY PAPERS
1
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Scholarly Papers (1)
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1.
Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy, Research, and Practice
Number of pages: 35
Posted: 06 Feb 2025
A. Feder Cooper
,
Christopher A. Choquette-Choo
,
Miranda Bogen
,
Matthew Jagielski
,
Katja Filippova
,
Ken Liu
,
Alexandra Chouldechova
,
Jamie Hayes
,
Yangsibo Huang
,
Niloofar Mireshghallah
, Ilia Shumailov,
Eleni Triantafillou
,
Peter Kairouz
,
Nicole Mitchell
,
Percy Liang
,
Daniel E. Ho
,
Yejin Choi
,
Sanmi Koyejo
,
Fernando Delgado
,
James Grimmelmann
,
Vitaly Shmatikov
,
Christopher De Sa
,
Solon Barocas
,
Amy Cyphert
,
Mark A. Lemley
,
Danah Boyd
,
Jennifer Wortman Vaughan
,
Miles Brundage
,
David Bau
,
Seth Neel
,
Abigail Jacobs
,
Andreas Terzis
,
Hanna Wallach
,
Nicolas Papernot
and
Katherine Lee
Microsoft Research, Google DeepMind, Independent, Google DeepMind, Google DeepMind, Stanford University, Independent, Google DeepMind, Google Research, University of Washington - Paul G. Allen School of Computer Science & Engineering, Google DeepMind, Google DeepMind, Google Research, Google Research, Stanford University - Department of Computer Science, Stanford Law School, University of Washington, Stanford University, Cornell University, Cornell Law School, Cornell University - Cornell Tech NYC, Cornell University - Department of Computer Science, Microsoft ResearchCornell University, West Virginia University - College of Law, Stanford Law School, Microsoft Research, Microsoft Research New York City, Independent, Northeastern Univeristy, University of Pennsylvania - Statistics Department, University of Michigan at Ann Arbor, Google DeepMind, Microsoft Research New York City, University of Toronto, Toronto, Canada and Cornell University - Department of Computer Science
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Abstract:
machine unlearning, privacy, copyright, safety, Generative AI
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