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Responsibly Improving AI with Privacy-Sensitive Data: Principles, Theory, and Practice | Richard M. Karp Distinguished Lecture

Tuesday 15:30 Los Angeles (GMT-8)

Recording available

Berkeley, United States

Recording

1 h 10 min

Abstract

Brendan McMahan examines how AI systems can learn from high-quality information that is distributed and privacy-sensitive. He introduces principles for precise discussions of privacy and AI, then connects them to the theory and practical methods needed in real applications, including work on decentralised and privacy-preserving learning.

Topics

privacy-preserving learninghigh-quality information

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