Responsibly Improving AI with Privacy-Sensitive Data: Principles, Theory, and Practice

Large language models have revolutionized the field of machine learning, but a core tenet remains: AI systems need to be built and tuned using high-quality data from the right domain. As these systems increasingly touch our daily lives, the relevant data is frequently distributed and privacy sensitive. In this Richard M. Karp Distinguished Lecture, Brendan McMahan will present a framework of principles that helps bring precision to discussions of privacy and AI, and then dives into the theory and practice required to apply them in real scenarios. This lecture will explore how we can unlock the power of AI while safeguarding user trust.

Speaker: Brendan McMahan, Google