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TILOS-HDSI Seminar with Adam Oberman (McGill): AI safety theory: the missing middle ground

November 12 @ 11:00 - 12:00

Adam Oberman, McGill University

Abstract: Over the past few years, the capabilities of generative artificial intelligence (AI) systems have advanced rapidly. Along with the benefits of AI, there is also a risk of harm. In order to benefit from AI while mitigating the risks, we need a grounded theoretical framework.

The current AI safety theory, which predates generative AI, is insufficient. Most theoretical AI safety results tend to reason absolutely: a system is a system is “aligned” or “mis-aligned”, “honest” or “dishonest”. But in practice safety is probabilistic, not absolute. The missing middle ground is a quantitative or relative theory of safety — a way to reason formally about degrees of safety. Such a theory is required for defining safety and harms, and is essential for technical solutions as well as for making good policy decisions.

In this talk I will:

  1. Review current AI risks (from misuse, from lack of reliability, and systemic risks to the economy) as well as important future risks (lack of control).
  2. Review theoretical predictions of bad AI behavior and discuss experiments which demonstrate that they can occur in current LLMs.
  3. Explain why technical and theoretical safety solutions are valuable, even by contributors outside of the major labs.
  4. Discuss some gaps in the theory and present some open problems which could address the gaps.

Adam Oberman is a Full Professor of Mathematics and Statistics at McGill University, a Canada CIFAR AI Chair, and an Associate Member of Mila. He is a research collaborator at LawZero, Yoshua Bengio’s AI Safety Institute. He has been researching AI safety since 2024. His research spans generative models, reinforcement learning, optimization, calibration, and robustness. Earlier in his career, he made significant contributions to optimal transport and nonlinear partial differential equations. He earned degrees from the University of Toronto and the University of Chicago, and previously held faculty and postdoctoral positions at Simon Fraser University and the University of Texas at Austin.

Zoom: https://bit.ly/TILOS-Seminars

Details

Date:
November 12
Time:
11:00 - 12:00
Event Category:

Venue

HDSI 123 and Virtual
3234 Matthews Ln
La Jolla, CA 92093 United States
View Venue Website

Organizers

TILOS
Halicioglu Data Science Institute