Guest Lecture Series by Professor Joseph Halpern from Cornell University, USA

TAU Institute of Advanced Studies invites you to a lecture series by Lowy Distinguished guest professor Joseph Halpern, Joseph C. Ford Chair of Engineering, Computer Science Department at Cornell University (New York, USA).

"My research focuses on the interface between game and decision theory and computer science, on reasoning about knowledge and uncertainty, and on causality. I've also done work and continue to think actively about security, (fault tolerant) distributed computing, and modal logic." —Professor Joseph Halpern

The lectures will be part of the Computer Sciences Colloquium and Machine Learning Seminar.

Three lectures will cover certain aspects of reasoning about uncertainty and decision-making.

Lecture 3: Using Causal Models to Define Explanation

The lecture will be part of the Machine Learning Seminar

Professor Halpern will consider a definition of (causal) explanation that Judea Pearl and he gave, based on the notion of actual cause. Essentially, an explanation is a fact that is not known for certain but, if found to be true, would constitute an actual cause of the fact to be explained, regardless of the agent's initial uncertainty, and in addition, is sufficient for the fact to be explained to be true.

Professor Halpern will show that the definition handles well a number of problematic examples from the literature, and can be usefully applied to understand what various approaches to "explainable AI" are actually doing.

WHEN: February 14, 2024, 13:10 AM

WHERE: Checkpoint Building, Seminar Room 420

Light refreshments will be served before the lectures.

No prior registration required.