Department of Computer Science, Cornell University, USA
Tuesday 6 June 2006, 16:00
Seminar Room B10 (Basement)
Alexandra House, 17 Queen Square, London, WC1N 3AR
Causality, Responsibility, and Blame: A Structural-Model Approach
I first review the basic definition of causality introduced by Halpern and Pearl. This definition (like most in the literature) treats causality as an all-or-nothing concept; either A is a cause of B or it is not. We show how it can be extended to take into account the degree of responsibility of A for B. For example, if someone wins an election 11--0, then each person who votes for him is less responsible for the victory than if he had won 6--5. I then define a notion of degree of blame, which takes into account an agent's epistemic state. Roughly speaking, the degree of blame of A for B is the expected degree of responsibility of A for B, taken over the epistemic state of an agent. I also briefly discuss the extent to which definitions reflect how people use notions like cause, blame, and responsibility in practice.