This talk will provide an overview of work that I have done with Hana Chockler, Orna Kupferman, and Judea Pearl [1, 2, 10, 9] on defining notions such as causality, explanation, responsibility, and blame. I first review the Halpern-Pearl definition of causality-what it means that A is a cause of B-and show how it handles well some standard problems of causality. This definition of causality (like most in the literature) views causality as an all-or-nothing concept. Either A is a cause of B or it is not. I 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, each person is less responsible for his victory than if he had won 6-5. Finally, I show how this notion of degree of responsibility can be used to provide insight into model checking notions such as coverage.