Philosophy Department Colloquium
Bayesianism and the Evidence Problem
Lisa Cassell
University of Massachusetts/Amherst
4-6:00pm Wednesday, 15 February 2017, 456 Performing Arts & Humanities
Bayesianism is a theory that gives us norms for how the degrees of belief we have in certain propositions — our “credences” — ought to hang together. For instance, it tells me that if my credence that I will play baseball tomorrow is .3 and my credence that I will play basketball tomorrow is .4, then, if I believe that I will only play one or the other, my credence that I will either play baseball tomorrow or basketball tomorrow is .7. One of Bayesianism’s most attractive features is its updating norm, which gives us a simple and powerful way of revising our beliefs in the light of new evidence. However, Bayesians have an “Evidence Problem”: while their updating norm tells us what to do once we get evidence, it doesn’t tell us what it means to actually have evidence. In this talk, I consider two arguments — one in support of Bayesian’s updating norm and one against it — and show that both of these arguments fail. I go on to consider what these failures teach us about the Evidence Problem. I conclude by considering some different ways of resolving this problem.
The post talk: Bayesianism and the Evidence Problem, 4pm 2/15 appeared first on Department of Computer Science and Electrical Engineering.