James M. Joyce (Professor of Philosophy and of Statistics, University of Michigan). Professor Joyce was awarded his PhD. by the University of Michigan in 1991. As well as imprecise probabilities, his research interests include rational choice theory, causal reasoning, Bayesian approaches to statistics and inductive inference. His book "Foundations of Causal Decision Theory" (1999, Cambridge University Press) is considered the standard reference on causal decision theory. For more information, visit his website.
Imprecise Priors as Expressions of Epistemic Value
As is well known, imprecise prior probabilities can help us model beliefs in contexts where evidence is sparse, equivocal or vague. It is less well-known that they can also provide a useful way of representing certain kinds of indecision or uncertainty about epistemic values and inductive policies. If we use the apparatus of proper scoring rules to model a believer's epistemic values, then we can see her 'choice' of a prior as, partly, an articulation of her values. In contexts where epistemic values and inductive policies are less than fully definite, or where there is unresolved conflict among values, the imprecise prior will reflect this indefiniteness in theoretically interesting ways.