Eyewitness testimony is both an important and a notoriously unreliable type of criminal evidence. How should investigators, lawyers and decision-makers evaluate eyewitness reliability? In this article, I argue that Testimonial Inference to the Best Explanation is a promising, but underdeveloped prescriptive account of eyewitness evaluation. On this account, we assess the reliability of eyewitnesses by comparing different explanations of how their testimony came about. This account is compatible with, and complementary to both the Bayesian framework of rational eyewitness evaluation and (...) with prescriptive methods for eyewitness assessment developed by psychologists. Compared to these frameworks, the distinctive value of thinking in terms of competing explanations is that it helps us select, interpret and draw conclusions from the available evidence about the witness’s reliability. (shrink)

For any normative domain, we can theorize about what is good in that domain. Such theories include utilitarianism, a view about what is good morally. But there are many domains other than the moral; these include the prudential, the aesthetic, and the intellectual or epistemic. In this last domain, it is good to be knowledgeable and bad to ignore evidence, quite apart from the morality, prudence, and aesthetics of these things. This dissertation builds a theory that stands to the epistemic (...) domain as utilitarianism stands to the moral domain. It builds an epistemic value theory. (shrink)

The doctrinal paradox shows that aggregating individual judgments by taking a majority vote does not always yield a consistent set of collective judgments. Philip Pettit, Luc Bovens, and Wlodek Rabinowicz have recently argued for the epistemic superiority of an aggregation procedure that always yields a consistent set of judgments. This paper identifies several additional epistemic advantages of their consistency maintaining procedure. However, this paper also shows that there are some circumstances where the majority vote procedure is epistemically superior. The epistemic (...) value of maintaining consistency does not always outweigh the epistemic value of making true judgments. (shrink)

Several different Bayesian models of epistemic utilities (see, e. g., [37], [24], [40], [46]) have been used to explain why it is rational for scientists to perform experiments. In this paper, I argue that a model-suggested independently by Patrick Maher [40] and Graham Oddie [46]-that assigns epistemic utility to degrees of belief in hypotheses provides the most comprehensive explanation. This is because this proper scoring rule (PSR) model captures a wider range of scientifically acceptable attitudes toward epistemic risk than the (...) other Bayesian models that have been proposed. I also argue, however, that even the PSR model places unreasonably tight restrictions on a scientist's attitude toward epistemic risk. As a result, such Bayesian models of epistemic utilities fail as normative accounts-not just as descriptive accounts (see, e. g., [31], [14])-of scientific inquiry. (shrink)