On the Epistemic Significance of Noise

Abstract The large literature on the ethics of statistical evidence and its use in courtrooms is premised on the assumption that statistical evidence can be highly probabilifying (i.e. that it can support a very high credence). When statistical evidence seems to render a morally problematic proposition highly probable, scholars then divide over how they respond to the problem: some attempt to identify a different epistemic problem with the inference, while others grant the inference’s epistemic legitimacy but object to the conclusion on a moral or political basis. In this chapter, the authors argue that, in fact, it is very difficult to construct realistic cases in which statistical evidence is highly probabilifying. The authors explain how noisy data resulting from misclassification—a common feature of most realistic cases—drastically reduces statistical evidence’s probative value. As a result, it is not necessary to advert to additional theoretical bells and whistles to explain why one ought not form a high credence based on statistical evidence in most realistic cases.