Reconsidering the Rule of Consideration: Probabilistic Knowledge and Legal Proof

Abstract

In this paper, I provide an argument for rejecting Sarah Moss's recent account of legal proof. Moss's account is attractive in a number of ways. It provides a new version of a knowledge-based theory of legal proof that elegantly resolves a number of puzzles about mere statistical evidence in the law. Moreover, the account promises to have attractive implications for social and moral philosophy, in particular about the impermissibility of racial profiling and other harmful kinds of statistical generalisation. In this paper, I show that Moss's account of legal proof crucially depends on a moral norm called the rule of consideration. I argue that we have a number of reasons to be sceptical of this rule. Once we reject the rule, it is not clear that Moss's account of legal proof is either plausible or attractive.

Algorithmic Decision-making, Statistical Evidence and the Rule of Law

“…Similarly, some philosophers have argued that beliefs about persons are subject to different moral norms than beliefs about non-persons, such as a special "rule of consideration" for the possibility that the person in question is an exception to a valid statistical generalization (Moss 2018: 221). However, those accounts falter in the face of ambiguity as to whether the object of a statistical generalization is a person (the driver of the blue bus) or not (the bus), and also presuppose moral principles (such as what it is required to treat someone as an individual) that are more controversial than the Powerful Intuition itself (Smartt 2022). This makes such accounts dialectically unsuited to unseat the common-sense claim that, whatever else we may want from trials, we always have reason to value accuracy in verdicts.…”