Clayton M Littlejohn

This is part of an authors meets critics session on Daniel Star's wonderful book, Knowing Better. I discuss a potential problem with Kearns and Star's Reasons as Evidence thesis. The issue has to do with the difficulties we face is we treat normative reasons as evidence and impose no possession conditions on evidence. On such a view, it's hard to see how practical reasoning could be a non-monotonic process. One way out of the difficulty would be to allow for (potent) unpossessed reasons but insist that all evidence is possessed evidence. This option, I argue, isn't open to proponents of the Reasons as Evidence thesis. Instead, it seems that they'll have to say that all normative reasons are identified with pieces of possessed evidence. This requires the proponents of the Reasons as Evidence thesis to impose epistemic constraints on norms that some of us find objectionable.

Could it be right to convict and punish defendants using only statistical evidence? In this paper, I argue that it is not and explain why it would be wrong. This is difficult to do because there is a powerful argument for thinking that we should convict and punish defendants using statistical evidence. It looks as if the relevant cases are cases of decision under risk and it seems we know what we should do in such cases (i.e., maximize expected value). Given some standard assumptions about the values at stake, the case for convicting and punishing using statistical evidence seems solid. In trying to show where this argument goes wrong, I shall argue (against Lockeans, reliabilists, and others) that beliefs supported only by statistical evidence are epistemically defective and (against Enoch, Fisher, and Spectre) that these epistemic considerations should matter to the law. To solve the puzzle about the role of statistical evidence in the law, we need to revise some commonly held assumptions about epistemic value and defend the relevance of epistemology to this practical question.