Normative Uncertainty without Unjustified Value Comparisons

Jennifer Rose Carr [AJP, 2020] proposes a method to maximize expected value under normative uncertainty without Intertheoretic Value Comparison (IVC). Carr argues that this method avoids IVC because it avoids theories: the agent’s credence is distributed among a normative hypotheses of a particular type, which don’t constitute theories. However, I argue that Carr’s method doesn’t avoid or help to solve what I consider as the deeper problem of IVC, which isn’t specific to comparing theories as such. This threatens the implementability of Carr’s method. Fortunately, I also show how Carr’s method can nevertheless be implemented. I identify a type of normative uncertainty where the deeper problem of IVC is not a necessary obstacle to maximizing expected value: uncertainty that stems from indecisive normative intuitions. In some of the cases that feature such uncertainty, the agent could justifiably construct each normative hypothesis by reference to the same unit of value. This (positive) part of my argument complements not only Carr’s argument, but also some moderate defenses of IVC. The combination of Carr’s paper and mine illuminates the conditions for maximizing expected value under normative uncertainty without unjustified value comparison.