Publications

Journal Article

Many philosophers have argued that statistical evidence regarding group characteristics (particularly stereotypical ones) can create normative conflicts between the requirements of epistemic rationality and our moral obligations to each other.

In a recent paper, Johnson-King and Babic argue that such conflicts can usually be avoided: what ordinary morality requires, they argue, epistemic rationality permits.

In this paper, the authors show that as data gets large, Johnson-King and Babic’s approach becomes less plausible. More constructively, the authors build on their project and develop a generalized model of reasoning about stereotypes under which one can indeed avoid normative conflicts, even in a big data world, when data contain some noise.

In doing so, the authors also articulate a general approach to rational belief updating for noisy data.