What's Sex Got To Do With Fair Machine Learning?

Understand

Debate about fairness in machine learning has largely centered around competing definitions of what fairness or nondiscrimination between groups requires.

• However, little attention has been paid to what precisely a group is.
• Many recent approaches to "fairness" require one to specify a causal model of the data generating process.
• These exercises make an implicit ontological assumption that a racial or sex group is simply a collection of individuals who share a given trait.