Fair and Optimal Cohort Selection for Linear Utilities

Understand

The rise of algorithmic decision-making has created an explosion of research around the fairness of those algorithms.

• While there are many compelling notions of individual fairness, beginning with the work of Dwork et al., these notions typically do not satisfy desirable composition properties.
• To this end, Dwork and Ilvento introduced the fair cohort selection problem, which captures a specific application where a single fair classifier is composed with itself to pick a group of candidates of size exactly $k$.
• In this work we introduce a specific instance of cohort selection where the goal is to choose a cohort maximizing a linear utility function.