Reviews: Hunting for Discriminatory Proxies in Linear Regression Models

Summary This paper describes a framework for detecting proxy variables in a linear regression framework. It poses the problem as two optimization problems and presents (with proofs only in supplemental material) theorems that relate the solutions to the two optimization problems to cases of proxy existence in a problem. The paper also describes incorporation of an exempt variable, a proxy that is deemed acceptable for use for one reason or another. The paper leverages a prior work that defines a proxy in a classification framework as a variable that is associated with a sensitive attriute and causally infulential on the decision of the system. The paper describes how to reformulate this definition for the case of linear regression.