The discovery of discrimination

Abstract

Discrimination discovery from data consists in the extraction of discriminatory situations and practices hidden in a large amount of historical decision records. We discuss the challenging problems in discrimination discovery, and present, in a unified form, a framework based on classification rules extraction and filtering on the basis of legally-grounded interestingness measures. The framework is implemented in the publicly available DCUBE tool. As a running example, we use a public dataset on credit scoring.