Why Fairness Cannot Be Automated: Bridging the Gap Between EU Non-Discrimination Law and AI

This article identifies and explores a gap between commonly used statistical measures of fairness and rulings and evidentiary standards of the European Court of Justice. The authors suggest that current standards to bring discrimination claims limit the potential for a standardized system of addressing algorithmic discrimination in the EU because they are too contextual and open to interpretation. Additionally, the authors argue that law provides little guidance on addressing cases when algorithms, not humans, are the discriminators. The authors propose conditional demographic disparity as an appropriate statistical measure of fairness to harmonize legal and industry perspectives.