Injustice of Fairness

A substantial and growing field, algorithmic ethics aims to mitigate harms and realize social good. The fairness paradigm dominates this field across AI, machine learning, and other data-driven domains. But so far, efforts toward fairness have been unsuccessful, yielding algorithmic harms that propagate and persist. Jenny L. Davis and Apryl A. Williams explain why algorithmic fairness perpetually fails and shift the foundation of algorithmic ethics to displace fairness in favor of an "algorithmic reparation" centered around repair and redress.  The stakes are high because algorithms are everywhere—from law to love, health care to housing, education to media, and beyond. More than just lines of code or mathematical operations, algorithms carry history, configure the present, and actively shape the future. Set against a backdrop of societal instability and technological transformation, The Injustice of Fairness offers a careful critique, an original framework, and a blueprint for social change with algorithms as entry points and levers.