Time: Friday, Sept. 11 12:30 PM - 1:30 PM      Location: MKB 622

After Algorithmic Fairness: The Myth of Neutrality and Power of Repair

Abstract:

Abstract: The field of algorithmic ethics is substantial and growing, working to mitigate harms and realize social good. The fairness paradigm dominates this field across AI, machine learning, and other data-driven domains. Algorithmic fairness aims to a) undercut human biases by replacing subjective assessments with 'objective' computation and b) eliminate biases in data and data-derived outputs. Despite significant investment from academia, industry, and government, algorithmic fairness has failed to live up to its promise. Algorithmic harms propagate and persist while social inequities amplify and embed. This talk presents algorithmic reparation as an alternate proposal. Drawing on a paper, collaborative workshop, special issue, and especially, aforthcoming book, the talk delineates a reparative paradigm for algorithmic futures. This begins with a critique of fairness as a viable value standard, making the case for a shift toward redress. This shift is supported by a tripartite framework of algorithmic reparation and its implementation across diverse uses-cases, along with careful consideration of the obstacles and inroads to reparative praxis.

Bio:

Jenny L. Davis is the Gertrude Conaway Vanderbilt Chair and Professor of Sociology at Vanderbilt University, Honorary Professor of Sociology at The Australian National University, and Non-Resident Fellow at the Center for Democracy and Technology.