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A Harm-Reduction Framework for Algorithmic Fairness
Published
In this article, we recognize the profound effects that algorithmic decision-making can have on people's lives and propose a harm-reduction framework for algorithmic fairness. We argue that any evaluation of algorithmic fairness must consider a counterfactual analysis of the effects that algorithmic design, implementation, and use have on the well-being of individuals.