Today's article comes from the Cambridge Forum on AI: Law and Governance. The authors are Basu et al., from the University of Lille, in France. In this paper, they're proposing a bias-reduction framework called "Fair Game". It wraps a model inside a loop, between an auditor and a debiasing algorithm. And the whole interaction gets structured as a reinforcement learning problem.
DOI: 10.1017/cfl.2025.8
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