Abstract
In this study, we propose a bias-mitigation algorithm, dubbed ProxyMute, that uses an explainability method to detect proxy features of a given sensitive attribute (e.g., gender) and reduces their effects on decisions by disabling them during prediction time. We evaluate our method for a job recruitment use-case, on two different
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