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Task-specific experimental design for treatment effect estimation
Understanding causality should be a core requirement of any attempt to build real impact through AI.
Explainability for fair machine learning
Moreover, motivated by the linearity of Shapley explainability, we propose a meta algorithm for applying existing training-time fairness interventions, wherein one trains a perturbation to the original model, rather than a new model entirely.
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