X Hacking: The Threat of Misguided AutoML

Abstract: (XAI) interpretable machine learning methods to trust in model predictions and derived insights, yet also present a perverse incentive for to manipulate XAI metrics to support pre-specified conclusions. This paper introduces the concept of X-, a of p-hacking applied to XAI metrics such as Shap values. We show how an

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