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Taking the Whys Seriously: Limitations of Counterfactual Explanations in Justification and Recourse

arXiv · AI, language, vision and robotics · article · Aug 31, 2026 · UTC

Counterfactual explanations (CEs) are widely used in explainable artificial intelligence (AI) to show how a model's outputs would change if the input features were manipulated. This technique is used for a range of tasks such as debugging models, explaining predictions, justifying decisions, and providing algorithmic recourse. In this paper, we explore the normative legitimacy of employing counterfactuals in real-life model deployment settings. We discuss the different stakes involved in these different purposes for which CEs are commonly employed, and find stricter requirements for justificat

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