Explainable AI for the EU Right to Explanation: A Systematic Review of the Law-XAI Translation Gap
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Abstract (arXiv)
When algorithms make or influence consequential decisions---about loan eligibility, hiring, or healthcare---EU law grants affected individuals a Right to Explanation. Yet whether (and how) Explainable AI (XAI) can satisfy this right in practice remains poorly understood, with direct implications for individuals' ability to contest automated decisions that affect their lives. This paper presents a systematic literature review of XAI in the context of the EU Right to Explanation, with particular focus on Art. 15(1)(h) GDPR, Art. 86 AI Act (AIA), and related instruments. We consider papers published from 2024 onwards, as the final version of the AIA was published in July 2024---with Art. 86 being added late. From 2643 initial records identified by a deliberately broad search, we review 57 full texts, of which only 19 papers demonstrate substantive integration of both legal and technical perspectives, showing gaps in the interdisciplinary synthesis of the current regulatory framework. We document three problematic patterns across the corpus: Most misidentify the GDPR legal basis; few engage with the CJEU's Dun & Bradstreet judgment (likely due to publication timing); and the distinction between explanation form (governed by addressee) and content (governed by legal purpose) is often conflated. We conceptualize this as the Addressee/Purpose Framework, propose a four-phase blueprint for operationalization, and identify six concrete open research questions. Without further progress, the Right to Explanation risks remaining a formal obligation without a technically realizable path to compliance.
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10 of 39 references.
References · 10
- 2017Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPRcited by 1,089
- 2018A Survey Of Methods For Explaining Black Box Modelscited by 973
- 2022From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AIcited by 302
- 2023Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directionscited by 125
- 2019Sanity Checks for Saliency Metricscited by 119
- 2020Open Source Software for Efficient and Transparent Reviewscited by 35
- 2022What Makes a Good Explanation?: A Harmonized View of Properties of Explanationscited by 22
- 2024How should AI decisions be explained? Requirements for Explanations from the Perspective of European Lawcited by 11
- 2025Unlocking the Black Box: Analysing the EU Artificial Intelligence Act's Framework for Explainability in AIcited by 11
- 2025Efficiently Transforming Neural Networks into Decision Trees: A Path to Ground Truth Explanations with RENTTcited by 1
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