The European Union has proposed the Artificial Intelligence Act intending to regulate AI systems, especially those used in high-risk, safety-critical applications such as healthcare. Among the Act's articles are detailed requirements for transparency and explainability. The field of explainable AI (XAI) offers technologies that could address many of these requirements. However, there are significant differences between the solutions offered by XAI and the requirements of the AI Act, for instance, the lack of an explicit definition of transparency. We argue that collaboration is essential between lawyers and XAI researchers to address these differences. To establish common ground, we give an overview of XAI and its legal relevance followed by a reading of the transparency and explainability requirements of the AI Act and the related General Data Protection Regulation (GDPR). We then discuss four main topics where the differences could induce issues. Specifically, the legal status of XAI, the lack of a definition of transparency, issues around conformity assessments, and the use of XAI for dataset-related transparency. We hope that increased clarity will promote interdisciplinary research between the law and XAI and support the creation of a sustainable regulation that fosters responsible innovation.

翻译：欧盟已提出《人工智能法案》，旨在监管人工智能系统，尤其是用于医疗等高风险、安全关键领域的系统。该法案的条款中包含了关于透明度和可解释性的详细要求。可解释人工智能（XAI）领域提供的技术能够满足其中许多要求。然而，XAI提供的解决方案与《人工智能法案》的要求之间存在显著差异，例如缺乏对透明度的明确定义。我们认为，律师与XAI研究人员之间的合作对于弥合这些差异至关重要。为建立共识，我们概述了XAI及其法律意义，随后解读了《人工智能法案》以及相关《通用数据保护条例》（GDPR）中关于透明度和可解释性的要求。接着，我们讨论了四个可能因差异引发问题的主要议题，具体包括：XAI的法律地位、透明度定义的缺失、符合性评估问题，以及XAI在数据集相关透明度中的使用。我们希望，更清晰的阐述能促进法律与XAI之间的跨学科研究，并助力制定可持续的法规，以推动负责任的创新。