The rapidly advancing domain of Explainable Artificial Intelligence (XAI) has sparked significant interests in developing techniques to make AI systems more transparent and understandable. Nevertheless, in real-world contexts, the methods of explainability and their evaluation strategies present numerous limitations.Moreover, the scope of responsible AI extends beyond just explainability. In this paper, we explore these limitations and discuss their implications in a boarder context of responsible AI when considering other important aspects, including privacy, fairness and contestability.

翻译：可解释人工智能（XAI）这一快速发展领域已引发对开发使人工智能系统更透明、更易理解技术的极大兴趣。然而，在实际应用中，可解释性方法及其评估策略仍存在诸多局限。此外，负责任人工智能的内涵远不止于可解释性。本文探讨了这些局限，并在考虑隐私、公平性和可争议性等其他重要方面时，将其置于更广泛的负责任人工智能背景下讨论其影响。