There is an urgent need in many application areas for eXplainable ArtificiaI Intelligence (XAI) approaches to boost people’s confidence and trust in Artificial Intelligence methods. Current works concentrate on specific aspects of XAI and avoid a comprehensive perspective. This study undertakes a systematic survey of importance, approaches, methods, and application domains to address this gap and provide a comprehensive understanding of the XAI domain. Applying the Systematic Literature Review approach has resulted in finding and discussing 155 papers, allowing a wide discussion on the strengths, limitations, and challenges of XAI methods and future research directions.

中文翻译：

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可解释的人工智能：重要性、使用域、阶段、输出形状和挑战


许多应用领域迫切需要 eXplainable 人工智能 （XAI） 方法，以增强人们对人工智能方法的信心和信任。目前的作品集中在 XAI 的特定方面，而避免了全面的视角。本研究对重要性、方法、方法和应用领域进行了系统调查，以解决这一差距并提供对 XAI 领域的全面理解。应用系统文献综述方法，找到并讨论了 155 篇论文，从而可以就 XAI 方法的优势、局限性和挑战以及未来的研究方向进行广泛讨论。