Understanding black box models has become paramount as systems based on opaque Artificial Intelligence (AI) continue to flourish in diverse real-world applications. In response, Explainable AI (XAI) has emerged as a field of research with practical and ethical benefits across various domains. This paper highlights the advancements in XAI and its application in real-world scenarios and addresses the ongoing challenges within XAI, emphasizing the need for broader perspectives and collaborative efforts. We bring together experts from diverse fields to identify open problems, striving to synchronize research agendas and accelerate XAI in practical applications. By fostering collaborative discussion and interdisciplinary cooperation, we aim to propel XAI forward, contributing to its continued success. We aim to develop a comprehensive proposal for advancing XAI. To achieve this goal, we present a manifesto of 28 open problems categorized into nine categories. These challenges encapsulate the complexities and nuances of XAI and offer a road map for future research. For each problem, we provide promising research directions in the hope of harnessing the collective intelligence of interested stakeholders.

中文翻译：

---

可解释的人工智能（XAI）2.0：开放挑战和跨学科研究方向的宣言

随着基于不透明人工智能 (AI) 的系统在各种现实应用中不断蓬勃发展，理解黑匣子模型已变得至关重要。作为回应，可解释的人工智能（XAI）已经成为一个在各个领域具有实际和道德效益的研究领域。本文重点介绍了 XAI 的进步及其在现实场景中的应用，并解决了 XAI 中持续存在的挑战，强调需要更广泛的视角和协作努力。我们汇集了来自不同领域的专家来发现开放性问题，努力同步研究议程并加速 XAI 的实际应用。通过促进协作讨论和跨学科合作，我们的目标是推动 XAI 向前发展，为其持续成功做出贡献。我们的目标是制定一个全面的提案来推进 XAI。为了实现这一目标，我们提出了一份宣言，其中包含 28 个未决问题，分为九类。这些挑战概括了 XAI 的复杂性和细微差别，并为未来的研究提供了路线图。对于每个问题，我们都提供有前景的研究方向，希望能够利用感兴趣的利益相关者的集体智慧。