Explainable AI (XAI) is often promoted with the idea of helping users understand how machine learning models function and produce predictions. Still, most of these benefits are reserved for those with specialized domain knowledge, such as machine learning developers. Recent research has argued that making AI explainable can be a viable way of making AI more useful in real-world contexts, especially within low-resource domains in the Global South. While AI has transcended borders, a limited amount of work focuses on democratizing the concept of explainable AI to the "majority world", leaving much room to explore and develop new approaches within this space that cater to the distinct needs of users within culturally and socially-diverse regions. This article introduces the concept of an intercultural ethics approach to AI explainability. It examines how cultural nuances impact the adoption and use of technology, the factors that impede how technical concepts such as AI are explained, and how integrating an intercultural ethics approach in the development of XAI can improve user understanding and facilitate efficient usage of these methods.

翻译：可解释人工智能（XAI）常被宣传为帮助用户理解机器学习模型运作方式及预测生成机制的技术工具。然而，这些益处大多局限于具备专业领域知识（如机器学习开发者）的特定群体。近期研究表明，将人工智能变得可解释，尤其是针对全球南方低资源领域，是提升该技术在现实场景实际效用的可行途径。尽管人工智能已突破地域限制，但鲜有研究聚焦于将可解释人工智能概念推广至"多数世界"，这一领域仍有待探索适合文化与社会多样性区域用户特殊需求的新方法。本文提出将跨文化伦理方法应用于人工智能可解释性的概念框架，系统分析文化差异如何影响技术采纳与应用、阻碍人工智能等技术概念阐释的因素，以及将跨文化伦理视角融入XAI开发如何提升用户理解并促进这些方法的有效运用。