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原理及预测机制的工具。然而，这些益处大多局限于具备专业领域知识的群体（如机器学习开发者）。近期研究表明，使人工智能具备可解释性，是提升其在真实世界场景（尤其是全球南方低资源领域）实用性的可行路径。尽管人工智能已跨越国界，但将可解释人工智能概念普及至"多数世界"（即发展中国家/地区）的研究仍十分有限，这使得该领域在探索和开发契合文化多样性地区用户独特需求的新方法方面存在广阔空间。本文提出将跨文化伦理方法纳入人工智能可解释性的理论框架，探讨文化差异如何影响技术采纳与应用、阻碍AI等技术概念解释的因素，以及在开发可解释人工智能过程中融入跨文化伦理方法如何提升用户理解能力并促进这些方法的有效使用。