提出三维文化能力框架，让AI评估更准确可靠。
Defining Cultural Capabilities for AI Evaluation: A Taxonomy Grounded in Intercultural Communication Theory
- 从跨文化沟通理论出发，构建认知、敏感度、适应性三层能力模型。
- 明确指出当前评估多仅限于事实记忆，缺乏对文化互动的深层考察。
- 适合关注AI跨文化应用与伦理评估的研究者和开发者使用。
针对人工智能系统在跨文化场景中的包容性与有效性评估，现有研究普遍存在文化能力概念模糊、术语混用、评估维度单一等问题，通常仅聚焦于对不同人口、地区或国家事实信息的记忆。为解决这一建构性模糊问题，本文基于跨文化沟通理论，提出一个三层文化能力分类体系：文化认知（是否知晓）回答‘模型知道吗？’；文化敏感度（如何呈现知识）回答‘它如何表述知识？’；文化胜任力（能否动态调整）回答‘它能否随交互演进而适应？’。该框架不仅澄清了概念，更可作为提升真实多元文化环境中AI评估有效性和可解释性的实用工具。若缺乏此类概念明晰，评估结果可能夸大模型能力，导致在文化敏感场景中做出不当部署决策。
原文摘要 · Abstract (English)
Tremendous efforts have been put into evaluating the inclusivity and effectiveness of AI systems across cultures. However, the cultural capabilities considered in much of the literature remain vaguely defined, are referred to using interchangeable terminology, and are typically limited to recalling accurate information about various demographics, regions, and nationalities. To address this construct ambiguity, we draw from Intercultural Communication scholarship and propose a three-level taxonomy of AI-relevant cultural capabilities: Cultural Awareness answers "Does the model know?", Cultural Sensitivity answers "How does it frame its knowledge?", and Cultural Competence answers "Can it adapt as the interaction evolves?". Beyond conceptual clarification, we position this taxonomy as a practical tool for improving the validity and interpretability of AI evaluation in real-world, multicultural settings. Without such construct clarity, evaluation results risk overstating model capabilities and may lead to inappropriate deployment decisions in culturally sensitive contexts.
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