翻译困境：通用伦理价值观为何无法在全球语境中实现有效转译
Lost in Translation: How Universal Ethical Values Fail to Translate Across Global Contexts
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中文总结 AI 辅助
该研究通过多国专家访谈发现AI伦理框架存在翻译鸿沟，提出多元治理路径以适配全球不同语境的AI伦理需求。
中文摘要 AI 辅助
AI伦理框架将公平、透明、问责等价值观视为普适性的，且可在不同语境中统一落地。我们研究了来自10个国家的14位专家对实践中AI的理解、对核心价值观的重新解读以及对替代治理方案的构想。研究发现，AI部署存在结构性不平等条件，表现为基础设施受限、掠夺性实践以及技术的“神秘化”，这些因素从根本上塑造了人们对风险与机遇的认知。研究结果显示，专家会根据当地道德逻辑重新解读价值观：隐私是集体性和关系性的而非个体性的；透明是构建信任的问责而非技术层面的披露；公平是获取与代表性的平等而非结果的均等。我们将这些差异界定为编码化的全球框架与本地化实践之间的翻译鸿沟。最后，我们提出了多元治理的路径，该路径重新分配认知权威，并将伦理协商视为持续的、依赖语境的过程，而非固定的技术标准。
英文摘要
AI ethics frameworks treat values such as fairness, transparency, and accountability as universal and uniformly operationalizable across contexts. We examined how 14 experts across 10 countries made sense of AI in practice, reinterpreted core values, and envisioned governance alternatives. We found that AI deployment is characterized by structurally unequal conditions, marked by infrastructural constraints, extractive practices, and a "mystification" of technology, which fundamentally shape perceptions of risks and opportunities. Our findings reveal that experts reinterpret values to fit local moral logics: privacy as collective and relational rather than individual; transparency as trust-building accountability rather than technical disclosure; and fairness as equity in access and representation rather than parity in outcomes. We identify these as translation gaps between encoded global frameworks and situated local practices. Finally, we propose pathways toward plural governance that redistributes epistemic authority and treats ethical negotiation as an ongoing, context-sensitive process rather than a settled technical standard.
