Lost in Translation: How Universal Ethical Values Fail to Translate Across Global Contexts

2026-08-20

AI Summary

研究探讨了全球AI伦理框架在不同国家和地区应用时遇到的问题，通过14位专家的观点揭示了价值观如何被本地化理解，并提出了一种多元化的治理方法。

Abstract

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.

Problem

• AI ethics
• universal values
• global contexts
• translation gaps
• local moral logics

Innovation

• context-sensitive ethics
• translation gaps
• plural governance
• local moral logics