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arXiv 2603.05723cs.CLcs.AI
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生成式人工智能的文化视角与期望:一种全球调查方法

Cultural Perspectives and Expectations for Generative AI: A Global Survey Approach

Google Research(谷歌研究院);Google(谷歌);Google DeepMind(谷歌DeepMind)

Erin van Liemt, Renee Shelby, Andrew Smart, Sinchana Kumbale, Richard Zhang, Neha Dixit, Qazi Mamunur Rashid, Jamila Smith-Loud

AI总结:

本文通过全球调查探讨生成式人工智能在文化代表中的挑战与解决方案,提出参与式方法和文化敏感框架以促进文化多样性。

摘要:

关于全球范围内生成式人工智能是否以及如何代表文化的看法缺乏实证证据。本文通过大规模全球调查评估了与生成式人工智能相关的文化理解与信念。我们收集了不同群体对文化意义的看法,以及生成式人工智能应如何处理文化制品、概念或价值观。我们直接从这些社区中提炼出文化的工作定义,以理解其概念复杂性以及它们与生成式人工智能中表示的关系。我们从欧洲、北美、南美、亚洲和非洲的不同地区进行了调查。我们最后提出了一些建议,为文化和生成式人工智能开发提供指导。这包括参与式方法、优先考虑超越地理的特定文化维度,如宗教和传统,以及一个敏感框架来处理文化“红线”。

英文摘要:

There is a lack of empirical evidence about global attitudes around whether and how GenAI should represent cultures. This paper assesses understandings and beliefs about culture as it relates to GenAI from a large-scale global survey. We gathered data about what culture means to different groups, and about how GenAI should approach the representation of cultural artifacts, concepts, or values. We distill working definitions of culture directly from these communities to build an understanding of its conceptual complexities and how they relate to representations in Generative AI. We survey from across parts of Europe, North and South America, Asia, and Africa. We conclude with a set of recommendations for Culture and GenAI development. These include participatory approaches, prioritizing specific cultural dimensions beyond geography, such as religion and tradition, and a sensitivity framework for addressing cultural ``redlines''.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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