Cultural Perspectives and Expectations for Generative AI: A Global Survey Approach
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Abstract (arXiv)
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''.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 12 of its 39 references that are in the map. First posted on arXiv 5 Mar 2026.
Builds on
12 of 39 references.
References · 12
- 2023Towards Measuring the Representation of Subjective Global Opinions in Language Modelscited by 437
- 2020Closing the AI Accountability Gap: Defining an End-to-End Framework for Internal Algorithmic Auditingcited by 384
- 2024Towards Measuring and Modeling "Culture" in LLMs: A Surveycited by 167
- 2024The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Modelscited by 144
- 2023Social Biases through the Text-to-Image Generation Lenscited by 127
- 2022The Ghost in the Machine has an American accent: value conflict in GPT-3cited by 105
- 2024Survey of Cultural Awareness in Language Models: Text and Beyondcited by 103
- 2025Randomness, Not Representation: The Unreliability of Evaluating Cultural Alignment in LLMscited by 54
- 2024NormAd: A Framework for Measuring the Cultural Adaptability of Large Language Modelscited by 48
- 2020Participatory Problem Formulation for Fairer Machine Learning Through Community Based System Dynamicscited by 31
- 2025Risks of Cultural Erasure in Large Language Modelscited by 9
- 2024Socially Responsible Data for Large Multilingual Language Modelscited by 7
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Citing papers per year: 2026: 2.
2 papers.