Surveys Considered Harmful? Reflecting on the Use of Surveys in AI Research, Development, and Governance
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Abstract (arXiv)
Calls for engagement with the public in Artificial Intelligence (AI) research, development, and governance are increasing, leading to the use of surveys to capture people's values, perceptions, and experiences related to AI. In this paper, we critically examine the state of human participant surveys associated with these topics. Through both a reflexive analysis of a survey pilot spanning six countries and a systematic literature review of 44 papers featuring public surveys related to AI, we explore prominent perspectives and methodological nuances associated with surveys to date. We find that public surveys on AI topics are vulnerable to specific Western knowledge, values, and assumptions in their design, including in their positioning of ethical concepts and societal values, lack sufficient critical discourse surrounding deployment strategies, and demonstrate inconsistent forms of transparency in their reporting. Based on our findings, we distill provocations and heuristic questions for our community, to recognize the limitations of surveys for meeting the goals of engagement, and to cultivate shared principles to design, deploy, and interpret surveys cautiously and responsibly.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 30 of its 209 references that are in the map. First posted on arXiv 26 Jul 2024.
Builds on
30 of 209 references.
References · 30
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18 more
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Built on by
Citing papers per year: 2025: 2; 2026: 1.
3 papers.
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- 2026An Exploratory Study on LLM-Generated Code and Comments in Code Repositoriescited by 2
- 2026An Exploratory Study on LLM-Generated Code and Comments in Code Repositories2 Jul 2026
- 2025Understanding Gender Bias in AI-Generated Product Descriptions3 Jun 2025
- 2025The Hall of AI Fears and Hopes: Comparing the Views of AI Influencers and those of Members of the U.S. Public Through an Interactive Platform8 Apr 2025