mlsanityData to 7 Oct 2026

Public Opinion and The Rise of Digital Minds: Perceived Risk, Trust, and Regulation Support

arXiv 2504.21849 ↗First posted 30 Apr 2025cs.CY cs.AI cs.HCcited by 3

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Abstract (arXiv)

Governance institutions must respond to societal risks, including those posed by generative AI. This study empirically examines how public trust in institutions and AI technologies, along with perceived risks, shape preferences for AI regulation. Using the nationally representative 2023 Artificial Intelligence, Morality, and Sentience (AIMS) survey, we assess trust in government, AI companies, and AI technologies, as well as public support for regulatory measures such as slowing AI development or outright bans on advanced AI. Our findings reveal broad public support for AI regulation, with risk perception playing a significant role in shaping policy preferences. Individuals with higher trust in government favor regulation, while those with greater trust in AI companies and AI technologies are less inclined to support restrictions. Trust in government and perceived risks significantly predict preferences for both soft (e.g., slowing development) and strong (e.g., banning AI systems) regulatory interventions. These results highlight the importance of public opinion in AI governance. As AI capabilities advance, effective regulation will require balancing public concerns about risks with trust in institutions. This study provides a foundational empirical baseline for policymakers navigating AI governance and underscores the need for further research into public trust, risk perception, and regulatory strategies in the evolving AI landscape.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 2 of its 100 references that are in the map. First posted on arXiv 30 Apr 2025.

Builds on

2 of 100 references.

References · 2

  1. 2024Perceptions of Sentient AI and Other Digital Minds: Evidence from the AI, Morality, and Sentience (AIMS) Surveycited by 15
  2. 2024The AI Double Standard: Humans Judge All AIs for the Actions of Onecited by 6

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 1; 2026: 2.

3 papers.