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Understanding Citizens' Acceptance of <scp>AI</scp> in Policymaking: How Policy Domains, Levels of <scp>AI</scp> Involvement, and Stereotypical Perceptions Shape Public Support

Tessa Haesevoets et al.

Policy Studies Journal2026https://doi.org/10.1111/psj.70114article
AJG 3ABDC B
Weight
0.50

What the paper says

ABSTRACT This study examines UK citizens' perceptions of Artificial Intelligence (AI) in policymaking. We first explored the interactive influence of three empirically derived policy issue types (technical, mixed, and ideological issues) and five different levels of AI involvement (ranging from no involvement to full involvement) on public acceptance (RO1). Our results showed that acceptance of AI is highest in technical issues, particularly in a co‐decisive role. For mixed issues, AI was moderately accepted, with advisory roles being most preferred. In contrast, ideological issues were met with the lowest levels of acceptance, with most respondents favoring little or no AI involvement. Secondly, we examined how stereotypical perceptions of AI and human decision‐makers influence AI acceptance using the competence–warmth framework (RO2). While humans are perceived as both competent and warm, AI is seen as competent but lacking warmth. Moreover, across all three policy issue types, higher perceived human competence reduced AI acceptance, whereas higher perceived AI competence increased it. Additionally, perceived lack of AI warmth undermined acceptance in mixed and ideological issues. Together, these findings highlight the complex factors influencing public acceptance of AI in governance and underscore how stereotypical perceptions function as underlying drivers of these preferences.

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https://doi.org/https://doi.org/10.1111/psj.70114

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@article{tessa2026,
  title        = {{Understanding Citizens' Acceptance of <scp>AI</scp> in Policymaking: How Policy Domains, Levels of <scp>AI</scp> Involvement, and Stereotypical Perceptions Shape Public Support}},
  author       = {Tessa Haesevoets et al.},
  journal      = {Policy Studies Journal},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1111/psj.70114},
}

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Understanding Citizens' Acceptance of <scp>AI</scp> in Policymaking: How Policy Domains, Levels of <scp>AI</scp> Involvement, and Stereotypical Perceptions Shape Public Support

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.