Document Type

Journal Article

Publication Date

7-7-2026

Keywords

Algorithmic Governance, Social Health Policies, Communication Ecologies

School

McAnulty College and Graduate School of Liberal Arts

Primary Author Department

Rhetoric and Communication Department

Abstract

The promises of artificial intelligence (AI) as a solution to challenges facing health systems increasingly link technological innovation with improvements in efficiency and access. However, the legitimacy of AI-supported health policies depends not only on scientific competence but also on public trust in scientific institutions. Using data from the international Trust in Science Project (71,922 respondents across 68 countries), this study analyses multidimensional trust and communication ecologies to reconstruct relational configurations of trust, termed ‘Figures of Relevance’. Findings reveal that whilst scientific competence is widely recognised, perceptions of institutional openness vary markedly, shaping heterogeneity in trust. The study identifies four distinct trust configurations linked to demographic and communicational factors. These insights inform a preliminary framework for designing AI-enabled health social policies that emphasise institutional openness and tailored communication strategies, aiming to strengthen legitimacy and equitable social inclusion in health governance. Thus, rather than treating trust as an individual attribute, the study reconstructs relational configurations through which scientific legitimacy is experienced.

Rights

© 2026 Kochav Koren. This work is made available for educational and scholarly purposes.

Open Access

Yes

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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