Building Trust in Government AI: Balancing Innovation and Privacy in Healthcare Services

Abstract The increasing integration of artificial intelligence in healthcare services has raised concerns about privacy, accountability, and public trust, particularly for vulnerable populations. This study examines state-level governance frameworks regulating artificial intelligence in the United States healthcare. It analyzes 141 enacted state laws to identify key regulatory themes, including data privacy, electronic health records, patient consent, biometric data, and algorithmic transparency. Findings reveal regional disparities and fragmented legal protections, suggesting that regulatory inconsistency may undermine public trust and exacerbate healthcare inequalities. The paper concludes with theory-informed policy recommendations to strengthen governance frameworks while supporting responsible innovation.

Authors

Publication Details

Journal
Public Organization Review
Published
2026-05-11
DOI
https://doi.org/10.1007/s11115-026-01018-z
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Building Trust in Government AI: Balancing Innovation and Privacy in Healthcare Services

Daniel J. Mallinson, Pedro Robles, Lauren Azevedo, Eric Best
Public Organization Review
Artificial Intelligence in Healthcare and Education
article

Building Trust in Government AI: Balancing Innovation and Privacy in Healthcare Services

Daniel J. Mallinson, Pedro Robles, Lauren Azevedo, Eric Best
article en

Abstract

Abstract The increasing integration of artificial intelligence in healthcare services has raised concerns about privacy, accountability, and public trust, particularly for vulnerable populations. This study examines state-level governance frameworks regulating artificial intelligence in the United States healthcare. It analyzes 141 enacted state laws to identify key regulatory themes, including data privacy, electronic health records, patient consent, biometric data, and algorithmic transparency. Findings reveal regional disparities and fragmented legal protections, suggesting that regulatory inconsistency may undermine public trust and exacerbate healthcare inequalities. The paper concludes with theory-informed policy recommendations to strengthen governance frameworks while supporting responsible innovation.

Public Organization Review
Openalex Percentile: Top 9%
Artificial Intelligence in Healthcare and Education
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