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<p>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.</p>

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月11日

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  • Pedro Robles,
  • Lauren Azevedo,
  • Eric Best,
  • Daniel J. Mallinson

摘要

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.