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<p>Artificial Intelligence (AI) technologies are increasingly prevalent in healthcare, yet without adaptive governance, even well-designed systems risk exacerbating health inequalities. This perspective examines five interconnected governance domains: legal frameworks, evidence generation, regulation and market access, workforce readiness, and public trust. We argue these form a cyclical governance chain in which weaknesses cascade across domains, and identify critical gaps and system-level reforms to ensure AI reduces rather than amplifies disparities.</p>

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Artificial intelligence needs better health systems to reduce inequalities

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月17日

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  • Robin van Kessel,
  • Alexander W. Carter,
  • Khurram Nasir,
  • Elias Mossialos

摘要

Artificial Intelligence (AI) technologies are increasingly prevalent in healthcare, yet without adaptive governance, even well-designed systems risk exacerbating health inequalities. This perspective examines five interconnected governance domains: legal frameworks, evidence generation, regulation and market access, workforce readiness, and public trust. We argue these form a cyclical governance chain in which weaknesses cascade across domains, and identify critical gaps and system-level reforms to ensure AI reduces rather than amplifies disparities.