<p>The integration of Artificial Intelligence (AI) in health systems has the potential to revolutionize healthcare delivery, but it also raises significant concerns regarding bias, transparency, and accountability. This paper proposes a novel “Do Good” framework that prioritizes patient-centered design, transparency, and accountability in AI development and deployment, addressing the limitations of existing approaches. By combining human rights, bioethics, and health systems principles, our framework provides a comprehensive and proactive approach to ensuring that AI systems are safe, effective, and equitable. Our analysis highlights the need for a paradigm shift in healthcare ethics and practice, from a traditional “Do No Harm” principle to a more proactive “Do Good” approach, enabled by AI. We demonstrate the applicability of our framework through a critical examination of existing regulatory processes, health technology assessment, and public procurement of AI, and identify key areas for future research and development.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Artificial intelligence (AI) in health systems: introducing a ‘Do Good’ approach

  • Elsa Papadopoulou,
  • Themis Exarchos,
  • Sasa Jenko,
  • Katarina Krepelkova,
  • Joana Namorado

摘要

The integration of Artificial Intelligence (AI) in health systems has the potential to revolutionize healthcare delivery, but it also raises significant concerns regarding bias, transparency, and accountability. This paper proposes a novel “Do Good” framework that prioritizes patient-centered design, transparency, and accountability in AI development and deployment, addressing the limitations of existing approaches. By combining human rights, bioethics, and health systems principles, our framework provides a comprehensive and proactive approach to ensuring that AI systems are safe, effective, and equitable. Our analysis highlights the need for a paradigm shift in healthcare ethics and practice, from a traditional “Do No Harm” principle to a more proactive “Do Good” approach, enabled by AI. We demonstrate the applicability of our framework through a critical examination of existing regulatory processes, health technology assessment, and public procurement of AI, and identify key areas for future research and development.