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<p>Efforts to research, implement and scale responsible Artificial Intelligence (AI) for addressing health challenges in low- and middle-income countries (LMICs) are often fragmented. It limits collaboration and slows progress. Communities of Practice (CoPs) offer a promising approach to fostering shared learning and supporting the use of AI to strengthen health systems and improve health outcomes. The Artificial Intelligence for Global Health Community of Practice (AI4GH CoP), established in 2023, connects researchers, implementers and policymakers across the Global South to co-create and scale responsible AI solutions for public health priorities. This case study examines the design, functioning and outputs of the AI4GH CoP using a structured community roadmap. It illustrates a model for advancing responsible AI in LMICs by reinforcing local expertise and facilitating context-specific knowledge exchange and capacity building in ethical, regulatory and operational aspects of AI in global health. These lessons can inform the establishment of similar CoPs.</p>

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The AI4GH community of practice: strengthening LMIC-Led artificial intelligence for global health

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月21日

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  • Mylena Maria Guedes de Almeida,
  • Mercedes Rumi,
  • Marina Bowder,
  • Prince Adjei,
  • Bryain Maradiaga-Mendoza,
  • Marina Albada,
  • Adam Dale,
  • Salvia Zeeshan,
  • Simran Siraj,
  • Nour El Arnaout,
  • Rosalind Parkes-Ratanshi,
  • Anneka Wickramanayake,
  • Peiling Yap,
  • Cintia Cejas,
  • Trudie Lang

摘要

Efforts to research, implement and scale responsible Artificial Intelligence (AI) for addressing health challenges in low- and middle-income countries (LMICs) are often fragmented. It limits collaboration and slows progress. Communities of Practice (CoPs) offer a promising approach to fostering shared learning and supporting the use of AI to strengthen health systems and improve health outcomes. The Artificial Intelligence for Global Health Community of Practice (AI4GH CoP), established in 2023, connects researchers, implementers and policymakers across the Global South to co-create and scale responsible AI solutions for public health priorities. This case study examines the design, functioning and outputs of the AI4GH CoP using a structured community roadmap. It illustrates a model for advancing responsible AI in LMICs by reinforcing local expertise and facilitating context-specific knowledge exchange and capacity building in ethical, regulatory and operational aspects of AI in global health. These lessons can inform the establishment of similar CoPs.