AI for Improved Public Health and Climate-Resilient Health Systems

Generative AI (GenAI) has shown the transformative capabilities of Large Language Models (LLMs) in creating new insights and fostering a cycle of continuous learning and improvement. With essential human oversight for accuracy and resilience, GenAI is positioned to accelerate revolutionary digital health technologies. However, presenting a balanced view of GenAI’s benefits, limitations, and risks is crucial for enabling responsible regulation that encourages innovation, benefits healthcare professionals, and maintains high standards of patient safety.

The proposed IC program will demonstrate GenAI’s role in advancing inclusive, equitable healthcare by fostering community engagement and digital autonomy. Proven innovations like digital biomarkers and endpoints (e.g., the Google HeAR project), consensus LLMs (e.g., applied as digital tumor boards), and AI medical scribes (e.g., Nabla) highlight how GenAI can address healthcare gaps, empower underserved populations, and respond to critical needs in climate-health resilience, healthcare access, and workforce support.

The IC Program invites membership and participation to present use cases, explore the downstream applications of LLMs in generative AI, and contribute to regulatory and code-of-practice development, advancing international standards in healthcare innovation.

To advance a sustainable framework for these frontier technologies, the Initiative outlines four strategic pillars to address the complex intersections of healthcare access, climate impacts, and equitable health:

1. Fostering Collaboration
   LLM-powered consensus tools (e.g., Google DeepMind’s “Habermas Machine,”), exemplify how GenAI can facilitate inclusive dialogue and informed decision-making across health teams, enhancing coordination and clarity. Models like this serve as powerful enablers of medical knowledge sharing and evidence-based telehealth access, fostering community engagement and expanding essential healthcare services to a wider audience.
2. Establishing a Code of Practice (CoP)
   As these new applications often reside in regulatory grey areas, the program aims to create an actionable Code of Practice to guide the responsible use of GenAI in healthcare. This includes defining the ethical scope, intended purpose, and regulatory classification, particularly for applications integrating GenAI with telehealth-derived data. The CoP will serve as a roadmap for compliant, secure, and impactful applications across varied healthcare contexts.
3. Promoting Ethical Commercialization
   For the responsible commercialization of GenAI, the program advocates for a governance framework emphasizing transparency, equity, diversity, and inclusion. These principles guide the development and distribution of GenAI-driven healthcare applications, ensuring accessibility and shared value creation through open innovation—especially for populations with limited healthcare access.
4. Clarifying Regulatory Pathways and Fostering Continuous Learning
   Demonstrating GenAI’s real-world applications provides clarity around regulatory requirements and best practices across the AI lifecycle. Key areas include data governance, adherence to standards, and the development of collaborative infrastructure to enable integration across diverse environments. Ethical commercialization, paired with a focus on continuous learning and public engagement, will help bridge evidence gaps and support advancements in climate-health resilience and equitable healthcare access through new study methods like digital phenotyping and micro-randomization trials.

• Regulators and government officials
• Healthcare leaders
• AI and technology innovators
• Academic and research leaders
• NGO and advocacy leaders
• International organization representatives
• Investors and venture capitalists
• Community leaders and representatives

To learn more about the program and how to join the AI for Improved Public Health and Climate-Resilient Health Systems activity, please express your interest by completing the AI for Improved Public Health and Climate-Resilient Health Systems interest form.