Description of Session
USAID could join a panel with implementers to present the AI for Global Health: Defining a Collective Path Forward report. The report share four key pieces of analysis to help drive thinking across the global health field about deploying and scaling artificial intelligence in global health: 1). An overview of AI use cases that could have the greatest impact on improving health quality, cost, and access in LMICs 2). Four groupings of AI use cases that show high potential for scale and impact in LMICs:a). AI-Enabled Population Health, b). Frontline Health Worker (FHW) Virtual Health Assistant, c). Patient Virtual Health Assistant, and d). Physician Clinical Decision Support Tools 3). A detailed assessment of critical challenges to scaling AI in LMICs: data availability and quality; sustainability of business models; data privacy, ethics, and ownership; regulatory and policy issues; health systems integration; lack of trust; and lack of agreed upon standards for assessing the impact of AI tools 4). A discussion of seven priority investment areas we believe are critical in order to accelerate the use of AI in global health: 1) investment in responsible, sustainable innovation 2) scaling support, 3) ROI and evidence, 4) data capture, 5) interoperability, 6) building ecosystems/supporting governments in LMIC contexts, and 7) coordination of stakeholders involved in AI in global health
