Health Equity in AI Development and Policy: An AI-enabled Study of International, National and Intra-national AI Infrastructures

Abstract

This study examines how concerns related to equity in AI for health are reflected at the international, national, and sub-national level. Utilizing unsupervised learning over corpora of published AI policy documents and graph structurization and analysis, the research identifies and visualizes the presence and variation of these concerns across different geopolitical contexts. The findings reveal interesting differences in how these issues are prioritized and addressed, highlighting the influence of local policies and cultural factors. The study underscores the importance of tailored approaches to AI governance in healthcare, advocating for increased global collaboration and knowledge sharing to ensure equitable and ethical AI deployment. By providing a comprehensive analysis of policy documents, this research contributes to a deeper understanding of the global landscape of AI in health, potentially offering insights for policymakers and stakeholders.