AI-Y: A Checklist for Population Ethics in Global AI Health

This presentation introduces the AI-Y Checklist, a practical framework for evaluating the ethical dimensions of artificial intelligence in global population health, and demonstrates its application through six diverse case studies spanning areas such as dementia care, environmental forecasting, mental health, and disease diagnosis across high- and low-resource settings. Drawing on a structured literature review and cross-contextual analysis, it examines key ethical dimensions including generalizability, accountability, transparency, governance, and equitable access, revealing recurring gaps such as limited local validation, weak accountability mechanisms, and barriers to accessibility. By situating ethical evaluation within real-world applications, the document highlights both the promise and shortcomings of current AI tools and emphasizes that technical performance alone is insufficient for responsible implementation. The AI-Y Checklist is presented as both a diagnostic and guiding instrument to support librarians, health professionals, and developers in advancing trustworthy, equitable, and sustainable AI deployment in population health.