Ethical Sourcing in Health Data Supply Chains: Considerations for ML/AI Training

Episode notes

Health data affects artificial intelligence in important ways. Camille Nebeker, Ed.D., M.S., UC San Diego, explains why ethically sourced data is foundational to building trustworthy, AI-ready health data repositories. Nebeker examines how ethical sourcing applies across the full data lifecycle, including consent, governance, transparency, data quality, privacy, stewardship, and community engagement. She also shows how ideas from supply chain management and value sensitive design help teams identify ethical tensions and improve decision-making. This work helps explain why ethics cannot be added at the end of AI development and points toward more accountable data practices that support public trust and stronger downstream performance. Series: "Exploring Ethics" [Science] [Show ID: 41368]

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