Amends the Public Health Service Act to create a grant program, administered by the Health Resources and Services Administration, funding AI education for medical students, residents, and faculty. Requires grantees to report on AI educational integration and outcomes. Prioritizes underserved communities.
Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the risk subdomain are described.
All other risk subdomains had no coverage in this document.
Risk Coverage Summary
This document has minimal coverage of AI risks, with brief mentions of only 3 risk subdomains: bias/discrimination (1.1), patient data privacy (2.1), and algorithm transparency (7.4). The document's primary focus is on creating educational programs rather than comprehensively addressing AI risks, though it requires education about ethical implications including bias, privacy, and transparency.
Good coverage — Comprehensive governance measures or mitigations with clear procedures relating to the sector are explicitly described.
All other sectors had no coverage in this document.
Sectors Summary
This document primarily governs two sectors: Health Care and Social Assistance (through requirements for AI literacy in medical practice) and Educational Services (through grant requirements for medical schools and residency programs). Both sectors receive substantial, detailed coverage throughout the legislation.
Hard Law
Legislative Status Summary
This is a binding legislative bill enacted by the U.S. Congress that amends the Public Health Service Act, creating legally enforceable grant program requirements with mandatory reporting obligations and formal administrative enforcement through the Health Resources and Services Administration.
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Lifecycle stages covered by the documents, as defined in the OECD Framework for the Classification of AI Systems
AI Lifecycle Summary
The document primarily addresses the Deploy and Operate and Monitor stages of the AI lifecycle, focusing on education for deployment and ongoing use of AI systems in medical practice. It does not substantially cover earlier stages like planning, data collection, or model building.
Terms relating to technical scope that are mentioned or implicitly referenced in the document
Technical Scope Summary
The document explicitly defines and mentions AI systems (machine-based systems) and addresses task-specific AI applications in healthcare (diagnostics, treatment recommendations, predictive analytics). It does not mention frontier AI, general purpose AI, foundation models, generative AI, compute thresholds, or open-weight models.
Document data from AGORA, CSET Emerging Technology Observatory.