Establishes programs for AI-driven vehicle technology research, focusing on electrification, machine learning for manufacturing, autonomous systems, cybersecurity, and advanced energy solutions. Requires periodic reporting and coordination among federal agencies. Allocates funding for these initiatives through 2028.
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
The document has minimal coverage of AI risk domains, with limited explicit focus on risks. Primary coverage relates to cybersecurity vulnerabilities (2.2) in connected and autonomous vehicles, and minimal mentions of automation safety concerns (7.3). The document is primarily focused on research and development programs rather than risk mitigation, with most AI-related content addressing capabilities rather than harms.
Good coverage — Comprehensive governance measures or mitigations with clear procedures relating to the sector are explicitly described.
Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the sector are described.
All other sectors had no coverage in this document.
Sectors Summary
This Act primarily governs AI use in the Trade, Transportation and Utilities sector through vehicle technology research and development. It also has significant coverage of the Information sector (connected vehicle systems and computing), Manufacturing (vehicle and component production), and Scientific Research and Development Services (research programs and academic centers). Public Administration is governed through federal agency coordination requirements.
Hard Law
Legislative Status Summary
This is a binding federal statute enacted by the U.S. Congress with mandatory language establishing programs, requiring reports, and authorizing appropriations with legal force.
Proposer
Target
Enforcer
Monitor
Lifecycle stages covered by the documents, as defined in the OECD Framework for the Classification of AI Systems
AI Lifecycle Summary
The document covers multiple AI lifecycle stages with primary focus on Plan and Design, Build and Use Model, Deploy, and Operate and Monitor stages. It addresses research and development of AI-driven vehicle technologies including machine learning for manufacturing, autonomous systems, and connected vehicle technologies throughout their lifecycle from planning through operational monitoring.
Terms relating to technical scope that are mentioned or implicitly referenced in the document
Technical Scope Summary
The document explicitly addresses AI systems and AI models in the context of vehicle technologies, particularly focusing on machine learning applications, autonomous systems, and connected vehicle technologies. It does not use terminology like 'frontier AI', 'general purpose AI', or 'foundation models', but focuses on task-specific applications in transportation. No compute thresholds are mentioned.
Document data from AGORA, CSET Emerging Technology Observatory.