AI Training Expansion Act of 2023

• Authority: United States Congress
• Parent authority: Federal government
• Jurisdiction: United States
• Collections: U.S. federal laws
• Most recent activity: Defunct
• Most recent activity date: 2025-01-03

Risk subdomain coverage

Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the risk subdomain are described.

• Governance failure

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

This document has minimal to no coverage of specific AI risk domains. It focuses on establishing training programs for federal employees to understand AI capabilities, risks, and best practices, but does not address specific risk subdomains in detail. The document mentions risks and benefits in general terms without elaborating on particular risk categories.

Sector coverage

Good coverage — Comprehensive governance measures or mitigations with clear procedures relating to the sector are explicitly described.

• Public Administration (excl. National Security)

All other sectors had no coverage in this document.

Sectors Summary

This legislation exclusively governs the Public Administration sector, specifically targeting federal executive branch agencies and their employees. It does not regulate AI use in private sector industries or other economic sectors.

Legislative Status

Hard Law

Legislative Status Summary

This is a binding federal statute enacted by Congress with mandatory obligations for executive agencies. The document uses mandatory language ('shall') and creates legally enforceable requirements for AI training programs.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Entities: Ms. Mace; Mr. Connolly; United States Congress; House of Representatives
• Summary: The document was introduced in the House of Representatives by Ms. Mace and Mr. Connolly, making them the proposers. The broader proposing body is the United States Congress.

Target

• Entity Types: AI_Governance_Actor
• Entities: Executive agencies; Office of Management and Budget; Office of Personnel Management; Federal Government employees in acquisition positions; management officials; supervisors; employees in data or technology positions
• Summary: The Act targets executive branch employees, specifically those in acquisition positions, management officials, supervisors, and data/technology positions. The Director of OMB is tasked with establishing the training program.

Enforcer

• Entity Types: AI_Governance_Actor
• Entities: Director of the Office of Management and Budget; Office of Personnel Management
• Summary: The Director of OMB is designated as the primary authority to establish and oversee the AI training program. OPM is referenced for position classification purposes.

Monitor

• Entity Types: AI_Governance_Actor
• Entities: Director of the Office of Management and Budget
• Summary: The Director of OMB is responsible for monitoring through feedback mechanisms and updating the training program based on participant feedback.

AI Lifecycle Stages

Lifecycle stages covered by the documents, as defined in the OECD Framework for the Classification of AI Systems

• Plan and Design
• Collect and Process Data
• Build and Use Model
• Verify and Validate
• Deploy
• Operate and Monitor

AI Lifecycle Summary

The document does not focus on specific AI lifecycle stages but rather on training federal employees about AI across all stages. It mentions developing, deploying, and managing AI systems, suggesting coverage of multiple lifecycle stages at a high level.

Technical Scope

Terms relating to technical scope that are mentioned or implicitly referenced in the document

• AI Models
• AI Systems

Technical Scope Summary

The document uses general terminology referring to both 'AI models' and 'AI systems' without defining them. It does not mention frontier AI, general purpose AI, foundation models, generative AI, predictive AI, open-weight models, or compute thresholds. The focus is on broad AI training rather than specific technical categories.