AI Advancement and Reliability Act of 2024

• 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

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

• AI system security vulnerabilities
• Governance failure
• Lack of capability or robustness

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

• Cyberattacks, weapon development or use
• Competitive dynamics
• AI possessing dangerous capabilities
• Lack of transparency or interpretability

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

The document has minimal to good coverage of approximately 5-7 subdomains, with primary focus on AI system security (2.2), lack of capability or robustness (7.3), competitive dynamics (6.4), and governance failure (6.5). Coverage is concentrated in system safety, security vulnerabilities, and governance domains, with emphasis on evaluation and testing infrastructure rather than specific harm mitigation.

Sector coverage

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

• Scientific Research & Development Services
• Public Administration (excl. National Security)

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

• Professional & Technical Services
• Educational Services
• National Security

All other sectors had no coverage in this document.

Sectors Summary

This is a federal government policy establishing research and standards infrastructure. It does not directly regulate specific economic sectors but rather creates a center to develop voluntary best practices and evaluation methods applicable across multiple sectors. The document mentions collaboration with various sectors but does not impose sector-specific governance requirements.

Legislative Status

Hard Law

Legislative Status Summary

This is a binding federal statute enacted by the United States Congress with mandatory establishment requirements, appropriations authorization, and specific obligations for federal agencies. The document uses mandatory language throughout and creates legally enforceable obligations.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Summary: This is a Congressional Act proposed and enacted by the United States Congress, as indicated by the legislative format and structure of the document.

Target

• Entity Types: AI_Governance_Actor, AI_Developer
• Summary: The Act primarily targets federal agencies with mandatory obligations to establish the Center and Consortium. Private sector entities, AI developers, and other stakeholders are invited to participate voluntarily in the Consortium and collaborative activities.

Enforcer

• Entity Types: AI_Governance_Actor
• Summary: The Under Secretary is responsible for implementing and overseeing the Center's activities. Congressional committees enforce compliance through oversight, reporting requirements, and appropriations control. The Act explicitly states no new enforcement authority is created.

Monitor

• Entity Types: AI_Governance_Actor
• Summary: The Under Secretary monitors implementation through annual reporting to Congressional committees. The Center conducts ongoing evaluation and benchmarking of AI systems. The Consortium evaluates stakeholder needs and identifies gaps in Center activities.

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 comprehensively covers multiple AI lifecycle stages with particular emphasis on Verify and Validate, and Operate and Monitor stages. It addresses Plan and Design through research and standards development activities, and Build and Use Model through evaluation of capabilities. The focus is on establishing infrastructure for testing, evaluation, and ongoing monitoring of AI system reliability, robustness, resilience, security, and safety throughout the entire lifecycle.

Technical Scope

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

• AI Systems
• Open Weight / Open Source

Technical Scope Summary

The document explicitly mentions AI systems as the primary focus but does not specifically reference AI models as a separate concept. It does not mention frontier AI, general purpose AI, task-specific AI, foundation models, generative AI, predictive AI, open-weight models, or specific compute thresholds. The scope is broadly applicable to artificial intelligence systems across use cases and sectors.