Reliable Artificial Intelligence Research Act of 2025

• Authority: United States Congress
• Parent authority: Federal government
• Jurisdiction: United States
• Collections: U.S. federal laws
• Most recent activity: Proposed
• Most recent activity date: 2025-12-03

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
• Lack of capability or robustness
• Lack of transparency or interpretability

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

• Compromise of privacy
• False or misleading information
• AI pursuing its own goals

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

The document primarily addresses AI system safety, failures, and limitations (Domain 7), with strong focus on lack of robustness (7.3) and lack of transparency/interpretability (7.4). It also has coverage of privacy and security risks (2.2) through its emphasis on adversarial robustness and vulnerability testing. Coverage is concentrated on technical AI safety challenges rather than broader societal risks.

Sector coverage

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

• Scientific Research & Development Services

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

• Information
• Public Administration (excl. National Security)
• National Security

All other sectors had no coverage in this document.

Sectors Summary

This Act does not directly regulate specific economic sectors but rather funds research competitions that are sector-agnostic. The competitions aim to advance AI interpretability and adversarial robustness applicable across multiple industries. The document mentions potential applications in government and industry generally, with emphasis on high-impact, high-risk use cases across various sectors.

Legislative Status

Hard Law

Legislative Status Summary

This is a Congressional bill enacted by the U.S. Senate and House of Representatives, using mandatory language ('shall') throughout and authorizing specific appropriations of $10 million for fiscal years 2026-2030. It creates legally binding obligations on the Secretary of Homeland Security.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Summary: The document is a Congressional bill enacted by the legislative branch of the U.S. government, as indicated by the standard enacting clause.

Target

• Entity Types: AI_Governance_Actor, AI_Developer
• Summary: The Act's primary target is the Secretary of Homeland Security who must carry out the requirements. Secondary targets include AI developers and researchers who would participate in the prize competitions to advance interpretability and adversarial robustness.

Enforcer

• Entity Types: AI_Governance_Actor
• Summary: The Secretary of Homeland Security has the administrative authority to implement the Act's requirements. Congressional committees provide oversight through mandatory reporting requirements.

Monitor

• Entity Types: AI_Governance_Actor
• Summary: The Act establishes mandatory reporting to specific congressional committees to evaluate competition outcomes, assess gaps in interpretability and adversarial robustness fields, and recommend congressional action.

AI Lifecycle Stages

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

• Plan and Design
• Build and Use Model
• Verify and Validate

AI Lifecycle Summary

The document primarily addresses the Build and Use Model stage through prize competitions for developing interpretable and adversarially robust AI models. It also covers Verify and Validate through red-teaming and testing requirements. The focus is on advancing research methodologies rather than governing complete lifecycle stages from design through operational monitoring.

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 explicitly mentions AI models, AI systems, and AI products. It focuses on commercially available or widely used AI products and high-impact, high-risk applications but does not specifically reference frontier AI, general purpose AI, foundation models, generative AI, or compute thresholds.