Fair Artificial Intelligence Realization 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: 2025-09-11

Risk subdomain coverage

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

• False or misleading information

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

• Unfair discrimination and misrepresentation
• Disinformation, surveillance, and influence at scale
• Lack of capability or robustness
• Lack of transparency or interpretability

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

The document primarily addresses misinformation risks (3.1) with good coverage, requiring truthfulness, accuracy, and acknowledgment of uncertainty in LLM responses. It has minimal coverage of ideological manipulation (related to 4.1), potential discrimination concerns (1.1), robustness issues (7.3), and transparency requirements (7.4). The focus is narrowly on content quality and neutrality rather than broader AI safety or security risks.

Sector coverage

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

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

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

• Information

All other sectors had no coverage in this document.

Sectors Summary

The document governs AI procurement by federal government agencies, primarily covering Public Administration excluding National Security and National Security sectors. It does not directly regulate private sector industries but affects AI developers seeking to sell LLMs to federal agencies.

Legislative Status

Hard Law

Legislative Status Summary

This is a federal bill from the United States Congress that creates binding procurement requirements for federal agencies using mandatory language ('shall') and establishes enforceable obligations through the federal procurement system.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Summary: The document is presented as 'A BILL' to be 'enacted by the Senate and House of Representatives of the United States of America in Congress assembled', indicating that the United States Congress is the proposing body.

Target

• Entity Types: AI_Developer, AI_Governance_Actor
• Summary: The document explicitly targets 'the head of each agency' for procurement restrictions and sets requirements that 'Developers of large language models shall not intentionally encode partisan or ideological judgments'. The definition section comprehensively defines which federal agencies are covered.

Enforcer

• Entity Types: AI_Governance_Actor
• Summary: The document places the obligation on 'the head of each agency' to ensure procurement compliance, implying that agency heads have enforcement authority through their procurement decisions. No separate enforcement body is explicitly designated.

Monitor

• Summary: The document does not explicitly designate any monitoring body, oversight mechanism, or reporting requirements. No entity is specifically tasked with tracking compliance or evaluating implementation.

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
• Deploy

AI Lifecycle Summary

The document primarily addresses the Build and Use Model stage by establishing development principles for LLMs, and the Deploy stage through federal procurement restrictions. It implicitly covers Plan and Design (requiring developers to design models with specified principles) and Verify and Validate (agencies must verify compliance before procurement). Data collection and ongoing monitoring stages are not addressed.

Technical Scope

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

• AI Models
• Generative AI

Technical Scope Summary

The document explicitly defines and focuses on 'large language models' as a specific category of 'generative AI model'. It does not mention frontier AI, general-purpose AI, task-specific AI, foundation models (as distinct from LLMs), predictive AI, compute thresholds, or open-weight models. The scope is narrowly focused on LLMs used in federal procurement.