Comment Integrity and Management 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

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

• False or misleading information
• Pollution of information ecosystem
• Disinformation, surveillance, and influence at scale
• Fraud, scams, and targeted manipulation
• Governance failure
• Lack of transparency or interpretability

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

The document has minimal coverage of AI risk domains, with primary focus on misinformation risks (3.1, 3.2) related to AI-generated comments in the regulatory process. It addresses aspects of malicious actors (4.1, 4.3) through mass comment manipulation and fraud, and touches on governance (6.5) through regulatory process integrity. Coverage is concentrated in information integrity and democratic process protection.

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 document governs AI use within Public Administration (excluding National Security) by regulating how federal agencies manage AI-generated and mass comments in the regulatory rulemaking process. It does not govern AI use in private sector industries but rather establishes procedures for government agencies' internal operations.

Legislative Status

Hard Law

Legislative Status Summary

This is a binding federal statute enacted by the United States Congress with mandatory obligations on federal agencies, enforceable through administrative law mechanisms and oversight by OMB and GAO.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Summary: The document is a federal legislative act passed by the House of Representatives on May 6, 2024, and received by the Senate on May 7, 2024, indicating Congress as the proposing authority.

Target

• Entity Types: AI_Governance_Actor
• Summary: The Act applies to federal agencies that accept electronic comments in the regulatory process, requiring them to verify human origin of comments, identify mass and AI-generated comments, and establish policies for managing such comments.

Enforcer

• Entity Types: AI_Governance_Actor
• Summary: OMB Director is mandated to issue guidance for implementation, the Administrator of General Services must update systems, and Congressional committees receive oversight reports from GAO.

Monitor

• Entity Types: AI_Governance_Actor
• Summary: GAO is explicitly mandated to monitor and report on the identification of computer-generated comments and their effects on the rulemaking process within 2 years of enactment.

AI Lifecycle Stages

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

• Build and Use Model
• Verify and Validate
• Operate and Monitor

AI Lifecycle Summary

The document does not focus on AI development lifecycle stages but rather on the deployment and operational use of AI-generated content (computer-generated comments) in the federal regulatory comment process. It addresses the verification, identification, and management of AI outputs after they have been generated and deployed for public use.

Technical Scope

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

• Generative AI

Technical Scope Summary

The document explicitly mentions AI in the context of computer-generated comments but does not define or distinguish between AI models, AI systems, or specific types of AI. It focuses on AI-generated content (comments) rather than AI system architectures or capabilities. No compute thresholds, foundation models, or model release approaches are mentioned.