AI Labeling 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

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

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

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

The document primarily addresses misinformation risks (3.1, 3.2) through mandatory disclosure requirements for AI-generated content. It also covers malicious actor risks (4.1, 4.3) by preventing removal of disclosures and requiring detection standards. There is minimal coverage of governance mechanisms (6.5) through the establishment of a working group, and system transparency (7.4) through metadata requirements.

Sector coverage

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

• Information
• Professional & Technical Services

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

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

All other sectors had no coverage in this document.

Sectors Summary

This legislation applies broadly across all sectors where generative AI systems are developed, licensed, or used to produce content. The primary sectors governed are Information (AI developers, platforms, social media) and Professional and Technical Services (AI system developers and consultants). The working group includes representation from multiple sectors.

Legislative Status

Hard Law

Legislative Status Summary

This is a binding federal statute introduced in the U.S. Senate with mandatory disclosure requirements, enforcement by the Federal Trade Commission, and penalties for non-compliance under the Federal Trade Commission Act.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Entities: Mr. Schatz; Mr. Kennedy; United States Senate; Committee on Commerce, Science, and Transportation
• Summary: The bill was introduced in the U.S. Senate by Senators Schatz and Kennedy and referred to the Committee on Commerce, Science, and Transportation, indicating these are the proposing entities.

Target

• Entity Types: AI_Developer, AI_Deployer
• Entities: developers of generative artificial intelligence systems; third-party licensees; end users
• Summary: The Act explicitly targets entities that develop generative AI systems, third-party licensees who license such systems, and end users who deploy them to produce AI-generated content.

Enforcer

• Entity Types: AI_Governance_Actor
• Entities: Federal Trade Commission
• Summary: The Federal Trade Commission is explicitly designated as the enforcement body with authority to enforce the Act's requirements and impose penalties for violations.

Monitor

• Entity Types: AI_Governance_Actor
• Entities: National Institute of Standards and Technology; AI-Generated Content Consumer Transparency Working Group; Committee on Commerce, Science, and Transportation of the Senate; Committee on Energy and Commerce of the House of Representatives
• Summary: NIST is tasked with establishing a working group to develop technical standards and detection frameworks, with reporting obligations to Congressional committees for oversight.

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
• Deploy
• Operate and Monitor

AI Lifecycle Summary

The document primarily focuses on the Deploy and Operate and Monitor stages by requiring disclosure mechanisms on AI-generated content outputs and establishing detection standards. It also addresses Build and Use Model through requirements on developers to implement disclosure features in their systems.

Technical Scope

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

• AI Systems
• Generative AI

Technical Scope Summary

The document explicitly covers generative AI systems and AI chatbots. It does not mention frontier AI, general purpose AI, task-specific AI, foundation models, or compute thresholds. It focuses on AI systems that generate or substantially modify content across multiple modalities (image, video, audio, multimedia, text).