Regulates developers and deployers of AI algorithms to prevent discrimination and disparate impacts, requiring pre-deployment evaluations and annual assessments. Authorizes the FTC and states to enforce compliance, and creates a private right of action. Establishes transparency and consumer rights.
Good coverage — Comprehensive governance measures or mitigations with clear procedures relating to the risk subdomain are explicitly described.
Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the risk subdomain are described.
All other risk subdomains had no coverage in this document.
Risk Coverage Summary
The document has good coverage of approximately 8-10 subdomains, with strong focus on discrimination and toxicity (1.1, 1.3), privacy compromise (2.1), AI system security (2.2), misinformation (3.1), lack of transparency (7.4), and lack of robustness (7.3). Coverage is concentrated in fairness, transparency, and AI system reliability domains.
Good coverage — Comprehensive governance measures or mitigations with clear procedures relating to the sector are explicitly described.
Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the sector are described.
All other sectors had no coverage in this document.
Sectors Summary
This legislation governs AI use across virtually all economic sectors through its definition of 'consequential actions.' It has particularly detailed coverage of Employment, Educational Services, Health Care and Social Assistance, Finance and Insurance, Housing (Real Estate), Criminal Justice (Public Administration and National Security), and Government Benefits. The law applies to any developer or deployer using covered algorithms for consequential actions in these domains.
Hard Law
Legislative Status Summary
This is a binding federal statute with mandatory obligations, enforcement mechanisms including FTC enforcement, state attorney general enforcement, and private right of action, with specific civil penalties of $15,000 per violation or 4% of annual revenue.
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Target
Enforcer
Monitor
Lifecycle stages covered by the documents, as defined in the OECD Framework for the Classification of AI Systems
AI Lifecycle Summary
The document comprehensively covers multiple AI lifecycle stages with primary focus on Verify and Validate, Deploy, and Operate and Monitor stages. It requires pre-deployment evaluations, annual impact assessments, and ongoing monitoring. The Plan and Design stage is addressed through stakeholder consultation requirements, while Build and Use Model is covered through training data and methodology documentation requirements.
Terms relating to technical scope that are mentioned or implicitly referenced in the document
Technical Scope Summary
The document focuses on 'covered algorithms' defined as computational processes derived from machine learning, natural language processing, artificial intelligence techniques, or similar complexity that make or facilitate consequential decisions. It does not explicitly mention frontier AI, general purpose AI, foundation models, generative AI, predictive AI, open-weight models, or compute thresholds. The scope is defined functionally based on use in consequential actions rather than by model type or capability.
Document data from AGORA, CSET Emerging Technology Observatory.