Prohibits surveillance-based AI systems from determining prices and wages unless specific transparency and fairness criteria are met. Requires Federal Trade Commission and Equal Employment Opportunity Commission to enforce provisions. Grants states and individuals the right to pursue legal actions.
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 subdomains, with strong focus on surveillance and privacy (2.1, 4.1), transparency (7.4), and economic concerns (1.1, 1.3, 6.2). Coverage is concentrated in privacy, surveillance prevention, algorithmic fairness, and transparency domains related to pricing and wage discrimination.
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, as it applies to any 'person engaged in commerce' using automated decision systems for pricing or wage-setting. The broadest impact is on retail trade, e-commerce, hospitality, transportation, and any employment sectors, with explicit inclusion of common carriers (telecommunications/utilities) and nonprofit organizations.
Hard Law
Legislative Status Summary
This is a binding Congressional bill (H.R.4640) with mandatory prohibitions, explicit enforcement mechanisms through federal agencies (FTC, EEOC), state actions, and private rights of action, with specified monetary penalties.
Proposer
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 primarily focuses on the Deploy and Operate and Monitor stages of the AI lifecycle, requiring transparency procedures before deployment and ongoing accuracy verification during operation. There is minimal coverage of earlier stages like planning, data collection, or model building.
Terms relating to technical scope that are mentioned or implicitly referenced in the document
Technical Scope Summary
The document explicitly covers 'automated decision systems' broadly defined to include AI systems using machine learning, statistics, and data processing techniques. It does not distinguish between frontier AI, general purpose AI, or task-specific AI, applying uniformly to all automated decision systems used for pricing or wage-setting. No compute thresholds or distinctions between open-weight and closed models are mentioned.
Document data from AGORA, CSET Emerging Technology Observatory.