Establishes a pilot program to promote privacy-enhancing technologies like homomorphic encryption and federated learning. Requires development of a petition process and an auditing system for oversight. Mandates ongoing audits and allows withdrawal for non-compliance. Provides liability limitations for compliant participants.
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 minimal coverage of risk domains, primarily addressing privacy compromise (2.1) and security vulnerabilities (2.2) through privacy-enhancing technologies. It does not substantially address most AI-specific risks, focusing instead on data privacy and security governance mechanisms.
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 document governs all sectors that handle covered data, as it applies broadly to 'covered entities' without sector-specific limitations. The pilot program for privacy-enhancing technologies is sector-agnostic and available to any entity that collects, processes, or transfers covered data across all economic sectors.
Hard Law
Legislative Status Summary
This is a binding federal statute enacted by the United States Congress with mandatory compliance requirements, enforcement mechanisms through the Federal Trade Commission, civil penalties, and ongoing audit requirements for covered entities.
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 addresses the Deploy and Operate and Monitor stages of the AI lifecycle through its focus on implementing privacy-enhancing technologies in operational systems and establishing ongoing audit mechanisms. It also covers aspects of Plan and Design through the petition process requiring demonstration of security practices.
Terms relating to technical scope that are mentioned or implicitly referenced in the document
No technical scope terms identified.
Technical Scope Summary
The document does not explicitly mention AI models, AI systems, or any specific categories of AI (frontier, general purpose, task-specific, foundation models, generative, or predictive). It focuses on privacy-enhancing technologies as technical solutions for data security. There is no mention of compute thresholds or open-weight/open-source models.
Document data from AGORA, CSET Emerging Technology Observatory.