CREATE AI 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.

• Compromise of privacy
• AI system security vulnerabilities
• Power centralization and unfair distribution
• Governance failure

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

• Increased inequality and decline in employment
• Competitive dynamics
• Lack of capability or robustness

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

The document has minimal to good coverage of approximately 6-8 subdomains, with primary focus on governance structures (6.5), power centralization (6.1), inequality (6.2), privacy (2.1), security vulnerabilities (2.2), and system robustness (7.3). Coverage is concentrated in socioeconomic, privacy/security, and system safety domains, with emphasis on democratizing AI access and establishing oversight mechanisms.

Sector coverage

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

• Scientific Research & Development Services
• Educational Services

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

• Professional & Technical Services
• Public Administration (excl. National Security)
• National Security

All other sectors had no coverage in this document.

Sectors Summary

This document primarily governs AI research and development activities across the Scientific Research and Development Services sector and Educational Services sector. It establishes infrastructure for AI research accessible to researchers, educators, and students, with secondary applicability to Public Administration (federal agencies) and Professional and Technical Services (small businesses receiving federal funding).

Legislative Status

Hard Law

Legislative Status Summary

This is a binding legislative act passed by the United States Congress establishing the National Artificial Intelligence Research Resource with mandatory obligations, enforcement mechanisms, and formal legal authority. The document uses mandatory language throughout ('shall') and creates legally binding requirements for federal agencies.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Summary: The document is a Congressional bill enacted by the legislative branch of the United States government, as indicated by the opening enactment clause.

Target

• Entity Types: AI_Developer, AI_Deployer, AI_User, AI_Infrastructure_Provider
• Summary: The Act explicitly defines eligible users who can access the NAIRR resources, including researchers, students, educators, and employees of various entities. These users will develop, deploy, and use AI systems using NAIRR resources.

Enforcer

• Entity Types: AI_Governance_Actor
• Summary: The Act establishes multiple governance bodies with enforcement and oversight authority, including the NSF as the primary agency, the NAIRR Steering Subcommittee for strategic oversight, and the Program Management Office for operational enforcement.

Monitor

• Entity Types: AI_Governance_Actor
• Summary: The Act establishes comprehensive monitoring mechanisms through multiple bodies that evaluate performance, conduct audits, and provide oversight of NAIRR operations and compliance.

AI Lifecycle Stages

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

• Plan and Design
• Collect and Process Data
• Build and Use Model
• Verify and Validate
• Deploy
• Operate and Monitor

AI Lifecycle Summary

The document covers multiple AI lifecycle stages with primary focus on Build and Use Model (providing computational resources and data for model development), Verify and Validate (establishing testbeds for testing and benchmarking), and Operate and Monitor (ongoing oversight and evaluation). It also addresses Plan and Design through governance structures and Deploy through access provisioning.

Technical Scope

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

• AI Models
• AI Systems
• Open Weight / Open Source

Technical Scope Summary

The document explicitly mentions AI systems, AI models, and AI testbeds. It does not specifically define or mention frontier AI, general purpose AI, task-specific AI, foundation models, generative AI, predictive AI, or compute thresholds. There is one reference to open source software environments but not specifically to open-weight models.