AI in Government Act of 2020

• Authority: United States Congress
• Parent authority: Federal government
• Jurisdiction: United States
• Collections: U.S. federal laws
• Most recent activity: Enacted
• Most recent activity date: 2020-12-27

Risk subdomain coverage

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

• Governance failure

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

• Unfair discrimination and misrepresentation
• Unequal performance across groups
• Compromise of privacy
• AI system security vulnerabilities
• Lack of transparency or interpretability

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

The document has minimal coverage of risk domains, with primary focus on governance structures (6.5) and bias mitigation (1.1, 1.3). Coverage is limited to establishing institutional frameworks and identifying best practices for bias mitigation, rather than comprehensive risk management across multiple domains.

Sector coverage

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

• Public Administration (excl. National Security)

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

• Scientific Research & Development Services
• National Security

All other sectors had no coverage in this document.

Sectors Summary

This document exclusively governs the Public Administration sector, specifically federal government agencies' use of artificial intelligence. It does not regulate private sector activities or specific industries outside of federal government operations.

Legislative Status

Hard Law

Legislative Status Summary

This is a binding legislative act passed by the United States Congress with mandatory obligations, specific timelines, and designated enforcement authorities.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Summary: This is an Act of Congress, as indicated by the legislative format and citation structure. Congress is the proposing authority for this federal legislation.

Target

• Entity Types: AI_Governance_Actor, AI_Deployer
• Summary: The Act applies to federal agencies that use or plan to use artificial intelligence technologies. Multiple specific agencies are named as targets for coordination and compliance requirements.

Enforcer

• Entity Types: AI_Governance_Actor
• Summary: The Director of OMB is designated to issue binding memoranda and receive agency compliance plans. The Administrator of GSA manages the AI CoE. The Director of OPM establishes occupational standards. These entities have oversight and enforcement authority.

Monitor

• Entity Types: AI_Governance_Actor
• Summary: The AI CoE is established to monitor and facilitate AI adoption across government. The Director receives and reviews agency plans. Congressional committees receive reports for oversight purposes.

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 deployment and operational monitoring. It addresses planning through the AI CoE's advisory functions, data management policies, and ongoing monitoring through public reporting and periodic updates.

Technical Scope

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

• AI Models
• AI Systems

Technical Scope Summary

The document explicitly mentions 'artificial intelligence' and 'AI technologies' throughout but does not define specific technical categories such as frontier AI, general purpose AI, foundation models, or compute thresholds. It references AI algorithms and data training but remains technology-neutral in its approach.