FAA Research and Development Act of 2023, Sec. 215 ("Air Traffic Control Training")

• 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

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

• Lack of capability or robustness

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

The document has minimal coverage of AI risk domains, with only implicit mention of system safety concerns (7.3 Lack of robustness) through its focus on improving training effectiveness and performance. The document is primarily procedural, mandating research into AI technologies for training purposes rather than addressing specific AI risks.

Sector coverage

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

• Trade, Transportation & Utilities
• Public Administration (excl. National Security)

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

• Educational Services

All other sectors had no coverage in this document.

Sectors Summary

The document primarily governs the Trade, Transportation and Utilities sector, specifically air transportation and air traffic control services. It mandates research into AI technologies for training air traffic controllers within the national airspace system.

Legislative Status

Hard Law

Legislative Status Summary

This is a binding legislative act passed by the United States Congress with mandatory obligations on the FAA Administrator, including required research activities and Congressional reporting within specified timeframes.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Entities: United States Congress
• Summary: The document is Section 215 of the FAA Research and Development Act of 2023, which is federal legislation enacted by the United States Congress.

Target

• Entity Types: AI_Governance_Actor
• Entities: FAA Administrator; Federal Aviation Administration
• Summary: The legislation directly targets the FAA Administrator, requiring them to carry out research programs and submit reports. The research also involves collaboration with labor organizations and other stakeholders in the air traffic control domain.

Enforcer

• Entity Types: AI_Governance_Actor
• Entities: United States Congress; appropriate committees of Congress
• Summary: Congress enforces compliance through oversight mechanisms, including mandatory reporting requirements to Congressional committees and control over appropriations.

Monitor

• Entity Types: AI_Governance_Actor
• Entities: appropriate committees of Congress
• Summary: Congressional committees monitor implementation through the required report on research findings, which must be submitted within one year of enactment.

AI Lifecycle Stages

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

• Plan and Design
• Verify and Validate
• Deploy

AI Lifecycle Summary

The document primarily covers the Plan and Design stage by mandating research to assess AI technologies for air traffic control training. It also addresses Verify and Validate through requirements to evaluate proven technologies before deployment, and Deploy through the development of deployment timelines for accredited training programs.

Technical Scope

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

• AI Models

Technical Scope Summary

The document explicitly mentions artificial intelligence and machine learning as technologies to be assessed for air traffic control training. It does not define these terms or specify particular types of AI systems, models, or compute thresholds. The focus is on AI as a training tool rather than on specific AI architectures or capabilities.