Servicemember Quality of Life Improvement and National Defense Authorization Act for Fiscal Year 2025, Section 233 ("Management and utilization of digital data to enhance maintenance activities")

• Authority: United States Congress
• Parent authority: Federal government
• Jurisdiction: United States
• Collections: FY2025 NDAA;NDAA provisions
• Most recent activity: Enacted
• Most recent activity date: 2024-12-23

Risk subdomain coverage

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

• AI system security vulnerabilities
• Governance failure

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

The document has minimal coverage of risk domains, with limited focus on AI system security (2.2) and governance failure (6.5). The document primarily addresses technical infrastructure and data management policies rather than AI-specific risks and harms.

Sector coverage

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

• National Security

All other sectors had no coverage in this document.

Sectors Summary

This document exclusively governs the National Security sector, specifically addressing Department of Defense maintenance activities for military aircraft, ships, and ground vehicles using AI and digital data systems.

Legislative Status

Hard Law

Legislative Status Summary

This is a binding federal statute enacted by the United States Congress as part of the National Defense Authorization Act for Fiscal Year 2025, with mandatory requirements and specific implementation timelines.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Entities: United States Congress
• Summary: This section is part of the Servicemember Quality of Life Improvement and National Defense Authorization Act for Fiscal Year 2025, which is enacted by the United States Congress as the legislative authority.

Target

• Entity Types: AI_Governance_Actor, AI_Deployer
• Entities: Under Secretary of Defense for Acquisition and Sustainment; Secretaries of the military departments; Chief Digital and Artificial Intelligence Officer of the Department of Defense; vendors
• Summary: The document targets Department of Defense entities responsible for developing and implementing AI and data management policies for military maintenance activities, as well as vendors who provide proprietary systems and data.

Enforcer

• Entity Types: AI_Governance_Actor
• Entities: Committees on Armed Services of the Senate and the House of Representatives; Under Secretary of Defense for Acquisition and Sustainment
• Summary: Congressional oversight is provided through the Armed Services Committees, which receive mandatory briefings. The Under Secretary has implementation authority and is accountable for policy development and execution.

Monitor

• Entity Types: AI_Governance_Actor
• Entities: Committees on Armed Services of the Senate and the House of Representatives
• Summary: The Congressional Armed Services Committees monitor implementation through mandatory briefings on policy development and implementation status.

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
• Deploy
• Operate and Monitor

AI Lifecycle Summary

The document primarily addresses the Deploy and Operate and Monitor stages of the AI lifecycle, focusing on implementing AI and automated systems for maintenance data management and establishing ongoing monitoring protocols. It also covers aspects of Plan and Design through required strategy development.

Technical Scope

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

• AI Systems

Technical Scope Summary

The document explicitly mentions artificial intelligence and automated systems in the context of military maintenance data management. It does not specify particular AI model types, compute thresholds, or distinguish between frontier, general purpose, or task-specific AI.