Prohibits the wrongful publication of intimate visual images, including AI-generated digital forgeries, within military settings. Defines responsibilities and exemptions while establishing consent criteria. Emphasizes harm intentions in unlawful distributions. Expands definitions to cover AI-related manipulations and intimate visual depictions.
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 good coverage of approximately 4 risk subdomains, with strong focus on toxic content (1.2), privacy compromise (2.1), false information via deepfakes (3.1), and fraud/manipulation (4.3). Coverage is concentrated in content harm, privacy protection, and misuse prevention domains, specifically addressing AI-generated intimate imagery used to harm individuals.
Good coverage — Comprehensive governance measures or mitigations with clear procedures relating to the sector are explicitly described.
All other sectors had no coverage in this document.
Sectors Summary
This Act exclusively governs the National Security sector, as it applies only to persons subject to the Uniform Code of Military Justice (military personnel). It does not extend to civilian sectors or general commercial activities.
Hard Law
Legislative Status Summary
This is a binding federal statute enacted by the U.S. Congress that amends the Uniform Code of Military Justice with mandatory criminal prohibitions, court-martial enforcement mechanisms, and explicit criminal penalties for violations.
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 stages of the AI lifecycle, focusing on the use and distribution of AI-generated digital forgeries (deepfakes) after they have been created. It does not significantly address the planning, data collection, or model development stages, but rather governs the deployment and operational use of AI outputs in military contexts.
Terms relating to technical scope that are mentioned or implicitly referenced in the document
Technical Scope Summary
The document explicitly mentions artificial intelligence, machine learning, and software in the context of creating digital forgeries, but does not reference specific AI model types (frontier, GPAI, foundation models, etc.), compute thresholds, or distinctions between generative/predictive AI. The focus is on AI outputs (synthetic intimate imagery) rather than technical AI system characteristics.
Document data from AGORA, CSET Emerging Technology Observatory.