Sensible Classification Act of 2023, Sec. 7: Implementation of Technology for Classification and Declassification

• 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.

• AI system security vulnerabilities

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

The document has minimal coverage of risk domains, with only subdomain 2.2 (AI system security vulnerabilities) receiving a score above 1. The focus is on implementing AI/ML technology for classification/declassification systems rather than addressing AI risks comprehensively.

Sector coverage

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

• Public Administration (excl. National Security)
• National Security

All other sectors had no coverage in this document.

Sectors Summary

This document exclusively governs Public Administration and National Security sectors, requiring federal government agencies including defense and intelligence organizations to implement AI/ML technology for classification and declassification of national security information.

Legislative Status

Hard Law

Legislative Status Summary

This is a binding legislative act from the United States Congress with mandatory language requiring specific actions by federal officials within defined timeframes.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Entities: United States Congress
• Summary: The document is titled 'Sensible Classification Act of 2023' and is identified as being from the United States Congress, indicating Congress as the proposing authority for this legislation.

Target

• Entity Types: AI_Governance_Actor, AI_Developer
• Entities: Administrator of the Office of Electronic Government of the Office of Management and Budget; Secretary of Defense; Director of the Central Intelligence Agency; Director of National Intelligence; Director of the Information Security Oversight Office; head of the National Declassification Center of the National Archives and Records Administration; Public Interest Declassification Board; the President; Federal Government
• Summary: The document targets federal government officials and agencies who must research, implement, and adopt AI/ML technology solutions for classification and declassification systems across the Federal Government.

Enforcer

• Entity Types: AI_Governance_Actor
• Entities: Congress; the President
• Summary: Congress serves as the enforcement body through its oversight authority, requiring mandatory reports from the Administrator and the President. The President also has enforcement authority in determining adoption of the recommended technology solution.

Monitor

• Entity Types: AI_Governance_Actor
• Entities: Congress; the President
• Summary: Congress monitors implementation through mandatory reporting requirements, while the President monitors the Administrator's recommendations and makes determinations regarding adoption.

AI Lifecycle Stages

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

• Plan and Design
• Deploy
• Operate and Monitor

AI Lifecycle Summary

The document primarily covers the Plan and Design stage by requiring research into AI/ML technology solutions for classification systems. It also addresses Deploy stage through requirements for interoperable implementation across the Federal Government, and implicitly touches on Operate and Monitor through the ongoing nature of classification/declassification systems.

Technical Scope

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

• AI Models
• AI Systems
• Task-specific AI

Technical Scope Summary

The document explicitly mentions both machine learning and artificial intelligence as technologies to be researched and implemented. It does not specify particular AI model types, compute thresholds, or distinguish between general purpose and task-specific AI. The focus is on AI/ML as enabling technologies for classification/declassification systems.