Montana HJ 4 (Interim study of artificial intelligence)

• Authority: Montana
• Parent authority: State governments
• Jurisdiction: United States
• Collections: U.S. state and local documents
• Most recent activity: Enacted
• Most recent activity date: 2025-01-27

Risk subdomain coverage

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

• Compromise of privacy
• Loss of human agency and autonomy
• Increased inequality and decline in employment
• Economic and cultural devaluation of human effort
• Governance failure
• Lack of transparency or interpretability

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

This document has minimal coverage of risk domains as it is a legislative resolution requesting a study rather than implementing governance measures. It briefly mentions 3-4 risk-related topics to be studied including privacy interests, employment and economic impacts, transparency requirements, and governance structures. Coverage scores are low (2) as these are mentioned only as study topics without substantive discussion of the risks themselves.

Sector coverage

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

• Public Administration (excl. National Security)

All other sectors had no coverage in this document.

Sectors Summary

This document primarily concerns Public Administration, as it directs state agencies to conduct a study on AI regulation and mentions developing an AI code of ethics for state agencies. It does not directly govern any private sector industries, though the study will examine impacts across Montana's economy broadly.

Legislative Status

Other

Legislative Status Summary

This is an internal legislative process document - a joint resolution directing the Legislative Council to conduct an interim study on AI. It is not binding law that creates legal obligations, nor is it soft law guidance for external parties. It is a procedural directive for legislative research and does not regulate AI development or deployment.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Entities: Montana Senate; Montana House of Representatives
• Summary: The document is explicitly authored and proposed by the Montana state legislature as indicated by the title and resolution language.

Target

• Entity Types: AI_Governance_Actor
• Entities: Montana Legislative Council; appropriate interim committee or statutory committee
• Summary: The resolution directs the Legislative Council to conduct the study through designated committees or staff. The study will examine entities that develop or deploy AI systems, but the resolution itself targets the Legislative Council for action.

Enforcer

• Summary: This resolution does not establish enforcement mechanisms as it is a directive for a study, not binding regulation.

Monitor

• Entity Types: AI_Governance_Actor
• Entities: Montana Legislative Council; appropriate committee designated by the Legislative Council; 70th Legislature
• Summary: The Legislative Council will oversee the study, with findings reviewed by a designated committee and ultimately reported to the 70th Legislature.

AI Lifecycle Stages

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

• Build and Use Model
• Deploy
• Operate and Monitor

AI Lifecycle Summary

The document references multiple lifecycle stages by directing study of entities that 'develop or deploy' AI systems, implicitly covering development, deployment, and operational stages. However, as this is a study directive rather than regulatory document, it does not substantively govern any particular lifecycle stage.

Technical Scope

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

• AI Systems

Technical Scope Summary

The document uses only the general term 'artificial intelligence' without defining it or distinguishing between different AI types, models, or systems. There is no mention of technical specifications, compute thresholds, or specific AI architectures.