Minnesota House Bill 4772

• Authority: Minnesota
• Parent authority: State governments
• Jurisdiction: United States
• Collections: U.S. state and local documents
• Most recent activity: Enacted
• Most recent activity date: 2024-05-17

Risk subdomain coverage

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

• False or misleading information
• Disinformation, surveillance, and influence at scale
• Fraud, scams, and targeted manipulation

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

• Pollution of information ecosystem
• Cyberattacks, weapon development or use
• AI possessing dangerous capabilities

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

The document has good coverage of approximately 4-5 subdomains, with strong focus on malicious actors (4.1 Disinformation, surveillance, and influence at scale; 4.3 Fraud, scams, and targeted manipulation), misinformation (3.1 False or misleading information), and AI system capabilities (7.2 Dangerous capabilities). Coverage is concentrated in the malicious use and misinformation domains.

Sector coverage

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

• Information
• Public Administration (excl. National Security)

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

• Arts, Entertainment & Recreation

All other sectors had no coverage in this document.

Sectors Summary

The document primarily governs the Information sector (broadcasting, telecommunications, data processing) and Public Administration (election processes). It also has implications for Arts, Entertainment, and Recreation through its regulation of media content dissemination.

Legislative Status

Hard Law

Legislative Status Summary

This is a binding criminal statute with explicit enforcement mechanisms including imprisonment, fines, and disqualification from office for violations.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Entities: Minnesota Legislature; Minnesota House
• Summary: This is Minnesota House Bill 4772, which amends Minnesota Statutes 2023 Supplement, section 609.771. The proposer is the Minnesota state legislative body.

Target

• Entity Types: Affected_Stakeholder
• Entities: Individuals disseminating deep fakes; Candidates for state or local office; Broadcasters; Cable television systems
• Summary: The statute targets any person who disseminates deep fakes to influence elections, with specific provisions for candidates and exemptions for broadcasters required by federal law to disseminate content.

Enforcer

• Entity Types: AI_Governance_Actor
• Entities: Minnesota courts; Minnesota criminal justice system
• Summary: The statute is enforced through the Minnesota criminal justice system, with courts having authority to impose sentences, fines, and supplemental judgments declaring forfeiture of office.

Monitor

• Summary: The document does not specify any monitoring body or oversight mechanism. Enforcement appears to rely on criminal prosecution after violations occur rather than proactive monitoring.

AI Lifecycle Stages

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

• Deploy
• Operate and Monitor

AI Lifecycle Summary

The document does not focus on AI development lifecycle stages but rather on the deployment and use of deep fake technology in specific contexts (election influence). It primarily addresses the Deploy and Operate stages through restrictions on dissemination.

Technical Scope

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

• Generative AI

Technical Scope Summary

The document explicitly mentions deep fakes (a form of generative AI) but does not define or discuss AI models, AI systems, frontier AI, general purpose AI, foundation models, compute thresholds, or open-weight models. The focus is narrowly on the output (deep fakes) rather than the underlying AI technology.