Utah HB 464 (Social Media Amendments)

• Authority: Utah
• Parent authority: State governments
• Jurisdiction: United States
• Collections: U.S. state and local documents
• Most recent activity: Enacted
• Most recent activity date: 2024-03-13

Risk subdomain coverage

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

• Exposure to toxic content

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

The document primarily addresses risks in the Human-Computer Interaction domain (5.1, 5.2) with strong focus on overreliance and loss of agency for minors. It also covers Discrimination & Toxicity (1.2) through content exposure protections, and Socioeconomic & Environmental concerns (6.2) regarding impacts on minors' well-being. Coverage is concentrated on protecting minors from excessive social media use and its mental health consequences.

Sector coverage

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

• Information

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

• Health Care & Social Assistance

All other sectors had no coverage in this document.

Sectors Summary

The document exclusively governs the Information sector, specifically social media companies that operate algorithmically curated social media services. The regulation focuses on platforms that use curation algorithms and engagement-driven design elements to deliver content to users.

Legislative Status

Hard Law

Legislative Status Summary

This is a binding state statute enacted by the Utah Legislature establishing legal obligations, private rights of action, civil penalties, and court enforcement mechanisms for social media companies regarding minors' use of algorithmically curated services.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Entities: Utah Legislature
• Summary: The document is a legislative bill enacted by the Utah Legislature, as indicated by the opening phrase and legislative structure.

Target

• Entity Types: AI_Deployer, AI_Developer
• Entities: social media companies operating algorithmically curated social media services
• Summary: The law explicitly targets social media companies that operate algorithmically curated services, imposing requirements for parental consent, usage limits, and liability for mental health harms to minors.

Enforcer

• Entity Types: AI_Governance_Actor, Affected_Stakeholder
• Entities: Utah courts, parents/legal guardians of minors, Utah minor account holders
• Summary: Enforcement is primarily through private rights of action brought by minors or their parents in court, with courts adjudicating claims and awarding damages. There is no designated regulatory agency for enforcement.

Monitor

• Summary: The document does not establish any specific monitoring body or oversight mechanism. Compliance is enforced through private litigation rather than regulatory 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 primarily addresses the Deploy and Operate and Monitor stages of AI lifecycle, focusing on requirements for deployed algorithmically curated social media services and their ongoing operation with minors. It does not address earlier stages like planning, data collection, or model building.

Technical Scope

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

No technical scope terms identified.

Technical Scope Summary

The document explicitly addresses algorithmically curated social media services, focusing on curation algorithms and engagement driven design elements. It does not use standard AI terminology like 'AI models' or 'AI systems' but clearly regulates algorithmic systems. No compute thresholds, foundation models, or distinctions between generative/predictive AI are mentioned.