Rhode Island HB 6654 (2022)

• Authority: Rhode Island
• Parent authority: State governments
• Jurisdiction: United States
• Collections: U.S. state and local documents
• Most recent activity: Enacted
• Most recent activity date: 2022-06-29

Risk subdomain coverage

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

• Overreliance and unsafe use

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

• Compromise of privacy
• Fraud, scams, and targeted manipulation
• Lack of capability or robustness

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

The document has minimal coverage of AI risk domains, with limited focus on system safety and failures (7.3 - lack of robustness) and human-computer interaction (5.1 - overreliance). The legislation primarily addresses procedural safeguards for AI-assisted eye assessments rather than comprehensive AI risk mitigation. Coverage is concentrated in ensuring clinical standards and preventing inappropriate reliance on automated assessments.

Sector coverage

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

• Health Care & Social Assistance

All other sectors had no coverage in this document.

Sectors Summary

This legislation specifically governs AI use in the Health Care and Social Assistance sector, with focused regulation of eye care services including optometry and ophthalmology. The document establishes comprehensive requirements for providers using AI-based assessment mechanisms to conduct eye assessments and generate prescriptions.

Legislative Status

Hard Law

Legislative Status Summary

This is a binding state statute enacted by the Rhode Island legislature with mandatory requirements, civil penalties up to $10,000 per violation, and enforcement mechanisms through the Department of Health and Attorney General's office.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Summary: This is a House Bill (HB 6654) enacted by the Rhode Island state legislature in 2022, as indicated by the document title and the legislative format including 'SECTION 1' and 'SECTION 2' structure typical of state statutes.

Target

• Entity Types: AI_Developer, AI_Deployer
• Summary: The statute applies to any 'person' who uses assessment mechanisms (including AI devices) to conduct eye assessments, and specifically regulates 'providers' who are licensed healthcare professionals using these technologies to generate prescriptions.

Enforcer

• Entity Types: AI_Governance_Actor
• Summary: The statute explicitly designates the Department of Health and the Office of the Attorney General as enforcement bodies with authority to file complaints, conduct administrative hearings, and impose civil penalties.

Monitor

• Entity Types: AI_Governance_Actor
• Summary: The Department of Health is granted authority to promulgate rules and regulations, enforce compliance, and take disciplinary action, which implies ongoing monitoring responsibilities for implementation and compliance with the statute.

AI Lifecycle Stages

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

• Collect and Process Data
• Verify and Validate
• Deploy
• Operate and Monitor

AI Lifecycle Summary

The document primarily focuses on the Deploy and Operate and Monitor stages of the AI lifecycle. It establishes requirements for how AI-based assessment mechanisms must be deployed in clinical practice and mandates ongoing operational standards including record-keeping, patient verification, and adherence to clinical care standards during use.

Technical Scope

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

• Task-specific AI

Technical Scope Summary

The document explicitly mentions AI devices as a type of assessment mechanism but does not define or distinguish between AI models, AI systems, or specific categories like frontier AI, general purpose AI, or foundation models. It takes a broad, technology-neutral approach to regulating automated assessment mechanisms regardless of their underlying AI architecture.