Rhode Island SB 2083 (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

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
• Overreliance and unsafe use
• Lack of capability or robustness

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

The document has minimal coverage of approximately 3-4 subdomains, with focus on AI system safety and reliability (7.3), human-computer interaction risks related to overreliance (5.1), and potentially privacy concerns (2.1). Coverage is concentrated in system safety, failures, and limitations domain, with minimal attention to other risk areas.

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

The document primarily governs the Health Care and Social Assistance sector, specifically regulating AI-based eye assessment mechanisms used by licensed healthcare providers. It establishes comprehensive requirements for the use of AI in eye care services including patient interaction, verification procedures, and prescription generation.

Legislative Status

Hard Law

Legislative Status Summary

This is a binding state statute with mandatory requirements, civil penalties up to $10,000 per violation, enforcement mechanisms through the Department of Health and Attorney General, and administrative hearing procedures for violations.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Entities: Rhode Island State Legislature
• Summary: This is a state bill (SB 2083) passed by the Rhode Island legislature in 2022, indicating the state legislative body as the proposer of this governance instrument.

Target

• Entity Types: AI_Developer, AI_Deployer
• Entities: Persons operating assessment mechanisms in Rhode Island; Healthcare providers licensed under chapters 35.1 or 37 of title 5
• Summary: The law targets both persons who operate AI-based assessment mechanisms for eye care and healthcare providers who use these mechanisms to conduct eye assessments or generate prescriptions. The document defines 'person' broadly to include individuals, corporations, partnerships, and other legal entities.

Enforcer

• Entity Types: AI_Governance_Actor
• Entities: Rhode Island Department of Health; Office of the Attorney General
• Summary: The Department of Health is explicitly designated to enforce the law through rulemaking, administrative proceedings, and disciplinary actions. The Attorney General's office is also authorized to file complaints for violations.

Monitor

• Entity Types: AI_Governance_Actor
• Entities: Rhode Island Department of Health
• Summary: The Department of Health is implicitly responsible for monitoring compliance through its enforcement authority, rulemaking powers, and ability to bring administrative proceedings against violators.

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 eye assessment mechanisms must be deployed in Rhode Island and mandates ongoing provider oversight and verification during operation. There is minimal coverage of earlier lifecycle stages.

Technical Scope

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

• AI Systems
• Task-specific AI

Technical Scope Summary

The document explicitly mentions AI systems through its definition of 'assessment mechanism' which includes 'artificial intelligence devices.' It focuses on task-specific AI for eye assessments and does not mention general purpose AI, frontier AI, foundation models, generative AI, open-weight models, or compute thresholds.