New York artificial intelligence act (New York AI act)

• Authority: New York
• Parent authority: State governments
• Jurisdiction: United States
• Collections: U.S. state and local documents
• Most recent activity: Proposed
• Most recent activity date: 2025-01-08

Risk subdomain coverage

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

• Unfair discrimination and misrepresentation
• Unequal performance across groups
• Governance failure
• Lack of capability or robustness
• Lack of transparency or interpretability

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

• Compromise of privacy
• AI system security vulnerabilities
• False or misleading information
• Overreliance and unsafe use
• Loss of human agency and autonomy

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

The document has good coverage of approximately 8-10 subdomains, with strong focus on discrimination and toxicity (1.1, 1.3), privacy compromise (2.1), misinformation (3.1), governance failure (6.5), and AI system safety failures (7.3, 7.4). Coverage is concentrated in fairness, transparency, and accountability domains with emphasis on preventing algorithmic discrimination in high-risk AI systems.

Sector coverage

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

• Finance & Insurance
• Management, Administrative & Support Services
• Educational Services
• Health Care & Social Assistance
• Public Administration (excl. National Security)

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

• Trade, Transportation & Utilities
• Information
• Real Estate, Rental & Leasing

All other sectors had no coverage in this document.

Sectors Summary

The document governs AI use across multiple sectors through its definition of 'consequential decisions' which explicitly covers employment, education, housing, utilities, healthcare, financial services, legal services, and government services. The act applies broadly to any sector where AI systems make decisions affecting important life chances of New York residents.

Legislative Status

Hard Law

Legislative Status Summary

This is a binding legislative act with mandatory obligations, enforcement mechanisms including civil penalties up to $20,000 per violation, injunctive relief, private right of action, and enforcement by the Attorney General. The document uses mandatory language throughout ('shall', 'must', 'required') and creates legally enforceable obligations for AI developers and deployers.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Entities: New York State Legislature; Senator Gonzalez
• Summary: The document is a legislative bill introduced by Senator Gonzalez to the New York State Senate, as indicated in the header and introduction section.

Target

• Entity Types: AI_Developer, AI_Deployer
• Summary: The act explicitly targets developers and deployers of high-risk AI systems, defining these entities and imposing comprehensive obligations on them including audits, reporting, risk management, and liability for algorithmic discrimination.

Enforcer

• Entity Types: AI_Governance_Actor
• Entities: New York Attorney General; New York Supreme Court
• Summary: The Attorney General is designated as the primary enforcement authority with powers to investigate, promulgate rules, receive reports and audits, and bring enforcement actions. The Supreme Court has jurisdiction over enforcement proceedings and private actions.

Monitor

• Entity Types: AI_Governance_Actor, Affected_Stakeholder
• Entities: New York Attorney General; Independent Auditors
• Summary: The Attorney General maintains oversight through receipt of reports and audits, maintenance of a public database, and evaluation of risk management programs. Independent third-party auditors are required to conduct regular audits of high-risk AI systems. End users and employees also have monitoring roles through appeal rights and whistleblower protections.

AI Lifecycle Stages

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

• Plan and Design
• Collect and Process Data
• Build and Use Model
• Verify and Validate
• Deploy
• Operate and Monitor

AI Lifecycle Summary

The document comprehensively covers multiple AI lifecycle stages with particular emphasis on verification/validation, deployment, and operation/monitoring. It addresses planning through risk management requirements, data collection through training data documentation, model building through developer obligations, and extensively covers testing, deployment notification, and ongoing monitoring requirements.

Technical Scope

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

• AI Systems

Technical Scope Summary

The document explicitly defines and covers AI systems broadly, with detailed definitions of high-risk AI systems that make consequential decisions. It does not specifically mention frontier AI, general purpose AI, foundation models, generative AI, predictive AI, open-weight models, or compute thresholds. The focus is on AI systems used for consequential decisions regardless of their technical architecture.