New York Bill A5309

• 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: 2023-03-07

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
• Lack of transparency or interpretability

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

• Unequal performance across groups
• Compromise of privacy
• Environmental harm
• Lack of capability or robustness

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

The document has minimal to good coverage of approximately 5-6 subdomains, with primary focus on unfair discrimination (1.1), privacy compromise (2.1), lack of transparency (7.4), and lack of robustness (7.3). Coverage is concentrated in discrimination/fairness, transparency requirements, and AI system reliability domains.

Sector coverage

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

• Public Administration (excl. National Security)

All other sectors had no coverage in this document.

Sectors Summary

This bill governs AI procurement across all sectors of New York state government operations. The primary sector governed is Public Administration (excluding National Security), as the bill applies to state units including governmental agencies, political subdivisions, and public benefit corporations. The governance extends to any sector where state government operates or procures AI systems.

Legislative Status

Hard Law

Legislative Status Summary

This is a binding legislative act that amends New York state finance law and executive law with mandatory procurement requirements for state units purchasing algorithmic decision systems. The bill uses mandatory language ('shall purchase') and establishes enforceable legal obligations.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Entities: New York State Assembly; M. of A. SOLAGES
• Summary: The bill was introduced by Member of Assembly SOLAGES and referred to the Committee on Governmental Operations, indicating it was proposed by the New York State Legislature.

Target

• Entity Types: AI_Governance_Actor, AI_Deployer
• Entities: state units; governmental agencies; political subdivisions; public benefit corporations of the state
• Summary: The bill explicitly targets state units purchasing algorithmic decision systems. State units are defined as 'the state and any governmental agency or political subdivision or public benefit corporation of the state.'

Enforcer

• Entity Types: AI_Governance_Actor
• Entities: commissioner of taxation and finance
• Summary: The commissioner of taxation and finance is explicitly designated with regulatory authority to implement and enforce the provisions of this subdivision.

Monitor

• Entity Types: AI_Governance_Actor
• Entities: commissioner of taxation and finance
• Summary: While not explicitly stated as a monitoring role, the commissioner of taxation and finance's regulatory authority implicitly includes monitoring compliance with the procurement standards established by the bill.

AI Lifecycle Stages

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

• Plan and Design
• Verify and Validate
• Deploy
• Operate and Monitor

AI Lifecycle Summary

The document primarily focuses on the procurement and deployment stages of AI systems by state units. It establishes requirements for purchasing algorithmic decision systems that adhere to responsible AI standards, with emphasis on transparency, fairness, harm avoidance, and risk evaluation. The document does not explicitly address data collection, model building, or ongoing operational monitoring stages.

Technical Scope

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

• AI Models
• AI Systems

Technical Scope Summary

The document explicitly defines and covers 'algorithmic decision systems' which encompasses AI systems broadly. 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 algorithmic decision systems that impact individuals, regardless of specific AI type or architecture.