New York S 9104 (Establishes the position of chief artificial intelligence officer)

• Authority: New York
• Parent authority: State governments
• Jurisdiction: United States
• Collections: U.S. state and local documents
• Most recent activity: Enacted
• Most recent activity date: 2024-06-04

Risk subdomain coverage

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

• Unfair discrimination and misrepresentation
• Compromise of privacy
• AI system security vulnerabilities
• False or misleading information
• Disinformation, surveillance, and influence at scale
• Fraud, scams, and targeted manipulation
• AI pursuing its own goals
• Lack of capability or robustness
• Lack of transparency or interpretability

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

The document provides minimal to good coverage of approximately 8-9 risk subdomains, with primary focus on discrimination (1.1), privacy and security (2.1, 2.2), misinformation (3.1, 4.1), fraud and manipulation (4.3), AI system performance and robustness (7.1, 7.3), and transparency (7.4). Coverage is concentrated in governance mechanisms to mitigate these risks within state government AI use.

Sector coverage

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

• Public Administration (excl. National Security)

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

• Scientific Research & Development Services
• Educational Services
• Health Care & Social Assistance

All other sectors had no coverage in this document.

Sectors Summary

This document exclusively governs AI use within New York State government agencies, boards, commissions, and authorities, falling squarely within the Public Administration sector. It does not directly regulate AI use in private sector industries, though advisory functions may touch on various sectors where state government operations intersect.

Legislative Status

Hard Law

Legislative Status Summary

This is a binding legislative enactment by the New York State Legislature that uses mandatory language throughout and establishes legally enforceable obligations for state agencies regarding AI governance.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Summary: The document is a legislative bill proposed by the New York State Legislature, as indicated by the formal enactment language and bill number (S 9104).

Target

• Entity Types: AI_Governance_Actor
• Summary: The bill explicitly targets state governmental entities that use, develop, procure, or deploy AI systems and automated decision-making systems.

Enforcer

• Entity Types: AI_Governance_Actor
• Summary: The bill establishes the Chief AI Officer and Office of AI with explicit authority to investigate, audit, and recommend deactivation of non-compliant AI systems used by state agencies.

Monitor

• Entity Types: AI_Governance_Actor
• Summary: The Chief AI Officer has explicit monitoring and auditing duties, supported by an Advisory Committee, with annual reporting requirements to the Legislature.

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 addresses multiple AI lifecycle stages with primary emphasis on Plan and Design, Verify and Validate, Deploy, and Operate and Monitor stages. It covers governance frameworks from initial planning through ongoing operational oversight of AI systems used by state agencies.

Technical Scope

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

• AI Models
• AI Systems
• Predictive AI

Technical Scope Summary

The document explicitly defines and covers both AI and automated decision-making systems broadly. It does not distinguish between frontier AI, general purpose AI, task-specific AI, foundation models, or set compute thresholds. The definitions are technology-neutral and comprehensive.