Responsible AI safety and education act

• Authority: New York
• Parent authority: State governments
• Jurisdiction: United States
• Collections: Editors' Picks;U.S. state and local documents
• Most recent activity: Proposed
• Most recent activity date: 2025-03-05

Risk subdomain coverage

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

• AI system security vulnerabilities
• Cyberattacks, weapon development or use
• Governance failure
• AI pursuing its own goals
• AI possessing dangerous capabilities
• 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
• Disinformation, surveillance, and influence at scale
• Fraud, scams, and targeted manipulation
• Loss of human agency and autonomy
• Competitive dynamics

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 malicious actors (4.1, 4.2, 4.3), AI system security (2.2), competitive dynamics (6.4), governance (6.5), and AI safety failures (7.1, 7.2, 7.3). Coverage is concentrated in security, misuse prevention, and AI safety domains.

Sector coverage

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

• Information
• Scientific Research & Development Services

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

• Educational Services
• Public Administration (excl. National Security)
• National Security

All other sectors had no coverage in this document.

Sectors Summary

This document does not govern AI use within specific economic sectors. Rather, it regulates large developers of frontier AI models regardless of the sector in which they operate. The regulation applies to the AI development industry itself (Information sector and Scientific Research and Development Services) but does not impose sector-specific requirements on AI deployment in healthcare, finance, or other application domains.

Legislative Status

Hard Law

Legislative Status Summary

This is a binding legislative act from the New York State Assembly that establishes mandatory requirements with civil penalties for non-compliance and enforcement by the Attorney General.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Summary: The document is a New York State Assembly bill introduced by multiple Assembly members and referred to various committees for consideration.

Target

• Entity Types: AI_Developer
• Summary: The act specifically targets 'large developers' who train frontier models with specific compute thresholds and cost requirements, imposing transparency, safety, and disclosure obligations on these entities.

Enforcer

• Entity Types: AI_Governance_Actor
• Summary: The Attorney General is explicitly granted enforcement authority to bring civil actions and impose penalties, while the Division of Homeland Security and Emergency Services receives safety incident disclosures and has access to safety protocols.

Monitor

• Entity Types: AI_Governance_Actor
• Summary: The same entities that enforce also monitor through receiving safety and security protocols, safety incident reports, and having access to unredacted documentation for oversight purposes.

AI Lifecycle Stages

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

• Plan and Design
• Build and Use Model
• 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, with some coverage of Build and Use Model and Verify and Validate stages. It establishes requirements for pre-deployment safety protocols, testing, and post-deployment monitoring and incident reporting for frontier AI models.

Technical Scope

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

• AI Models
• Frontier AI
• AI Systems
• Compute Threshold

Technical Scope Summary

The document explicitly defines and covers AI models, artificial intelligence systems, and frontier AI models with specific compute thresholds (10^26 operations, $100M+ compute cost). It does not explicitly mention general purpose AI, task-specific AI, foundation models, generative AI, predictive AI, or open-weight models. Compute thresholds are central to the regulatory framework.