Establishes policy for North Dakota's AI use to ensure safety, privacy, and ethical standards. Requires AI reliability, transparency, and accountability. Mandates risk management, privacy assessments, and compliance with legal frameworks. Directs NDIT to provide training and evaluate new AI technologies.
Good coverage — Comprehensive governance measures or mitigations with clear procedures relating to the risk subdomain are explicitly described.
Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the risk subdomain are described.
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 privacy compromise (2.1), AI system security (2.2), false information (3.1), lack of robustness (7.3), and lack of transparency (7.4). Coverage is concentrated in privacy/security, misinformation risks, and AI system safety domains. The policy addresses operational risks and governance but does not extensively cover malicious actor scenarios, socioeconomic impacts, or advanced AI safety concerns.
Good coverage — Comprehensive governance measures or mitigations with clear procedures relating to the sector are explicitly described.
Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the sector are described.
All other sectors had no coverage in this document.
Sectors Summary
This is an internal government policy that primarily governs AI use within the Public Administration sector. It applies to North Dakota executive branch state agencies and the University Systems Office, covering government operations and public services. The policy does not regulate private sector activities or other economic sectors.
Hard Law
Legislative Status Summary
This is a binding internal government policy with mandatory compliance requirements, enforcement mechanisms, and clear accountability structures for North Dakota executive branch agencies.
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Enforcer
Monitor
Lifecycle stages covered by the documents, as defined in the OECD Framework for the Classification of AI Systems
AI Lifecycle Summary
The document covers multiple AI lifecycle stages with primary focus on Deploy and Operate and Monitor stages. It addresses planning through risk assessment requirements, verification through validation and testing requirements, deployment through approval processes, and ongoing monitoring through regular assessments. The Build and Use Model stage receives minimal coverage, while data collection is not substantially addressed.
Terms relating to technical scope that are mentioned or implicitly referenced in the document
Technical Scope Summary
The document explicitly mentions AI, Machine Learning, Large Language Models, Deep Learning, and Generative AI with definitions provided. It does not mention frontier AI, general purpose AI, task-specific AI, foundation models, predictive AI, open-weight models, or compute thresholds. The focus is on generative AI tools and general AI/ML technologies used in government operations.
Document data from AGORA, CSET Emerging Technology Observatory.