§32 · Lane 7 — Australian Regulatory Primary Instruments

NIST AI 600-1 — Generative AI Profile mapped to AU Voluntary AI Safety Standard

NIST (2024) · NIST AI 600-1

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Bibliographic data

Title
NIST AI 600-1 — Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile (July 2024)
Authors / Issuing body
National Institute of Standards and Technology (NIST), U.S. Department of Commerce
Venue / Publisher
U.S. Department of Commerce, NIST
Year
2024
Designation
Standard
Licence
Stable URL — refer to publisher for full licence terms.

How to cite

NIST (2024). NIST AI 600-1 — Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile (July 2024). U.S. Department of Commerce, NIST. https://www.nist.gov/itl/ai-risk-management-framework.

The generative-AI specific profile of the NIST AI RMF. Identifies twelve risk categories unique or exacerbated by generative AI — confabulation, dangerous content, data privacy, environmental, human-AI configuration, information integrity, information security, intellectual property, obscene content, toxicity, value chain, and value alignment — and recommends 200+ actions across the Govern / Map / Measure / Manage functions.

Why it matters for NETEVO

The 600-1 profile is the most operationally detailed international document on generative-AI specific governance. Two operational consequences follow.

First, the twelve risk categories — confabulation, dangerous content, data privacy, environmental, human-AI configuration, information integrity, information security, intellectual property, obscene content, toxicity, value chain, and value alignment, each unique to or exacerbated by generative AI — pair cleanly with the harms-and-benefits taxonomy in Annex C of the ISO/IEC 42005 impact assessment standard. They supply a generative-AI specific overlay for an AI impact assessment workflow without abandoning the ISO/IEC schema.

Second, the 200+ recommended actions, organised across the Govern / Map / Measure / Manage functions, read as a procurement-ready checklist for any organisation deploying generative AI. Many Australian organisations are deploying generative AI ahead of clear AU regulatory expectations on the modality; 600-1 fills that gap with US-authored but internationally citable substance. Cross-walked into the language of the NSW AIAF and the Voluntary AI Safety Standard, those actions become an AU-readable artefact backed by the most detailed international guidance on generative-AI risk.

One boundary matters. NIST AI 600-1 is properly read as a cross-jurisdictional benchmark — the document to reach for when generative-AI specificity is needed — not as the Australian regulatory anchor.

Where NETEVO applies this

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