statements ยท statement-BATCH-2026-006-008

source-BATCH-2026-005-002

Organizations can use structured public feedback to test whether a system behaves as intended and to inform lifecycle decisions.

Statement context

Statement type
recommendation
Exact source locator
PDF file p. 53 (document p. 49), Appendix A.1.5 "Structured Public Feedback", July 2024 version
Source date
Unknown
Role at source time
institutional author of the NIST AI RMF profile
Evidence character
normative recommendation
Scope
Participatory engagement, field testing, and red-teaming for generative-AI systems.

Recorded uncertainty: The profile describes possible uses and does not estimate effectiveness.

Indexed source: Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile

Evidence lineage and transparency

Relationship fieldLinked identifiers
topic idstopic-ai-agents, topic-ai-governance, topic-cybersecurity, topic-non-human-identity

Machine review: machine checked. Human review: approved. Workflow: published.

Complete structured record
statement id
statement-BATCH-2026-006-008
source id
source-BATCH-2026-005-002
person id
Unknown
institutional author
National Institute of Standards and Technology
book edition id
Unknown
speaker role at source time
institutional author of the NIST AI RMF profile
organization at source time
National Institute of Standards and Technology
statement type
recommendation
neutral paraphrase
Organizations can use structured public feedback to test whether a system behaves as intended and to inform lifecycle decisions.
direct quote
Unknown
direct quote rights note
Unknown
exact locator
PDF file p. 53 (document p. 49), Appendix A.1.5 "Structured Public Feedback", July 2024 version
locator type
pdf_page
source date
Unknown
topic ids
topic-ai-agents, topic-ai-governance, topic-cybersecurity, topic-non-human-identity
executive role context
role-ciso, role-cio, role-cto, role-general-counsel, role-board-director
industry context
cross-sector
geographic context
United States, cross-sectoral global applicability
evidence character
normative_recommendation
factual verification status
not_applicable
statement scope
Participatory engagement, field testing, and red-teaming for generative-AI systems.
uncertainty
The profile describes possible uses and does not estimate effectiveness.
extraction method
Machine-assisted close reading of the exact verified source version; original neutral paraphrase; human review pending.
machine extraction confidence
0.94
independent agent review status
not_started
publication status
published
workflow status
published
machine review status
machine_checked
human review status
approved
reviewed by
Murray Newlands
reviewed at
2026-08-16T23:17:22Z
Provenance and revision history
{
  "provenance": [
    {
      "source_url": "https://nvlpubs.nist.gov/nistpubs/ai/NIST.AI.600-1.pdf",
      "accessed_at": "2026-08-15",
      "retrieval_method": "Exact verified source version inherited from BATCH-2026-005 and statement-level close reading",
      "exact_locator": "PDF file p. 53 (document p. 49), Appendix A.1.5 \"Structured Public Feedback\", July 2024 version",
      "content_hash": "6e73620ab6b64e90ef2c04bf0e0d6246185a2f4b1b13cab0df494496cff89b6a",
      "batch_id": "BATCH-2026-006",
      "prompt_id": "OEII-STATEMENT-CODING",
      "prompt_version": "2.0",
      "notes": "Source eligibility inherited from source-BATCH-2026-005-002; human attribution and publication review pending."
    }
  ],
  "revision_history": [
    {
      "changed_at": "2026-08-16T23:17:22Z",
      "changed_by": "Murray Newlands",
      "summary": "Approved for the governed-identities pilot release under the exact scope, exclusions, rights treatment, and limitations recorded in issue #18.",
      "batch_id": "BATCH-2026-006"
    }
  ]
}

Open machine-readable record