APPLIED GUIDE
Human review in AI workflows
Human review works when the reviewer has authority, context, time, and clear rejection criteria. A checkbox after an opaque output is not meaningful oversight. Review should happen before irreversible actions and focus on the failure modes that matter.
Recommended process
Human review works when the reviewer has authority, context, time, and clear rejection criteria. A checkbox after an opaque output is not meaningful oversight. Review should happen before irreversible actions and focus on the failure modes that matter.
- Name the accountable role, not ‘the human.’
- Give the reviewer original sources and relevant context.
- Define reject, correct, escalate, and approve paths.
Review checklist
Use this checklist before accepting the output or turning it into an action.
- Sample routine cases and review every high-impact exception.
- Track overrides and repeated failure patterns.
CONCRETE EXAMPLE
Observable result
An AI drafts incident summaries, but a supervisor verifies facts and uncertainty before the record enters the official system.
- Name the accountable role, not ‘the human.’
- Give the reviewer original sources and relevant context.
- Define reject, correct, escalate, and approve paths.
PRIMARY SOURCES
Check the basis for this guide.
NIST · 2023
AI Risk Management Framework 1.0
NIST · 2023
NIST AI RMF Playbook
NIST · 2024
Generative AI Profile — NIST AI 600-1
Frequently asked questions
Can human review make any AI workflow safe?
No. Some uses should be prohibited or narrowed because reviewers lack reliable evidence, time, authority, or an acceptable error rate.
Is a citation enough to trust an answer?
No. Confirm that the cited source exists, is current, and actually supports the claim made.
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