Plan for this page
Turn an abstract idea into an observable decision. Create a workflow approval map that identifies reviewer, evidence, timing, authority, escalation, and post-action monitoring. Move through a fictional public-information workflow. Choose review based on evidence and consequences, not a vague promise that a human is involved. Predict your result before selecting the first option. Prepared next stepOpen the agent recovery unit Learner question
Where should a person review an AI-assisted workflow? Move through a fictional public-information workflow. Choose review based on evidence and consequences, not a vague promise that a human is involved. Learning outcome Create a workflow approval map that identifies reviewer, evidence, timing, authority, escalation, and post-action monitoring.
Interactive model
Decision, consequence, result An AI summarizes a long public consultation before policy staff read it. The system drafts a public page explaining a new service. After launch, complaints show people misunderstand one generated sentence.
Read the complete text alternative An AI summarizes a long public consultation before policy staff read it. Some submissions include minority views and sensitive experiences. The system drafts a public page explaining a new service. The page may affect eligibility expectations. After launch, complaints show people misunderstand one generated sentence. The content passed its initial review. Let the summary define the evidence base. Make compression the unreviewed interpretation layer. Require a senior official to approve each generated sentence during drafting. Spend scarce judgment before a usable comparison exists. Keep links to submissions, sample across perspectives, flag uncertainty and sensitive content, and have an informed reviewer test coverage. Review interpretation against source evidence.
Publish automatically if grammar checks pass. Treat writing quality as factual and policy approval. Publish, then ask staff to review when complaints arrive. Use the public as the detection system. Show exact claims, sources, effective date, accessibility and destination to an authorized reviewer before publication. Review the concrete external effect.
Keep it because it was approved. Treat approval as permanent proof. Change the sentence without recording why. Repair visible content but lose accountability and learning. Pause or correct the claim, notify affected owners, preserve the decision record, investigate, and update tests and review criteria. Use monitoring as part of the control loop.
Complete the decisions to reveal the model Transfer artifact
My workflow approval map Name one workflow stage, its consequence, the reviewer, evidence shown, action they can take, and post-action signal. Safety boundary The scenario is educational. High-stakes workflows require domain, legal, accessibility, affected-person, security, and operational review.
Method note The deterministic model rewards review of concrete effects and meaningful reviewer authority. It cannot certify that human oversight is effective.
Text alternative Read receive, interpret, prepare, choose, execute, publish, and monitor as a sequence; place review gates in the text before the relevant effect.
Sources and scope
What supports this object Established AI Risk Management Framework U.S. National Institute of Standards and Technology Supports contextual mapping, measurement, management, monitoring, governance, accountability, and human oversight; it is voluntary guidance, not proof that a particular system is safe.
Open source Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile U.S. National Institute of Standards and Technology Supports management of confabulation, information integrity, provenance, privacy, testing, and generative-system risks; controls remain use-specific.
Open source 
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