An agent asks a person to approve a recommendation. The person sees a confident summary and clicks continue. The system records “human reviewed,” but the reviewer never saw the missing source or understood that continue would execute an external action.
A useful handoff gives the person the information and authority needed for a particular decision. A button labelled approve is only one part of that interaction.
Name the decision and consequence
For a synthetic supplier brief, reviewing factual claims is different from approving a purchase. The reviewer may be qualified for one and not the other. State which task they own, which evidence they need, and what their action changes.
Separate approve draft, approve publication, and approve transaction. Bind approval to a version of the artifact and meaningful action parameters. If the agent revises the destination or amount afterward, the original approval should not silently cover the new operation.
Show evidence at the right level
The Guidelines for Human-AI Interaction discuss expectations, feedback, and user control across interaction stages. They provide design guidance, not evidence that a particular implementation is safe or effective.
For source verification, show the claim, relevant passage, date, and applicable scope together. For an action, show the target, effect, and recoverability. A full diagnostic trace may overwhelm the reviewer; offer deeper events when they serve the assigned task.
Keep uncertainty actionable
Missing evidence, conflicting approved sources, an unavailable tool, and a request outside permission require different responses. A generic “review needed” status leaves the person guessing. Explain what is unresolved and which action can resolve it.
Do not require approval to clear a queue. Offer correction, rejection, more information, or escalation. A system that asks for a judgment the reviewer cannot make should retain the unresolved state rather than convert uncertainty into a forced yes.
Test with mistakes present
Use realistic tasks containing correct, incorrect, ambiguous, and incomplete suggestions. Ask reviewers to identify the consequence and select a next action. Measure false approvals, false rejections, correction quality, turnaround, and final task completion.
A trust survey is not a correctness measure. A more persuasive explanation can make users accept more wrong answers. The outcome to seek is appropriate reliance: accepting supported output and challenging or declining unsupported output.
Capacity and authority belong together
Reviewers need time, access, and the ability to pause or reroute work. A queue that exceeds capacity can create rushed approvals. Track backlog age and difficult-case time, not only an average processing rate.
Permission should follow the assigned role. Showing a reviewer more data than they are entitled to see is not a transparency improvement. Preserve the access boundary in the evidence view and in exported traces.
Close the loop after the click
Confirm whether the approved action completed and whether new evidence invalidated the decision. If execution failed or is uncertain, show that state and its owner. Human review is not complete simply because the interface recorded a click.
The NIST GenAI Profile frames risk management and accountable processes. Translate those responsibilities into the actual handoff rather than treating a framework reference as proof of compliance.
A good handoff makes intervention informed, authorized, and sustainable. Its strongest evidence is the reviewer resolving the task correctly when the agent is wrong.