Look for path-changing questions
A human decision belongs where one answer sends the work forward and another answer changes, pauses, or ends it. Common signals include:
- the sources do not support a material statement;
- two interpretations would produce different consequences;
- an external action could affect another person;
- the workflow reaches an uncertainty it was not designed to settle.
These are accountability points. They are different from a broad review of writing quality.
Record the decision beside the artifact
The record should name the question, the material inspected, the choice, and its effect on the next stage. This makes accountability visible without copying private deliberation into public work.
The NIST AI Risk Management Framework treats governance and risk management as connected functions. W3C PROV-O can represent relationships among an artifact, the activity that changed it, and the responsible agent. CommonMark offers a readable way to keep the decision note alongside the workflow.
Fit the human role to consequence
This approach fits recurring work where some stages are routine but a small number of decisions affect accuracy, reputation, money, access, or another person's options. It fits poorly when “human in the loop” means an unnamed person glances at every result without authority to change anything.
The goal is not maximal manual control. It is visible accountability at the moments that can alter the result.
Put a person at the unsupported claim
The synthetic decision point asks one person to remove the unsupported schedule claim or seek a source that can support it.
Place this decision in the workflow
Return to Map an AI Workflow for One Recurring Job to see the complete operating path. Use AI Workflow Handoffs to deliver the material a decision-maker needs. Read AI Workflow Triggers when a person must also control when the job begins.