Human-in-the-Loop
Human-in-the-loop is a design pattern where people review, approve, or correct an AI system's proposals before they take effect. It keeps human judgement on the critical path for high-risk or low-confidence decisions while automation handles the routine volume.
Synonyms: HITL, human in the loop, human oversight, human review
Human-in-the-loop is the practical answer to the question of how much to trust automation. Rather than choosing between full autonomy and manual labor, it routes work by risk: confident, grounded, low-stakes actions proceed automatically, while sensitive ones pause for a person to approve or amend. This keeps throughput high without ceding accountability, and it generates a record of who decided what. Done well, the loop tightens over time as evidence and policy prove which categories of work are safe to automate further.