Human-in-the-Loop (HITL)
A design in which a human reviews or approves an AI system's actions before or after they take effect. The IMDA paper is candid that meaningful HITL is hard to sustain at the speed agentic systems operate at, and suggests calibrating oversight intensity to action-level risk rather than applying uniform review to every action.
Defined in 3 GAGE programs, which carry 5 distinct definitions of it. The wording above is taught in Agentic AI Governance: Applied Mastery.
How each discipline defines it
The same term does different work depending on who is using it. These are the definitions as each program teaches them, unedited.
A design in which a human reviews or approves an AI system's actions before or after they take effect. The IMDA paper is candid that meaningful HITL is hard to sustain at the speed agentic systems operate at, and suggests calibrating oversight intensity to action-level risk rather than applying uniform review to every action.
An oversight pattern in which the agent may not complete a specific action until a human approves that specific action. The human is a required gate between the agent's proposal and the world. Suited to irreversible, high-blast, or rights-affecting tasks at manageable volume.
The deliberate placement of a human judgment or approval step at the highest-leverage points of an automated AI process, rather than reviewing everything or nothing; the formal name for the core skill of the CRAFT A (Assign) stage.
an oversight model where every agent action requires human approval before execution.
An oversight mode where the AI proposes and a human must approve, edit, or reject before the action executes, so nothing consequential happens without a human decision. Suited to high-stakes, irreversible actions.
Where it is taught
The exact lessons this term appears in. The first 7 topics of every program are free with a free account.
- Agentic vs. Traditional AI: What Changed · AI Fundamentals, AI Literacy & Professional Conduct
- AI Workflow Design Fundamentals and Preventing Technical Debt · Practical AI Workflow Design and Prompt Engineering, AI Literacy & Professional Conduct
- Orchestration Protocols for Human Oversight · Critical Thinking and Context Engineering, AI Literacy & Professional Conduct
- Who Pays When the Agent Errs II · The Law and the Regulators, Agentic AI Governance: Applied Mastery
- The oversight pattern: human-in-the-loop, on-the-loop, and out-of-the-loop, chosen per task with reasons · Agents Under Command, AI Governance: Applied Mastery
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.