Human-in-the-loop (HITL) is the older and more widely understood model. The AI makes a recommendation or produces an output, and a human reviews and approves it before any action is taken. The human is a gate. Nothing happens without the gate opening.
Human-on-the-loop (HOTL) is the model that emerges when those conditions break. The AI acts autonomously on a continuous stream of decisions, and the human monitors from a supervisory position. The human is not a gate. The human is an observer with override authority. The distinction is subtle in theory and enormous in practice.
When a human reviews every AI decision, the human is engaged. Each action requires attention, however briefly. When a human monitors a stream of AI decisions from a supervisory position, the human must sustain attention on a system that mostly works correctly. This is a vigilance task, and humans are famously bad at vigilance tasks.
The appropriateness of HOTL depends on two variables: the cost of a wrong decision and the reversibility of that decision.
Q: How is human-on-the-loop different from fully autonomous AI?
A: In a fully autonomous system, there is no human oversight. The AI makes decisions and executes actions with no mechanism for human intervention. HOTL preserves human oversight but relocates it from before the action to during or after. The human remains accountable. The difference is the timing of the intervention, not its existence.