# Where should a person step in to contribute judgement without becoming a bottleneck?
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language: en
content_type: note-question
status: published
description: Human intervention brings knowledge and authority, but an imprecise design can turn it into a queue of reviews without context.

## Why it matters

"Human in the loop" tends to be used as a generic guarantee of control. In practice it can mean very different things: completing a piece of data, validating an inference, choosing between trade-offs, authorising an action, resolving an exception or stopping the system.

When those functions are not distinguished, the person receives too many cases, reviews without knowing why, reconstructs the context from several applications, or mechanically confirms proposals they can no longer assess with any attention.

The result is an automation that looks prudent but shifts the work and concentrates the risk in a human queue.

## What we know so far

The intervention can be designed from four dimensions:

- **impact:** what consequences an incorrect decision has;
- **uncertainty:** which part of the context or the inference is still open;
- **reversibility:** whether the action can be safely undone;
- **authority:** who is entitled to accept its consequences.

The person should receive a decision package, not a technical dump: current state, information used, reason for escalation, proposed option, permitted alternatives, consequences and a way of correcting the context.

It is also worth observing the intervention as part of the system:

- waiting time;
- percentage of proposals corrected;
- frequency of each reason for referral;
- load per person or function;
- decisions confirmed without modification;
- cases that escalate again;
- recurring exceptions that ought to produce a rule or a redesign.

The person must be able to contribute more than a binary answer. In many cases they need to limit the scope, ask for information, modify the proposal, leave the case open or stop the journey.

## What remains open

It remains open how to adapt intervention thresholds dynamically without the system simply learning to imitate historical approvals.

Also how to measure review fatigue before it shows up as an error; how to distribute authority when several areas share the consequences; and how to stop a reduction in escalations from hiding cases the system has stopped recognising as uncertain.

The hardest question may be an organisational one: which decisions a person really wants to keep, and which they keep today only because the system does not yet know how to prepare them well.

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