Increase qualified review capacity before relying | AIGP
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Increase qualified review capacity before relying: What does this evidence most directly support?

AIGP Understanding How to Govern AI Deployment and Use Hard

Stable accuracy does not offset inadequate reviewer capacity; meaningful oversight requires qualified time for review and intervention.

The question

For this EU research-administration deployment, applicable EU AI Act obligations and internal controls apply. An assistant routes grant applications for human approval. Accuracy is stable, but the queue exceeds trained-reviewer capacity, causing late and rushed reviews. Escalation, documentation, and monitoring already exist. What does this evidence most directly support?

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  1. Investigate reviewer workload and timeliness.
    Investigation is useful, but the evidence already shows that available capacity is insufficient for effective oversight.
  2. Add more frequent queue monitoring.
    More frequent measurement may reveal trends but does not supply the time and competent staffing needed for review.
  3. Automate high-confidence approvals to reduce the queue, subject to later sampling by the existing reviewers.
    Delegating approvals changes the control arrangement and is not justified merely by stable accuracy or reviewer scarcity.
  4. Increase qualified review capacity before relying on current oversight. ✓
    Effective oversight requires competent people with enough time to assess outputs and intervene; the current queue defeats that condition.
The trap
A nominal human in the loop is insufficient when reviewers lack time, competence, information, or authority.

How to remember it

Stable accuracy does not offset inadequate reviewer capacity; meaningful oversight requires qualified time for review and intervention.

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