Test staffed override: At design time, which evidence best | AIGP
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Test staffed override: At design time, which evidence best resolves whether human fallback is genuinely

AIGP Understanding How to Govern AI Development Medium

Fallback is credible only when intervention, escalation, and appeal work in practice, not merely when a reviewer is named.

The question

A school administration plans an AI system to recommend course placements. Some recommendations may be inappropriate, and students need a timely way to obtain correction. At design time, which evidence best resolves whether human fallback is genuinely available?

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  1. Test staffed override, escalation, and student appeal procedures. ✓
    Testing these procedures demonstrates whether competent staff can intervene and students can obtain correction when recommendations cause problems.
  2. Document expected placement benefits and administrative costs.
    Benefits and costs support contextual assessment but do not demonstrate that students can obtain timely human correction.
  3. Record the model’s placement accuracy.
    Accuracy does not show whether staff can intervene, correct recommendations, or provide students an effective alternative process.
  4. Identify a staff member nominally assigned to review outputs.
    Naming a reviewer does not establish sufficient time, information, authority, escalation, or appeal mechanisms for meaningful intervention.
The trap
Look for tested authority and pathways to correction, especially where affected people need appeal.

How to remember it

Fallback is credible only when intervention, escalation, and appeal work in practice, not merely when a reviewer is named.

How many of these would you get right?

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