Reduce false negatives first: Which evaluation priority | AIGP
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Reduce false negatives first: Which evaluation priority follows?

AIGP Understanding How to Govern AI Development Hard

Because missed medical shipments carry greater consequences, evaluate and set acceptance criteria around reducing false negatives.

The question

A logistics scheduler flags deliveries for rerouting. A false negative can leave a time-critical medical shipment on its original route, while a false positive mainly causes an avoidable dispatch review. Which evaluation priority follows?

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  1. Optimize the positive predictive value of rerouting alerts.
    Positive predictive value limits unnecessary reviews but does not directly prioritize preventing missed medical shipments.
  2. Maximize overall classification accuracy.
    Overall accuracy can favor the more common outcome while underweighting costly misses involving time-critical medical shipments.
  3. Reduce false negatives first. ✓
    The stated harm makes missed time-critical shipments more consequential, so acceptance criteria should emphasize reducing false negatives.
  4. Balance false-positive and false-negative rates equally.
    Equal weighting conflicts with the scenario’s unequal consequences and could accept too many dangerous missed interventions.
The trap
Identify which error causes the more serious stated harm before choosing the primary metric.

How to remember it

Because missed medical shipments carry greater consequences, evaluate and set acceptance criteria around reducing false negatives.

How many of these would you get right?

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