Evaluate across shifts: Which evaluation requirement | AIGP
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Evaluate across shifts: Which evaluation requirement is decisive?

AIGP Understanding How to Govern AI Development Medium

Representative evaluation must cover the deployment population’s shifts, equipment, lighting, and defect conditions.

The question

A manufacturing inspection model was trained mostly on daytime images from one production line using clean equipment. Deployment will cover day and night shifts, three equipment versions, varied lighting, and several defect types. Which evaluation requirement is decisive?

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  1. Use a random held-out split from the existing image collection.
    A held-out split supports evaluation independence, but it cannot represent conditions absent from the collected images.
  2. Evaluate across shifts, equipment versions, lighting conditions, and defect types. ✓
    Testing must reflect deployment conditions and relevant subgroups so performance and limitations are meaningful for the intended population.
  3. Report overall accuracy separately for daytime and nighttime images.
    Stratified reporting helps reveal differences, but absent equipment and defect conditions still require representative evaluation data.
  4. Increase the image count from the current production line.
    More images from one line may improve volume but will not establish representation across shifts, equipment, lighting, and defects.
The trap
Compare test coverage with real deployment conditions; random sampling cannot represent conditions absent from the source data.

How to remember it

Representative evaluation must cover the deployment population’s shifts, equipment, lighting, and defect conditions.

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