Control false negatives: Which evidence should receive priority | AIGP
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Control false negatives: Which evidence should receive priority before approval?

AIGP Understanding How to Govern AI Development Easy

Prioritize measuring and limiting false negatives because missed eligible applicants carry greater harm.

The question

A housing administrator uses a screening model to flag applications for manual review. Missing a potentially eligible applicant is more harmful than reviewing an extra eligible applicant. Which evidence should receive priority before approval?

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  1. Compare error rates across applicant subgroups before setting a threshold
    Subgroup analysis is important for fairness assessment, but it does not by itself prioritize controlling the stated false-negative harm.
  2. Maximize precision among flagged applications
    Higher precision may reduce unnecessary reviews but can increase missed eligible applicants.
  3. Optimize overall classification accuracy
    Overall accuracy treats errors in aggregate and may not control the more harmful missed-eligibility cases.
  4. Control false negatives
    False negatives represent missed eligible applicants, the error type identified as more harmful.
The trap
Translate the stated harm into the corresponding error type before selecting performance evidence.

How to remember it

Prioritize measuring and limiting false negatives because missed eligible applicants carry greater harm.

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More Understanding How to Govern AI Development questions

Part of the Certsqill AIGP question bank · Understanding How to Govern AI Development · Every answer, right and wrong, comes with its own explanation.