Set thresholds using documented error costs: Which control | AIGP
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Set thresholds using documented error costs: Which control is most direct?

AIGP Understanding How to Govern AI Development Easy

Different consequences require measuring and choosing thresholds according to documented false-positive and false-negative costs.

The question

An employment-screening model flags applicants for rejection. A false positive rejects a qualified applicant, while a false negative advances an unqualified applicant for further review; the consequences differ. Privacy, provenance, representative testing, and subgroup measurement are otherwise satisfied. Which control is most direct?

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  1. Optimize overall classification accuracy
    Overall accuracy treats errors alike and may choose a threshold misaligned with the distinct consequences of each error type.
  2. Report only the combined error rate
    A combined rate hides whether costly false positives or less costly false negatives dominate the screening outcomes.
  3. Use identical thresholds for every applicant
    A uniform threshold may be operationally simple, but it does not address the unequal consequences identified in the scenario.
  4. Set thresholds using documented error costs ✓
    Cost-sensitive threshold selection reflects the different consequences of false positives and false negatives in this workflow.
The trap
When error consequences differ, prioritize cost-sensitive error analysis over undifferentiated accuracy.

How to remember it

Different consequences require measuring and choosing thresholds according to documented false-positive and false-negative costs.

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