Trigger review when the population or data use materially | AIGP
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Trigger review when the population or data use materially: Which review trigger is most decisive?

AIGP Understanding the Foundations of AI Governance Medium

Material changes in population or data use should trigger review because they can change fitness, limitations, and risk.

The question

A housing administrator reviews an AI-assisted application triage policy annually. Midyear, the tool begins serving a different applicant population and receives a new data source. Which review trigger is most decisive?

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  1. Wait for the next scheduled annual policy review.
    A calendar review may be useful, but waiting ignores material changes to population and data use.
  2. Trigger review when the population or data use materially changes. ✓
    Material changes can alter appropriateness, representativeness, limitations, and risk, requiring policy reassessment before continued reliance.
  3. Review only after applicants report an adverse outcome.
    Complaints may reveal problems, but review should not depend on harm being reported after deployment changes.
  4. Review whenever the model’s aggregate accuracy remains below its original benchmark.
    Accuracy trends matter, but unchanged accuracy does not remove risks created by a different population or data source.
The trap
Prefer triggers tied to changed use, population, data, or risk—not only dates, complaints, or one metric.

How to remember it

Material changes in population or data use should trigger review because they can change fitness, limitations, and risk.

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