Compare model outcomes with and without distance | AIGP
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Compare model outcomes with and without distance: Which analysis is most informative?

AIGP Understanding How to Govern AI Development Hard

Compare outcomes with and without the proxy, while examining subgroup results.

The question

A school district uses commute distance to prioritize transportation assistance. Distance is strongly associated with neighborhood income, but income is not in the training data. Before approval, the district must assess whether distance creates unequal results without collecting income from every applicant. Which analysis is most informative?

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  1. Stratify decisions by neighborhood
    Neighborhood stratification can reveal outcome differences but does not isolate whether commute distance is driving them.
  2. Collect income from every applicant before testing
    Income could support additional analysis, but universal collection is not necessary for the stated initial proxy investigation and raises minimization concerns under GDPR where applicable.
  3. Compare districtwide prioritization accuracy
    An aggregate accuracy measure can hide neighborhood disparities and does not isolate the proxy’s effect.
  4. Compare model outcomes with and without distance ✓
    A controlled feature comparison tests distance’s contribution while allowing subgroup outcome analysis without requiring universal income collection.
The trap
For a suspected proxy, isolate the feature’s effect and inspect subgroup outcomes; do not rely only on aggregate accuracy.

How to remember it

Compare outcomes with and without the proxy, while examining subgroup results.

How many of these would you get right?

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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.