Test subgroup outcomes and inspect correlated inputs | AIGP
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Test subgroup outcomes and inspect correlated inputs: Which mitigation best addresses the remaining risk?

AIGP Understanding How to Govern AI Development Medium

An excluded attribute may remain encoded through correlated inputs, so inspect proxies and test subgroup outcomes.

The question

An employee-assistance tool prioritizes requests using workload, schedule, and commute fields. Testing shows lower priority for employees from one neighborhood, although neighborhood is excluded. Which mitigation best addresses the remaining risk?

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  1. Test subgroup outcomes and inspect correlated inputs. ✓
    Subgroup outcome testing shows whether the disparity persists, while inspecting correlations can identify permitted features encoding neighborhood membership.
  2. Add neighborhood explicitly and impose a fairness constraint.
    Making neighborhood explicit may expose the association, but adding a sensitive attribute and a constraint does not by itself validate the resulting prioritization or remove other proxy effects.
  3. Drop the neighborhood field.
    The field is already excluded, and removing it does not address proxy information carried by commute, schedule, or workload variables.
  4. Reweight training records to equalize neighborhood representation.
    Reweighting may change representation but does not by itself identify proxy features or establish that subgroup prioritization is acceptable.
The trap
After removing a sensitive field, check whether other inputs encode it and produce unequal outcomes.

How to remember it

An excluded attribute may remain encoded through correlated inputs, so inspect proxies and test subgroup outcomes.

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