When a feature is flagged as a potential proxy variable, the Technical SME conducts a justification review to determine whether the feature should be retained, decorrelated, or removed. The review balances the feature’s predictive value against its proxy risk, and the reasoning is documented for each flagged feature.

The review considers three questions. First, is the feature’s predictive value for the legitimate intended purpose substantive and difficult to replace with alternative features that carry lower proxy risk? A feature that marginally improves accuracy but strongly correlates with a protected characteristic is harder to justify than a feature that is essential for the system’s core function. Second, can the proxy risk be mitigated through in-processing techniques (fairness constraints, adversarial debiasing) without unacceptable accuracy loss? If fairness constraints can neutralise the proxy effect during training, retention may be defensible. Third, does the feature’s removal introduce other risks, such as reduced model performance for the subgroup the proxy represents?

For each flagged feature, the AISDP records the correlation statistic, the predictive importance (SHAP-based or permutation importance), the justification for the retention decision, and the mitigation applied if the feature is retained. Features that are removed are also documented, with the rationale for removal and any impact on model performance.

The feature registry maintains the complete set of proxy variable assessments, providing a single reference for reviewers and auditors. The registry is updated whenever features are added, removed, or modified.

Key outputs

• Justification review documentation per flagged feature
• Retention/removal decision with rationale
• Mitigation specification for retained proxy variables