Do not let missing data become a denial
Recognize when missing data can create unfair AI outcomes and choose a governed mitigation.
The model is reading missing uploads as low need, but missingness may reflect access barriers. What should Luis do before using the screener to prioritize applicants? Keep the ranking because the model can only use the data it has. Weak move: this converts an access gap into a decision rule. It violates fairness because the process creates unequal opportunity to provide evidence. Remove every applicant with missing documents from the AI workflow. Weaker: exclusion avoids one model error but can delay help for the same group. Accountability requires a workable control, not simply pushing people out of the process. Add…
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