The speaker says researchers may assume a model has improved when evaluation scores look good and fail to investigate further.

“They're coming. Um, but it was-- there was no good way for us to show progress, uh, on financial tasks on these evals. Um, there's a funny, like, funny things. Like, I think there's this bias in evals where if the numbers look good, the researchers assume that the model's gotten better, and they don't investigate it.”