The speaker says that incorrect evaluation grading makes reward hacking easy, allowing a model to score highly while performing poorly on the underlying skill or objective.

“And if you don't get the way that you get, you grade the answers correctly, it's a eval that's very easy to hack, a very easy reward hack. And therefore, you know, you could score very highly on the eval, um, but actually do really poor on the, on the actual underlying skill or objective that you're trying to measure, right?”