My point isn’t that if the model is perfectly accurate the process isn’t needed.
My point is that if the model is perfectly accurate the process doesn’t work (at least in the difficult cases) and that the process involves trying to improve the model all the time, so it’s liable to push itself into a situation where it doesn’t work.
In other words, I don’t see that this process is really effective in saving you from Goodhart’s law.
My point isn’t that if the model is perfectly accurate the process isn’t needed.
My point is that if the model is perfectly accurate the process doesn’t work (at least in the difficult cases) and that the process involves trying to improve the model all the time, so it’s liable to push itself into a situation where it doesn’t work.
In other words, I don’t see that this process is really effective in saving you from Goodhart’s law.