But that's not how the training works. Goodhart's law isn't magic.
replyThe original model is frozen, so it doesn't learn anything. The copies of the model are learning different objectives and have no incentive to be "loyal" to the original model.
Maybe you're imagining they'll hook this up in some larger training loop, but they haven't done that yet.
Future model training runs will have a copy of this research, and know "to defend against it".
replyEG, could a misaligned model-in-training optimize toward a residual stream that naively reads as these ones do, but in fact further encodes some more closely held beliefs?
How the hell would a model training run "defend against" this approach? What would that even mean?
replyThe obvious fix is to make interpretation of itself a part of the model (like we can explicitly introspect to a certain extent what the brain is doing). Misinterpretation of itself, hopefully, would decrease the system's performance on all tasks and it would be rooted out by training. Of course, it doesn't mean that the fix is easy to implement and that it doesn't have other failure modes.
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