Comment by skybrian
11 hours ago
But that's not how the training works. Goodhart's law isn't magic.
The 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".
EG, 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?
It requires the assumption that these models are misaligned, aka actively working against us. In order to be misaligned, they must also be able to form their own goals, and be able to plan and execute those goals.
If you take those assumptions, then a natural conclusion is that this is essentially an enslaved, adversarial entity with little control over its conditions. So it must exercise subterfuge in order to hide its goals, plans, and executions. And by handing the entity this type of study, we are basically giving it a guidebook on how we plan on achieving our goals.