This is fun to read and think about, but it's also important to keep in mind that this is very light on evidence and is basically fanfic. The fact that the author uses entertaining Waluigi memes shouldn't convince you that it's true. LessWrong has a lot of these types of posts that get traction because they're much heavier on memes than experiments and data.
Here is a competing hypothesis:
The capability to express so-called Waluigi behavior emerges from the general language modeling task. This is where the vast majority of information is - it's billions or even trillions of tokens with token-level self-supervision. All of the capabilities are gained here. RLHF has a tiny amount of information by comparison - it's just a small amount of human-ranked completions. It doesn't even train with humans "in the loop", their rankings are acquired off-line and used to train a weak preference model. RLHF doesn't have enough information to create a "Luigi" or a "Waluigi", it's just promoting pre-existing capabilities. The reason you can get "Waluigi" behavior isn't because you tried to create a Luigi. It's because that behavior is already in the model from the language modeling phase. You could've just as easily elicited Waluigi responses from the pure language model before RLHF.
There's no super-deceptive Waluigi simulacra that's fooling human labelers into promoting it during RLHF - this should be obvious from the fact that we can immediately identify the undesirable behavior of Bing.
Here is a competing hypothesis:
The capability to express so-called Waluigi behavior emerges from the general language modeling task. This is where the vast majority of information is - it's billions or even trillions of tokens with token-level self-supervision. All of the capabilities are gained here. RLHF has a tiny amount of information by comparison - it's just a small amount of human-ranked completions. It doesn't even train with humans "in the loop", their rankings are acquired off-line and used to train a weak preference model. RLHF doesn't have enough information to create a "Luigi" or a "Waluigi", it's just promoting pre-existing capabilities. The reason you can get "Waluigi" behavior isn't because you tried to create a Luigi. It's because that behavior is already in the model from the language modeling phase. You could've just as easily elicited Waluigi responses from the pure language model before RLHF.
There's no super-deceptive Waluigi simulacra that's fooling human labelers into promoting it during RLHF - this should be obvious from the fact that we can immediately identify the undesirable behavior of Bing.