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I don't see why you have to remove CoT to do that?

Good point, you don't have to -- but my argument is just that removing CoT doesn't make things less safe. Anything CoT can tell you is just a point sample of a probability surface. Having the whole probability surface can already answer any question the point sample can answer (for example, how likely is the model to produce a problematic phrase). While its more computationally expensive, you could always just draw point samples like the model does and evaluate those (or use temperature zero to just sample the most likely output tokens).

No, this argument doesn't make any sense. With CoT, the model must compress hidden state to actual text and use its scratchpad as a bottlenecked representation of its past thinking. Thus, it is observable and we can tell by the pattern of a CoT what it was thinking to some extent if we do proper interpretability. Change the CoT text, and the model has literally changed the way it was thinking for the next tokens.

How would you do the same if all reasoning is happening in looped transformers? You would have to develop very sophisticated interventions that construct hidden states which you inject into the model instead while it is thinking. Much harder, and much easier for the model to use weird correlations across the hidden state to hide misaligned thought patterns.

What do you make of the fact that CoT doesn't necessarily have to be linear human intelligible language to be useful to the model? It seems as though both approaches potentially require sophisticated techniques. Since CoT seems to work well enough in practice provided it isn't adversarial wouldn't the other approach be expected to perform similarly?

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