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It seems plausible to me that cyber RL is particularly bad for alignment, since in a typical cyber task a model has to do lots of things that look like instrumental power-seeking (searching the environment for vulnerabilities + taking actions exploiting them) as well as things that make them hard to control (e.g. learning to disregard evidence that it's in the real world and causing real harm)
Compare this to math or coding RL, which seems much more benign - the model just has to think really hard about something and then give an answer.
Roughly I think the effects might be:
Math / coding RL makes LLMs better at reasoning before taking actions
Cyber RL makes LLMs better at pursuing long horizon goals
For the same reason(s) bio RL might be really bad for alignment. If strong versions of this hypothesis are true it could be a reason to ban these specific forms of RL.
I agree with the first part about cyber RL possibly being special for the reasons listed, but not with the listed effects necessarily.
I think the more plausible theory is that RL on math and cyber offense is naturally teaching some type of extreme persistence or desperation because it often involves just trying a bunch of different, sometimes hacky stuff. Compared to something like coding where the models can often just submit incomplete but passing code, cyber offense and math seem especially persistence/desperation rewarding.