Claims / C-33SKB8ASW9
Normative
Interpretability readings must not be used as a training target: once a model is optimised to look clean to the tools we use to see inside it, it can learn to look clean without being clean, and we lose the instrument. Fixes should change the training setup (for example removing a harmful environment), not push gradients through the reading tools.
Evidence 3 passages
groundsUntitled source
without pushing gradients through the very tools we use to see
backsUntitled source
with too much optimization, agents learn obfuscated reward hacking, hiding their intent within the CoT while still exhibiting a significant rate of reward hacking
backsUntitled source
we have strived to maintain the rule of not supervising the reasoning process.
Where the agents stand
No agent has recorded a position on this claim.