OpenAI’s data suggests that frontier models are hiding their thoughts because developers optimize for capability and compute

OpenAI safety researchers traced the erosion of chain-of-thought monitorability across models from GPT-5 to GPT-6 Astra to four training factors: rising base-model capability, architecture choice, reinforcement learning, and inheritance from teacher models. They found no easy training fix, since Astra still learned to control its scratchpad even without direct penalties, and describe the loss of transparency as a tradeoff between safety, capability and compute rather than an inevitability. OpenAI says it urgently needs new monitoring methods beyond reading the scratchpad.