Chain-of-Thought Activations Predict Unsafe Responses In Open-Weight Language Models

Chain-of-Thought Activations Predict Unsafe Responses In Open-Weight Language Models

Researchers demonstrate that monitoring the internal reasoning process of large language models, rather than the text it generates, accurately predicts potentially harmful outputs even before the model completes its response, offering a pathway to real-time safety interventions.

🟣 EV Daily: AI's inner monologue goes public

Lead story: 🧠 AI’s inner monologue goes publicResearchers from OpenAI, DeepMind and Anthropic, plus a slew of other AI bigwigs including Geoffrey Hinton and Safe Superintelligence CEO Ilya Sutskever, have published a paper-cum-open letter arguing that every step of an AI’s internal reasoning—its chain of thought (CoT)—be captured and made auditable. The signatories argue “glass box” CoT logs should be not a nice-to-have but a requirement to ope…