OpenAI and Chain of Thought Control

OpenAI recently introduced CoT-Control, a tool designed to improve control over the reasoning processes of large language models (LLMs). Initial results indicate that models encounter significant difficulties in autonomously governing their own "chains of thought."

This discovery reinforces the importance of monitorability as a crucial element in ensuring the safety and reliability of artificial intelligence systems. The ability to observe and understand the internal decision-making process of models becomes fundamental to prevent unexpected or unwanted behavior.

For those evaluating on-premise deployments, there are trade-offs to consider carefully. AI-RADAR offers analytical frameworks on /llm-onpremise to evaluate these aspects.