This research was completed for LASR Labs 2025 by Benjamin Arnav, Pablo Bernabeu-Pérez, Nathan Helm-Burger, Tim Kostolansky and Hannes Whittingham. The team was supervised by Mary Phuong. Find out more about the program and express interest in upcoming iterations here. Read the full paper: "CoT Red-Handed: Stress Testing Chain-of-Thought Monitoring."

Chain-of-thought (CoT) monitoring—where safety systems review a model's intermediate reasoning steps—is gaining traction at frontier labs like Google DeepMind and OpenAI as a safeguard against harmful AI actions. Despite intense interest, systematic evaluation has been limited. Our research examines the efficacy of this method and reveals a nuanced picture: CoT monitoring increases safety in situations where sabotage is subtle yet can be surprisingly ineffective against blatant harmful actions. We also discovered that a hybrid approach—using separate monitors for CoT and final actions and combining these suspicion scores—significantly improves sabotage detection compared to single-monitor strategies.