Developing Nuclear Safeguards for AI

Co-developed an AI classifier with the NNSA and DOE national laboratories to distinguish concerning nuclear-related conversations from benign ones with 96% accuracy in preliminary testing. This classifier has been deployed on Claude traffic to monitor for misuse. The approach involved using a curated set of nuclear risk indicators shared by the NNSA to build a real-time content classifier. Validation was performed using synthetic data generated from NNSA examples, and the system was refined based on feedback. Real-world deployment revealed the need for hybrid safety systems, such as hierarchical summarization, to handle nuanced conversations and reduce false positives. This work demonstrates a model for public-private partnerships in AI safety and risk mitigation.