Lawrence Chan

Lawrence Chan

As AI Science Advisor to the California Governor’s Office of Emergency Services (Cal OES), Lawrence will advise senior leadership on frontier AI safety and risk assessment, with a particular emphasis on critical safety incidents, AI and cyber defense, and risk from developers’ internal deployment of AI, such as sabotage by AI agents and automated AI R&D. He will also coordinate with AI governance leads across California’s state government and facilitate cross-sector collaboration with the academic research community, the private sector, and community and nonprofit organizations

Lawrence joins Cal OES from METR, where he conducted pre-deployment and benchmarking evaluations of frontier AI models, focusing on empirical measurements designed for communication with policymakers and the public. He co-led METR’s research measuring the “time horizon” of AI agents, which was covered in Nature and has become a widely used metric for tracking AI progress. He previously researched mechanistic interpretability and adversarial training at Redwood Research. His technical reports served as evidence for recent state government action on AI governance in California, including for the Joint California Policy Working Group on AI Frontier Models, and he has experience providing informal technical briefings to congressional staff and senior federal officials in Washington, D.C.

He is currently on leave from his PhD program at UC Berkeley, where he is affiliated with the Center for Human-Compatible AI and the InterACT Lab. He holds undergraduate degrees in computer science, logic, and economics from the University of Pennsylvania’s Jerome Fisher Program in Management & Technology, where he worked with the Good Judgment Project on using machine learning to assist forecasting.