Emergency Response Measures for Catastrophic AI Risk
arXiv:2511.05526
Abstract
Chinese authorities are extending the country's four-phase emergency response framework (prevent, warn, respond, and recover) to address risks from advanced artificial intelligence (AI). Concrete mechanisms for the proactive prevention and warning phases, however, remain under development. This paper analyzes an implementation model inspired by international AI safety practices: frontier safety policies (FSPs). These policies feature pre-deployment evaluations for dangerous capabilities and tiered, pre-planned safety measures. We observe close alignment between FSPs and the proactive phases of China's emergency response framework, suggesting that the FSP model could help operationalize AI emergency preparedness in a manner consistent with China's established governance principles.
Accepted to the Workshop on Regulatable ML at the 39th Conference on Neural Information Processing Systems (NeurIPS 2025)