On August 4, 2026, the Stanford Human Intelligence Institute (Stanford HAI) released a report stating that as generative artificial intelligence evolves into systems with world-model capabilities, how to effectively govern these AI systems that can simulate, predict, and even intervene in the real world has become the most urgent policy challenge today and in the future. The study emphasized that traditional regulatory frameworks are unable to address the complex risks posed by world models, and there is an urgent need to establish new interdisciplinary and cross-border governance mechanisms to balance technological innovation with public safety.
The Stanford Center for Human-Centered AI released a briefing, systematically discussing for the first time how to govern the “world model”. It pointed out that its regulatory complexity far exceeds that of large language models. The world model is the foundation for building spatial intelligence; it can create representations of the physical environment and predict the consequences of actions. Currently, it is being applied in commercial contexts such as crisis response, autonomous driving, and robot manufacturing. Since the world model involves physical risks rather than just information risks, its errors can lead to personal injury or property damage. Therefore, policymakers need to address this technological challenge promptly.