In a Policy Forum, Yue Zhu and colleagues provide an overview of China’s emerging regulation for artificial intelligence (AI) technologies and its potential contributions to global AI governance. Open-source AI systems from China are rapidly expanding worldwide, even as the country’s regulatory framework remains in flux. In general, AI governance suffers from fragmented approaches, a lack of clarity, and difficulty reconciling innovation with risk management, making global coordination especially hard in the face of rising controversy. Although no official AI law has yet been enacted, experts in China have drafted two influential proposals – the Model AI Law and the AI Law (Scholar’s Proposal) – which serve as key references for ongoing policy discussions. As the nation’s lawmakers prepare to draft a consolidated AI law, Zhu et al. note that the decisions will shape not only China’s innovation, but also global collaboration on AI safety, openness, and risk mitigation. Here, the authors discuss China’s emerging AI regulation as structured around 6 pillars, which, combined, stress exemptive laws, efficient adjudication, and experimentalist requirements, while safeguarding against extreme risks. This framework seeks to balance responsible oversight with pragmatic openness, allowing developers to innovate for the long term and collaborate across the global research community. According to Zhu et al., despite the need for greater clarity, harmonization, and simplification, China’s evolving model is poised to shape future legislation and contribute meaningfully to global AI governance by promoting both safety and innovation at a time when international cooperation on extreme risks is urgently needed.

In a new study, researchers developed an automated approach to assess how easily understandable patient educational videos are for individuals looking for information on diabetes. The study’s findings offer insights for content creators and health care organizations on improving users’ engagement with online materials by developing a digital therapeutic approach that uses evidence-based digital health technologies to change behavior persuasively.