Yueying Yu, a Master of Global Affairs candidate at the Munk School of Global Affairs and Public Policy, is beginning research on how national strategies can improve the safety and security of artificial intelligence. Her project will compare governance approaches in the United States and China and examine how policymakers are trying to reduce the risks of fast-moving AI technologies.
Key facts
- Yu is a Master of Global Affairs candidate at the Munk School of Global Affairs and Public Policy.
- She is a Lupina-IPL Fellow with the Innovation Policy Lab.
- Her research focuses on national strategies for AI safety and security.
- The project will compare AI safety governance frameworks in the United States and China.
- The study will review scholarship, government frameworks, state-level legislation, and official statements.
Why this research matters for graduate policy students and AI researchers
Yu’s project is aimed at a policy question that affects governments, researchers, and graduate students working on technology governance: how to shape rules that respond to the rapid development of AI without losing sight of safety and security. The work is positioned as a comparative analysis, so its practical value lies in clarifying how two major national systems are organizing policy priorities.
The project is also relevant for anyone tracking the policy landscape around emerging technologies. Yu’s research interests include AI policy, the startup ecosystem, and the history of technology, and her background includes communications work connected to philanthropy and policy initiatives in K-12 education and educational technology. That mix suggests the project sits at the intersection of technology, public policy, and real-world institutional decision-making.
- Focus area: AI safety and security governance.
- Countries compared: the United States and China.
- Research materials: scholarship, government frameworks, state-level legislation, and official statements.
- Supervisor: Professor Aaron Gluck-Thaler.
What will the research examine?
Yu’s project will look at national strategies designed to enhance the safety and security of AI technologies. It will compare the policy frameworks used in the United States and China, then draw out differences in their priorities and the ways each country is trying to manage risk.
Rather than focusing only on high-level policy statements, the study will consider a wider documentary base, including academic scholarship, government frameworks, state-level legislation, and official statements. That structure indicates an effort to connect formal policy design with the practical steps governments are taking now.
Who is Yueying Yu?
Yu is a Master of Global Affairs candidate at the Munk School and a Lupina-IPL Fellow in the Innovation Policy Lab. She earned a Bachelor of Arts in English and Comparative Literature, with a concentration in creative writing, from the University of North Carolina at Chapel Hill, where she graduated with highest distinction.
Before joining Munk, Yu worked as a Communications Associate for a consultancy in Washington, D.C. There, she supported planning and execution of philanthropic and policy initiatives in K-12 education and educational technology. That experience helped shape her interest in emerging technologies and the political dynamics around them.
What is the project likely to contribute?
The project is set up to produce a comparative view of AI safety governance that can help explain how national actors mitigate the risks created by rapid AI development. By examining distinct policy priorities in the United States and China, the research may help identify common patterns as well as differences in governance strategy.
For readers following AI policy, the practical takeaway is that the study is not just about abstract regulation. It is about how governments can build safety and security into their national approaches to one of the fastest-moving technology sectors.
