Minhee Kang

Minhee Kang is a graduate researcher at Yale University working at the intersection of AI governance, intellectual property, and digital accountability.

Her master’s research at Yale examines how legal rights, including data deletion, erasure, and compensation, can be made enforceable in large language model systems. Her work uses a comparative analysis of AI training data governance frameworks in the United States, the European Union, China, and South Korea. She also develops approaches that embed legal accountability requirements directly into AI system architectures, identifying machine unlearning and retrieval governance as critical pathways for compliance at the Yale Digital Ethics Center.

She holds a Master of Laws in Intellectual Property from Seoul National University. Her thesis, Strategies for Utilizing AI Training Data: Legal Categorization and Policy Implications, proposed a novel framework for legally categorizing AI training data to establish clearer accountability in AI systems. She graduated summa cum laude from Korea University with a double major in History and Humanities, a foundation that informs her interdisciplinary approach to institutional analysis and technology governance.

She serves as Lead Venture Development Program Coordinator at Yale’s Tsai Center for Innovative Thinking, where she supports early stage startups on AI, intellectual property, and data governance, and moderates public discussions on AI ethics and innovation. She actively contributes to international intellectual property discourse through WIPO ADR Young and has participated in WIPO initiatives addressing vaccine patent governance during the global health crisis. Through training as an AI Legal Engineering Specialist, she integrates legal theory with technical implementation.