Research Overview
My research examines the legal and governance challenges of emerging technologies, focusing on how biomedical data and artificial intelligence are reshaping legal relationships and governance boundaries. My work centers on two connected areas: health and genetic data governance, including human biobanks, secondary uses of health data, and polygenic risk scores; and AI governance, particularly transparency, explainability, and legal accountability in algorithmic and automated decision-making.
A central question in my research is how law should respond when technology changes the ways personal data is collected and knowledge is produced. I am particularly interested in how technological change unsettles existing legal assumptions about individual rights, public interests, decision-making discretion, and institutional responsibility, and what forms of governance are needed in response.
In the longer term, I seek to develop an integrated account of technology governance through a “data–algorithms–action” continuum. This approach examines how technological systems structure knowledge and decision-making power, and how law should respond at different stages of that process.
My broader goal is to develop an analytical framework for institutional governance, strengthen the dialogue between legal theory and governance practice, and translate academic research into institution-building that serves the public interest.
I currently lead the AI Governance Laboratory at the Institute of European and American Studies, Academia Sinica, an interdisciplinary platform connecting legal and technological research with concrete governance challenges. For related research and activities, please see the AI Governance Lab website: https://ai-gov-lab-ieas.github.io/en/.