Date: October 8, 2025 (Wednesday)

Time: 6:30pm – 7:30pm

Venue: Academic Conference Room, 11/F Cheng Yu Tung Tower, The University of Hong Kong

Speaker: Christoph Engel (Professor Emeritus, Max Planck Institute for Research on Collective Goods)

Large Language Models hold the potential to change legal research quite profoundly. This lecture will bracket the technical background, normative concerns, and legal impediments, and will focus on the many promising applications: legal text as data; LLMs as a proxy for legally relevant behavior; legal interpretation aided with LLMs; outsourcing of legal research to LLMs; delegation of case handling to LLMs.

Christoph Engel is Professor Emeritus and founding Director of the Max Planck Institute for Research on Collective Goods in Bonn, where he has been a Scientific Member since 1997. He is also a Distinguished Senior Research Fellow at the ETH Zurich Center for Law and Economics and a Member of the Pontifical Academy of Social Sciences. A pioneering figure in the field of empirical legal studies, his research examines the behavioral foundations of law, which he tends to interpret as a tool for governing society. He earned his doctorate and habilitation from the Universities of Tübingen and Hamburg respectively. He has been awarded honorary doctorates by the Hebrew University of Jerusalem and Copenhagen University as well as a lifetime achievement award by the European Association of Law and Economics.

Moderator: Benjamin Chen, Associate Professor and Director of Law and Technology Centre, The University of Hong Kong Faculty of Law

To register, please go to https://hkuems1.hku.hk/hkuems/ec_regform.aspx?guest=Y&UEID=102777.

We are applying for a CPD point from the Law Society of Hong Kong for this event.  This event is free of charge for students and attendees who do not opt for CPD.  For registrants who opt for CPD, a fee of HK$ 300 will be charged per person.  Payment link will be provided later and the fee is non-refundable.

For inquiries, please contact Ms. Grace Chan at  / 3917 4727.