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Foreword
GenAI and the Future of Legal Education
The rapid adoption of GenAI is reshaping foundational legal research, drafting, and analysis. As automated systems assume tasks traditionally assigned to trainees and junior associates, law schools face pressing questions: how must legal pedagogy adapt, what core competencies will define the next generation of lawyers, and how can institutions teach both technical proficiency and ethical judgment?
This mini-conference brings together legal educators and practitioners from Hong Kong's leading law faculties to examine how academic institutions must adapt. Associate Professor Dr Stuart HARGREAVE (Faculty of Law, CUHK) will discuss how educators can build bespoke AI tools to model ethical usage in teaching and research, while Mr Ubaid-Ur REHMAN (School of Law, CityUHK) will address adapting vocational training to cultivate early-career supervisory judgment. Finally, Mr Brian TANG (Faculty of Law & LITE Lab, HKU) will share a case study on HKU's award-winning LITE Lab@HKU, demonstrating how experiential and interdisciplinary law school labs can provide authentic, hands-on AI learning that balances doctrinal legal education with the new mindsets required to prevent cognitive surrender. Through these featured presentations and a panel discussion, we invite faculty members, practitioners, and students to discuss the concrete pedagogical and practical shifts shaping the future of legal education.
Why Multi-Disciplinary GenAI Mini-Conferences?
While individual sectors face distinct technical and regulatory challenges, GenAI alters the core mechanics of higher education across all fields. The impact of this technology on assessment design, skill cultivation, and academic integrity cannot be fully understood or resolved through a single disciplinary lens. By launching this multi-disciplinary mini-conference series, we aim to break down academic silos and foster collaborative problem-solving across faculties. These sessions provide a vital space to compare how different fields—from the professional schools to the sciences and humanities—are restructuring their curricula, redefining "foundational" skills, and building student resilience against technology dependence. Ultimately, an interdisciplinary approach allows us to share practical pedagogical strategies, identify common policy needs, and co-design a unified, ethical framework for AI literacy that prepares students for an increasingly integrated professional landscape.
Meet the Featured Speakers
Principal Professional Practitioner, Faculty of Law
Director, LITE Lab
The University of Hong Kong
PCLL Programme Director & Senior Teaching Consultant
School of Law
City University of Hong Kong
Associate Dean (External Engagement) & Associate Professor
Faculty of Law
The Chinese University of Hong Kong
Join the Discussion
Beyond Cognitive Surrender: Reshaping Legal Education and Professional Formation in the Age of GenAI
New Cognitive Pathways
AI can replace much of the traditional basic work of junior lawyers, including document review, basic drafting, etc. But this traditional work was also a way in which junior lawyers developed their skills, intuition, knowledge, etc. How should law schools respond to this reality? Or is it better left to the profession?
The Assessment Crisis
What is the future of assessment? Is there any space left for long-form written assignments completed at home? Is there any solution other than in-class exams?
Institutional & Regulatory Friction
Regulators are necessarily conservative – the standard common law course load remains basically the same across jurisdictions. How can law schools balance the load between the substantive knowledge the regulators require whilst adding in the AI skills and knowledge the profession requires?
Scaling Beyond Boutique Electives
Experiential AI "law labs" are mostly boutique electives for a limited number of students. Are we at risk of creating a two-tier system of law graduates - those trained in AI legal tech and those who are not? Will the latter still have successful legal careers?
Operational Fluency Asymmetry
We expect faculty members to model ethical AI usage, but many students possess far greater operational fluency with these tools than their professors. How do law schools navigate this asymmetry, where faculty members must evaluate AI ethics and judgment without possessing the same hands-on technical familiarity as the students they are grading?
Programme Rundown
