AI and Legal Education: Back to the Drawing Board? A Case Study in Academic Writing

The incorporation of Artificial Intelligence (AI) into educational paradigms holds significant promise, especially in the nuanced domain of legal studies. A pilot study conducted at Tilburg Law School centered around academic writing and legal analysis and serves as the backdrop for this presentation. The study illuminates both the advantages and limitations of employing ChatGPT within legal education. The derived pilot insights are invaluable for the future redesign of legal education. ChatGPT offers multiple benefits, serving as an interactive research aide that navigates students through legal databases and helps pinpoint pertinent case law and statutes. This aligns with the learning objectives of acquiring foundational legal knowledge and honing research skills. Furthermore, ChatGPT's simulation capabilities enable students to refine their analytical and communicative competencies through real-time legal scenarios. Ethical considerations are also integrated into these simulations, contributing to the development of ethical awareness—a crucial learning outcome. For advanced studies, ChatGPT facilitates complex legal research and aids in the cultivation of specialized legal expertise. Its capacity to emulate intricate, multi-jurisdictional legal issues is instrumental in fostering strategic legal thinking. Moreover, ChatGPT's utility in simulations involving negotiation and client counseling contributes to the mastery of professional skills and ethical leadership. However, the technology is not without its challenges. Risks include potential breaches of data confidentiality and the possibility of reinforcing incorrect legal interpretations due to the lack of human supervision. In addition, it could exacerbate the already existing cleavages between groups of students. There will be a difference between the various subscription plans, technological abilities and competencies of students, internet and data access, cultural and linguistic limitations or backgrounds and the biased nature of the AI tools themselves.