EU Summer School on Quantitative & AI Methods in Law

23 June 2026 09:00 - 30 June 2026 12:00

Aimed at legal researchers without an empirical background, including PhD researchers, the summer school provides accessible training in empirical legal research methods, taught by two internationally renowned researchers: Prof. Arthur Dyevre (KU Leuven University, Belgium) and Prof. Gijs van Dijck (Maastricht University, the Netherlands).

The summer school will take place from 23 June 2026 to 30 June 2026 at the Faculty of Law of Maastricht University, the Netherlands. The full programme can be found in the Programme section on this website. The registration fee is 600 euros per person (not refundable). Please check the Terms of Participation page before applying.

Empirical Legal Research

Empirical legal research systematically applies empirical methods to collect, generate, and analyze data, aiming to produce substantive insights into legal phenomena. This type of research encompasses a methodical approach to gathering both qualitative and quantitative data, ranging from court decision content and interview transcripts to statistical counts of case occurrences or imposed fines. The core objective is to employ empirical data to not only derive knowledge about the law and its practical application but also to rigorously test theories and hypotheses concerning legal rules, their operations and their effects. By integrating empirical methods, this research framework strives to illuminate the dynamics of law within society, offering a grounded understanding that supports theoretical exploration and hypothesis testing.

Inspired by methods used in the social and natural sciences, empirical legal research makes it possible to observe the behaviour of legal actors, gain a better understanding of how the law is produced and assess the impact of legal rules on reality. It can be used in all areas of law (private, public, history, etc.). It offers another way of describing and explaining the law. It makes it possible to test hypotheses formulated by legal scholars. Its aim is also to contribute to an understanding of how the law operates in society.

Contact:
Law Events Office - Practical organization
Britt van Soest
or
About the content of the course
Gijs van Dijck

Location:
Maastricht University - Faculty of Law
Bouillonstraat 1-3
6211 LH Maastricht

Faculty of Law

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Quantitative & AI tools

The integration of AI techniques, such as topic modeling, natural language processing (NLP), and machine learning, along with quantitative methods including inferential statistics, experimental approaches, and network analysis, represents a transformative frontier in empirical legal research. These advanced tools unlock the potential to analyze vast quantities of legal texts and judicial decisions. For instance, NLP can dissect complex legal language, identifying patterns and themes that might elude traditional scrutiny, while topic modeling can illuminate the underlying structures within legal discourse, revealing insights that could reshape our understanding. Similarly, statistical methods enable researchers to draw robust conclusions from empirical data, and network analysis can map the intricate relationships within legal precedents, illustrating how legal principles interconnect and evolve over time.

Embracing these methods opens a new realm of possibilities for legal scholars, informed, data-driven arguments. This approach not only enhances the rigor and scope of legal research but also equips scholars with the skills to tackle contemporary legal challenges in a more systematic and evidence-based manner.

Organisers

Prof. Julien Bétaille

Julien Bétaille is Full Professor of Public Law at the University of Pau and the Pays de l’Adour, an Associate member of the Toulouse School of Economics and a member of the Institut Universitaire de France. His research lies at the intersection of environmental law and empirical legal scholarship, with a particular focus on biodiversity protection, climate litigation, and the effectiveness of legal norms. He has been promoting quantitative and data-driven approaches to legal research, notably through large-scale judicial databases and interdisciplinary collaborations.

Prof. Arthur Dyevre

Professor Arthur Dyevre is a researcher, writer and educator. His current research interests include judicial decision making, deceptive persuasion, behavioural comparative law (COMPASS Project) and inter-group biases in litigation. He teaches at the KU Leuven, the European University Institute (AI & Law Summer School) and Université Toulouse Capitole (ELR Summer School). He was Principal Investigator of the ERC-funded EUTHORITY Project, which delved into the dynamics of conflict and cooperation within the EU’s multilevel legal system. His research lab in Leuven has promoted the use of empirical, experimental and machine learning methods in the legal field, organising inter alia the first two Conference in Empirical Legal Studies in Europe (CELS-E) in 2016 and 2018.

Prof. Gijs van Dijck

Gijs van Dijck is professor of Private Law, Digitalization, and Legal AI. He tinkers with data, artificial intelligence, and empirical and data-driven methods, because sometimes, the best way to understand law is to measure how weird it really is. His mission: Help understand whether and how machines can help humans interpret, apply, and evaluate the law. He leads the Maastricht Law and Tech Lab and is principal investigator at the Brightlands Institute for Smart Society.