LEGAL INFORMATICS

The course aims to provide students with an introduction to current and possible intersections between law and information sciences and technologies, showing how these can contribute, in different ways, to the work and education of jurists, broadly understood both as legal scholars and as practitioners. Particular attention will be devoted to the ways in which concepts, models, methods, and tools developed within Computer Science and the computational sciences can open the way to new forms of representation, analysis, and understanding of legal and socio-legal phenomena, fostering the emergence of new approaches to the empirical study of law. After an introduction to the conceptual and historical foundations of Legal Informatics and an overview of its main branches, the course explores the role that computation and data can play not only at the application level, but also as instruments of inquiry and knowledge production. Through the discussion of research cases, guided activities, and collective discussions, students will be encouraged to reflect on the research questions, methodological choices, and theoretical assumptions that accompany the use of computational tools in the legal domain. The course also aims to foster a critical and active engagement with the topics addressed and with the relevant scientific literature. To this end, students will be guided in selecting and discussing topics consistent with their own interests, including through the development of a short essay on issues addressed in the course.

No specific technical prerequisites. The course is designed for law students and does not require prior knowledge of programming or advanced mathematics.

Knowledge and understanding: students will acquire knowledge of the main branches of Legal Informatics, its historical antecedents, and the key concepts required to understand the role of computation in legal study and practice. Applied knowledge and understanding: students will be able to identify and discuss the use of computational methods and tools in concrete legal research and application cases, connecting research questions, forms of representation, data, models, and analytical techniques. Making judgements: students will critically assess the opportunities, assumptions, and limitations of computational approaches, distinguishing empirical findings, methodological choices, and theoretical interpretations. Communication skills: students will clearly present and discuss a scientific contribution, a research question, and the main methodological choices involved, using language appropriate to the dialogue between law and Computer Science. Learning skills: students will develop the ability to navigate interdisciplinary scientific literature independently, identify relevant contributions, and design a short individual path of further study.

1. Legal Informatics: conceptual foundations - information, computation, reasoning, and representation - computational thinking and problem formulation - computation, scientific knowledge, and computational epistemology - Computational Social Science, digital traces, and interdisciplinarity 2. Legal Informatics: historical foundations - law, calculation, and measurement - Leibniz, Holmes, Cardozo, Loevinger, and Jurimetrics - Wiener, cybernetics and feedback; Losano and legal cybernetics 3. Legal Informatics: mapping the field - concept, scope, and main branches of the discipline - legal computing and the legal regulation of information technologies - functions of computing in legal practice, institutions, and scholarship 4. Legal Informatics in action - legal information, documentation, retrieval, and representation - processing and structuring of legal texts, drafting, and visualisation - Artificial Intelligence and Law: knowledge-based systems, NLP, machine learning, neural networks, and Large Language Models 5. Toward Computational Legal Science - the empirical turn, Computational Legal Studies, and Computational Legal Empiricism - modelling, network analysis, social simulation, and agent-based modelling 6. Research cases and workshops - discussion of selected research cases - reading, presentation, and discussion of scientific contributions - development of a short individual research note.

Teaching materials include the lectures, the course presentation, and additional materials made available by the instructor through MyLuiss. Course presentation: - Nicola Lettieri, Law in Turing's Cathedral. Resources and Ideas for the Legal Informatics Course, course presentation (Prezi), A.Y. 2026/2027, updated throughout the course. Common readings: - The Concept and Branches of Legal Informatics, teaching material prepared by the instructor on the basis of Giovanni Sartor, "Nozione e settori dell'informatica giuridica", in Ginevra Peruginelli and Mario Ragona (eds.), L'informatica giuridica in Italia. Cinquant'anni di studi, ricerche ed esperienze, ITTIG-CNR, Edizioni Scientifiche Italiane, 2014, pp. 59-73. - Nicola Lettieri, "Law in Turing's Cathedral: Notes on the Algorithmic Turn of the Legal Universe", in Woodrow Barfield (ed.), The Cambridge Handbook of the Law of Algorithms, Cambridge University Press, 2021, pp. 691-721. Individual reading: each student will select, in consultation with the instructor, at least one scientific paper for closer study according to their thematic or methodological interests. The selected paper will provide the starting point for a short presentation and for the development of the final assignment. Students may choose from readings suggested by the instructor or identify other relevant scientific contributions. Additional readings and materials relating to individual weeks will be indicated and made available through MyLuiss during the course.

Lectures and discussion: lectures combined with questions, guided discussion, and collective reflection on the concepts introduced. Reading and inquiry: analysis of scientific papers, research cases, and interdisciplinary materials, with attention to research questions, methodological choices, and theoretical assumptions. Practice: introductory hands-on activities devoted to information representation, network analysis, models, and simulation, without requiring prior programming skills. Collaboration: short small-group activities, collective discussion, and peer feedback. Production: selection and presentation of a scientific contribution and development of a short individual research note.

The final assessment, expressed on a 30-point scale, will be based on a short individual research note developed from a research question and at least one scientific contribution selected in consultation with the instructor. The work will be presented and discussed orally. Assessment will consider students' understanding of the topics addressed in the course, their ability to identify and formulate a research question, their awareness of theoretical and methodological choices, their critical use of scientific literature, and the clarity of their argument. Participation in seminar activities, presentations, and discussions during the course will contribute to the overall assessment.

The assignment of final papers or theses will be agreed with the instructor on the basis of the student's interests, the consistency of the topic with the areas covered by the course, and the availability of an appropriate research path.