MACHINE INTELLIGENCE AND LAW

For third-year students, this course marks the culmination of the legal informatics strand within the overall curriculum, comprising five preparatory workshops and a final course delivered across the first three years of the single-cycle master's degree programme in law. Together, the workshops and the Course in Intelligent Machines and Law form a unified, progressive pathway designed to foster both the intellectual curiosity and the substantive knowledge required to engage with the complex interplay between information technology and law. The aim is to train lawyers equipped to confront the challenges arising from the legal implications of information technology across every sector of social and professional life — and, given the subject's inherently interdisciplinary character, to address the so-called new rights associated with the use of self-learning machines. The course examines the legal dimensions of civil liability for AI systems (including autonomous vehicle systems), self-executing contracts, and the protection of fundamental human rights, with particular attention to EU legislation and relevant Italian and international case law. Students will be expected to acquire the technical and legal grounding necessary to understand complex phenomena in which the interaction between law and technology is especially pronounced — such as the use of artificial intelligence in the legal professions, medicine, and the economic and social sciences. This represents a strategic objective for the Law Department, as familiarity with information technologies and their disruptive impact on society, law, the economy, and institutions is an indispensable foundation for training future jurists. The technological revolution of recent years demands professionals capable of applying established legal categories to wholly new phenomena and, where necessary, of devising innovative solutions that regulate emerging realities in accordance with the general principles of the legal order. This requires, above all, an understanding of the fundamental architecture of networks, the languages of mathematics, and the logic of algorithms, so as to assess their full impact on fundamental human rights. As the culmination of this three-year programme of technical and legal study, the Course in Intelligent Machines and Law represents a moment of synthesis, drawing together the knowledge accumulated through the practical workshops and prior courses.

To take the exam, students must have passed the preparatory exam in Digital Law and Data Protection and the digital skills assessment test.

Knowledge and Understanding On successful completion of this course, students will have acquired a comprehensive understanding of the principal subject areas, including the current academic debate on the application of artificial intelligence in economic, social, and institutional contexts, and the complex legal issues arising from the application of law to the operation of intelligent machines across their respective fields of deployment. Applied Knowledge and Understanding Students will demonstrate the ability to construct and sustain reasoned arguments concerning the legal dimensions of artificial intelligence applications across a range of domains, encompassing civil, criminal, and administrative law, as well as the fields of forensic medicine, the judiciary, robotics, and autonomous transport. Making Judgements Students will be capable of gathering, critically evaluating, and interpreting relevant scientific and legal information and data pertaining to the subject matter. Communication Skills Students will be able to communicate information, concepts, problems, and proposed solutions within the field of legal informatics with clarity and precision, employing appropriate scientific and legal terminology. Learning Skills Upon completion of the course, students will have developed the academic competencies required to undertake subsequent study with a substantial degree of independence.

Intelligent Machines, Inductive Process, and Autonomous Learning - The Thinking Machine: From Turing to Searle - Neural Networks, Deep Learning, and Artificial Intelligence - Justice, fundamental rights and artificial intelligence - The robotic ruling - Intelligent machines and legal professions - Algorithmic administrative activity - Artificial intelligence and personal data protection - Generative artificial intelligence and intellectual property protection - Self-driving cars - Artificial intelligence and robotics - AI, blockchain and electronic voting - Predictive AI and jurisdictional activity.

The teaching material consists of the content of the lectures given by the teacher, documents and other audiovisual materials shared on Luiss Learn. Recommended text: G. Buonomo, G. Ciacci, A. Costanzo (eds.), Macchine intelligenti e diritto, Giappichelli, Torino, 2025.

The course is delivered through in-person and online lectures, complemented by individual assignments and group work, including papers, role-playing exercises, and simulations based on current Italian and international case law. Teaching activities also incorporate the analysis of judicial cases and contributions from expert practitioners.

The assessment framework is designed to reward regular attendance and active participation. The final mark, expressed out of 30, is determined on the basis of attendance, classroom participation, performance in the interim assessments, and the outcome of the final oral examination. Assessed components: Interim Assessment (after the first part of the course): analysis of a legal case and one open-ended question. End-of-Course Test (reserved for attending students): a multiple-choice questionnaire consisting of 30 questions. Eligibility for the end-of-course test, which grants access to the simplified oral examination, is restricted to students who have attended at least two-thirds of the scheduled classes. Justified absences on grounds of study or health may not exceed 50% of total class hours. Students who obtain a score of at least 26 out of 30 in the end-of-course test will be required, in the oral examination, to answer only on those topics for which incorrect answers were given. The simplified oral examination is valid solely for the first examination sitting at which the student chooses to present.

Students wishing to be assigned a dissertation topic are required to have passed the examination with a strong mark following regular attendance of the course. Proposals will be evaluated on the basis of the originality of the chosen subject and the innovative nature of the selected research methodology.