This course is the core teaching unit of the academic programme in Legal Informatics, Data Protection, and Artificial Intelligence, forming part of the common core curriculum of the single-cycle Master's degree in Law. Together with its companion courses, it constitutes a unified three-year educational pathway designed to equip students with the knowledge needed to navigate the complex legal challenges posed by artificial intelligence and information and communications technologies in all areas of social and professional life. Given the interdisciplinary nature of the subject, the course addresses the following areas: new rights arising from the use of intelligent, self-learning machines, civil liability for the use of AI systems, including autonomous vehicles, automatically executed contracts (smart contracts), protection of fundamental rights of the person, relevant EU legislation and Italian and international case law. By the end of the three-year programme, students will have acquired the technical and legal knowledge required to analyse complex legal problems at the intersection of law and technology, including the use of AI in the legal professions, medicine, and the economic and social sciences. Students will also develop an understanding of the basic architecture of computing languages and AI systems, enabling them to assess the impact of these technologies on fundamental rights and to apply traditional legal categories to entirely novel phenomena.

Learning Outcomes Upon successful completion of this course, students will have achieved the following learning outcomes: Knowledge and Understanding: Students will demonstrate comprehensive knowledge of the foundational principles of the subject, including the current scholarly debate surrounding the application of AI in economic, social, and institutional contexts, as well as the complex legal issues arising from the regulation of intelligent machines across their various fields of application. Applied Knowledge and Understanding: Students will be able to construct and sustain well-reasoned arguments concerning the legal dimensions of artificial intelligence applications in civil, criminal, and administrative law, as well as in the medico-legal, judicial, robotics, and autonomous transport sectors. Independent Judgement: Students will be able to gather, critically evaluate, and interpret relevant scientific and legal information and data pertaining to the subject matter. Communication Skills: Students will demonstrate the ability to communicate ideas, problems, and solutions in the field of AI law clearly and effectively, employing appropriate scientific and legal terminology. Lifelong Learning Skills: Upon completion of the course, students will have developed the analytical and methodological skills necessary to pursue further study and professional development with a high degree of autonomy.

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.

Recommended text: G. Buonomo, G. Ciacci, A. Costanzo (eds.), Intelligent Machines and Law, Giappichelli, Turin, 2025. The teaching material consists of the content of the lessons given by the teacher, handouts and documents shared on the course web pages (https://www.my.luiss.it/) or distributed during the lessons.

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.

Eligibility for dissertation supervision is subject to the candidate having passed the examination with a strong result following regular attendance. Particular consideration will be given to the originality of the chosen topic and the innovative nature of the selected research methodology.