ARTIFICIAL INTELLIGENCE AND LAW

The course aims to provide students with a systematic knowledge of artificial intelligence, its legally relevant application profiles and its regulation and to develop the ability to understand the logic of machine learning processes and autonomous algorithmic decisions, with attention to both technical aspects and cultural and institutional implications. To this end, it addresses the essential notions of artificial intelligence theory, natural languages and formal languages, as well as the logical foundations of algorithms and machine learning and the concrete impact of AI ethics. Correspondingly, a method is developed that refines the understanding of the logical and methodological tools used by the jurist ─ both in the interpretation of the rules and in the reconstruction of the facts ─ to compare them with the logic of AI so as to understand the advantages and risks of the use of AI. Through an empirical and laboratory approach, based on the analysis of practical cases, concrete applications, regulatory scenarios and emerging legal problems. The course also introduces the national, European and international framework of the regulation of artificial intelligence, with particular reference to the European strategy, the AI Act, the Italian law on AI and the main multilateral and comparative experiences.

A basic familiarity with logic and abstract reasoning is recommended.

Knowledge and understanding: students will acquire systematic knowledge of artificial intelligence, its technical foundations, and its main legal, social, and economic implications. Applied knowledge and understanding: students will apply the knowledge acquired to the analysis of practical cases and AI applications across different areas of law, identifying legal issues and possible regulatory solutions. Making judgements: students will collect and interpret relevant information, data, and sources, critically assessing the impact of AI systems on rights, liability, institutions, and markets. Communication skills: students will communicate problems and solutions relating to artificial intelligence and its regulation, using appropriate technical-legal language. Learning skills: students will develop the skills necessary to continue independently the study of the relationship between intelligent machines and law and to keep their knowledge up to date in light of technological and regulatory developments.

1. Introduction to and Theory of Artificial Intelligence essential definitions • cognitivism (strong AI and A. Turing) and behaviourism (weak AI and J. Searle) • natural languages and formal languages 2. Algorithms and Machine Learning: Logical Foundation • supervised and unsupervised learning • generative AI • predictive algorithms • biases and hallucinations • neural networks 3. Rationality and Algorithmic Decision-Making • transparency as “explainability” • fairness • quality • responsibility • human-centricity 4. Legal rationality and artificial intelligence. 1. Forms of legal knowledge and the limits of AI applied to law. 2. current principles of national and EU regulation 5 . IV law and regulation 1. European Strategy and the AI Act 2. Italian law on AI. Main multilateral (UN, OECD) and comparative (USA, China) international positions. 6. With the empirical and laboratory-based approach, moving from the specific practical case to the broader question or principle, issues related to the following possible areas will be examined: • civil law (legal personhood and algorithmic civil liability • criminal law (criminal liability, predictive policing, and predictive justice) • autonomous driving • intellectual property and generative AI • labour law • marketing • algorithmic democracy and elections • AI and legislation • algorithmic administration • autonomous weapons systems

Giuseppe D’Acquisto: Intelligenza Artificiale – Elementi, (Giappichelli) Giuseppe D’Acquisto: Decisioni Algoritmiche: equità, casualità, trasparenza, (Giappichelli) AA.VV. (a cura di G. Buonomo - G. Ciacci - A. Costanzo), Macchine Intelligenti e Diritto, Giappichelli, 2025). Recommended readings (mandatory for non-attending students!): D. Andler, Il duplice enigma. Intelligenza artificiale e intelligenza umana, Einaudi, 2023.

Learning: lectures and online quizzes Practice: guest lectures by experts, case studies, and simulations Inquiry: analysis of ideas and information across a range of materials and resources, using legal databases to collect and analyse data and compare texts Collaboration: small-group work, discussion of peers’ findings, and development of shared outcomes Discussion: seminars and in-class group discussions Production: essays, reports, and presentations A specific part of the course is dedicated to the in-depth study of the implications of AI in the various areas of law with exercises focusing on the analysis of practical cases and jurisprudential decisions relating to topics covered in class.

The final grade, expressed on a 30-point scale and included in the overall grade point average, will be determined on the basis of the following components and corresponding percentages: 75% assessment of coursework: participation must be guaranteed with at least one vote on the legal part and one on the technological 10% active participation in class 15% final examination (either written or oral)

The intermediate written tests may concern: 1. - artificial intelligence topics with particular reference to computational, algorithmic or application aspects. A critical analysis of models and their limits is required; 2. - the relationship between legal logic and the logic of artificial intelligence. The ability to critically analyze the problems posed by concrete cases is required. The topics specifically related to computational and algorithmic aspects are developed in coordination with the co-teacher, as well as the legal component is developed in coordination with the co-teacher.