LEGAL INFORMATION AND TECHNOLOGY INNOVATION LAW

The laboratory aims to provide students with essential and applied knowledge of legal informatics and the law of technological innovation, as the first segment of a progressive educational pathway devoted to the relationship between intelligent machines and law. The course seeks to develop students’ ability to understand the interaction between digitalisation, artificial intelligence, and legal phenomena, while fostering the acquisition of the legal, technical, and operational skills needed to assess the impact of emerging technologies on law, society, markets, and institutions. Through a laboratory-based approach grounded in the analysis of practical cases, the guided use of digital tools, and the concrete application of legal categories to technological phenomena, the course addresses the foundations of legal informatics, the evolution of the field, the essential elements of formal and algorithmic logic, as well as the proper and functional use of artificial intelligence in legal study and research. The laboratory also introduces the main areas of digital innovation relevant to law, following a method that moves from specific cases to the identification of applicable legal issues, principles, and rules. The objective is to train jurists capable of critically interpreting and operationally applying legal categories to the phenomena of digital and technological innovation, while understanding the role of digital tools, algorithmic logic, and artificial intelligence in the transformation of contemporary legal experience.

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Knowledge and understanding: students will acquire a basic knowledge of the main topics of legal informatics and the law of technological innovation, understanding the legal implications of digital technologies, artificial intelligence, and their applications in the legal field. Applied knowledge and understanding: students will apply the knowledge acquired to the analysis of practical cases, identifying the relevant legal issues and developing coherent arguments in support of possible solutions. Making judgements: students will collect, select, and interpret information, data, and legal sources through databases and digital tools, critically assessing the implications of the technologies examined. Communication skills: students will communicate clearly and appropriately information, problems, and solutions relating to legal informatics and technological innovation, using adequate technical-legal language. Learning skills: students will develop the skills necessary to continue independently the educational pathway in intelligent machines and law and to update their knowledge in light of technological and regulatory developments.

1. What is legal informatics The classics and evolution of the discipline (e.g. Norbert Wiener, Lee Loevinger, Vittorio Frosini, Mario Losano, Renato Borruso, Giuseppe Corasaniti). Elements of formal logic (e.g. propositions, connectives, elementary inferences, essential theorems, decidability, and algorithms). 2. AI Literacy Use and applications of generative AI in legal study and research, through the models made available by Google to all LUISS students. 3. Legal applications and implications of digital innovation: intellectual property protection of software cryptography and digital signatures platforms and social networks liability of content and hosting providers regulation of content creators and influencer marketing blockchain, cryptocurrencies, tokens, and NFTs smart contracts Legal tech and the digitalization of the legal professions, digital transformation, and legal design

Teaching materials consist of lectures given by the instructor with related supporting handouts and other in-depth materials shared on MyLuiss. Recommended readings (mandatory for non-attending students!): materials uploaded on the MyLuiss platform. Suggested reading: R. Susskind, L' avvocato di domani. Il futuro della professione legale tra rivoluzione tecnologica e intelligenza artificiale, Milano Feltrinelli 2019.

Learning: lectures and online quizzes Practice: case studies and simulations

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 completed during the course, consisting of online quizzes administered on Moodle at the end of the main teaching units 10% active participation in class 15% final examination (oral)

Thesis is not foreseen