LEGAL INFORMATION AND TECHNOLOGY INNOVATION LAW

Marco Iecher, Matteo Di Raimondo

Instructional goals

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.

Prerequisites

None.

Intended learning outcomes

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.

Course Contents

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: cryptography and digital signatures blockchain, cryptocurrencies, tokens, and smart contracts.

Reference Books

Teaching materials consist of the content of the lectures delivered by the instructor, the related handouts, and other materials shared on MyLuiss. Recommended readings (mandatory for non-attending students!): Ciacci. (2026). Profili di informatica giuridica (3ª ed.). Cedam.

Teaching Methods

Learning: lectures- Practice: case studies and simulations Inquiry: analysis of ideas and information across a range of materials and resources, using data bases and the LLMs authorised by the University to collect and analyse data and compare texts

Assessment Method

The final grade, expressed out of 30 and relevant for the overall average, will be based on the assessment of the following components, according to their respective percentage weights: 75% ongoing assessment, based on two closed-answer quizzes taken on the MyLuiss platform during the course 10% active participation in class 15% final examination (oral exam).

Thesis assignment criteria

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Week 1

Introduction to the Course Legal Informatics, Algorithms, and Innovation

Week 2

AI Literacy (1) How artificial intelligence works: machine learning, deep learning and generative models (LLMs); introduction to the Google AI tools made available by Luiss to students and teachers

Week 3

Internet, Networks, and Protocols (Why the Internet Works: Standards, Protocols, Network Architecture)

Week 4

Cryptography (integrity, authenticity, encryption, without mathematical or legal implications)

Week 5

Blockchain (distributed ledger, consensus, immutability, exclusively on a technical level)

Week 6

AI Literacy (2) Applied use of generative AI in legal study and research: prompting techniques, critical verification of sources and results, limits and risks (hallucinations and bias); guided practice with the Google tools authorised by the University. Mid-term assessment on the topics covered so far.

Week 7

Digital identity and digital expression (electronic domicile and electronic document) Digital signature (digital signature and certified email)

Week 8

Information technology freedom, big data, and business and institutional organization

Week 9

Databases of open regulatory sources (Normattiva and hypertext codes; Official Journal; description of archives and search functions; website search; general functions of the search system for laws and legally binding acts)

Week 10

Intellectual property of software (with appropriate examples)

Week 11

Illustrations regarding the most significant categories of computer-related offences

Week 12

Final Test