MACHINE INTELLIGENCE AND LAW

This course is the last stage of the overall didactic structure of Legal Informatics of the LUISS master's degree in Law, which is made up of five preparatory laboratories and a course spread over the first three years. These teaching classes constitute a unitary and progressive path according to a logical itinerary studied in order to implement the student's sensitivity for the mutual interaction between information technology and law. The intent is to train a jurist who can be ready to face the legal challenges of the digital dimension, increasingly pervasive and transversal in every professional sector, and of IT applications in the legal sector. To this end, the student will also have to acquire purely technical and IT knowledge to fully understand the technological phenomena of which he or she may be required to evaluate the legal implications and effects. This is a strategic goal that the Department of Law has set itself, as it is impossible to imagine the figure of a jurist today who is not fully familiar with digital tools and is unable to analyze the impact of the most disruptive technological applications on society, law, markets and institutions at a global level. The overwhelming innovation encouraged by national and European public policies requires versatile professional figures, capable of applying the traditional categories of law to unprecedented technological phenomena, or even of building new ones better able to regulate the present. To do this, it is required an understanding of the basic architecture of networks, as well as the languages of mathematics and the logic of algorithms, in order to be able to read them in the forms of law. The Intelligent Machines and Law course is the culmination of the three-year course of technical and legal studies in Legal Informatics. As such, it is the stage where to put all the acquired knowledge into a systematic view of the topic as a whole but also analytically and in depth. Most of the course is in fact devoted to illustrating the most disruptive applications of information technology and AI and to the involvement of all fields of law in the definition of detailed principles and rules that safeguard individuals and society against the impact of such technologies. The young jurist expected at the end of the path described is able to continue his/her studies, having chosen a characterizing profile within which he/she will be able to continue to deepen aspects of informatics specific to that legal practice, but only after having acquired a general knowledge both technical and legal of digitization and its legal implications.

Knowledge and comprehension: to achieve knowledge of some cutting-edge topics in the relevant field of study with the appropriate teaching support, knowledge of the debate and rules relating to the application of AI in significant economic and institutional fields, understanding of the practical and intellectual challenges represented by the activity of intelligent machines for law, its general theory and its various practices. Applied knowledge and comprehension: devising and supporting arguments related to the legal implications of the applications of artificial intelligence in the most diverse socio-economic fields. Making autonomous judgements: collecting and interpreting scientific and legal information relevant for the subject. Communication skills: communicating information, ideas, problems and solutions on Legal Informatics, using the specific scientific language. Ability to learn: having developed the skills necessary to undertake subsequent studies with a high degree of autonomy.

Intelligenza artificiale, machine learning e diritto.

I. Legal rationality and artificial rationality II. Principles for algorithmic decisions III. Applications

The teaching material consists of the content of the lessons given by the lecturer, related handouts and other materials shared on Luiss Learn. G.D’Acquisto, Decisioni Algoritmiche. Equità, causalità, trasparenza. Giappichelli Recommended readings: S.Russell, Human compatible. Penguin

Acquisition: lectures, podcasts and online quizzes Practice: guest speakers, case study and simulation Investigation: analyzing ideas and information in a range of materials and resources, using legal databases to collect and analyze data and comparing texts Collaboration: small group project, discussing others’ output and building joint output Discussion: seminars, group based class discussion, online forums and synchronous and asynchronous discussion Production: essays, reports, presentations and blogs

The final grade, expressed out of 30 and regularly falling within the student's curricular average, will result from the weighted average of the grades previously obtained in the preparatory laboratories and at the outcome of the exam of this course for the respective following quotas: 1/7 Linguaggio e logica delle macchine (LABGP1) 1/7 Laboratorio di informatica giuridica (LABGP2) 1/7 Intelligenza artificiale (LABGP3) 1/7 Intelligenza artificiale, machine learning e diritto (LABGP4) 1/7 Diritto digitale e tutela dei dati (LABGP5) 2/7 Macchine intelligenti e diritto (MID1) The vote of the latter will derive from the evaluation of the following items for the respective percentage share: 20% attendance 10% active participation during classes 50% intermediate tests 20% final exam (written and oral) N.B. In order to be able to assign a grade effectively corresponding to the weighted average of the grades achieved in the Legal informatics long-course, the student will be admitted to take the exam and the subsequent evaluation only after showing a printout of the self-certification showing the exams taken and the respective grades, which can be found on the personal webselfservice.

The competences are assessed via an oral and a written test. 50% of the final grade will be given by the theoretical part and 50% of the final grade will be given by the practical part.