Course Syllabus
Obiettivi
The main aim is for the students to acquire an in-depth understanding of the course contents, such as the basic features of normative reasoning, the current problems of and approaches to the interaction of law and artificial intelligence, privacy and data protection.
The course moreover aims at making the students acquire the ability to identify the structure of arguments and theories, to present focused objections to arguments and theories, and to rationally defend a point of view, possibly original, in order to communicate it effectively.
Contenuti sintetici
The course aims at introducing and discussing the essential features of normative and legal reasoning, some of the main current problems and approaches of law and artificial intelligence, the historical evolution and the sources of personal data protection law (e.g., G.D.P.R., d.lgs. 196/2003 e d.lgs. 101/2018).
Programma esteso
The course will deal with the problems of the definition of AI techniques in legal texts, actual and projected uses of AI in the civil and criminal legal domain, the proposed EU AI regulation, law-following AI, the control and alignment problems, normative uncertainty and normative risk, the fundamental elements and regulation (national, european and international) of personal data protection law.
Prerequisiti
None.
Modalità didattica
Lectures. Discussion sessions. Seminars. Guided readings of research papers. Talks by invited experts. Project work.
Materiale didattico
Students who attend at least 75% of the meetings:
The required materials will be made available during the course.
All other students:
EU AI Act, in its current draft.
F. Faroldi, General AI and Transparency in the EU AI Act, i-lex, 14, 2, 2021, pp. 56–68.
F. Faroldi, Lecture Notes on Law and AI, available at the end of the course.
F. Lagioia and G. Sartor, AI Systems Under Criminal Law: a Legal Analysis and a Regulatory Perspective, Philosophy and Technology, (2020) 33:433–465.
J. Schuett, Risk Management in the Artificial Intelligence Act, European Journal of Risk Regulation (2023), 1–19.
Periodo di erogazione dell'insegnamento
First semester
Modalità di verifica del profitto e valutazione
There will be no intermediate assessments. The final assessment will be a written exam employing a mix of multiple-choice questions, to evaluate knowledge of the course content, and open questions, to evaluate critical and argumentative skills. Partial credit might be assigned for optional in-class work.
Orario di ricevimento
After class on Tuesdays at 10.30, and by appointment.
Aims
The main aim is for the students to acquire an in-depth understanding of the course contents, such as the basic features of normative reasoning, the current problems of and approaches to the interaction of law and artificial intelligence, privacy and data protection.
The course moreover aims at making the students acquire the ability to identify the structure of arguments and theories, to present focused objections to arguments and theories, and to rationally defend a point of view, possibly original, in order to communicate it effectively.
Contents
The course aims at introducing and discussing the essential features of normative and legal reasoning, some of the main current problems and approaches of law and artificial intelligence, the historical evolution and the sources of personal data protection law (e.g., G.D.P.R., d.lgs. 196/2003 e d.lgs. 101/2018).
Detailed program
The course will deal with the problems of the definition of AI techniques in legal texts, actual and projected uses of AI in the civil and criminal legal domain, the proposed EU AI regulation, law-following AI, the control and alignment problems, normative uncertainty and normative risk, the fundamental elements and regulation (national, european and international) of personal data protection law.
Prerequisites
None.
Teaching form
Lectures. Discussion sessions. Seminars. Guided readings of research papers. Talks by invited experts. Project work.
Textbook and teaching resource
Students who attend at least 75% of the meetings:
The required materials will be made available during the course.
All other students:
EU AI Act, in its current draft.
F. Faroldi, General AI and Transparency in the EU AI Act, i-lex, 14, 2, 2021, pp. 56–68.
F. Faroldi, Lecture Notes on Law and AI, available at the end of the course.
F. Lagioia and G. Sartor, AI Systems Under Criminal Law: a Legal Analysis and a Regulatory Perspective, Philosophy and Technology, (2020) 33:433–465.
J. Schuett, Risk Management in the Artificial Intelligence Act, European Journal of Risk Regulation (2023), 1–19.
Semester
First semester
Assessment method
There will be no intermediate assessments. The final assessment will be a written exam employing a mix of multiple-choice questions, to evaluate knowledge of the course content, and open questions, to evaluate critical and argumentative skills. Partial credit might be assigned for optional in-class work.
Office hours
After class on Tuesdays at 10.30, and by appointment.