Knowledge and understanding: Students should demonstrate a good knowledge of the legal methodology and of its applications to emerging technologies, as well as the main ethical and social implications related to this field.
Applying knowledge and understanding: Students should demonstrate a good knowledge of the main rules applicable (at least in Europe) and of the most frequent argumentations applicable to legal issues, ethical questions, and social implications of artificial intelligence.
Making judgements: Students should have the ability to organise the acquired knowledge and to make judgments on regulatory issues, ethical dilemmas, and social implications of artificial intelligence on the basis of limited and incomplete information.
Communication skills: Students should have the ability to present their own view vis-à-vis the general features and contents of the rules applicable in Europe to artificial intelligence, as well as to illustrate the main ethical and social aspects related to this field.
Learning skills: Students should have the ability to articulate and interpret European notions and techniques pertinent to the rules applicable to artificial intelligence in Europe and to the different concepts and theories related to this field.

The course aims to provide an advanced overview of the main legal rules, as well as the most important ethical and social issues on Artificial Intelligence applications, with specific regard to the European context.
Part I: Legal issues
1. AI for law vs Law for AI
2. Law on AI. Preliminary Caveats
3. European Law on AI: The Proposal for an Artificial Intelligence Act
4. European Law on AI: Privacy Law
5. European Law on AI: Transparency Obligations
6. European Law on AI: Fairness and Non-Discrimination
7. European Law on AI: Accountability
Part II: Ethical and social issues
1. Digital ethics
2. Ethics of artificial intelligence
3. Bias and discrimination
4. Transparency
5. Robustness and security
6. Human agency and accountability
7. Good life
8. Social and environmental sustainability

Mandatory readings:
(1) European Commission. 2019. Ethics guidelines for trustworthy AI, Publications Office, 2019. https://data.europa.eu/doi/10.2759/346720
(2) Future of Life Institute. 2024. High-Level Summary of the AI Act. https://artificialintelligenceact.eu/wp-content/uploads/2024/11/Future-of-Life-InstituteAI-Act-overview-30-May-2024.pdf
Optional readings:
(1) Smuha, NA (ed). 2025. The Cambridge Handbook of the Law, Ethics and Policy of Artificial Intelligence. CUP. https://www.cambridge.org/core/books/cambridge-handbook-of-the-law-ethics-and-policy-of-artificial-intelligence/0AD007641DE27F837A3A16DBC0888DD1
(2) Floridi, L., 2023. The ethics of artificial intelligence: Principles, challenges, and opportunities. OUP.
(3) Stahl, B.C., Schroeder, D., Rodrigues, R., 2023. Ethics of artificial intelligence: case studies and options for addressing ethical challenges. Springer. https://doi.org/10.1007/978-3-031-17040-9
(4) Hildebrandt, M. 2020. Law for Computer Scientists and Other Folk, OUP. https://academic.oup.com/book/33735
(5) Scantamburlo, T., Charlesworth, A. and Cristianini, N., 2019. Machine Decisions and Human Consequences. In Yeung, K., Lodge, M. (eds.), Algorithmic Regulation. OUP. arXiv:1811.06747
(6) Infantino, M. Wang, W., 2019. Algorithmic Torts: A Prospective Comparative Overview, 28 Transnational Law & Contemporary Problems 309-362. https://papers.ssrn.com/3225576

Part I: Legal issues 1. AI for law vs Law for AI 2. Law on AI. Preliminary Caveats 3. European Law on AI: The Proposal for an Artificial Intelligence Act 4. European Law on AI: Privacy Law 5. European Law on AI: Transparency Obligations 6. European Law on AI: Fairness and Non-Discrimination 7. European Law on AI: Accountability Part II: Ethical and social issues. 1. Digital ethics 2. Ethics of artificial intelligence 3. Bias and discrimination 4. Transparency 5. Robustness and security 6. Human agency and accountability 7. Good life 8. Social and environmental ustainability

Beside Socratic teaching, there will be an open discussion of relevant problems and cases.

Students will be graded on the basis of a written test of 2 hours, in English, covering the course syllabus. The test will be made up of three open-ended questions covering the issues covered by the compulsory readings and in class. Depending on the correctness, completeness and precision of their answers, students will receive up to 10 points per answer. The final grade will be determined by summing the grades obtained for all three questions. The minimum grade to pass the exam is 18/30. To obtain the maximum score (30/30 cum laude), students will have to demonstrate, in the answer to each question, that they have an excellent knowledge of all the issues investigated.

This course explores topics closely related to one or more goals of the United Nations 2030 Agenda for Sustainable Development (SDGs).