Data Protection, Law and Ai
A.Y. 2024/2025
Learning objectives
The course is meant to explain to the students the intersections between the protection of personal data and the evolution of AI systems. As a fundamental right, data protection is shaping the way that AI systems are regulated. At the end of the course, the student will be able to identify the essential elements prescribed by law in order to collect, use and process the personal data in AI context. The student should also be able to know the subjects of a data governance plan and understand the mandatory assessments that are required according both for data protection and for the level of risk of the AI system.
Expected learning outcomes
- Frame the role of data protection in AI systems
- Acquire a general knowledge of the duties related with the processing of personal data
- Know the role of Supervisory Authorities in regulating AI systems
- Understand the "by design" and "by default" principles
- Perform a data protection impact assessment
- Understand the concepts of anonymization and pseudonymization
- Acquire basics of information security for the protection of personal data required by the law
- Acquire a general knowledge of the duties related with the processing of personal data
- Know the role of Supervisory Authorities in regulating AI systems
- Understand the "by design" and "by default" principles
- Perform a data protection impact assessment
- Understand the concepts of anonymization and pseudonymization
- Acquire basics of information security for the protection of personal data required by the law
Lesson period: Second semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course can be attended as a single course.
Course syllabus and organization
Single session
Responsible
Lesson period
Second semester
Course syllabus
1. Introduction;
2. The fundamental right to personal data protection;
3. General Principles of European Data Protection Law;
4. Data protection definitions;
5. The Legal Conditions relating to processing of personal data;
6. Data protection roles and responsibilities;
7. The obligations of the controller and of the processor (I part);
8. The obligations of the controller and of the processor (II part);
9. Risk based approach and cybersecurity;
10. Security measures and data protection;
11. Data breaches and remedies to security incidents;
12. AI regulation in EU;
13. AI regulation in other countries;
14. An ethical approach to AI;
15. Human Rights Impact Assessment;
16. The economic value of data;
17. The Member States' Independent Supervisory Authorities;
18. Case history of AI and data protection;
19. AI liability;
20. New challenges of AI and data protection.
2. The fundamental right to personal data protection;
3. General Principles of European Data Protection Law;
4. Data protection definitions;
5. The Legal Conditions relating to processing of personal data;
6. Data protection roles and responsibilities;
7. The obligations of the controller and of the processor (I part);
8. The obligations of the controller and of the processor (II part);
9. Risk based approach and cybersecurity;
10. Security measures and data protection;
11. Data breaches and remedies to security incidents;
12. AI regulation in EU;
13. AI regulation in other countries;
14. An ethical approach to AI;
15. Human Rights Impact Assessment;
16. The economic value of data;
17. The Member States' Independent Supervisory Authorities;
18. Case history of AI and data protection;
19. AI liability;
20. New challenges of AI and data protection.
Prerequisites for admission
No prerequisites are required.
Teaching methods
Lectures and paper and case studies based discussions.
Teaching Resources
The course is based on open access books and papers. The references will be published before and during the course to be more updated.
Assessment methods and Criteria
The exam is oral. The oral exam consists of a discussion on the topics included in the mandatory references. The exam is aimed at ascertaining the preparation and argumentative capacity of the student.
Professor(s)
Reception:
The tutoring will be delivered on appointment to be scheduled by email.