INTELLECTUAL PROPERTY COMPETITION AND DATA PROTECTION LAW

Course objectives

The aim of the course is to provide students with an overview of the functioning of intellectual property, competition and data protection law from both an economic and legal perspective. By the end of the course students are expected to have acquired a general understanding of the main policy issues involved, and should be able to identify and apply the relevant legal rules, both substantial and procedural, in situations that can be considered routinary to professionals and businesses operating in the data science industry.

Channel 1
SALVATORE ORLANDO Lecturers' profile

Program - Frequency - Exams

Course program
The course is aimed at providing students with cognitive and methodological elements so as to become familiar with the most important governance sources and attached analysis issues relevant to the data driven economy. The program (6 cfu) is as follows: Part I: INTELLECTUAL PROPERTY LAW (BASIC NOTIONS OF IP LAW IN CONNECTION WITH THE GOVERNANCE OF THE DATA DRIVEN ECONOMY) I.1 From the information society to the data driven economy (the rise of new legal issues) I.2 IP law basic notions and protection of IP Rights in the data driven economy I.2.1 Software and copyright law I.2.2 Text&Data Mining (copyright law and Artificial Intelligence Act) 1.2.3 Case studies (Anthropic et aliis) PART II: COMPETITION LAW (BASIC NOTIONS OF COMPETITION LAW IN CONNECTION WITH THE GOVERNANCE OF THE DATA DRIVEN ECONOMY) II.1 Competition law basic notions II.2 Fairness towards competitors and towards online users in the data driven economy (Digital Markets Act and Unfair Commercial Practices Directive) II.3 Case studies (Google, Meta, Apple) PART III: DATA PROTECTION LAW (BASIC NOTIONS OF DATA PROTECTION LAW IN CONNECTION WITH THE GOVERNANCE OF THE DATA DRIVEN ECONOMY) III.1 Data protection law basic notions (the European general data protection Regulation, GDPR) III.2 Data protection issues in the data driven economy III.2.1 Automated decisions and profiling III.2.2 AI Act and GDPR
Prerequisites
English proficiency
Books
Slides presented by Prof. S.Orlando and uploaded on Classroom platform
Frequency
Attendance to lessons is highly recommended
Exam mode
Written test with multiple choices plus written responses (free text) to ad hoc questions
Lesson mode
Presentation with slides + interaction with students in classroom (Qs&As and follow-up discussion) + examples of written tests used for the written exam
  • Lesson code1047215
  • Academic year2025/2026
  • CourseData Science
  • CurriculumSingle curriculum
  • Year2nd year
  • Semester2nd semester
  • SSDIUS/04
  • CFU6