Duration
24h Th
Number of credits
Lecturer
Substitute(s)
Language(s) of instruction
English language
Organisation and examination
Teaching in the first semester, review in January
Schedule
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
The purpose of this seminar is two-fold. First, it consists in presenting and analysing the most salient issues relating to the approaches, methods and strategies of regulation of big data and new technologies (in particular Artificial Intelligence - AI) in the European Union (EU). These issues will be addressed during a 6-hour cycle of lectures.
Second, the seminar will allow enrolled students to choose a research topic related to one of the outlined regulatory issues. Students will be required to identify the main challenges, advantages, disadvantages, as well as opportunities and possibilities for improvement (in particular of the EU's regulatory framework) by using the knowledge and methodologies acquired during within respective training (law, political science or applied sciences). Written reports of at least 3000 words presenting the students' (thorough and critical) analysis will be submitted by the end of the seminar. The reports will be presented and discussed, with the aim of stimulating a dialogue between lawyers, political scientists and engineers in the course of six discussion sessions.
Learning outcomes of the learning unit
Solid understanding of the approaches and methods followed in regulating AI and big data in the EU.
Solid knowledge and understanding of the regulatory challenges as well as opportunities presented by new technologies, in particular AI.
Development of legal drafting skills in English.
Development of the ability to present in English before a mixed audience comprised of lawyers, political scientists and engineers.
Active participation in debates on the six main themes addressed in the seminar.
This course contributes to the learning outcomes II.1, II.2, V.1, V.2, VI.1, VI.2, VI.3, VI.4, VII.1, VII.2, VII.3, VII.4, VII.5 of the MSc in data science and engineering.
This course contributes to the learning outcomes II.1, II.2, V.1, V.2, VI.1, VI.2, VI.3, VI.4, VII.1, VII.2, VII.3, VII.4, VII.5 of the MSc in computer science and engineering.
Prerequisite knowledge and skills
Openeness to, and exploration of various aspects of the interrelationship between law and new technologies
Planned learning activities and teaching methods
The seminar will be held in person. During the first part (6h ex catedra cycle of lectures) PPTs will be used and made available on the eCampus platform.
The second part will consist of presentation and discussion sessions. These sessions will be preceded by individual tutoring sessions with the TAs responsible for monitoring the students' research and drafting advancement.
Mode of delivery (face to face, distance learning, hybrid learning)
Face-to-face course
Additional information:
Part 1:
22.9.2021: Big Data, AI and Regulation in the EU: the (murky) big picture and the emerging 'big questions' (lecture)
29.09.2021: Transparency, fairness, robustness and explainability: sufficient 'defensive shields' for programmers, users and deployers of AI? (lecture)
06.10.2021: Accountability and liability: who to protect and who to punish when the 'algorithm did it'? (lecture)
Part 2:
Sessions will be held on Wednesdays from 10.45 to 12.45.
1.10.2021: choice of topic to be communicated to Mr. Jérôme De Cooman and Mr. Cyril Fischer (a topic re-assignment may occur if many students choose the same topic)
13.10.2021: meeting with tutors and preparation of reports
20.10.2021: submission of the first drafts of the reports via the eCampus platform
27.10.2021: meeting with tutors for feedback on first drafts of reports (by email, in person)
10.11.2021: presentations and discussions of reports - Theme I: AI and Liability
17.11.2021: presentations and discussions of reports - Theme II: Big Data vs Data Minimization
24.11.2021: presentations and discussion of reports - Theme III: Regulation by Design
1.12.2021: presentations and discussion of reports - Theme IV: AI and Competition Law
8.12.2021: presentations and discussion of reports - Theme V: Profiling
15.12.2021: presentations and discussion of reports - Theme VI: Patentability
17.12.2021 at 11.00: submission of final reports via the eCampus platform.
Recommended or required readings
Materials will be made available to enrolled students
Assessment methods and criteria
Exam(s) in session
Any session
- In-person
oral exam
Written work / report
Continuous assessment
Additional information:
No exam, ongoing evaluation
- submission of a written report: 12 points
- oral presentation of the report: 4 points
- participation in discussions: 4 points
Work placement(s)
Organizational remarks
See the mode of delivery tab above
Contacts
Lecturer:
lgrozdanovski@gmail.com
Assistants
Jerome.decooman@uliege.be
Cyril.Fischer@uliege.be