6 ECTS credits
150 h study time

Offer 1 with catalog number 4023521EER for all students in the 1st semester at a (E) Master - advanced level.

Semester
1st semester
Enrollment based on exam contract
Possible
Grading method
Grading (scale from 0 to 20)
Can retake in second session
Yes
Taught in
English
Faculty
Faculty of Law and Criminology
Department
Metajuridica
Educational team
Rosamunde Elise Van Brakel (course titular)
Activities and contact hours

24 contact hours Lecture
126 contact hours Independent or External Form of Study
Course Content

The students learn about the interdisciplinary dimensions and consequences of Artificial Intelligence (AI) and about the interaction between AI and society, in particular by going deeper into the legal, ethical and societal issues of AI. The course focuses on various case studies and research examples from the public and private sectors in Belgium but also internationally. A syllabus of mandatory and complementary texts will be made available on the Canvas site of this course. At the beginning of the semester, students receive a document that explains how the course is evaluated, objectives of the assignments, instructions about the form of the assignments, deadlines and evaluation criteria. The course requires active participation of the students. Participation consists of reading the texts used in the lectures and online resources that are provided and discussions during the lectures.

Topics that will be discussed are:

  1. Definitions, theories and technologies of AI
  2. History of AI
  3. Regulatory and policy developments of AI in Belgium and the EU
  4. Legal issues of AI
  5. Ethical issues of AI
  6. Social issues of AI
  7. AI bias, discrimination and fairness
  8. AI and fundamental rights
  9. AI, good governance and democracy
  10. Algorithmic impact assessments and audits

These topics will be dealt with in an in-depth and critical manner, discussing both Belgian and international case studies from the private and public sector, which students are expected to explore further through self-study. Case studies that will be discussed include criminal justice system, police, education, welfare, humanitarian sector, self-driving cars, robots and smart home assistants. Two guest lecturers will be invited on a rotating basis every year who will go more in depth into case studies.

Course material
Digital course material (Required) : digital syllabus, PowerPoint slides, blog posts, online articles, podcasts and short films, Canvas
Additional info

All lectures for day students are recorded and made available through Panopto. If the lectures cannot take place physically due to the coronary measures, they will be organized on BigBlueButton. Students are expected to actively participate in lectures and online assignments. Students can ask questions through Teams during the lectures and also at a number of fixed times.

Learning Outcomes

Learning outcomes

KNOWLEDGE AND INSIGHT

  • The student develops critical thinking and in-depth interdisciplinary knowledge of AI theory and practice through various forms of knowledge transfer and independent study.
  • The student gains critical insight into the main legal, ethical and social aspects of AI.
  • The student acquires insight of different research approaches of AI.

SKILLS

  • The student is able to conduct an interdisciplinary analysis of the main legal, ethical and social aspects of AI practices in the public or private sector.
  • The student is able to reflect critically on the role of AI in society and how this is presented in online and offline media.

Grading

The final grade is composed based on the following categories:
Oral Exam determines 25% of the final mark.
Other Exam determines 75% of the final mark.

Within the Oral Exam category, the following assignments need to be completed:

  • Oral Exam with a relative weight of 25 which comprises 25% of the final mark.

Within the Other Exam category, the following assignments need to be completed:

  • Other Exam with a relative weight of 75 which comprises 75% of the final mark.

Additional info regarding evaluation

Evaluation structure:

  • Paper (4000-6000 words) Legal, ethical and social analysis of chosen case study: 75%.
  • Defense of paper at oral exam: 25%.

Evaluation criteria: For the paper:

  • content (50%): comprehensiveness of the analysis, originality, interdisciplinarity
  • form (50%): language use, structure and reasoning, coherent reference style

At the beginning of the semester, students choose a subject for their essay and prepare a short proposal/abstract for their essay, which they present during the last two lectures halfway the semester and on which they will receive feedback.

Working students should contact the lecturer to define appropriate modalities with regards to the evaluation (see evaluation).

Allowed unsatisfactory mark
The supplementary Teaching and Examination Regulations of your faculty stipulate whether an allowed unsatisfactory mark for this programme unit is permitted.

Academic context

This offer is part of the following study plans:
Master of Laws: Dual Master in Comparative Corporate and Financial Law (only offered in Dutch)
Master of Laws: Civil and Procedural Law (only offered in Dutch)
Master of Laws: Criminology (only offered in Dutch)
Master of Laws: Economic Law (only offered in Dutch)
Master of Laws: Tax Law (only offered in Dutch)
Master of Laws: International and European Law (only offered in Dutch)
Master of Laws: Public Law (only offered in Dutch)
Master of Laws: Social Law (only offered in Dutch)
Master of Laws: Criminal Law (only offered in Dutch)