Learning outcomes

The course will enable students to :

  • understand the field of artificial intelligence including its technical, historical and human dimensions
  • adopt a critical vision in order to use AI wisely, reflectively and responsibly
  • adopt a scientific and reasoned vision of AI (benefits and risks)
  • be able to defend or oppose the use of AI in an organisation or society
Here is the list of teachers involved in this course: 
 
  • Agathe Picron
  • Aline Wilmet
  • Amélie Lachapelle
  • Anne-Sophie Lemaire
  • Anthony Simonofski
  • Benoît Frénay
  • Benoît Michaux
  • Benoît Vanderose
  • Bruno Dumas
  • Catherine Linard
  • Dominique Lambert
  • Élise Degrave
  • Isabelle Linden
  • Jean-François NISOLLE
  • Juliette Ferry-Danini
  • Katrien Beuls
  • Michel Ajzen
  • Michaël Lognoul
  • Michaël Lobet
  • Nathanaël Laurent
  • Nicolas Franco
  • Nicolas Ruffini-Ronzani
  • Sébastien Dujardin
  • Sophie Vanmeerhaeghe
  • Xavier Devroey

Content

The schedule below shows the content of the course (which may be adjusted slightly as the course will be given for the first time this year; the number of hours is given as an indication):

1) Foundations of AI

  • Preamble (1h): introduction, history of AI, course outline and assessment methods
  • Computer science basics (1 hour): anatomy of a computer, vocabulary, how software is developed,...
  • Fundamentals of AI (6 hrs): types of AI, logid and expert systems, neural networks, generative AI, LLM,...

2) AI and individuals

  • Users and AI (2 hrs): notions of user experience, design principles for AI, transparency and accessibility,...
  • Towards responsible AI (2 hrs): bias, responsibility, relationship with the world and reality, sustainable AI and energy demand,...

3) AI and organisations

  • Use of AI and managerial vision (2 hrs): decision support, automation, organisational applications, new technologies,...
  • Disciplinary applications of AI (4h = 8 x 30 minutes, different speakers ): geospatial AI, AI in history, impact on the profession of developer, AI in physics, AI in medicine,...

4) AI and society

  • Relationship between AI and society (2h): responsibility, impact on society (digital divide, inequalities, etc.), risks (crime, fake news, etc.),...
  • What does the law say about AI (2 hrs): regulations on AI, legal imperatives (copyright, plagiarism, privacy, etc.), impact of AI on law and justice,...
  • AI and education (2 hrs): impact of AI on education.

Assessment method

The assessment consists of a use case of AI from the student's field of study (e.g. coding for computing, problem solving in physics, etc.) with a critical analysis: what is the quality of the proposed solution, what are its limitations, what problems have been encountered, etc.? The work will be presented as a poster.

Language of instruction

French
Training Study programme Block Credits Mandatory
Master in Physics Finalité approfondie 1 3 No
Master in Economics : General (Evenings and Weekends Schedule) Standard 1 5 No
Master in Physics Finalité didactique 1 3 No
Master in Management (Evenings and Weekends Schedule) Standard 1 5 No
Advanced Master in Computer Science and Innovation Standard 1 5 No
Master in Economics : General (Evenings and Weekends Schedule) Standard 1 5 No
Master in Physics Finalité spécialisée en physique et data 1 3 No
Additional teaching units for the Master's degree in Management Sciences (715P) Standard 1 3 No
Master in Physics Standard 1 3 No
Master in Physics Finalité spécialisée en physique du vivant 1 3 No
List of cross-disciplinary teaching units Standard 1 3 No
Master in Management, Professional focus (Evenings and Weekends Schedule) Standard 1 5 No
Master in Management, Professional focus (Evenings and Weekends Schedule) Standard 2 5 No
Master of Education, Section 4: Biology Standard 2 3 No
Master in Physics Finalité approfondie 2 3 No
Bachelor in Economics and Management Standard 2 3 No
Master in Economics : General (Evenings and Weekends Schedule) Standard 2 5 No
Master of Education, Section 4: Chemistry Standard 2 3 No
Bachelor in Law Standard 2 3 No
Master in Physics Finalité didactique 2 3 No
Bachelor in Political Sciences : General Standard 2 3 No
Master of Education, Section 4: Physics Standard 2 3 No
Bachelor in Law Erasmus Belgica UHasselt 2 3 No
Bachelor in Mathematics Standard 2 3 No
Master in Physics Finalité spécialisée en physique et data 2 3 No
Bachelor in Computer Science Standard 2 3 No
Bachelor in Information and Communication Standard 2 3 No
Master in Physics Finalité spécialisée en physique du vivant 2 3 No
Bachelor in Business Engineering Standard 2 5 Yes
Bachelor in Information and Communication Standard 3 5 Yes
Bachelor in Modern Languages and Literatures: German, Dutch and English Standard 3 3 No
Bachelor in Biology Standard 3 3 No
Bachelor in Biomedical Sciences Standard 3 3 No
Bachelor in Law Standard 3 3 No
Bachelor in Law Erasmus Belgica UHasselt 3 3 No
Bachelor in Mathematics Standard 3 3 No