Learning outcomes

By the end of the course, students will be able to:

  • Present the main concepts of AI.
  • Distinguish between explicit knowledge models (symbolic AI) and implicit knowledge models (connectionist AI).
  • Discuss the ethical and social impacts and challenges of AI.
  • Illustrate these ethical issues through examples from science fiction.
  • Explain the symbolic paradigms of AI:
  • Problem solving.
  • First-order logic.
  • Ontologies.
  • Probabilistic reasoning.
  • Solve limited exercises in these paradigms.


Goals

Main purposes of the course are :

  • To introduce you to Information and Knowledge Modeling concepts, methods and languages that are relevant for doing Business Analysis
  • To introduce you to scientific reading and to the science-based approach of different domains related to Information and Knowledge Modeling

 

Content

This course examines:

  • Implicit and explicit models of knowledge.
  • In particular, it presents:
  • Problem solving.
  • First-order logic.
  • Ontologies.
  • Probabilistic reasoning.
  • Finally, it explores the ethical issues raised by AI through science fiction films.

Table of contents

  1. Introduction to ethical questions
  2. Explicit knowledge modelling techniques
  3. Problem solving
  4. First-order logic
  5. Ontologies
  6. Probabilistic reasoning
  7. Exercises and applications
  8. Problem solving
  9. First-order logic
  10. Ontologies
  11. Probabilistic reasoning
  12. Ethical questions and their illustration

Teaching methods

The course combines three teaching methods:

  • Lectures by the professor
  • Presentations by students based on a reference work and literature
  • Presentations by students illustrating ethical issues explored in literature using science fiction films

Assessment method

Students are assessed on the basis of:



  • the quality of the content of their presentations (substance)
  • the quality of their oral presentations (form)
  • the quality of their personnal participation in discussions
  • an individual oral examination


Given the collective and monitoring arrangements, the assignments and their presentations are subject to a single assessment, and the mark obtained is valid for both sessions.


The oral examination is only open to students who have presented their assignements (Article 38 of the REE).

Sources, references and any support material

Slides will be made available via Webcampus.

Mandatory Readings

Further references will be provided during the presentations.

Language of instruction

English
Training Study programme Block Credits Mandatory
Master in Management, Professional focus in Digital Enterprise Transformation Standard 1 5 No
Master in Business Engineering Finalité spécialisée en data science 1 5 Yes
Master in Business Engineering Finalité spécialisée en Sustainable & Digital Management 1 5 Yes
Master in Management, Professional focus in Digital Enterprise Transformation Standard 2 5 No
Master in Business Engineering Finalité spécialisée en data science 2 5 Yes
Master in Business Engineering Finalité spécialisée en Sustainable & Digital Management 2 5 Yes