Artificial Intelligence and societal transformations

Structure : EUR ELMI
Niveau du cours : M1, M2, PhD
Code de l'UE : BMUIST1
Semestre : Impair
Lieu d'enseignement : Campus Saint Jean d'Angély
Langue : Anglais


Students in the first or second year of one of the following Masters : CODEEN, CESUN, Expertise Economique, DI, IMTT, SD, RMI, CCPro, Analyse financière et gestion des actifs, Conseille patrimonial et financier, as well as Ph.D students (EUR ELMI/GREDEG).


There are no prerequisites for this course. Everyone is welcome!




Learning outcomes

At the end of this course, learners will be able to...

  • explain key aspects of artificial intelligence as a technology,
  • demonstrate critical awareness of current issues in artificial intelligence development,
  • explore artificial intelligence applications and discuss their impact on economic dynamics, business models, work, and science.

Modern Artificial Intelligence (AI) can be seen as a series of advances in the fields of computer science, applied mathematics and statistics; however, as AI is increasingly embedded into software and products and is enabled by the availability of data and complex hardware technologies, it becomes the engine of profound changes in the way our societies and economies work. As with previous technological breakthroughs, the societal transformations they produce can be identified, unpacked, and put in context.

This course will provide you with the tools to do that. The contents are organized around two main sections. In the first (Lectures 1-2-3), we will introduce AI and its enabling technology and explore from a “bird’s-eye view” what AI adoption implies in terms of economic incentives and business opportunities, re-organisation of labor, production, as well as scientific activities. We will explore how AI is implemented in different domains and sectors, and what are the costs we are bearing while developing such transformational innovation — in terms of new inequality, winners and losers, and environmental toll. After gaining a holistic view of AI, the second section (Lectures 4-5-6) will guide you through the details of the techniques and models that are the backbone of AI solutions. Combining explanations and guided hands-on tasks, you will dissect how neural networks work and learn the foundations of natural language processing (NLP), currently the most advanced and successful trajectory of AI development.

Upon successful completion of this course, students will be awarded 3 ECTS.

This course was co-developed by the EUR ELMI and the EFELIA team (École Française de l'Intelligence Artificielle) of the Institut 3IA Côte d'Azur.

We recommend that you bring your own laptop to each session. You will need a Google account and the Google Chrome browser.


Teaching methods
  • In-person lectures
  • Case studies (real-world applications)
  • Practical exercises
  • Moodle

Students’ progresses will be assessed continuously throughout the course (contrôle continu). More information on the assessment modes will be provided at the beginning of the course.

  • The relevant literature for each class will be indicated on Moodle in advance. For the lectures 1-2-3, students will be asked to read seminal or recent academic papers.
  • Vannuccini, S., & Prytkova, E. (2023). Artificial Intelligence’s new clothes? A system technology perspective. Journal of Information Technology, 0(0). (available on Moodle).
Resources for success
  • TUT'TOP : peer tutoring on methodological, social, administrative or logistical issues.
  • écri+ : to improve your written French.
  • Centre de ressources en langues : to improve your foreign language skills (French or other).
  • METODA : to improve your documentary research skills.
  • S'orienter / Se réorienter : to be advised by the university's career counsellors.
  • Centre de santé et aide sociale : to look after your physical and mental health, and to seek support in the event of social hardship.
  • Cellule Handicap : support for students with disabilities.
  • Plateforme de signalement : to report acts of violence, harassment or discrimination (sexual and gender-based violence, LGBTphobia, racism, xenophobia, etc.) you have witnessed or experienced at the university, and to get support.


Session Date Duration Professor Topic
1 05/10/2023
8h - 12h
4h Simone Vannuccini 1.A AI and technological breakthroughs
1.B AI from a system perspective: software, hardware, data
2 12/10/2023
8h - 12h
4h Simone Vannuccini 2.A AI and its impact on economic dynamics, business models, work, and science
3 19/10/2023
8h - 12h
4h Simone Vannuccini 3.A The societal and environmental costs of AI: dual uses, ethics, and unintended consequences
3.B Policy and geopolitics of AI
4 26/10/2023
8h - 12h
4h Anaïs Ollagnier 4.A Knowledge representation
4.B Introduction to Machine Learning
5 09/11/2023
8h - 12h
4h Anaïs Ollagnier 5.A Understanding Artificial Neural Networks (Multilayer Perceptron)
5.B Let’s go deeper (Convolutional Neural Networks)
6 16/11/2023
8h - 12h
4h Anaïs Ollagnier 6.A What is Natural Language Processing?
6.B Data Representation principles (Bag of Words, Embeddings, Language Models)