Descriptif
Students will learn:
- why different families of AI (symbolic, machine learning) present different risk profiles
- how risks of bias and discrimination manifest themselves in AI systems, and approaches to mitigate those risks
- why explainability prevents machine learning from being used in certain critical applications
- "meaningful human control" of AI systems
- the legal framework around AI: the European General Data Protection Regulation, Platform Regulation, the future AI Act, EU Charter of Fundamental Rights
Teaching will be structured around use cases, including autonomous lethal weapons, facial recognition, social media use of algorithms, algorithms to detect terrorist risk
Grading will be half based on multiple choice test, and half on a final paper.
Diplôme(s) concerné(s)
Format des notes
Numérique sur 20Littérale/grade réduitPour les étudiants du diplôme M2 Data Sciences
Le rattrapage est autorisé (Max entre les deux notes)- Crédits ECTS acquis : 3 ECTS
La note obtenue rentre dans le calcul de votre GPA.