Winter School on Causality and Explainable AI
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The CAUSALI-T-AI project of the PEPR IA is organizing a Franco-German school from October 20 to 24 at the Sorbonne Cluster for Artificial Intelligence (SCAI) in Jussieu, Paris.
This winter school brings together leading experts in causality and explainability—two key pillars of modern AI. While often studied separately, these fields are complementary: causality uncovers the underlying cause-effect mechanisms of data, while explainability sheds light on the behavior of predictive models. By bringing them together, this will open up new avenues for enhancing the reliability and interpretability of AI models. Designed for Master’s and PhD students, the program combines lectures, tutorials, and interdisciplinary discussions, including an accessible introductory tutorial tailored to Master’s students.
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