Whether the problem relates to the emerging risks of Generative AI, or to more routine risks linked to bias, explainability and robustness of classification or recommendation systems, our research and teaching teams work together, breaking down disciplinary silos to explore pragmatic solutions.
Under the European AI Act, cooperation across scientific disciplines is indispensable. Data scientists cannot address bias and fundamental rights risks alone, nor can lawyers and sociologists imagine solutions to AI risks without involving computer and data scientists. Télécom Paris’s brings these talents together, both in teaching and research. For each problem and use case, we confront different disciplinary points of view.
This multidisciplinary approach requires getting beyond the big principles, and into the operational realities of high-risk AI applications, understanding safety and regulatory constraints specific to particular industries (finance, public safety, health, public administration, energy, transport), and the intricacies of human-machine interactions (HCI).
We prepare our students, whether PhD students or engineering graduates, to collaborate in multidisciplinary environments focused on high-risk AI applications, within public administrations, large enterprises, start-ups, or regulators.
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