An interdisciplinary team

Our interdisciplinary team federates six academic fields (applied math, statistics, computer science, economics, law and sociology) around the ethical issues raised by artificial intelligence.

« To be reliable, a decision system must meet criteria of explainability in addition to performance criteria. We seek to integrate these criteria when learning these systems. »
Florence d’Alché-Buc, professor in massive data processing and mining at Télécom Paris and holder of the Data Science and Artificial Intelligence for Digitalized Industry and Services chair

« Hybrid approaches make it possible to combine symbolic AI (based on knowledge representation) and machine learning (especially from data) leading to a better explicability of algorithmic decisions. »
Isabelle Bloch, professor in applied mathematics and artificial intelligence, in particular for spatial reasoning, at Télécom Paris

« The European Commission and the regulators all want explainable algorithms, but the devil is in the detail. The questions that need to be answered are: for whom and why? »
Winston Maxwell, director, law and technology studies at Télécom Paris

« If, the explicability of algorithms is not necessarily necessary for an algorithm which plays chess, it becomes essential when it is about a critical system. »
David Bounie, head of the Department of Economics and Social Sciences at Télécom Paris