Explainable AI promises to make black-box models easier to understand. But Gustau Camps-Valls argues that, in science, an explanation of a model can easily be mistaken for an explanation of the world itself. His alternative starts with a deceptively simple principle: think first, act second, model last. Gustau Camps-VallsProfessor in Electrical Engineering, Universitat de ValènciaHi! PARIS International Visiting […]
As machine learning systems become embedded in critical decisions, from finance to infrastructure, the need for trustworthy, interpretable predictions has never been greater. Aymeric Dieuleveut, Professor of Statistics and Machine Learning at École polytechnique and scientific co-director of the Hi! PARIS Center, believes the key lies not in the models themselves, but in how we communicate their uncertainty.