The project will examine argumentation structures extracted from ML program behavior to support the conclusions they arrive at, thus enhancing the explainability of data-driven AI.
Another more general thread of this project will be to uncover the links of persuasion, biases, learnability and argumentation, linking with the projects of Loubes and Castet-Renard.
Programmes : IA acceptable, certifiable & collaborative
Thèmes : explicabilité, fair learning
Leïla Amgoud, DR CNRS, IRIT