RNTI

MODULAD
Une interface XAI pour des modèles d'apprentissage automatique à base d'arbres
In EGC 2025, vol. RNTI-E-41, pp.411-418
Abstract
We present an XAI protocol for ruling interactions between a tree-based ML model (the AI system) and its user U, in the context of a prediction task. The pieces of knowledge held by U concerning the prediction task are supposed to be representable by a consistent yet incomplete set of reliable classification rules. The proposed protocol aims to help U deciding what to do with each prediction made by AI (accept it, reject it). It also aims to improve the quality of further predictions made by AI thanks to the expertise of U, and, reciprocally, to complete the pieces of knowledge held by U by leveraging the predictions made by AI.