Jonathan Aigrain

Contextualization and exploration of local feature importance as explanations to improve understanding and satisfaction of non-expert users

The increasing usage of complex ML models to make important decisions has raised interest in explainable artificial intelligence (XAI). In this work, we focus on providing accessible and useful explanations for non-expert users. More specifically, we propose generic XAI design principles for contextualizing and allowi…