Combining Human-centred Explainability and Explainable AI

Janin Koch (1) , Vitor Fortes (2, 3)

1 EX-SITU - Extreme Situated Interaction - LISN
2 DFKI - Deutsches Forschungszentrum für Künstliche Intelligenz GmbH = German Research Center for Artificial Intelligence
3 University of Kaiserslautern [Kaiserslautern]

This position paper looks at differences between the current understandings of human-centered explainability and explainability AI. We discuss current ideas in both fields, as well as the differences and opportunities we discovered. As an example of combining both, we will present preliminary work on a new algebraic machine learning approach. We are excited to continue discussing design opportunities for human-centered explainability (HCx) and xAI with the broader HCxAI community.

Mots clés: Human-centered Explainability; xAI; Algebraic Machine Learning

Domaines: Interface homme-machine [cs.HC]

Janin Koch, Vitor Fortes. Combining Human-centred Explainability and Explainable AI. CHI 2022 - Conference on Human Factors in Computing Systems, ACM, Apr 2022, New Orleans, United States. ⟨hal-03943100⟩