Challenges in Evaluating Interactive Visual Machine Learning Systems
Résumé
In interactive visual machine learning (IVML), humans and machine learning algorithms collaborate to achieve tasks mediated by interactive visual interfaces. This human-in-the-loop approach to machine learning brings forth not only numerous intelligibility, trust and usability issues, but also many open questions with respect to the evaluation of the IVML system, both as separate components, and as a holistic entity that includes both human and machine intelligence. This article describes the challenges and research gaps identified in an IEEE VIS workshop on the evaluation of interactive visual machine learning systems.
Domaines
Interface homme-machine [cs.HC]
Origine : Fichiers produits par l'(les) auteur(s)