NOVA - A tool for eXplainable Cooperative Machine Learning

• Published in: International Conference on Affective Computing and Intelligent Interaction and workshops pp. 109 - 115
• Main Authors: Heimerl, Alexander, Baur, Tobias, Lingenfelser, Florian, Wagner, Johannes, Andre, Elisabeth
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.09.2019
• Subjects: 3G mobile communication; annotation tools; cooperative machine learning; explainable AI
• ISSN: 2156-8111
• DOI: 10.1109/ACII.2019.8925519

In this paper, we introduce a next-generation annotation tool called NOVA, which implements a workflow that interactively incorporates the 'human in the loop'. In particular, NOVA offers a collaborative annotation backend where multiple annotators join their workforce. A main aspect of NOVA is the possibility of applying semi-supervised active learning where Machine Learning techniques are used already during the annotation process by giving the possibility to pre-label data automatically. Furthermore, NOVA implements recent eXplainable AI (XAI) techniques to provide users with both, a confidence value of the automatically predicted annotations, as well as visual explanation. This way, annotators get to understand whether they can trust their ML models, or more annotated data is necessary.