Chromik, Michael2020-06-062020-06-062020https://dl.eusset.eu/handle/20.500.12015/3710The interdisciplinary field of explainable artificial intelligence (XAI) aims to foster human understanding of black-box machine learning models through explanation-generating methods. In this paper, we describe the need for interactive explanation facilities for end-users in XAI. We believe that interactive explanation facilities that provide multiple layers of customizable explanations offer promising directions for empowering humans to practically understand model behavior and limitations. We outline a web-based UI framework for developing interactive explanation flows based on SHAP.enText/Conference Paper10.18420/ecscw2020_p062510-2591