ALEEDSA: Augmented Reality for Interactive Machine Learning

Andrea Ferrario, Raphael Weibel, Stefan Feuerriegel

Abstract: In this work, we present ALEEDSA: the first system for performing interactive machine learning with augmented reality. The system is characterized by the following three distinctive features: First, immersion is used for visualizing machine learning models in terms of their outcomes. The outcomes can then be compared against domain knowledge (e.g., via counterfactual explanations) so that users can better understand the behavior of machine learning models. Second, interactivity with augmented reality along the complete machine learning pipeline fosters rapid modeling. Third, collaboration enables a multi-user setting, wherein machine learning engineers and domain experts can jointly discuss the behavior of machine learning models. The effectiveness of our proof-of-concept is demonstrated in an experimental study involving both students and business professionals. Altogether, ALEEDSA provides a more straightforward utilization of machine learning in organizational and educational practice.