In his talk on “AI-Emotion Recognition in the Wild and Explainable Interactive Machine Learning on Image Data”, Prof. Hinz provided two examples for the capabilities of Machine Learning to analyze image data. In the first case study, he demonstrated the potential of ML for medical diagnosis while highlighting the importance of Explainable AI methods and Human-in-the-loop concepts to arrive at meaningful results. The second case study from Marketing showed how standard smartphones can be used to predict the effectiveness from ads in a non-intrusive and easy-to-implement way.
About the Speaker
Oliver Hinz holds the Chair of Information Systems and Information Management at Goethe University Frankfurt. His research has been published in top journals like Information Systems Research (ISR), Management Information Systems Quarterly (MISQ), Journal of Marketing, Journal of Management Information Systems (JMIS), Decision Support Systems (DSS), Electronic Markets (EM), Business & Information Systems Engineering (BISE) and in a number of proceedings (e.g. ICIS, ECIS, PACIS).