Understand and explain decisions of intelligent systems from the user's point of view
We research and develop data-based intelligent user interfaces that are designed to satisfy the requirements and needs of humans. Our activities focus on the life cycle of modern applications such as autonomous driving and intelligent co-pilot (pilot-in-the-loop). This involves the development of user, domain and task models and the implementation of machine learning and intelligent data mining methods.
A further focus involves making AI decision paths understandable and increasing trust in autonomous systems. One way we do this is by examining models and user interfaces that transparently represent AI decisions. Our goal is to foster the integration and acceptance of intelligent systems in every possible field of application. We thus strive to design the interaction between humans and self-learning systems in such a way that it’s natural, intuitive, robust and reliable.