Like humans, AI systems have problem-solving capabilities in complex domains. In order that AI systems do not only generate new information from information as "black box systems", they should be realized as "white box systems", which provide the users with explanations and accountability as to how results were achieved. Explainable AI (XAI) as a sub-aspect enables users to question and understand results if necessary, and also to reject them if necessary. Human Centered AI turns AI systems into human-centric and cooperative systems. This makes technology ergonomic, understandable, and responsible. At IMIS, prototypes are developed that show what white box systems look like and how to interact with them.