In future AI-supported, data-driven production environments, the role of humans will change. The traditional plant operator will become a supervisor of (partially) autonomous systems. These systems act on the basis of constantly updated data, changing boundary conditions and targets. Therefore, methods must be developed that make machine decisions transparent and comprehensible and offer context-dependent options for action in order to ensure the sovereignty of humans and to use their creativity to optimize the overall process.

On the one hand, this includes intuitively comprehensible processing of machine decision-making, as well as compatible control and regulation approaches that allow the human supervisor to participate at a compatible pace. In addition, automation approaches are to be researched that allow humans and machines ("cobots") to work together in a natural way and do not require complex reconfiguration of safety mechanisms.