Competent in Use: Variable Autonomy of self-learning Systems in Hostile-to-Life Environments
Whether in space, in the deep sea or in disaster areas - operations in such hostile-to-life environments represent a major challenge with considerable risks for humans. Self-learning systems can help to reduce hazards and risks for humans or to make such environments accessible in the first place. Mission configurations, the degree of autonomy of self-learning systems and the intensity of interaction with humans can vary considerably. A good division of labor is critical to the success of collaboration between humans and self-learning systems. The working group Hostile-to-Life Environments of the Plattform Lernende Systeme has identified and investigated key requirements for this division of labor between humans and self-learning systems as well as for the competence of the self-learning systems in the respective situational context of application.