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In my research I focus on human-centered computing. Progress in artificial intelligence (AI), robotics, conversational agents, connectivity and sensing technology increases the capabilities of physical and virtual agents to operate more and more autonomously, possibly as team members, companions or partners of humans. However, the information and decision-making processes of these agents differ from human’s processes fundamentally. Fruitful human-agent collaboration requires the AI to develop meta-reasoning and meta-learning capabilities, which match the individual human and group needs, and which support the lifelong human-agent co-learning. Harmonizing the joint and interdependent social, cognitive and affective processes in the co-active learning process, is a major challenge for the research & development community, asking for a rigorous interdisciplinary approach. Social sciences (e.g., Psychology) and AI have to join and study agents and humans as part of an evolving mutually adaptive human-agent collective with hybrid intelligence. This way, AI-included technologies can augment team’s capabilities progressively, e.g. to integrate robotic partners into the healthcare teams, safety and security teams, and defense teams for improved performance and resilience.
A socio-cognitive engineering methodology has been developed and applied for the design of artificial, virtual or physical, agents (ePartners) that show social, cognitive and affective behaviors to enhance performance, resilience, health and/or wellbeing. In the safety and security domain, the ePartners entail methods and prototypes for sharing situation awareness, harmonizing workload distributions, and supporting stress-coping to enhance performance and resilience (e.g. in robot-assisted disaster response teams). In the health domain, examples are robotic and virtual assistants that help patients to cope with their chronic disease (e.g., diabetics) in different self-managements activities, and robots that help older adults with dementia and care givers to establish positive experiences of life in the care centers. Important buildings blocks of the hybrid intelligence are (1) the (computational) cognition and emotion models for performance and health support, (2) the human-robot partnership functions for attuning assistance to the individual user and momentary usage context, and (3) the design patterns for effective and efficient collaborative behavior.