Human Digital Twins and Generative Agents: Personalized and Adaptive Human-AI Interactions
While digital twins of machines have been widely discussed and implemented in research and practice the lecture “Human Digital Twins and Generative Agents: Personalized and Adaptive Human-AI Interactions” explores the emerging paradigm of Human Digital Twins and Generative Agents as a foundation for personalized and adaptive human–machine interaction. As organizations increasingly integrate AI into complex work and production systems, the need for human-centered, context-aware, and continuously learning human-machine interaction processes becomes a critical success factor. The session introduces the concept of the Human Digital Twins as a dynamic digital representation of individuals (e.g. workers) that capture elements like preferences, behaviors, competencies, decision processes and situational context. In combination with generative agents, these models enable AI-based systems to simulate, anticipate, and adapt to human preferences or decisions in real time and thus create a dynamic interface between humans and machines in human-machine interaction. Building on recent advances in generative AI, the lecture discusses how such systems can support co-creative decision-making, collaboration, and co-learning in digitalized work environments. Drawing on examples from industry and current research, the talk concludes by outlining practical implications for designing adaptive, personalized, and responsible interaction systems in line with the broader goals of AI-driven innovation for modern business and society.
Lecture at NEMO2026
Date/Time: Wednesday, July 29, 2026 at 09:30