Professorship for Human-Computer Interaction and Usable Safety Engineering

At the workgroup of Human-Computer Interaction and Usable Safety Engineering we deal with the conception, design, and development of digital systems, especially in safety-critical areas.

The central guiding question is: How does the design of technical systems influence safety regarding work, health, life, society, and the environment? The users of such systems are an integral part of the development process and are the focus of our research interest.

From a technical perspective, we are particularly interested in modern networked systems and AI-based applications. In this area of application, a broad field of research is of interest. For example, we study the impact of social media on opinion formation and the spread of disinformation online, as well as its impact on the safety of democracy, society, and health. Issues of social media design and the formulation of communication protocols and their interfaces can have a massive impact on prominent content and its effects on individuals and society.
On the other hand, we study the impact of decision support systems and recommendation systems in safety-critical systems (health, eHealth, public sector, BOS). Here, we primarily address issues of decision autonomy, privacy, and user-adaptive information representation. We seek to understand how different trade-offs between different goal criteria affect acceptance depending on the diversity of users.

The central approach is a multi-method approach that combines methods from computer science and the social sciences. Thus, methods of human-computer interaction (e.g., user-centered design, participatory design, walkthroughs, heuristic evaluation) are combined with methods of psychology (e.g., qualitative and quantitative empirical social research, acceptance research, conjoint methods, structural equation modeling) and with methods of socioinformatics (e.g., agent-based modeling, system dynamics modeling, computational social network analysis)  to find suitable answers to the increasingly complex questions of real-world requirements.

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