Human Experience Design
The goal of the Human Experience Design (HXD) research area is to ensure human autonomy in an increasingly digitized and automated world. Accordingly, we design, evaluate, and implement technical systems in such a way that humans are not passive users or mere data providers, but remain active, informed, and in control.
By combining psychological insights, educational concepts, and innovative technological developments, we create environments that enhance human capabilities.
Against this backdrop, we focus on the following areas of activity:
Immersive Future
Immersive technologies such as virtual and augmented reality enable new forms of visualization, simulation, collaboration, and knowledge transfer—especially when dealing with complex issues.
In combination with artificial intelligence, we model dynamic scenarios that can be used as training and experimentation environments. The goal is to present complex relationships in an understandable way, promote individual learning processes, and facilitate access to digital technologies. This is based on a consistent human-centered design approach that involves users in all phases of development, thereby ensuring acceptance, usability, and effectiveness.
Key research questions:
• How can AI and immersive media be combined to create dynamic scenarios?
• What requirements must human-machine interfaces meet to enable effective interaction in AI-supported immersive systems?
• How can complex data and processes be presented in a way that is understandable and actionable through immersive visualization?
• What pedagogical concepts are necessary to integrate immersive technologies sustainably into education and training?
• How can quality, transparency, and trust in AI-supported immersive applications be ensured?
• How can digital representations of real objects be created in a low-threshold and resource-efficient manner?
Information Security Awareness
Information security should not be viewed as a purely technical challenge; it arises from a complex interplay of technology, people, and organization. Human behavior, as a key component within this system, can contribute to both enhancing and compromising security. Accordingly, users must be actively incorporated into security strategies, just as technical and organizational measures are.
Information Security Awareness refers to people’s awareness, attitudes, and specific behaviors when dealing with information, IT systems, and digital threats.
Key research questions:
• What connection exists in the context of Information Security Awareness between security-related knowledge, individual attitudes, and actual security behavior?
• What security requirements arise in organizations, and how can these be addressed and sustainably met?
• Which interventions improve the security behavior of different target groups and contribute to the long-term maintenance of awareness?
• How can training and communication measures be integrated into organizational structures and work processes to achieve sustainable effects in strengthening information security awareness?
KI-Bewertung – Human in the Loop:
Künstliche Intelligenz (KI) sollte nicht als isolierte, rein algorithmische Prozessfähigkeit betrachtet werden. Vielmehr sollte sie als integraler Bestandteil soziotechnischer Arbeits- und Lebensumgebungen angesehen werden. Dieses Forschungsgebiet konzentriert sich auf die Intelligenz des Gesamtsystems – insbesondere in dessen Interaktion mit Menschen. Zu den wichtigsten Grundlagen zählen kontextspezifische Anforderungen an KI-Anwendungen sowie regulatorische und ethische Leitlinien wie der KI-Gesetzentwurf der Europäischen Union und die UNESCO-Empfehlung zur Ethik der künstlichen Intelligenz.
Zentrale Forschungsfragen:
• Wie lässt sich eine menschenzentrierte Gestaltung von KI-Systemen erreichen, die Vertrauen, Akzeptanz und ethische Integrität vereint?
• Wie müssen erklärbare KI-Mechanismen gestaltet sein, damit sowohl Laien als auch Experten die Entscheidungsgrundlagen eines KI-Systems nachvollziehen können?
• Welche Faktoren jenseits der technischen Genauigkeit bestimmen die langfristige Akzeptanz und den wahrgenommenen Nutzen von KI-Anwendungen in spezifischen Kontexten?
• Welche Designkriterien können das Risiko algorithmischer Verzerrungen in Entscheidungsprozessen wirksam minimieren?
• Welche Auswirkungen hat der langfristige Einsatz von KI-Anwendungen auf individuelle Kompetenzen?