Artificial intelligence systems are increasingly being adapted to human activities. Fed by data humans generate, they are working ever more closely with us in real time. The search for artificial intelligence is also a search for human values. An important part of our research is on how knowledge can be integrated into technologies and how it can be derived from them.
Ubiquitous stealth technologies have the ability to expand and support human knowledge, thereby optimizing people's potential and productivity, but also to exacerbate overlooked distortions and errors in increasingly complex, interconnected systems. To the extent that society is dependent on autonomous, intelligent, and critical software systems, new strategies must be found to ensure not only their existing quality aspects such as safety, efficiency, reliability, and security, but also the ethics of human-machine interactions and the associated socio-political implications.
Artificial intelligence systems are increasingly being adapted to human activities. Fed by data that we humans generate, they are working ever more closely with us in real time. It is becoming increasingly obvious that the search for artificial intelligence is also a search for human values. How knowledge can be integrated into and extracted from technologies is an important part of this research. Central aspects such as systematic discrimination (bias), trust, transparency, responsibility, sustainability, human-machine interaction, and the need for new forms of education are core topics of the research group.
Although they already influence the everyday life of citizens in a variety of ways, many AI systems have up to now been black boxes. Their public perception is significantly shaped by mistrust, but also by ignorance of the theoretical framework of these systems. Therefore, another goal of the research group is to involve the public in the scientific discourse on AI. We want to sharpen the awareness of citizens of the capabilities and limitations of AI technologies and to break new ground for scientific research through social dialogue and inclusion.
Both quantitative and qualitative methods of psychology, computer science, social sciences and cultural studies are applied: metrics of quality engineering, literature research, application case studies, discourse analyses, questionnaires, interviews, workshops and interactive events, public discussion forums and debates.
In our research, we consider intelligent algorithms as technologies on the one hand, and as cultural artifacts on the other hand, determined by the ontological position of the individual developer.
We analyse the state of the art of artificial intelligence from a technical point of view as well as the discourses (on AI), the symbolic violence involved, and the biases of such systems.
In addition to developing a theoretical framework for cultural technology research, we are working to broaden the horizons of the current state of user-oriented AI, AI for the common good, and inclusive AI. Our approach is characterized by questioning and deconstructing the current design principles for development of intelligent, critical systems and the development of alternatives to such systems.
Research Group Lead
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