The focus of this lecture is to give a comprehensive overview of (1) conceptual foundations, (2) methods, (3) applications in the emerging transdisciplinary research field of responsible AI.
In the first part of the lecture series, important concepts for human-AI interaction, such as trust, fairness, bias, responsibility and others are examined from a transdisciplinary perspective.
The second part of the lecture series focuses on mixed-methods approaches for investigating human-AI interaction and for participatory approaches to AI development. This includes qualitative methods from the social sciences (interviewing, group discussions, observational methods) as well as methods from design thinking and psychology.
In the third part, requirements and specific ethical and societal challenges for responsible AI development in various applications, such as AI systems in medicine, are presented.
Time and Location
Grading / Evaluation
Course materials and up-to-date information can be found in our ILIAS group.