Important dates: see “other information”, block seminar September 19th to 30th

Content
This course combines theoretical and scientific foundations from the field of Explainable Artificial Intelligence with the development of solution approaches for real-world problems. This includes:
• Communicating the status quo on the topic of Explainable Artificial Intelligence as well as relevant use cases, stakeholders and research opportunities
• In-depth application of Design Science Research as a design-oriented research approach
• Instantiation of possible solutions in prototypical IT-artifacts
• Use of qualitative and/or quantitative research methods for the development of generalizable design knowledge as well as the evaluation of possible solutions
• Working on interdisciplinary questions with high relevance for research and practice


Participation requirements:
• Basic knowledge in the topics of Artificial Intelligence/Machine Learning
• Interest in the scientific development and evaluation of IT-artifacts, which goes hand in hand with literature work
• Willingness to deal with qualitative and quantitative evaluation methods
• Interest in prototyping
Recommended prior knowledge:
• Basic knowledge of artificial intelligence and/or relevant programming skills (e.g., Python)
• Familiarity with (graphics) software for the design of prototypical information systems
(e.g., their user interfaces)


After successful completion of the module
• You have become acquainted with the research field of Explainable Artificial Intelligence and understood which consequences can result from the blackbox problem
• You have become acquainted with different methods and techniques from the field of Explainable Artificial Intelligence as well as their characteristics
• You have learned the core research process of Design Science Research and successfully applied the procedure in the context of a seminar paper
• You have worked on a scientific problem with practical relevance using scientific methods

Teaching forms
This module will be held as a 2-week long block course. After introductory lectures on the topics of Explainable Artificial Intelligence and Design Science Research by the lecturers, the students work independently on their scientific projects (in groups). Exchange among the groups through constructive discussions and feedback rounds is encouraged. The lecturers provide assistance with the work and give continuous feedback on the project and the associated seminar papers.
The XAI block seminar is held entirely via online (outbreak) sessions to enable collaboration with students at the Ruhr University Bochum.

Forms of examination
The examination consists of two parts:
• One graded presentation (30 %)
• Graded seminar paper (70 %)

Prerequisites for the award of credit points
• Regular participation
• Successful presentation of the intermediate and final results
• Successful processing and submission of the seminar paper

Other information:
• Information event regarding the seminar’s organization: April 22th, 1-2 pm (https://ruhr-uni-bochum.zoom.us/j/68248239344?pwd=TzFvUXUrRWhYQWVWRzhBZkUxSnUrUT09)
• Input presentations on XAI and Design Science (held by the SSKI and AAI chairs), building student groups (3/group), selection of topics by groups: September 15th, 9 am - 3 pm (participation is obligatory!)
• Block seminar: September 19th to 30th

This seminar is offered in cooperation with the Ruhr University Bochum with Prof. Dr. Christian Meske as an additional lecturer.

Contact: Hannes Kath,