- Ruhr-Universität Bochum
Forschungsfokus
- Explainable Artificial Intelligence
- Design Science Research
- Projekt: KI-unterstützte Steigerung der Mobilität und gesellschaftlichen Teilhabe von Senior*innen (KISS)
Publikationen
- Eisenhardt, D. and Hussein Keke, H. (2026). Construal Level Theory in Explainable AI: Effects of Explanation Formats on Reliance and Performance. In Proceedings of the 18th International Conference on Agents and Artificial Intelligence – Volume 1, ISBN 978-989-758-796-2, ISSN 2184-433X, pages 33-43.
- Hussein Keke, H., Eisenhardt, D., and Meske, C. (in press). Thinking Twice: A sequential approach to nudge towards reflective judgment in GenAI-assisted decision making. Wirtschaftsinformatik 2025 Proceedings. 43.
- Meske, C., Eisenhardt, D., Šešelja, D., Straßer, C., and Schneider, J. (2024). Mitigating Bias In Academic Publishing: Towards Responsible (Gen)Ai-Augmentation In Peer-Review Processes. MCIS 2024 Proceedings. Link
- Schneider, J., Eisenhardt, D., Utama, C., and Meske, C. (2023). Impact of Data Collection on ML Models: Analyzing Differences of Biases Between Low- vs. High-Skilled Annotators. Wirtschaftsinformatik (WI) 2023 Proceedings. 15 Link
- Bunde, E., Eisenhardt, D., Sonntag, D., Profitlich, H. J., and Meske, C. (2023). Giving DIAnA More TIME – Guidance for the Design of XAI-Based Medical Decision Support Systems. International Conference on Design Science Research in Information Systems and Technology (DESRIST), 2023, pp. 107-122. Link
- Breitenbach, J., Eisenhardt, D., Rieg, T., Baumgartl, H., Ulrich, P., Timm, I., and Buettner, R. (2022). Machine Learning-Based Health Behavior Prediction Using Resting-State EEG Data. AMCIS 2022 Proceedings. Link
