The Chair of Machine Learning and Uncertainty Quantification, presented two scientific papers at the 33rd European Conference on Information Systems (ECIS 2025) in Amman, Jordan. Under the conference's central theme, "Co-Creating Value for an Intelligent Future," current research results from the fields of algorithmic management and explainable artificial intelligence were presented:
- Schauer, A., Schikowski, N., & Schnurr, D. (2025). Algorithmic Management with Human Oversight: An Experimental Analysis
This paper experimentally investigates how different forms of human control affect the acceptance, effectiveness, and fairness of algorithmic management systems.
- Förster, M., Hagn, M., Hambauer, N., Jaki, P., Obermeier, A., Pinski, M., Schauer, A., Schiller, A., Benlian, A., Heinrich, B., Jussupow, E., Klier, M., Kraus, M. & Schnurr, D. (2025). A Taxonomy for Uncertainty-Aware Explainable AI
This interdisciplinary contribution develops a comprehensive taxonomy that systematically captures and classifies uncertainties in explainable AI systems. The goal is to increase the trustworthiness and transparency of AI-supported decision-making systems by taking a differentiated approach to different uncertainty dimensions.
The ECIS is one of Europe's leading conferences in the field of business and information systems. This year, it took place in Amman, the capital of Jordan.
Further information about the ECIS can be found on the following website: https://ecis2025.eu/ (external link, opens in a new window)
