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Aktuelles
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Together with colleagues from Würzburg, FAU and KIT we published two papers at the ECIS 2021 conference, which was held virtually in June.
The first paper, which was submitted in a joint effort by colleagues from the KIT (Jannis Walk, Niklas Kühl and Michael Vössing) and FAU (Patrick Zschech) proposes Design Principals and testable proposition for Computer-Vision-based Hybrid Intelligence Systems. Besides technical aspects, we also focused on the often neglected socio-technical facets, such as trust, control, and autonomy.
The paper is available here: https://aisel.aisnet.org/ecis2021_rp/127/
The second paper that was submitted together with colleauges from the JMU Würzburg (Jonas Wanner, Laurell Popp, Kevin Fuchs, Kevin Fuchs and Christian Janiesch) explores adoption barriers for AI-based systems in the context of predictive maintenance.
The paper is available here: https://aisel.aisnet.org/ecis2021_rip/40/
Artificial intelligence technology has started to shape how decisions are being taken and how intelligent information systems are being implemented today. However, artificial intelligence should not be considered as an abstract system property, but researchers and practitioners must also understand its inner workings as it affects many socio-technical issues downstream.
In our Electronic Markets fundamentals article “Machine Learning and Deep Learning”, together with co-authors Christian Janiesch and Kai Heinrich, we distinguish approaches for shallow machine learning and deep learning and explain the process of analytical model building from a more technical information systems perspective. Further, we detail four overarching challenges that research and practice will have to manage going forward.
The article aims to be a terminological baseline, gentle introduction and pointer to relevant work, as well as a motivator to approach said challenges.
The article is open access and available at: https://link.springer.com/article/10.1007%2Fs12525-021-00475-2