Track Chairs
Benedikt Berger, LMU Munich
Alexander Benlian, TU Darmstadt
Kristian Kersting, TU Darmstadt
Oliver Hinz, Goethe University Frankfurt
Description
The advancement of machine learning algorithms, the availability of large amounts of data to feed these algorithms, and increasing processing power have enabled the successful application of artificial intelligence (AI) capabilities in the field. Among those are speech recognition, natural language processing, computer vision, predictive analytics, and robotics.
Developers can now draw upon these capabilities to improve existing systems (e.g., machine translation) or innovate new technologies (e.g., smart speaker). We refer to information systems incorporating AI capabilities as AI-based systems. AI-based systems affect the relationship between humans and machines in solving tasks. AI-based systems can assist humans in an increasing number of tasks or even solve them autonomously. Furthermore, AI capabilities allow systems to appear more humanly and thus create anthropomorphic perceptions (i.e., by interacting via speech). AI-based systems offer opportunities for businesses to become more efficient or to innovate new products and services. However, AI-based systems need to be designed and implemented carefully to avoid unwanted drawbacks such as discrimination through bias in automated decision making. These developments open up a wide array of questions at the individual, organizational and societal level. This track wants to contribute towards answering these questions and provide insights regarding the best possible design and use of AI-based systems. The track is open for contributions to the topic from all theoretical and methodological angles. We also welcome work regarding the use of AI capabilities for research purposes and the impact of AI on information system discipline.
Covered areas include, but are not limited to:
· Hybrid and Augmented Intelligence
· Human-AI-Collaboration (Human-in-the-loop)
· AI-based Assistance Systems
· Development, Design, and Implementation of AI-based Systems
· Human-Robot-Interactions
· (Over)Trust in AI-based Systems
· Explainability and Transparency of AI-based Systems
· Anthropomorphic Systems and Perceptions of Humanness
· Business, Managerial, and Strategic Implications of AI
· AI-based Data Analytics and Decision Making
· AI-based Methods in IS Research
· Relationship between AI and IS Research
· Downsides of AI-based Systems: Bias, Discrimination, and Aversion
Associate Editors
· Martin Adam, TU Darmstadt
· Carsten Binnig, TU Darmstadt
· Philipp Ebel, University of St. Gallen
· Andreas Fink, Helmut-Schmidt-Universität/UniBw Hamburg
· Burkhardt Funk, Leuphana University of Lüneburg
· Peter Gomber, Goethe University Frankfurt
· Wolfgang König, Goethe University Frankfurt
· Cristina Mihale-Wilson, Goethe University Frankfurt
· Stefan Morana, Karlsruhe Institute of Technology
· Dirk Neumann, University of Freiburg
· Sarah Oeste-Reiß, University of Kassel
· Nicolas Pröllochs, University of Oxford
· Matthias Schumann, University of Göttingen
· Isabella Seeber, University of Innsbruck
· Kai Spohrer, University of Mannheim
Important Dates
Paper submission deadline: August 16th, 2019
Submission deadline for revised papers: November 11th, 2019
For further information please visit www.wi2020.de/<http://www.wi2020.de/>