Design, management and impact of AI-based systems
Track description
The rapid developments in the field of artificial intelligence (AI), the availability of more and more computing power and an unmanageable amount of data enable the use of AI-based systems in many new application scenarios. AI-based systems are ubiquitous and people interact with them in both private and business contexts. We ask Alexa in the morning what the weather will be like today, Google Maps navigates us to work, the intelligent system at work tells us that the machine needs to be serviced, and in the evening Netflix suggests a movie that suits us. In all these application scenarios it is normal for us humans to interact with an AI-based system. Beyond these examples, AI-based systems offer a wide range of opportunities for the entire economy and especially for those companies that manage to exploit the economic potential of AI-based systems for themselves.
In contrast to the multitude of opportunities that AI in general and AI-based systems in particular offer to individuals, companies or society, there are also a number of risks and dangers that must be taken into account. While AI-based systems are becoming increasingly complex and will soon be superior to humans in some areas (e.g. medical diagnostics), researchers and the public are also increasingly concerned with potential risks and concrete dangers from ethical, legal and social perspectives.
Many of the current AI-based systems and their underlying algorithms are not transparent enough to detect or prevent possible misuse or systematic errors. The intransparency of such AI-based systems can lead to users being knowingly or unknowingly discriminated against or even manipulated. AI-based systems must therefore be designed and implemented with special care to prevent undesired effects or misuse.
Possible topics
The rapid developments in the field of artificial intelligence (AI), the availability of more and more computing power and an unmanageable amount of data enable the use of AI-based systems in many new application scenarios. AI-based systems are ubiquitous and people interact with them in both private and business contexts. We ask Alexa in the morning what the weather will be like today, Google Maps navigates us to work, the intelligent system at work tells us that the machine needs to be serviced, and in the evening Netflix suggests a movie that suits us. In all these application scenarios it is normal for us humans to interact with an AI-based system. Beyond these examples, AI-based systems offer a wide range of opportunities for the entire economy and especially for those companies that manage to exploit the economic potential of AI-based systems for themselves.
In contrast to the multitude of opportunities that AI in general and AI-based systems in particular offer to individuals, companies or society, there are also a number of risks and dangers that must be taken into account. While AI-based systems are becoming increasingly complex and will soon be superior to humans in some areas (e.g. medical diagnostics), researchers and the public are also increasingly concerned with potential risks and concrete dangers from ethical, legal and social perspectives.
This track would like to invite the WI community to submit a contribution on an individual, organizational and societal level to the best possible design, management and impact of AI-based systems. It is open to all methods and types of contributions that address the following or related topics
● Hybrid and extended AI
● Cooperation between humans and AI (Human-in-the-Loop)
● AI-based assistance systems (for end users and companies)
● Development, design and implementation of AI-based systems
● Trust and distrust in AI-based systems
● Explanability and transparency of AI-based systems
● Operational and strategic effects of AI-based systems in companies
● Disadvantages of AI-based systems: distortions, discrimination and rejection
● Practical application of AI in organizations (e.g. AI and product innovation, AI and customer care, AI and marketing, AI and process optimization)
● Economic potentials of AI (e.g. new business models through the use of AI-based systems)
● Ethical, legal and social implications of AI and AI-based systems
Track Chairs
Cristina Mihale-Wilson is a research assistant at the Chair of Business Informatics and Information Management at the Goethe University Frankfurt am Main. Her research focuses on economic and social aspects as well as the potential of AI and AI-based systems. She is currently working in the interdisciplinary project ForeSight, which aims to develop an open AI-based platform for context-sensitive, intelligent and predictive services in the field of Smart Living. Within the three-year project, she is investigating the suitability, economic potential and sustainability of building intelligent services and AI-based systems for the Smart Living industry.
Stefan Morana has been junior professor for business administration, especially digital transformation and business informatics at Saarland University since 2020. He studied computer science at the University of Applied Sciences Darmstadt and received his doctorate in business informatics at the University of Mannheim. His research focuses on the design of interactive systems and methodological aspects of design-oriented research. His work has been published in the Journal of the Association for Information Systems, Decision Support Systems, International Journal of Human-Computer Studies, Business & Information Systems Engineering, and Communications of the Association for Information Systems, among others.
Alexander Benlian has been Professor for Information Systems & E-Services at the Technical University of Darmstadt since 2012. Prior to this, he received his doctorate and habilitation at the Ludwig-Maximilians-University of Munich. In 2015, he was offered a professorship for Business Information Systems (W3) at the University of Cologne, but declined. His work has been published in leading academic and practice-oriented journals, including Management Information Systems Quarterly, Journal of Management Information Systems, Journal of Service Research, Journal of the Association for Information Systems, MIS Quarterly Executive and Business & Information Systems Engineering.
Oliver Hinz studied Business Informatics at the Technical University of Darmstadt and then worked for Dresdner Bank for several years. As Assistant Professor for E-Finance & Electronic Markets he supported the E-Finance Lab Frankfurt from 2008 to 2011 and subsequently headed the Department of Business Informatics | Electronic Markets at the Technical University Darmstadt. Since 2017 he is Professor for Business Informatics and Information Management at the Goethe University Frankfurt. His work has been published in Information Systems Research, Management Information Systems Quarterly, Journal of Marketing, Journal of Management Information Systems and Business & Information Systems Engineering, among others.
Associate Editors
- Kevin Bauer, Goethe-Universität Frankfurt, bauer@sage.uni-frankfurt.de
- Eva Bittner, Universität Hamburg, bittner@informatik.uni-hamburg.de
- Philipp Ebel, Universität St. Gallen, philipp.ebel@unisg.ch
- Andreas Fink, Helmut-Schmidt-Universität/UniBw Hamburg, andreas.fink@hsu-hamburg.de
- Burkhardt Funk, Leuphana Universität Lüneburg, funk@uni.leuphana.de
- Peter Gomber, Goethe-Universität Frankfurt, gomber@wiwi.uni-frankfurt.de
- Peter Hofmann, Universität Bayreuth, peter.hofmann@fim-rc.de
- Andreas Holzinger, Medizinische Universität Graz, andreas.holzinger@medunigraz.at
- Christian Janiesch, TU Dresden, Christian.Janiesch@tu-dresden.de
- Wolfgang König, Goethe-Universität Frankfurt, wkoenig@wiwi.uni-frankfurt.de
- Matthias Kraus, ETH Zürich, mathiaskraus@ethz.ch
- Niklas Kühl, Karlsruher Institut für Technologie (KIT), kuehl@kit.edu
- Sarah Oeste-Reiß, Universität Kassel, oeste-reiss@uni-kassel.de
- Nicolas Pröllochs, Justus-Liebig-Universität Giessen, nicolas.proellochs@wi.jlug.de
- Matthias Schumann, Georg-August-Universität Göttingen, mschuma1@uni-goettingen.de
- Benedikt Berger, Ludwig-Maximilians-Universität München, benedikt.berger@bwl.lmu.de
- Kai Spohrer, Universität Mannheim, spohrer@uni-mannheim.de