The rapid developments in the field of artificial intelligence (AI), the availability of more and more computing power and huge amounts of data enable the use of AI-based systems in many new application scenarios. AI-based systems are omnipresent and people interact with them in both private and business contexts. We ask Alexa in the morning how the weather is going to be that day, Google Maps navigates us to work, the intelligent system at work tells us that a certain machine needs maintenance, and in the evening Netflix suggests a suitable film to watch. In all these cases it is normal for us to interact with an AI-based system. Yet, beyond these examples, AI-based systems open up new opportunities for the entire economy as a whole, and especially for those companies that manage to leverage the economic potential of AI 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 need to be considered. While AI-based systems are becoming more and more 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 particular care to prevent undesired effects or misuse.
This track would like to invite the WI community to submit contributions on an individual, organizational, and societal level about the impact, optimal design, and management of AI-based systems. It is open to all kinds of methods and types of contributions that address the following or related topics:
● Hybrid and Augmented Intelligence
● Human-AI-Collaboration (Human-in-the-loop)
● AI-based Assistance Systems (for individuals and organizations)
● Development, Design, and Implementation of AI-based Systems
● Trust in AI-based Systems
● Explainability and Transparency of AI-based Systems
● Business, Managerial, and Strategic Implications of AI
● The dark side of AI-based Systems: Bias, Discrimination, and Aversion
● 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 enabled by AI-based systems)
● Ethical, legal and social implications of AI and AI-based systems
Goethe University of Frankfurt
Cristina Mihale-Wilson is a research assistant at the Chair of Information Systems and Information Management at the Goethe University in Frankfurt am Main. Her research focuses on economic and social aspects, and potentials of AI and AI-based systems. Currently, she is working in the interdisciplinary project ForeSight, which aims at developing an open AI-based platform for context-sensitive, intelligent and predictive services in the field of Smart Living. Within the 3-year project, she is researching the suitability, economic potentials and sustainability of building smart services and AI-based systems for the Smart Living industry.
Since 2020 Stefan Morana is an Assistant Professor for Business Administration, especially Digital Transformation and Information Systems at Saarland University. He studied computer science at the University of Applied Sciences Darmstadt and earned his doctorate in information systems 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, amongst others, 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.
Technical University of Darmstadt
Alexander Benlian is a Professor of Information Systems & E-Services at Darmstadt University of Technology (TU Darmstadt) since 2012. Prior to 2012, he completed his doctorate and habilitation at the Ludwig-Maximilians-University in Munich. In 2015 he was offered a professorship for Business Informatics (W3) at the University of Cologne, which he 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.
Goethe-University of Frankfurt
Oliver Hinz studied at TU Darmstadt Business Administration and Information Systems and then worked several years for the Dresdner Bank. He supported the E-Finance Lab as Assistant Professor for E-Finance & Electronic Markets from 2008 to 2011 and headed the Chair of Information Systems | Electronic Markets at TU Darmstadt. Oliver is Chair of Information Systems and Information Management at Goethe University Frankfurt since 2017. His research has been published in journals like Information Systems Research, Management Information Systems Quarterly, Journal of Marketing, Journal of Management Information Systems, Business & Information Systems Engineering and in a number of proceedings.
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