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START Foundation: Coping with Bias and Fairness when Implementing and Using an AI System

Schwenke, Chiara ; Brasse, Julia; Förster, Maximilian ORCID iD icon 1; Klier, Mathias
1 Institut für Wirtschaftsinformatik (WIN), Karlsruher Institut für Technologie (KIT)

Abstract:

START Foundation annually supports nearly 200 young people with a migratory background through an individualized scholarship program aimed at personal development and identity building. In 2022, START Foundation expanded its reach by launching a digital learning platform, which faced challenges such as information overload and navigation difficulties due to a growing number of courses and a lack of individual support. To improve user experience on the digital learning platform, START Foundation explored implementing a recommender system for personalized course navigation based on methods from the field of artificial intelligence (AI). However, this exploration raised ethical concerns, particularly regarding bias and fairness in AI systems. In light of these concerns, the following questions emerged: Should START Foundation integrate the AI-based recommender system into its digital learning platform? If so, what factors should START Foundation consider regarding bias and fairness in its AI-based recommender system in order to prevent negative consequences for its scholars?


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Originalveröffentlichung
DOI: 10.17705/1CAIS.05443
Zugehörige Institution(en) am KIT Institut für Wirtschaftsinformatik (WIN)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2024
Sprache Englisch
Identifikator ISSN: 1529-3181
KITopen-ID: 1000192127
Erschienen in Communications of the Association for Information Systems
Verlag Association for Information Systems (AIS)
Band 54
Seiten 1036–1047
Schlagwörter Artificial Intelligence, Bias and Fairness, Education, Digital Learning Platform, Teaching Case
Nachgewiesen in Scopus
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