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Spitzer, Philipp ; Kühl, Niklas ; Goutier, Marc ; Kaschura, Manuel ; Satzger, Gerhard:
Transferring Domain Knowledge with (X)AI-Based Learning Systems.
2024
Veranstaltung: 32nd European Conference on Information Systems (ECIS)
, 13-19 June 2024
, Paphos, Cyprus.
(Veranstaltungsbeitrag: Kongress/Konferenz/Symposium/Tagung
,
Paper
)
Abstract
In numerous high-stakes domains, training novices via conventional learning systems does not suffice. To impart tacit knowledge, experts' hands-on guidance is imperative. However, training novices by experts is costly and time-consuming, increasing the need for alternatives. Explainable artificial intelligence (XAI) has conventionally been used to make black-box artificial intelligence systems interpretable. In this work, we utilize XAI as an alternative: An (X)AI system is trained on experts‘ past decisions and is then employed to teach novices by providing examples coupled with explanations. In a study with 249 participants, we measure the effectiveness of such an approach for a classification task. We show that (X)AI-based learning systems are able to induce learning in novices and that their cognitive styles moderate learning. Thus, we take the first steps to reveal the impact of XAI on human learning and point AI developers to future options to tailor the design of (X)AI-based learning systems.
Weitere Angaben
| Publikationsform: | Veranstaltungsbeitrag (Paper) |
|---|---|
| Begutachteter Beitrag: | Ja |
| Keywords: | Artificial Intelligence; Explainable AI; Human-Computer Interaction; Cognitive Style; Learning Systems; Mammography |
| Institutionen der Universität: | Fakultäten > Rechts- und Wirtschaftswissenschaftliche Fakultät > Fachgruppe Betriebswirtschaftslehre Fakultäten > Rechts- und Wirtschaftswissenschaftliche Fakultät > Fachgruppe Betriebswirtschaftslehre > Lehrstuhl Wirtschaftsinformatik > Lehrstuhl Wirtschaftsinformatik - Univ.-Prof. Dr.-Ing. Niklas Kühl |
| Titel an der UBT entstanden: | Ja |
| Themengebiete aus DDC: | 000 Informatik,Informationswissenschaft, allgemeine Werke > 004 Informatik 300 Sozialwissenschaften > 330 Wirtschaft 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
| Eingestellt am: | 27 Mär 2024 06:47 |
| Letzte Änderung: | 27 Mär 2024 06:47 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/89081 |