bei Google ScholarTitelangaben
Schemmer, Max ; Bartos, Andrea ; Spitzer, Philipp ; Hemmer, Patrick ; Kühl, Niklas ; Liebschner, Jonas ; Satzger, Gerhard:
Towards Effective Human-AI Decision-Making : The Role of Human Learning in Appropriate Reliance on AI Advice.
2023
Veranstaltung: International Conference on Information Systems (ICIS 2023)
, 10.-13.12.2023
, Hyderabad, India.
(Veranstaltungsbeitrag: Kongress/Konferenz/Symposium/Tagung
,
Paper
)
Abstract
The true potential of human-AI collaboration lies in exploiting the complementary capabilities of humans and AI to achieve a joint performance superior to that of the individual AI or human, i.e., to achieve complementary team performance (CTP). To realize this complementarity potential, humans need to exercise discretion in following AI’s advice, i.e., appropriately relying on the AI’s advice. While previous work has focused on building a mental model of the AI to assess AI recommendations, recent research has shown that the mental model alone cannot explain appropriate reliance. We hypothesize that, in addition to the mental model, human learning is a key mediator of appropriate reliance and, thus, CTP. In this study, we demonstrate the relationship between learning and appropriate reliance in an experiment with 100 participants. This work provides fundamental concepts for analyzing reliance and derives implications for the effective design of human-AI decision-making.
Weitere Angaben
| Publikationsform: | Veranstaltungsbeitrag (Paper) |
|---|---|
| Begutachteter Beitrag: | Ja |
| 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 |
| Eingestellt am: | 04 Okt 2023 08:20 |
| Letzte Änderung: | 04 Okt 2023 08:20 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/87034 |