Abstract
Despite significant advancements in medical artificial intelligence (AI) systems, these technologies are prone to mistake in their predictions. These mistakes can significantly affect medical experts’ willingness to continue using these systems. To mitigate potential discontinuation, existing research indicates that providing additional information alongside predictions, can lessen negative out- comes like discontinuation. Given the potential impact on users’ information processing, we hypothesize that AI explanations, detailing the system's decision- making process, can also influence the likelihood of discontinuing use after an AI mistake. Through an online experiment with medical experts (n=227), we demonstrate that such explanations can influence medical experts’ information processing and, consequently, mitigate the adverse effects on the actual discontinuation of AI systems following a mistake.
Original language | English |
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Publication date | 2024 |
Number of pages | 15 |
Publication status | Published - 2024 |
Externally published | Yes |
Event | 19th International Conference on Wirtschaftsinformatik. WI 2024 - Universität Würzburg, Würzburg, Germany Duration: 16 Sept 2024 → 19 Sept 2024 Conference number: 17 https://wi2024.de/ |
Conference
Conference | 19th International Conference on Wirtschaftsinformatik. WI 2024 |
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Number | 17 |
Location | Universität Würzburg |
Country/Territory | Germany |
City | Würzburg |
Period | 16/09/2024 → 19/09/2024 |
Internet address |
Keywords
- Artificial intelligence
- Decision-making
- Explainability
- Discontinuance
- Medicine