When AI Gets It Wrong: User Contestation and the Attribution of Error
Published in ICIS 2025 Proceedings, 2025
Recommended citation: Ur Rehman, Mati and Chen, Rui, "When AI Gets It Wrong: User Contestation and the Attribution of Error" (2025). ICIS 2025 Proceedings. 13. https://aisel.aisnet.org/icis2025/ethical_is/ethical_is/13/
AI adoption in organizations is on the rise; however, companies competing to adopt AI have failed to ensure proper use of AI. Recent and past public backlash and lawsuits due to AI errors have cost companies millions of dollars. Several industry reports highlight these issues. Establishing processes and encouraging employees to contest AI to avoid costly AI errors is of utmost importance. The recent legal regulations and guidelines also emphasize the importance of contestation of AI. This study seeks to understand how attribution affects AI contestation. Additionally, we seek to highlight the impact that the contestation process accessibility and psychological safety have on employees’ contestation of AI in the environment of uncertainty created by AI advancement. To the best of our knowledge, this is the first study to examine AI contestation in the IS context.