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  • What Tasks Lead to AI Aversion? The Moderated Mediation of Trust and Distrust

What Tasks Lead to AI Aversion? The Moderated Mediation of Trust and Distrust

July 07, 2024 IS

Topic:

What Tasks Lead to AI Aversion? The Moderated Mediation of Trust and Distrust

Time&Date: 

10:30 am - 12:00 pm, July 7, 2024 (Sunday)

Venue

Room 619, Teaching A Building

Zoom Link: 

https://cuhk-edu-cn.zoom.us/j/3985407949?pwd=QnZJMHU3SDUwaFdtWTF6N3RWcGlMdz09 

Meeting ID: 398 540 7949

Passcode: 779898

Speaker:

Prof. Huigang Liang (University of Memphis)

Abstract:

As artificial intelligence (AI) is gaining great traction, comprehending how users adopt or avert AI has become paramount. While users rely on AI to perform complex tasks, they are also concerned that it is risky to put too much reliance on AI. Users’ AI aversion seems to be driven by a mixed feeling consisting of both trust and distrust.  In this research, we attempt to unravel the intricate relationship among task characteristics, trust, distrust, and AI aversion. Based on an online randomized controlled experiment on Amazon Mechanical Turk, we find that task complexity influences AI aversion by inducing trust and distrust simultaneously. Moreover, the mediated effects are contingent on whether the task is subjective or objective. For objective tasks, task complexity reduces both trust and distrust, thus simultaneously enhancing and impeding AI aversion. In contrast, for subjective tasks, task complexity has no effect on AI aversion through trust but can significantly increase distrust to enhance AI aversion. By illustrating the heterogeneous treatment effects of task complexity mediated by trust and distrust and moderated by task subjectivity, our research yields surprising novel knowledge, which makes a significant contribution to the emerging field of AI aversion.

Biography:

Huigang Liang is FedEx Chair of Excellence in IS at Fogelman College of Business and Economics, University of Memphis. His research interests include socio-behavioral, managerial, and strategic information technology issues at both individual and organizational levels in a variety of contexts. His current research is focused on AI, cybersecurity, and healthcare IT. His work has appeared in MIS Quarterly, Information Systems Research, Journal of MIS, Journal of AIS, MIT Sloan Management Review, Communications of the ACM, Decision Support Systems, Information Systems Journal, Journal of Strategic Information Systems, and others. He is currently senior editor for JAIS and associate editor for ISR. His research has been funded by FedEx, NIH, and Sloan Foundation.

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