Abstract
This thesis investigates how feedback recipients’ use of artificial intelligence (AI) affects recipients’ trust in organizational settings. While prior research has focused on trust in AI as an autonomous agent, little is known about its interpersonal impact. Drawing on Mayer and Davis’s (1995) multidimensional model of trust, which includes ability, benevolence, and integrity, and attribution theory, we examine how AI use shapes recipients’ perceptions, focusing on perceived integrity as a mediator, with feedback valence and social identity as moderators.Three experimental studies using online and student samples tested these relationships. Study 1 compared trust toward feedback recipients who used AI with those who did not and found that AI usage indirectly influenced trust through perceived integrity. Study 2 added feedback valence as a moderator and showed that AI use reduced perceived integrity and trust under positive feedback but not under negative feedback. The divergent results regarding negative feedback in Studies 1 and 2 may be related to the social identity of the feedback giver (ingroup vs. outgroup) in the experimental setting. Thus, in Study 3, we tested social identity as a moderator in a negative feedback context but found no significant effects. Lower data quality in Study 3 suggests caution in interpreting these results.
Overall, this research highlights how AI integration in workplace tasks reshapes interpersonal evaluations, emphasizing perceived integrity as a key mechanism. The findings of three studies suggest that organizations should consider the interpersonal consequences in AI-augmented workplaces and point to the need for further research.
| Date of Award | 2025 |
|---|---|
| Original language | English |
| Awarding Institution |
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| Supervisor | Melody Man Chi CHAO (Supervisor) |
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