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Dual Perspectives: Navigating the Ambiguity of Trust in AI
Gaurav Bansal, Zhuoli Axelton, Pooja Agarwal
Despite the excitement around AI as a game-changing technology, an AI productivity paradox exists wherein scientists report a gap between AI advancements and actual gains in labor productivity. Therefore, this study attempts to understand how the AI productivity paradox could be explained through positive and negative valences associated with trust in AI at the individual employee level. Moreover, this study proposes that companies can employ proactive measures to alleviate employee concerns and enhance AI adoption to unlock productivity bottlenecks. The data for this study was collected from MTurk respondents using an experimental survey design. The findings demonstrate that open communication is pivotal in building trust, and trust in AI could exhibit both system-like and human-like attributes. Moreover, trust in AI may create ambivalence by simultaneously advancing intentions and triggering reactance, with human-like trust having a slightly greater impact on intentions. Theoretical, practical, and social implications are discussed.
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