Understanding the Necessary Conditions of Multi-Source Trust Transfer in Artificial Intelligence
Proceedings of the 55th Hawaii International Conference on System Sciences, Hawaii International Conference on System Sciences, (2022)Abstract
Trust plays an increasingly important role, especially in new emerging AI-capable technologies. While different frameworks on establishing trustworthy AI were developed, extant research mostly neglects trust transfer mechanisms. We focus on multi-source trust transfer while taking a dual trust perspective including trust in provider and trust in technology. Our study falls in the context of autonomous vehicles as a target and AI and vehicles as sources. While conducting a survey with 432 participants, we applied necessary condition analysis to understand which sources are necessary for a multi-source trust transfer. Our results indicate that for trust in technology, AI and vehicle technology are necessary sources. In contrast, for trust in provider, only vehicle provider represents a necessary source. We contribute to research by providing a fresh perspective on trust in AI-capable technologies, applying a novel data analysis method to reveal necessary trust sources, and consider duality of trust in trust transfer.
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