Chapter 12: A machine-learning approach to assessing public trust in AI-powered technologies
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Trust in artificial intelligence (AI) technologies is crucial for adoption, as it mitigates resistance and skepticism while increasing competence and reliance on human-machine interactions. Previous studies, however, oversimplify the concept of trust as familiarity or willingness, focusing on specific products in a limited range of industrial domains or laboratory settings and their current or potential users only. For a more comprehensive understanding of the public trust in AI, we propose a novel approach: a representative sample of participants (n = 1,127) was asked for their perceived desirability and possibility to replace human jobs with AI-powered machines, and then, the distinctive characteristics of replaceable jobs were identified. The results showed the tendency to trust in AI technologies characterized by mechanical functionality but not those that require cognitive and managerial skills or involve social interactions. The findings provide both theoretical and empirical foundations for the research on human-machine interactions and public acceptance of technologies.

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