Dimensions of artificial intelligence anxiety based on the integrated fear acquisition theory
By Jian Li, Jin-song Huang. Technology and Society, 2020
383 citations recorded by the source corpus.
Abstract With the rapid development of artificial intelligence (AI), AI anxiety has emerged and is receiving widespread attention, but research on this topic is not comprehensive. Therefore, we investigated the dimensions of AI anxiety using the theoretical model of integrated fear acquisition and a questionnaire survey. A total of 494 valid questionnaires were recovered. Through a first-order confirmatory factor analysis (CFA), a factor model of AI anxiety was constructed, and eight factors of AI anxiety were verified. Then, a second-order CFA was applied to verify the adaptation of the factor structure of AI anxiety to fear acquisition. We identified four dimensions of AI anxiety and proposed a theory of AI anxiety acquisition that illustrates four pathways of AI anxiety acquisition. Each pathway includes two factors that cause AI anxiety. We conclude by analyzing the limitations of current AI anxiety research and proposing a broader research agenda for AI anxiety.
Subfields: Applied Psychology, Experimental and Cognitive Psychology
View Paper: https://www.semanticscholar.org/paper/acec34441fd4f0b2dc4c269803dc736cf3f03dfc
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In Applied Psychology
In Experimental and Cognitive Psychology
Citations in the corpus
- The Roles of Personality Traits, AI Anxiety, and Demographic Factors in Attitudes toward Artificial Intelligence (2022, background): “Li and Huang (2020), on the other hand, added some features, such as privacy, transparency, bias, and ethics to the phenomenon of AI anxiety.”