A SEM-ANN analysis to examine impact of AI overreliance through a social cognitive lens: the roles of dependency, FOMO, addiction, and anxiety

通过社会认知视角,运用结构方程模型-人工神经网络(SEM-ANN)分析人工智能过度依赖的影响:依赖性、错失恐惧症(FOMO)、成瘾和焦虑的作用

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Abstract

The rapid integration of artificial intelligence (AI) has transformed how people learn, work, and make decisions, while raising growing concerns about AI overreliance. Drawing on Social Cognitive Theory (SCT), we investigated how AI dependency, fear of missing out (FOMO), addiction, and Anxiety influence AI overreliance, and examined the mediating role of cognitive overload and the moderating role of technostress. We employed a hybrid analysis method (SEM-ANN), which was used to validate the theoretical relationships and explore nonlinear interactions, using survey data from 504 working adults in Shanghai. Results revealed that AI dependency, FOMO, addiction, and Anxiety have significant positive effects on AI overreliance. Cognitive overload partially mediates these relationships, while technostress moderates the relationship between AI dependency and AI overreliance. The findings are important for both businesses and policymakers. Promoting AI literacy and digital mindfulness will help people use technology more wisely. This will help to better facilitate collaboration between humans and AI.

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