How does AI use drive individual digital resilience? a conservation of resources (COR) theory perspective

Artificial intelligence (AI) serves as a useful resource for replacing, supporting, and augmenting individuals in responding to external difficulties and enhancing individual resilience. However, little is known about the underlying laws of how AI can heighten individual resilience. This research ex...

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Published inBehaviour & information technology Vol. ahead-of-print; no. ahead-of-print; pp. 1 - 20
Main Authors Hu, Qian, Lu, Yaobin, Pan, Zhao, Wang, Bin
Format Journal Article
LanguageEnglish
Published London Taylor & Francis 18.11.2023
Taylor & Francis Ltd
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Summary:Artificial intelligence (AI) serves as a useful resource for replacing, supporting, and augmenting individuals in responding to external difficulties and enhancing individual resilience. However, little is known about the underlying laws of how AI can heighten individual resilience. This research examines the formation of individual resilience based on the consequences of different AI usage behaviours. Study 1 uses text mining to detect individual resilience based on the experience with AI. We identify not only individual resilience but also family resilience. Study 2, based on the context of the COVID-19 pandemic, collects online survey data from personal intelligent assistant users to investigate the transformation mechanism of AI usage behaviours to individual resilience. Drawing upon the conservation of resources theory, routine and infusion use are considered two levels of resource investments to strengthen the different degrees of individual resilience by coping responses (task-focused, emotion-focused, and avoidance coping). The findings confirm the differences between routine and infusion use in the formation of individual resilience, mediated by both task-focused and emotion-focused coping, without the mediating role of avoidance coping. Our research provides enlightenment for researchers and practitioners on building resilience and improving performance.
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ISSN:0144-929X
1362-3001
DOI:10.1080/0144929X.2022.2137698