Effects of ChatGPT Exposure on Affective Automation-Related Job Insecurity and Coping Intentions

Abstract

Large language models like ChatGPT dominate the public discourse with their potential to take over human labor. ChatGPT already outperforms human employees in specific cognitive tasks in white-collar jobs, potentially substituting work tasks. However, whether employees perceive ChatGPT as threatening to their employment and how they react to such potential threat remains largely unclear. Drawing from the cognitive appraisal theory of stress and recent empirical findings on embodied robots, we investigate whether mere exposure to ChatGPT (Study 1) or use of ChatGPT (Study 2) evokes affective automation-related job insecurity and, subsequently, turnover and learning intentions. Further, we investigate the moderating role of stable personality traits, in terms of core self-evaluations. The results of two online-experiments with German white-collar workers (N1 = 254; N2 = 391) demonstrate that neither mere exposure to ChatGPT nor use of ChatGPT elevate affective automation-related job insecurity, turnover and learning intentions. Findings indicate that white-collar workers do not perceive ChatGPT as threatening to their employment, regardless of their level of core self-evaluations. The lack of transferability of effects from embodied robots to ChatGPT indicates the essential role of technologies’ physical bodies for triggering job insecurity, and defuses concerns about unintended negative effects of ChatGPT for employees and organizations.

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