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Algorithmic opacity and employees’ knowledge hiding: medication by job insecurity and moderation by employee—AI collaboration

Year: 2025

Type: article

Abstract: We explored the effects of algorithmic opacity on employees’ playing dumb and evasive hiding rather than rationalized hiding. We examined the mediating role of job insecurity and the moderating role of employee-AI collaboration. Participants were 421 full-time employees (female = 46.32%, junior employees = 31.83%) from a variety of organizations and industries that interact with AI. Employees filled out data on algorithm opacity, job insecurity, knowledge hiding, employee-AI collaboration, and control variables. The results of the structural equation modeling indicated that algorithm opacity exacerbated employees’ job insecurity, and job insecurity mediated between algorithm opacity and playing dumb and evasive hiding rather than rationalized hiding. The relationship between algorithmic opacity and playing dumb and evasive hiding was more positive when the level of employee-AI collaboration was higher. These findings suggest that employee-AI collaboration reinforces the indirect relationship between algorithmic opacity and playing dumb and evasive hiding. Our study contributes to research on human and AI collaboration by exploring the dark side of employee-AI collaboration.

Source: Journal of Psychology in Africa

DOI: 10.32604/jpa.2025.065763

Authors: Chunhong Guo, Huifang Liu, Jingfu Guo

Institutions: Dongbei University of Finance and Economics, Shandong Youth University of Political Science, Dalian Minzu University

Language: English

Topic: Knowledge Management and Sharing

Subfield: Communication

Field: Social Sciences

Domain: Social Sciences

SDG: Decent work and economic growth

Open Access status: bronze

Funder: Social Science Foundation of Liaoning Province