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

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.

Authors

Publication Details

Journal
Journal of Psychology in Africa
Published
2025-01-01
DOI
https://doi.org/10.32604/jpa.2025.065763
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Huifang Liu, Chun Guo, Jirong Guo
Journal of Psychology in Africa
Ethics and Social Impacts of AI
article

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

Huifang Liu, Chun Guo, Jirong Guo
article en

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.

Journal of Psychology in AfricaVol. 35(3)
Social Science Foundation of Liaoning Province
Openalex Percentile: Top 83%
Ethics and Social Impacts of AI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.