Algorithmic Anxiety and Its Implications for Work Stress and Professional Self-Esteem among Employees in the Digital Age - Hidayat, Rahmat (International Journal of Psychology and Mental Health, 2025)
The digital transformation driven by the Fourth Industrial Revolution has introduced algorithmic management, a paradigm where artificial intelligence systems actively supervise, evaluate, and direct employees, creating unique psychological challenges known as algorithmic anxiety. This study aims to analyze the influence of algorithmic anxiety on work stress and professional self-esteem among employees in the digital era. Utilizing a quantitative approach with a causal associative design, the research involved 250 employees in Padang, aged 18 to 35, who work under algorithmic management systems, selected via convenience sampling. Data were collected through the Algorithmic Anxiety Scale (AAS), an adapted Perceived Stress Scale (PSS-10), and an adapted Rosenberg Self-Esteem Scale (RSES), and subsequently analyzed using simple linear regression. The results indicate that algorithmic anxiety significantly influences both work stress and professional self-esteem. Algorithmic anxiety positively correlates with work stress, while showing a negative correlation with professional self-esteem, accounting for an 8.8% variance in these dependent variables. Algorithmic management serves as a substantial source of psychological pressure in the modern workplace. Organizations should implement transparent algorithmic systems and provide psychological support programs to mitigate the negative impact of algorithmic anxiety on employee well-being and professional confidence.