Algorithm Brings People Closer: Fairness and Uncertainty in Interpersonal Relationship Closeness Under Algorithmic Management

With the proliferation of artificial intelligence (AI) products, Algorithmic Management (AM) is becoming an increasingly prevalent option for corporate governance. Meanwhile, the traditional boundaries between human–machine and interpersonal relationships are blurring. While some current studies suggest that AM is alienating interpersonal relationships within organizations, our research proposes and tests an alternative theoretical perspective, arriving at a contrasting conclusion: interpersonal relationship under AM can be closer. Focusing on employees in organizations utilizing AM, this study investigates how and why AM influences interpersonal relationship closeness (IRC). Grounded in Uncertainty Management Theory, we propose that by fostering a fairer working experience, AM enhances IRC at work by reducing employees’ uncertainty perception. The present research, comprising four studies, empirically establishes that the positive effect of AM on interpersonal closeness is transmitted via fairness perceptions and sequentially mediated by uncertainty reduction. Collectively, these findings challenge the prevailing negative narrative, extend Uncertainty Management Theory to the human–AI interaction context, and offer practical insights for organizations adopting AM.