Unpacking human-AI interaction: Exploring unintended consequences on employee Well-being in entrepreneurial firms through an in-depth analysis
通过对六家高科技创业企业的纵向案例研究，揭示了基于AI的人力资源系统对员工福祉的四种阴影体验及三类福祉阴影，并提出了缓解负面影响的路径。
This study explores the influence of AI-based HRM systems on employee well-being in seasoned entrepreneurial firms through a comparative longitudinal case study of six high-technology ventures. The findings reveal four main shadow experiences associated with AI-based HRM systems, including the erosion of interpersonal autonomy, surveillance-induced precarity, algorithmic bias dilemma, and personalized discontentment. These experiences contribute to three distinct categories of well-being shadows: psychological alienation, physical adaptive overload, and social marginalization. This study clarifies the complex mechanisms linking shadow experiences to well-being outcomes and identifies enablers that can mitigate adverse effects, such as agility and personal growth, streamlined efficiency and harmony, and resource empowerment and engagement. It also proposes actionable pathways for employees to address and overcome these shadows, including deepened introspection, empowered inner power, and refined resourcefulness. The findings provide novel insights into the dual-edged nature of human-AI interaction and offer insights for promoting sustainable well-being in the evolving workplace environment.