Algorithmic work-life balance: How algorithms influence gig-workers perceptions of work-life boundaries on platforms

With the rising trend of individuals embracing freelance work on online labor markets, it becomes crucial to comprehend how platforms and algorithms influence their experiences of well-being. This study employs a mixed methods approach to explore the effects of platforms and various algorithms, including matching, control, and rating algorithms, on freelancers' work-life balance. Drawing on preliminary data collected through surveys and interviews with freelancers on a major online labor market platform, our findings reveal that control and rating algorithms negatively impact work-life balance by amplifying feelings of insecurity among freelancers. However, we also discovered that freelancers who perceive the platform they work on as useful exhibit greater proficiency in navigating the boundaries between their work and family life. Our study sheds light on the intricate dynamics between platforms, algorithms, well-being, and work-life balance for freelancers and emphasizes the need for further exploration of algorithmic interventions that promote work-life balance in the online freelance context.