Driving with Algorithms Beyond Gig Work: Investigating How Algorithmic Management Affects Workers’ Practices in On-Demand Ride-Pooling Service

On-demand ride-pooling (ODRP) services are a new alternative modes of transportation that have recently emerged due to technological advancements. While algorithmic management plays a crucial role in ODRP services and can create complex workplace dynamics, the experiences of ODRP workers remain underexplored in the HCI field. To address this gap, we interviewed 16 drivers of Shucle, an ODRP service in South Korea. We examined the drivers' detailed work practices, focusing on the perceived challenges of working under algorithmic management and the perceived benefits and necessity of algorithmic management. This paper provides empirical evidence of the impact of algorithmic management on ODRP drivers' work environments and discusses the implications of our findings for supporting algorithmic workplaces in ODRP services. By positioning ODRP drivers as company employees embedded within a vast, dynamic traffic environment, our study extends algorithmic management scholarship beyond gig work and other algorithmic work contexts, offering fresh insights into how autonomy and accountability are configured across algorithmic workplaces.