Working the algorithm: Contextual skills of on-demand gig workers

This study explores the algorithmic skills of on-demand gig workers, such as food delivery workers and ride-hailing drivers, who navigate algorithmic management on a daily basis. While algorithms often constrain worker autonomy and reduce labor processes to standardized routines, we argue that gig workers cultivate practical algorithmic skills through their experiences. Drawing on interviews with 20 workers, we identify three dimensions of algorithmic skills: algorithmic awareness, algorithm learning and comprehension, and algorithm utilization and mastery, encompassing nine specific indicators: awareness of algorithm presence, recognition of data dependency, awareness of algorithmic evolution, understanding input–output relationships, reverse engineering, collaborative learning of algorithms, exploiting platform rules, leveraging technical tools, and experience-based decision-making. These skills afford workers meaningful agency, enabling them to navigate and occasionally challenge platform control. Compared with analyses rooted in the control-resistance framework, the algorithmic skill framework offers a more constructive and sustainable pathway for the future of human–algorithm collaboration in workplace contexts. This study also highlights the need to contextualize algorithmic skills within specific sociotechnical and occupational frameworks.