Uber's Drivers: Information Asymmetries and Control in Dynamic Work

TLDR: In this paper, the authors explore worker experiences within the on-demand economy and argue that Uber's digitally and algorithmically mediated system of flexible employment builds new forms of surveillance and control into the experience of using the system, resulting in asymmetries around information and power for workers.

Abstract: This empirical study explores labor in the on-demand economy using the rideshare service Uber as a case study. By conducting sustained monitoring of online driver forums and interviewing Uber drivers, we explore worker experiences within the on-demand economy. We argue that Uber’s digitally and algorithmically mediated system of flexible employment builds new forms of surveillance and control into the experience of using the system, which result in asymmetries around information and power for workers. In Uber’s system, algorithms, CSRs, passengers, semiautomated performance evaluations, and the rating system all act as a combined substitute for direct managerial control over drivers, but distributed responsibility for remote worker management also exacerbates power asymmetries between Uber and its drivers. Our study of the Uber driver experience points to the need for greater attention to the role of platform disintermediation in shaping power relations and communications between employers and workers.