Algorithmic management and the politics of demand: Control and resistance at Uber

Abstract

Arguably the world's most iconic platform organization, Uber relies on a disaggregated labour force and a technology application accessible to users on mobile devices. The company contracts with over three million drivers worldwide and has curated an infrastructure of platform-based control characterized by algorithmic processes. The effects of this new wave of control on the driver-led workforce are unclear. Drawing on interviews with 36 Uber drivers, mainly from Australia and France, this research investigates how the ‘gig economy’ workforce engages with platform-based control. We find that the platform organization's control algorithms operate with strong disciplinary effects. Drawing on Foucault's concept of self-formation, we examine worker responses to the new order of work. We highlight the way workers engage in practices to ‘take care of oneself’, by enduring, subverting or exiting the conditions of algorithmic management. We find that these practices are related to the distance embedded in the field between management and the workforce. In this way, we argue that the gig economy operates differently upon the ‘governable self’ and urge caution in relation to the use of algorithms to control at a distance.