The Uber Game: Exploring Algorithmic Management and Resistance

The algorithmic oversight, optimization and evaluation of worker performance is an increasing reality in many economic sectors. For those working within the growing economic sector known as the ‘gig’ or ‘on-demand’ economy, these algorithmic processes sit at the heart of their working day. Previous research drawing on interview and forum data (Kyung Lee et al., 2015; Rosenblat and Stark, 2016) has suggested an inequity of power between the operators of an algorithmic management system, and those working under it. This inequity arises through a lack of transparency around the rules that govern their work, and a lack of options for workers to influence those rules in response to the realities of their everyday work. This paper, based on a computer-aided content analysis of 28,458 forum threads, argues that whilst gig economy workers are governed by algorithmic systems, that same system facilitates resistance. By necessitating some form of user interaction and the provision of sufficient feedback, algorithmic management apps allow workers to collaboratively develop strategies of ‘rule discovery’ to continuously update their intuitions about the often hidden rules governing their everyday activity.