In your face : digital rider ratings and the facework process in the case of Uber

Uber is a contemporary technology company that matches consumers directly with service providers in the on-demand ride marketplace. In their management of drivers, Uber relies on consumer ratings of drivers to make employment decisions about which drivers are allowed to continue working and which drivers are deactivated, or removed from the app as a service provider. This project set out to investigate how and why Uber consumers rate the drivers who provide them with rides. Data from nine semi-structured interviews with Uber riders in a large, American city on the west coast reveal that Uber’s rating prompt is the primary catalyst for the collection of consumer ratings. The criteria constructions riders use to make decisions about rating vary due to subjectivity, differential holdings of criteria, and criteria contradictions, despite agreement on the importance of safety. Raters were also found to fall into four unique categories given the nature of their experiences and rating deployments: full spectrum raters, partial spectrum raters, empathetic raters, and binary raters. The project concludes with a discussion of the implications of these findings for Uber and generalized contexts, and presents alternative visions of driver evaluation as well as avenues for continued research on quantification, evaluation, and digital life.