Algorithmic Labor and Information Asymmetries: A Case Study of Uber’s Drivers

By Alex Rosenblat, Luke Stark, Finn Brunton, Karen Levy, Patrick Davison, Tamara Kneese, Mary L. Gray, Harry Campbell, Stacy Abder, S. Young and 5 more. 2016

1,278 citations recorded by the source corpus.

Subfields: Automotive Engineering, Marketing, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/98b1658bcca1a7ec393812a2c9ceffb3d96c84c3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Automotive Engineering

In Marketing

In Sociology and Political Science

Citations in the corpus

Between autonomy and control: Strategies of arbitrage in the “on-demand” economy (2018, neutral): “Postmates uses a dynamic pricing system (“Blitz” pricing) similar to those used by ridesharing firms Uber and Lyft (see Rosenblat and Stark, 2016; Scheiber, 2017).”
Labour process theory and the gig economy (2018, positive): “Instruments like Uber’s ‘surge pricing’ are described by Rosenblat and Stark (2016) as “ fundamental to its ability to structure control over its workers ” (Rosenblat and Stark, 2016: 3758) insofar as these determine what they describe as ‘power asymmetries’ which enable forms of ‘soft control’…”
The Challenges of Algorithm-Based HR Decision-Making for Personal Integrity (2019, positive): “For example, in a case study of Uber drivers, Rosenblat and Stark (2016) found that algorithm-based decision-making increases information asymmetries between management and drivers and decreases the drivers’ experience of control.”
Über-Alienated: Powerless and Alone in the Gig Economy (2021, positive): “While these ‘soft’ control strategies may create the initial appearance of worker choice and opportunity, many workers express skepticism or fatigue in the face of these incentive systems, viewing them instead as a pressure to remain constantly available for work (Rosenblat & Stark, 2016).”
Good Gig, Bad Gig: Autonomy and Algorithmic Control in the Global Gig Economy (2018, positive): “A far more effective means of control was the ‘algorithmic management’ enabled by platform-based rating and reputation systems (Lee et al., 2015; Rosenblat and Stark, 2016).”
Between a rock and a hard place: Freedom, flexibility, precarity and vulnerability in the gig economy in Africa (2020, positive): “However, research is beginning to show that workers do enjoy considerable freedom but are constrained by algorithmic controls set up by digital work platforms (Rosenblat and Stark, 2016; Wood et al., 2019b).”
Working on my own: Measuring the challenges of gig work (2021, neutral): “…point out how platforms and other forms of electronic monitoring manage workers’ behavior both at the micro level (e.g. assessing frequency of workers’ keyboard presses, citing Rosenblat and Stark, 2016) and at a more macro level (through the rating and reputation systems, such as “star” ratings).”
Platform-Capital’s ‘App-etite’ for Control: A Labour Process Analysis of Food-Delivery Work in Australia (2019, positive): “UberEATS, in contrast, allowed workers to operate wherever the service was offered and relied on ‘economic nudges’ (Rosenblat and Stark, 2016) in the form of surge-pricing (Gandini, 2018) called ‘boosts’ to entice workers to areas of high demand – relying on gamification-from-above (Woodcock and Joh”
“Is your gig any good?” Analysing job quality in the Australian platform-based food-delivery sector (2019, positive): “The gig economy is re-kindling historic debates concerning the changing configuration of work and capitalism, and whether these changes represent a Neo-Fordist or Post-Fordist extension (De Stefano, 2016; Healy et al., 2017; Knox and Warhurst, 2015; Rosenblat and Stark, 2016).”
The “sharing” economy: labor, inequality, and social connection on for‐profit platforms (2017, positive): “…becoming obsolete as platforms have begun to provide assets (e.g., ridesourcing platforms giving free vehicles to drivers) and to exercise more de facto control over hours and volume of work (Rosenblat & Stark, 2015; Scheiber, 2017; Schor, Attwood‐Charles, Cansoy, Ladegaard, & Wengronowitz, 2017).”
Community building on crowdwork platforms: Autonomy and control of online workers? (2020, positive): “Studies on the platform-mediated but locally fixed service work via Uber or Deliveroo show that, despite the rigid control, workers develop practices to outsmart the App-based management (Ivanova et al., 2018; Lee et al., 2015; Rosenblatt and Stark, 2016).”
Automation, Algorithms, and Beyond: Why Work Design Matters More Than Ever in a Digital World (2020, neutral): “(Rosenblat & Stark, 2016, p. 3768).”
Algorithmic Control in Platform Food Delivery Work (2019, positive): “In the case of Uber, for example, Rosenblat and Stark (2016) argue that such practices belie the claim that drivers confront the market in an unmediated way, as “independent contractors” or “entrepreneurs.””
Flexibility in the Gig Economy: Managing Time on Three Online Piecework Platforms (2018, positive): “Online gig work in general and online piecework in particular are thought to provide a great deal of formal flexibility for workers (Kuek et al. 2015), but little is known about the structural constraints in this type of work (on local gig work, see Rosenblat & Stark 2016).”