Managing Algorithms: partial automation of middle management and its implications for gig worker

Abstract

Platforms for gig work like Uber advertise their job opportunities as “entrepreneurial work” to potential workers and their company as technologically innovative to potential investors. One of the central features of these platforms is a layer of automated middle management in the form of a coordinating algorithm that interacts with workers completing tasks through the platform. The algorithmic middle management is useful to the platform as a status signaling tool to investors, a cost cutting measure, and a rhetorical tool for separating themselves further from their workforce. In practice, however, algorithms are limited in how well they can coordinate a widespread workforce and the extra management work falls to the workers themselves to manage. Using data from 41 interviews with Uber, Amazon, and Lyft gig workers, we examine the tasks that algorithm completes vs. the middle management tasks that fall to gig workers to complete on their own. We find that “entrepreneurial work” for these gig workers means that they must absorb several types of middle management tasks in addition to the tasks they were explicitly hired to do. Gig workers also bear the costs associated with representing a platform and themselves when there is any contrast between the projected expectations of the customer and the completed service.

CITATION: Enriquez, Diana, and Janet Vertesi. “Managing Algorithms: Partial Automation of Middle Management and Its Implications for Gig Worker.” Academy of Management Proceedings 2021, no. 1 (August 1, 2021): 16560. https://doi.org/10.5465/AMBPP.2021.16560abstract.