Algorithms of Suspicion: the Erosion of Worker Data Rights - 23 June 2023

This talk examines the assemblage of policies, practices, and algorithms of suspicion that control workers’ access to wages and work on digital labor platforms. Irani shows how “fraud” acts as a quasi-legal category that legitimizes and protects platform operators’ unilateral decisions to fire workers. This case study begins with the problem of opaque account suspensions suffered by good faith workers on the platform Amazon Mechanical Turk. Through an investigation of patents, research papers, and industry documentation, the talk constructs a view of the models and assumptions Amazon deploys to guess the difference between good and bad workers. These algorithms and the opaque organizational routines that deploy them submit workers to automated surveillance, suspicion, and terminating action – managing workers at scale and at a distance. These practices may have discriminatory consequences, sometimes in ways recognized by legally recognized protected categories and sometimes not. Irani concludes by arguing that existing digital rights frameworks must be revised to give workers rights and protections against platforms’ algorithmic forms of management.

Lilly Irani is an Associate Professor of Communication & Science Studies at University of California, San Diego where she co-directs the Just Transitions Initiative. She is Faculty Director of UC San Diego's new Labor Center.