Algorithmic identity regulation in the platform-based gig work of Indian food delivery workers

Abstract

How do algorithmic systems regulate worker identities by defining who they are expected to become? Identity regulation research has largely focused on how organizational discourse shapes worker identities. Yet, in platform labour, control is increasingly enacted through algorithmic systems that allocate tasks, monitor performance, and assign reputational scores in real time. Drawing on interviews with delivery partners and platform managers, supplemented by multi-source data, we examine how such systems shape the identities workers are encouraged to adopt or avoid, and how they engage with these processes. We make two key contributions. First, we theorize algorithmic identity regulation as a computational, sociomaterial, and affective form of normative control, whereby digital infrastructures continuously evaluate, rank, and allocate work, recalibrating workers’ identities through ongoing cycles of recognition, visibility, and devaluation. Second, we show how algorithmic identity regulation reshapes dignity at work by rendering recognition continuous, depersonalized, and datafied, making workers’ sense of worth increasingly contingent on algorithmic evaluation. In doing so, we show that algorithmic control not only manages work but shapes how workers define their value, worth, and place in the labour process.