Pseudo-Automation: How Labor-Offsetting Technologies Reconfigure Roles and Relationships in Frontline Retail Work
🤖 AI Summary
This study examines how self-checkout technology reconfigures frontline retail workers’ labor processes and interpersonal interactions. Employing qualitative methods—including in-depth interviews with current and former cashiers and ethnographic observation—and drawing on relational sociology, it reveals that under “pseudo-automation,” cashiers’ roles shift from service providers to surveillance agents and rule enforcers. Its primary contribution is the conceptual innovation of “relational repair”: a strategic response wherein workers mitigate customer–machine conflicts by attributing system failures to the machine (“machine scapegoating”) and compensating with intensified service. Empirically, the study documents three interrelated consequences: (1) multi-threaded tasking, (2) heightened problem-oriented labor, and (3) escalated counter workload. Challenging techno-determinist narratives of labor displacement, the research demonstrates how algorithmic management covertly intensifies interpersonal labor while prompting workers’ adaptive, yet precarious, tactical adjustments.
Application Category
📝 Abstract
Self-service machines are a form of pseudo-automation; rather than actually automate tasks, they offset them to unpaid customers. Typically implemented for customer convenience and to reduce labor costs, self-service is often criticized for worsening customer service and increasing loss and theft for retailers. Though millions of frontline service workers continue to interact with these technologies on a day-to-day basis, little is known about how these machines change the nature of frontline labor. Through interviews with current and former cashiers who work with self-checkout technologies, we investigate how technology that offsets labor from an employee to a customer can reconfigure frontline work. We find three changes to cashiering tasks as a result of self-checkout: (1) Working at self-checkout involved parallel demands from multiple customers, (2) self-checkout work was more problem-oriented (including monitoring and policing customers), and (3) traditional checkout began to become more demanding as easier transactions were filtered to self-checkout. As their interactions with customers became more focused on problem solving and rule enforcement, cashiers were often positioned as adversaries to customers at self-checkout. To cope with perceived adversarialism, cashiers engaged in a form of relational patchwork, using techniques like scapegoating the self-checkout machine and providing excessive customer service in order to maintain positive customer interactions in the face of potential conflict. Our findings highlight how even under pseudo-automation, workers must engage in relational work to manage and mend negative human-to-human interactions so that machines can be properly implemented in context.
Problem
Research questions and friction points this paper is trying to address.
Self-service technology
Workplace dynamics
Customer interaction
Innovation
Methods, ideas, or system contributions that make the work stand out.
Pseudo-Automation
Work Transformation
Customer Interaction
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