Paper Number
ECIS2026-2883
Paper Type
SP
Abstract
Digital labor platforms (DLP) use algorithmic control (AC) to align worker behaviors with organizational goals. A key limitation of AC is opacity — workers struggle to understand the inner workings of AC. The opacity of AC can undermine well-being and influence work-related outcomes such as compliance, resistance, and quitting. DLPs often employ dynamic, integrated AC systems to optimize worker behaviors, further increasing opacity. Early research has focused on how workers make sense of individual AC mechanisms but has overlooked how AC systems exacerbate opacity and workers’ reactions to it. We advance research on opaque AC by examining how workers cope with opaque AC systems. We conducted semi-structured interviews with 22 workers and managers on an app-based food delivery platform in China. Our preliminary analysis illustrates that workers cope with AC opacity by constructing a mental model of “the system”, using sensemaking to interpret it, and forming diverse evaluations of its fairness.
Recommended Citation
Hao, Hui; Hess, Traci J.; and Tarafdar, Monideepa, "How Do Workers Cope With An Opaque Algorithmic Control System?" (2026). ECIS 2026 Proceedings. 17.
https://aisel.aisnet.org/ecis2026/conf_theme/conf_theme/17
How Do Workers Cope With An Opaque Algorithmic Control System?
Digital labor platforms (DLP) use algorithmic control (AC) to align worker behaviors with organizational goals. A key limitation of AC is opacity — workers struggle to understand the inner workings of AC. The opacity of AC can undermine well-being and influence work-related outcomes such as compliance, resistance, and quitting. DLPs often employ dynamic, integrated AC systems to optimize worker behaviors, further increasing opacity. Early research has focused on how workers make sense of individual AC mechanisms but has overlooked how AC systems exacerbate opacity and workers’ reactions to it. We advance research on opaque AC by examining how workers cope with opaque AC systems. We conducted semi-structured interviews with 22 workers and managers on an app-based food delivery platform in China. Our preliminary analysis illustrates that workers cope with AC opacity by constructing a mental model of “the system”, using sensemaking to interpret it, and forming diverse evaluations of its fairness.
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