COVERT RESISTANCE AGAINST ALGORITHMIC CONTROL ON ONLINE LABOR PLATFORMS – A SYSTEMATIC LITERATURE REVIEW
Online labor platforms (OLP) such as Uber or Upwork heavily rely on algorithms instead of human managers to control workers’ behavior. While algorithmic control (AC) allows platform providers to control their workers efficiently, it is often perceived by workers as a tighter control (compared to human-based control) which increases their motivation to resist. Especially covert resistance (i.e., workers’ hard-to-observe oppositional actions) provides essential insights into how workers deal with AC that affect platforms’ longevity. In this study, we conducted a systematic literature review to develop a theoretical framework showing how and why workers perform covert resistance against AC. Further, our analysis reveals the enabling role of sensemaking for diverse forms of covert resistance. Overall, our study expands the literature on AC by shedding light on the formation of workers’ covert resistance. Therefore, we offer platform providers and policymakers crucial insights to create fairer working environments for workers under AC.
Jiang, Jennifer, "COVERT RESISTANCE AGAINST ALGORITHMIC CONTROL ON ONLINE LABOR PLATFORMS – A SYSTEMATIC LITERATURE REVIEW" (2023). ECIS 2023 Research Papers. 272.