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Making sense of algorithms: Workers' coping strategies for algorithmic management on digital platforms

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  • Zhao, Jie
  • Syed, Tahir Abbas

Abstract

Algorithmic management, characterised by data-driven and often opaque algorithmic decision-making, is transforming coordination and control in the digital labour market, affecting worker autonomy, earnings, power dynamics, and well-being. Despite recognition of its disruptive impact, how freelancers adapt to these challenges remains unclear. This study investigates the sensemaking processes freelancers on Upwork use to navigate algorithmic management, pairing advanced topic modelling and thematic analysis of large-scale Reddit data. We find that workers are not passive to algorithmic management but develop sophisticated, iterative coping strategies uniquely shaped by the platform's algorithmic architecture. Our findings advance literature by identifying the active agency of platform workers, highlighting the mechanisms through which sensemaking mediates adaptation to algorithmic systems. We provide guidance for transparent, equitable platform governance to improve digital labour experiences.

Suggested Citation

  • Zhao, Jie & Syed, Tahir Abbas, 2026. "Making sense of algorithms: Workers' coping strategies for algorithmic management on digital platforms," Technological Forecasting and Social Change, Elsevier, vol. 223(C).
    • Handle: RePEc:eee:tefoso:v:223:y:2026:i:c:s0040162525004743
    DOI: 10.1016/j.techfore.2025.124443
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    References listed on IDEAS

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