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Navigating the Legal Labyrinth: The Future of Data-Driven Platform Labor in China

Author

Listed:
  • Pengfei Li

    (Northwest Agriculture & Forestry University)

  • Miao Wang

    (Graduate School of Law in Sungkyunkwan University)

Abstract

Utilizing data-driven approaches to manage platform labor is a prime example of how big data is applied in modern labor practices. While touting advantages such as improved productivity and decreased human prejudice, it also brings a set of difficulties, including hazards to data security, worries about privacy, and the possibility of prejudices or discrimination. To tackle these difficulties, it is essential to enact laws specifically related to digital matters. This requires a careful and sophisticated approach that takes into account the intricate relationship between technical advancements and legal systems. This study employs a literature analysis approach based on theoretical jurisprudence to examine the management of data-driven platform labor in China’s context. Through careful examination of legislative responses and emphasis on evolving legal difficulties, it illuminates the complex processes in operation. Furthermore, it presents ideas from digital jurisprudence, including digital justice and algorithmic governance, which position data governance as a subject that encompasses multiple disciplines and necessitates interdisciplinary cooperation. Moreover, the study offers practical suggestions for improving digital legislative frameworks, with the goal of protecting individual rights and ensuring fairness in platform labor practices. This study explores the interdependent connection between technical progress, legal structures, and safeguarding individual rights in the digital era by adhering to the principles of the information economy.

Suggested Citation

  • Pengfei Li & Miao Wang, 2025. "Navigating the Legal Labyrinth: The Future of Data-Driven Platform Labor in China," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 16(2), pages 7016-7038, June.
    • Handle: RePEc:spr:jknowl:v:16:y:2025:i:2:d:10.1007_s13132-024-02099-1
    DOI: 10.1007/s13132-024-02099-1
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