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Extending the framework of algorithmic regulation. The Uber case

Author

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  • Eyert, Florian
  • Irgmaier, Florian
  • Ulbricht, Lena

Abstract

In this article, we take forward recent initiatives to assess regulation based on contemporary computer technologies such as big data and artificial intelligence. In order to characterize current phenomena of regulation in the digital age, we build on Karen Yeung's concept of “algorithmic regulation,” extending it by building bridges to the fields of quantification, classification, and evaluation research, as well as to science and technology studies. This allows us to develop a more fine‐grained conceptual framework that analyzes the three components of algorithmic regulation as representation, direction, and intervention and proposes subdimensions for each. Based on a case study of the algorithmic regulation of Uber drivers, we show the usefulness of the framework for assessing regulation in the digital age and as a starting point for critique and alternative models of algorithmic regulation.

Suggested Citation

  • Eyert, Florian & Irgmaier, Florian & Ulbricht, Lena, 2022. "Extending the framework of algorithmic regulation. The Uber case," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 16(1), pages 23-44.
    • Handle: RePEc:zbw:espost:228462
    DOI: 10.1111/rego.12371
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    References listed on IDEAS

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    Cited by:

    1. Ulbricht, Lena, 2020. "Algorithmen und Politisierung [Algorithms and politicization]," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 0, pages 255-278.
    2. Lena Ulbricht & Karen Yeung, 2022. "Algorithmic regulation: A maturing concept for investigating regulation of and through algorithms," Regulation & Governance, John Wiley & Sons, vol. 16(1), pages 3-22, January.
    3. Ulbricht, Lena & Yeung, Karen, 2022. "Algorithmic regulation: A maturing concept for investigating regulation of and through algorithms," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 16(1), pages 3-22.
    4. Noemi Festic, 2022. "Same, same, but different! Qualitative evidence on how algorithmic selection applications govern different life domains," Regulation & Governance, John Wiley & Sons, vol. 16(1), pages 85-101, January.
    5. Rocco Bellanova & Marieke de Goede, 2022. "The algorithmic regulation of security: An infrastructural perspective," Regulation & Governance, John Wiley & Sons, vol. 16(1), pages 102-118, January.
    6. Tobias D. Krafft & Katharina A. Zweig & Pascal D. König, 2022. "How to regulate algorithmic decision‐making: A framework of regulatory requirements for different applications," Regulation & Governance, John Wiley & Sons, vol. 16(1), pages 119-136, January.

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