IDEAS home Printed from https://ideas.repec.org/p/osf/mediar/7ejqn_v1.html
   My bibliography  Save this paper

Platform scams: Brazilian workers’ experiences of dishonest and uncertain algorithmic management

Author

Listed:
  • Grohmann, Rafael
  • Pereira, Gabriel

    (University of Amsterdam)

  • Guerra, Abel
  • Abílio, Ludmila Costhek
  • Moreschi, Bruno
  • Jurno, Amanda

Abstract

This article discusses how Brazilian platform workers experience and respond to platform scams through three case studies. Drawing from digital ethnographic research, vlogs/interviews of workers, and literature review, we argue for a conceptualization of “platform scam” that focuses on multiple forms of platform dishonesty and uncertainty. We characterize scam as a structuring element of the algorithmic management enacted by platform labor. The first case engages with when platforms scam workers by discussing Uber drivers’ experiences with the illusive surge pricing. The second case discusses when workers (have to) scam platforms by focusing on Amazon Mechanical Turk microworkers’ experiences with faking their identities. The third case presents when platforms lead workers to scam third parties, by engaging with how Brazilian click farm platforms’ workers use bots/fake accounts to engage with social media. Our focus on “platform scams” thus highlights the particular dimensions of faking, fraud, and deception operating in platform labor. This notion of platform scam expands and complexifies the understanding of scam within platform labor studies. Departing from workers' experiences, we engage with the asymmetries and unequal power relations present in the algorithmic management of labor.

Suggested Citation

  • Grohmann, Rafael & Pereira, Gabriel & Guerra, Abel & Abílio, Ludmila Costhek & Moreschi, Bruno & Jurno, Amanda, 2021. "Platform scams: Brazilian workers’ experiences of dishonest and uncertain algorithmic management," MediArXiv 7ejqn_v1, Center for Open Science.
    • Handle: RePEc:osf:mediar:7ejqn_v1
    DOI: 10.31219/osf.io/7ejqn_v1
    as

    Download full text from publisher

    File URL: https://osf.io/download/615e580486713b00b69076e2/
    Download Restriction: no
    File URL: https://libkey.io/10.31219/osf.io/7ejqn_v1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:osf:mediar:7ejqn_v1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: OSF (email available below). General contact details of provider: https://mediarxiv.org .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.