IDEAS home Printed from https://ideas.repec.org/h/elg/eechap/20885_4.html
   My bibliography  Save this book chapter

AI-enabled business model and human-in-the-loop (deceptive AI): implications for labor

In: Handbook of Artificial Intelligence at Work

Author

Listed:
  • Uma Rani
  • Rishabh Kumar Dhir

Abstract

In recent years, artificial intelligence (AI) systems have gained popularity and are expected to enhance efficiency and productivity. However, there is a common misconception that these systems are fully automated and will replace human labor. Emerging research indicates that AI-enabled business models rely heavily on human workers for training, development, monitoring and service of the AI. Human-in-the-loop processes remain fundamental to the operation of AI systems, which increasingly utilize a global pool of workers through digital labor platforms to perform multiple tasks. This chapter highlights the precarious working conditions of workers who perform tasks to support and develop AI systems, based on surveys conducted on microtask platforms. It also highlights the implications of the AI-enabled business models on transforming the nature of employment and job quality, and the risk of exacerbating inequalities and underlines the importance of promoting decent work for all.

Suggested Citation

  • Uma Rani & Rishabh Kumar Dhir, 2024. "AI-enabled business model and human-in-the-loop (deceptive AI): implications for labor," Chapters, in: Martha Garcia-Murillo & Ian MacInnes & Andrea Renda (ed.), Handbook of Artificial Intelligence at Work, chapter 4, pages 47-75, Edward Elgar Publishing.
  • Handle: RePEc:elg:eechap:20885_4
    as

    Download full text from publisher

    File URL: https://www.elgaronline.com/doi/10.4337/9781800889972.00011
    Download Restriction: no
    ---><---

    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:elg:eechap:20885_4. 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: Darrel McCalla (email available below). General contact details of provider: http://www.e-elgar.com .

    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.