IDEAS home Printed from https://ideas.repec.org/h/elg/eechap/21708_13.html
   My bibliography  Save this book chapter

Synthetic stakeholders: engaging the environment in organizational decision-making

In: Research Handbook on Artificial Intelligence and Decision Making in Organizations

Author

Listed:
  • Jen Rhymer
  • Alex Murray
  • David Sirmon

Abstract

Stakeholder theory suggests an array of different human actors-from individuals to collectives with various concerns-need to be considered in organizational decision-making. Yet recent advancements in agentic technologies, including artificial intelligence (AI), machine learning algorithms (ML), and distributed ledger technologies (DLTs), promise to disrupt this human-only affair. Critically, these technologies possess the agency to intentionally constrain, complement, or substitute for human action. As such, we frame these technologies as the basis of a potent new type of stakeholder: synthetic stakeholders. A synthetic stakeholder is a technology-based agent(s) that can learn and act as an independent representative in organizational decision-making processes. In this paper, we theorize the bounds of synthetic shareholders and address how they can engage in organizational decision-making. This research shows how often disregarded stakeholders, such as the natural environment, can gain a powerful and independent “voice” in organizational decision-making (Geisel, 1971).

Suggested Citation

  • Jen Rhymer & Alex Murray & David Sirmon, 2024. "Synthetic stakeholders: engaging the environment in organizational decision-making," Chapters, in: Ioanna Constantiou & Mayur P. Joshi & Marta Stelmaszak (ed.), Research Handbook on Artificial Intelligence and Decision Making in Organizations, chapter 13, pages 226-239, Edward Elgar Publishing.
  • Handle: RePEc:elg:eechap:21708_13
    as

    Download full text from publisher

    File URL: https://www.elgaronline.com/doi/10.4337/9781803926216.00022
    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:21708_13. 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.