IDEAS home Printed from https://ideas.repec.org/a/kap/jbuset/v192y2024i4d10.1007_s10551-024-05741-9.html
   My bibliography  Save this article

Generative Artificial Intelligence as Hypercommons: Ethics of Authorship and Ownership

Author

Listed:
  • Gazi Islam

    (Grenoble Ecole de Management)

  • Michelle Greenwood

    (Monash University)

Abstract

In this editorial essay, we argue that Generative Artificial Intelligence programs (GenAI) draw on what we term a “hypercommons”, involving collectively produced inputs and labour that are largely invisible or untraceable. We argue that automatizing the exploitation of common inputs, in ways that remix and reconfigure them, can lead to a crisis of academic authorship in which the moral agency involved in scholarly production is increasingly eroded. We discuss the relationship between the hypercommons and authorship in terms of moral agency and the ethics of academic production, speculating on different responses to the crisis of authorship as posed by GenAI.

Suggested Citation

  • Gazi Islam & Michelle Greenwood, 2024. "Generative Artificial Intelligence as Hypercommons: Ethics of Authorship and Ownership," Journal of Business Ethics, Springer, vol. 192(4), pages 659-663, July.
    • Handle: RePEc:kap:jbuset:v:192:y:2024:i:4:d:10.1007_s10551-024-05741-9
    DOI: 10.1007/s10551-024-05741-9
    as

    Download full text from publisher

    File URL: https://link.springer.com/10.1007/s10551-024-05741-9
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10551-024-05741-9?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:kap:jbuset:v:192:y:2024:i:4:d:10.1007_s10551-024-05741-9. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: https://www.springer.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.