IDEAS home Printed from https://ideas.repec.org/a/taf/tbitxx/v43y2024i14p3436-3460.html
   My bibliography  Save this article

The pursuit of happiness: the power and influence of AI teammate emotion in human-AI teamwork

Author

Listed:
  • Rohit Mallick
  • Christopher Flathmann
  • Caitlin Lancaster
  • Allyson Hauptman
  • Nathan McNeese
  • Guo Freeman

Abstract

As the world evolves, human-AI teams (HAT) have become increasingly more capable in their ability to complete task objectives. Due to this rising importance, it has become essential to understand the interpersonal dynamism between humans and AI to further optimise their performance potential. Given the demonstrated utility of emotional communication within human-human team structures, this research investigates the nature of AI-sourced positive emotions on human teammates. Through 47 interviews, our findings show that for these AI teammates to be accepted, human teammates have preferences on understanding the emotional utility prior to its presentation, as well as which emotions are situationally acceptable. Also, findings show that integrating emotions within AI teammates has a positive influence on human perceptions and behaviour in a task. In further detail, emotions act as status updates that allow human teammates to not only better understand their teammates' mental states but also understand how their AI teammates perceive the situation around them. Together, this gives insight into how AI emotional expressions influence the perception of social support on the wider Human-AI team. Mainly how emotions can be used to increase acceptance of AI teammates and improve the overall experience human teammates have within the task.

Suggested Citation

  • Rohit Mallick & Christopher Flathmann & Caitlin Lancaster & Allyson Hauptman & Nathan McNeese & Guo Freeman, 2024. "The pursuit of happiness: the power and influence of AI teammate emotion in human-AI teamwork," Behaviour and Information Technology, Taylor & Francis Journals, vol. 43(14), pages 3436-3460, October.
  • Handle: RePEc:taf:tbitxx:v:43:y:2024:i:14:p:3436-3460
    DOI: 10.1080/0144929X.2023.2277909
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/0144929X.2023.2277909
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/0144929X.2023.2277909?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.

    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:taf:tbitxx:v:43:y:2024:i:14:p:3436-3460. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/tbit .

    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.