IDEAS home Printed from https://ideas.repec.org/a/ucp/jacres/doi10.1086-730710.html
   My bibliography  Save this article

Giving AI a Human Touch: Highlighting Human Input Increases the Perceived Helpfulness of Advice from AI Coaches

Author

Listed:
  • Yue Zhang
  • Mirjam A. Tuk
  • Anne-Kathrin Klesse

Abstract

How can we increase the acceptance of artificial intelligence (AI) coaching advice? Across five studies (N=3,780), we document that people perceive AI advice as more helpful if human input is (made) salient. Utilizing a naturalistic field setting, study 1 shows that the more students believe that an AI coach contains human input, the more helpful the advice is perceived to be. We find that highlighting human input as an intervention strategy increases the perceived helpfulness of AI advice in the context of photography, compared to various control conditions (study 2 and follow-up study in the appendix, available onlineappendix). Study 3 shows that the effect is mediated by an increased subjective understanding of AI feedback when human input is highlighted. Study 4 provides evidence through moderation and shows that the positive impact of highlighting human input disappears under low levels of subjective understanding.

Suggested Citation

  • Yue Zhang & Mirjam A. Tuk & Anne-Kathrin Klesse, 2024. "Giving AI a Human Touch: Highlighting Human Input Increases the Perceived Helpfulness of Advice from AI Coaches," Journal of the Association for Consumer Research, University of Chicago Press, vol. 9(3), pages 344-356.
    • Handle: RePEc:ucp:jacres:doi:10.1086/730710
    DOI: 10.1086/730710
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1086/730710
    Download Restriction: Access to the online full text or PDF requires a subscription.
    File URL: http://dx.doi.org/10.1086/730710
    Download Restriction: Access to the online full text or PDF requires a subscription.
    File URL: https://libkey.io/10.1086/730710?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:ucp:jacres:doi:10.1086/730710. 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: Journals Division (email available below). General contact details of provider: https://www.journals.uchicago.edu/JACR .

    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.