IDEAS home Printed from https://ideas.repec.org/a/eee/joreco/v87y2025ics0969698925001833.html
   My bibliography  Save this article

Research on fear of artificial intelligence among the elderly: The key of education and the prison of female

Author

Listed:
  • Li, Wei
  • Chang, Yaping
  • He, Yinghao
  • Li, Hong

Abstract

With the growth in the aging population, attitudes toward artificial intelligence (AI) technology among the elderly continue to be an important area of research. This study demonstrates a positive relationship between age and fear of AI, with fear of dying as a mediator. Specifically, we propose and find that the elderly (65 years and older) are more afraid of AI than younger individuals (<65 years old). We find that elderly individuals face higher levels of fear of dying, which may exacerbate their fear of AI technology. Furthermore, a higher level of education effectively reduces fear of dying and fear of AI among the elderly. Notably, this study reveals a significant gender disparity in the reduction of fear of AI. Although education effectively reduces the fear of AI among elderly men, it remains ineffective in alleviating the same fear among elderly women. Using data from a nationally representative public survey (2015–2022), we apply ordinary least squares regression to test these relationships. The findings of this study not only highlight the urgent need for society to be cognizant of the technological divide but also emphasize the pivotal role of education in quelling fears of new technologies among the elderly. At the societal level, this study emphasizes the need to address AI-related fear faced by elderly women, which is crucial for fostering inclusive AI adoption and reducing age- and gender-based disparities.

Suggested Citation

  • Li, Wei & Chang, Yaping & He, Yinghao & Li, Hong, 2025. "Research on fear of artificial intelligence among the elderly: The key of education and the prison of female," Journal of Retailing and Consumer Services, Elsevier, vol. 87(C).
  • Handle: RePEc:eee:joreco:v:87:y:2025:i:c:s0969698925001833
    DOI: 10.1016/j.jretconser.2025.104404
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0969698925001833
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jretconser.2025.104404?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

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    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:eee:joreco:v:87:y:2025:i:c:s0969698925001833. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/journal-of-retailing-and-consumer-services .

    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.