IDEAS home Printed from https://ideas.repec.org/a/bla/glopol/v16y2025i3p467-473.html
   My bibliography  Save this article

Digital Yes‐Men: How to Deal With Sycophantic Military AI?

Author

Listed:
  • Jonathan Kwik

Abstract

Militaries have increasingly embraced decision‐support AI for targeting and other planning tasks. An emerging risk identified with respect to these models is ‘sycophancy’: the tendency of AI to align their outputs with their user's views or preferences, even if this view is incorrect. This paper offers an initial perspective on sycophantic AI in the military domain, and identifies the different technical, organisational and operational elements at play to inform more granular research. It examines the phenomenon technically, the risks it introduces to military operations, and the different courses‐of‐action militaries can take to mitigate this risk. It theorises that sycophancy is militarily deleterious both in the short and long term, by aggravating existing cognitive biases and inducing organisational overtrust, respectively. The paper then explores two main approaches to mitigation that can be taken: technical intervention at the model/design level (e.g., through finetuning), and user training. It theorises that user training is an important complementary measure to technical intervention, since sycophancy can never be comprehensively addressed only at the design stage. Finally, the paper conceptualises tools and procedures militaries could develop to minimise the negative effects sycophantic AI could have on users' decision‐making should sycophancy manifest despite all prior efforts at mitigation.

Suggested Citation

  • Jonathan Kwik, 2025. "Digital Yes‐Men: How to Deal With Sycophantic Military AI?," Global Policy, London School of Economics and Political Science, vol. 16(3), pages 467-473, June.
  • Handle: RePEc:bla:glopol:v:16:y:2025:i:3:p:467-473
    DOI: 10.1111/1758-5899.70042
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/1758-5899.70042
    Download Restriction: no

    File URL: https://libkey.io/10.1111/1758-5899.70042?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
    ---><---

    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:bla:glopol:v:16:y:2025:i:3:p:467-473. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/lsepsuk.html .

    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.