IDEAS home Printed from https://ideas.repec.org/a/eee/reveco/v101y2025ics1059056025003673.html
   My bibliography  Save this article

Financial perceptions and AI infringement risks

Author

Listed:
  • Wei, Tian
  • Wu, Han
  • Dowling, Michael
  • Mahdavi Ardekani, Aref

Abstract

Artificial intelligence (AI)-related intellectual property (IP) infringement involves the unauthorized use of copyrighted materials during model training and the creation of content that may violate copyright, trademark, or patent laws. This phenomenon presents critical financial risks for businesses, ranging from reputational harm and erosion of brand equity to potential litigation, regulatory scrutiny, and increased investor uncertainty. This study explores how to understand this emergent risk and the associated implications. To do so, we apply social capital theory to an analysis of 10,447 Chinese social media users' reactions to China's first AI-generated voice infringement lawsuit. Our findings suggest that out-tie social capital (exposure to diverse networks) tends to promote neutral or positive views, while in-tie social capital (strong, close-knit communities) initially encourages favorable attitudes but shifts toward ethical and risk concerns when potential financial damages are perceived. Our study, thus, highlights the interplay between social perception and corporate financial considerations in an era where AI increasingly shapes economic opportunities and liabilities.

Suggested Citation

  • Wei, Tian & Wu, Han & Dowling, Michael & Mahdavi Ardekani, Aref, 2025. "Financial perceptions and AI infringement risks," International Review of Economics & Finance, Elsevier, vol. 101(C).
  • Handle: RePEc:eee:reveco:v:101:y:2025:i:c:s1059056025003673
    DOI: 10.1016/j.iref.2025.104204
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1059056025003673
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.iref.2025.104204?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:eee:reveco:v:101:y:2025:i:c:s1059056025003673. 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: http://www.elsevier.com/locate/inca/620165 .

    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.