IDEAS home Printed from https://ideas.repec.org/a/eee/telpol/v48y2024i10s0308596124001484.html
   My bibliography  Save this article

Privacy and personal data risk governance for generative artificial intelligence: A Chinese perspective

Author

Listed:
  • Ye, Xiongbiao
  • Yan, Yuhong
  • Li, Jia
  • Jiang, Bo

Abstract

The rapid development of generative artificial intelligence (AI) has attracted global attention and posed challenges to existing data governance frameworks. The increased technical complexity and expanded scale of data usage not only make it more difficult to regulate AI but also present challenges for the current legal system. This article, which takes ChatGPT's training data and working principles as a starting point, examines specific privacy risks, data leakage risks, and personal data risks posed by generative AI. It also analyzes the latest practices in privacy and personal data protection in China. This article finds that while China's governance on privacy and personal data protection takes a macro-micro integration approach and a private-and-public law integration approach, there are shortcomings in the legal system. Given that the current personal data protection system centered on individual control is unsuitable for the modes of data processing by generative AI, and that private law is insufficient in safeguarding data privacy, urgent institutional innovation is needed to achieve the objective of “trustworthy AI.”

Suggested Citation

  • Ye, Xiongbiao & Yan, Yuhong & Li, Jia & Jiang, Bo, 2024. "Privacy and personal data risk governance for generative artificial intelligence: A Chinese perspective," Telecommunications Policy, Elsevier, vol. 48(10).
    • Handle: RePEc:eee:telpol:v:48:y:2024:i:10:s0308596124001484
    DOI: 10.1016/j.telpol.2024.102851
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0308596124001484
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.telpol.2024.102851?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:telpol:v:48:y:2024:i:10:s0308596124001484. 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/wps/find/journaldescription.cws_home/30471/description#description .

    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.