IDEAS home Printed from https://ideas.repec.org/p/osf/socarx/ud94h.html
   My bibliography  Save this paper

Democratization, state capacity and developmental correlates of international artificial intelligence trade

Author

Listed:
  • Unver, Hamid Akin

    (Ozyegin University)

  • Ertan, Arhan S.

    (Bogazici University)

Abstract

Does acquiring artificial intelligence (A.I.) technologies from the U.S. or China render countries more authoritarian or technologically less advantageous? In this article, we explore to what extent importing A.I./high-tech from the U.S. and/or China goes parallel with importers’ a) democratization or autocratization, b) state capacity, and c) technological progress across a decade (2010–2020). Our work demonstrates that not only are Chinese A.I./high-tech exports not congruous with importers’ democratic backsliding, but autocratization attributed to Chinese A.I. is also visible in importers of U.S. [AH1] A.I. In addition, for most indicators, we do not observe any significant effect of acquiring A.I. from the U.S. or China on importers’ state capacity or technological progress across the same period. Instead, we find that the story has a global inequality dimension as Chinese exports are clustered around countries with a lower GDP per capita, whereas U.S. high-technology exports are clustered around relatively wealthier states with slightly weaker capacity over territorial control. Overall, the article empirically demonstrates the limitations of some of the prevalent policy discourses surrounding the global diffusion of A.I. and its contribution to democratization, state capacity, and technological development of importer nations.

Suggested Citation

  • Unver, Hamid Akin & Ertan, Arhan S., 2023. "Democratization, state capacity and developmental correlates of international artificial intelligence trade," SocArXiv ud94h, Center for Open Science.
  • Handle: RePEc:osf:socarx:ud94h
    DOI: 10.31219/osf.io/ud94h
    as

    Download full text from publisher

    File URL: https://osf.io/download/65863344034461236a68f544/
    Download Restriction: no

    File URL: https://libkey.io/10.31219/osf.io/ud94h?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

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:osf:socarx:ud94h. 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: OSF (email available below). General contact details of provider: https://arabixiv.org .

    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.