IDEAS home Printed from https://ideas.repec.org/a/tec/journl/ojs10917.html

The Impact of Artificial Intelligence on Job Loss: Risks for Governments

Author

Listed:
  • Mohamad Hassan Soueidan

    (Al-Jinan University, Lebanon)

  • Rodwan Shoghari

    (Al-Jinan University, Lebanon)

Abstract

The rapid advancement of Artificial Intelligence (AI) technologies presents both opportunities and challenges for labor markets globally. By adopting a qualitative methodology, this study analyses the impact of AI integration in jobs on the labor market and the subsequent policy responses by governments. The study specifies the industries and jobs that are highly susceptible to AI-driven automation, particularly those characterized by routine and repetitive tasks. The study also acknowledges the potential for AI to create new job categories. Key findings suggest that while AI poses a significant risk of job displacement in several sectors, it also offers opportunities for economic growth, opening of new jobs and innovation. Moreover, the study highlights various government strategies employed globally, including up-skilling and re-skilling initiatives, strengthening social protection systems, and fostering AI-human collaboration. These strategies aim to mitigate the adverse impacts of AI on employment and ensure a balanced transition to AI-integrated economies. Based on these strategies, the paper suggests some recommendations for governments to address AI-driven job losses, emphasizing the importance of multidisciplinary education, ethical AI use, inclusive growth strategies, and international cooperation.

Suggested Citation

  • Mohamad Hassan Soueidan & Rodwan Shoghari, 2024. "The Impact of Artificial Intelligence on Job Loss: Risks for Governments," Technium Social Sciences Journal, Technium Science, vol. 57(1), pages 206-223, May.
    • Handle: RePEc:tec:journl:ojs:10917
    DOI: 10.47577/tssj.v57i1.10917
    as

    Download full text from publisher

    File URL: https://techniumscience.com/index.php/socialsciences/article/view/10917
    Download Restriction: no
    File URL: https://libkey.io/10.47577/tssj.v57i1.10917?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:tec:journl:ojs:10917. 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: Tasente Tanase The email address of this maintainer does not seem to be valid anymore. Please ask Tasente Tanase to update the entry or send us the correct address (email available below). General contact details of provider: .

    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.