IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-981-97-0597-9_6.html
   My bibliography  Save this book chapter

Ambition, Capacity, Reality, Insights, and Prospects

In: The Use of Artificial Intelligence in the Public Sector in Shanghai

Author

Listed:
  • Diego Todaro

    (Ca’ Foscari University of Venice)

Abstract

Shanghai has solid capacities to implement its ambitious plans for AI in the public sector. These capacities are mobilized in a coordinated, systemic, and proactive strategy, which is manifested in three major policy initiatives that are actively fostering the use of AI in the public sector. Namely: the Government Online-Offline Shanghai, the Single Platform for Urban Management, and the AI pilot application scenarios. The analysis of these case studies highlights their strengths and limitations in deploying AI in the public sector. It shows that these policy initiatives have improved the provision of public services by successfully integrating AI in public sector activities and have contributed to spurring the diffusion of public sector AI applications in Shanghai. The significance of these findings goes beyond the study of Shanghai, as they can be used to obtain an improved understanding of some key research topics identified by the literature on AI in the public sector. By assessing the advantages and shortcomings of Shanghai’s AI strategy in light of the broader findings of public sector AI scholarship, it is possible to identify the lessons that can be learnt from the experience of the municipality, the unanswered questions, and derive useful elements to gauge the possible development trajectories of public sector AI applications in Shanghai.

Suggested Citation

  • Diego Todaro, 2024. "Ambition, Capacity, Reality, Insights, and Prospects," Springer Books, in: The Use of Artificial Intelligence in the Public Sector in Shanghai, chapter 0, pages 555-615, Springer.
    • Handle: RePEc:spr:sprchp:978-981-97-0597-9_6
    DOI: 10.1007/978-981-97-0597-9_6
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:spr:sprchp:978-981-97-0597-9_6. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.