IDEAS home Printed from https://ideas.repec.org/a/spr/infosf/v25y2023i6d10.1007_s10796-021-10174-0.html
   My bibliography  Save this article

Role of Risks in the Development of Responsible Artificial Intelligence in the Digital Healthcare Domain

Author

Listed:
  • Shivam Gupta

    (NEOMA Business School)

  • Shampy Kamboj

    (National Institute of Technology Hamirpur)

  • Surajit Bag

    (International University of Rabat)

Abstract

The use of artificial intelligence (AI) in the healthcare field is gaining popularity. However, it also raises some concerns related to privacy and ethical aspects that require the development of a responsible AI framework. The principle of responsible AI states that artificial intelligence-based systems should be considered a part of composite societal and technological systems. This study attempts to establish whether AI risks in digital healthcare are positively associated with responsible AI. The moderating effect of perceived trust and perceived privacy risks is also examined. The theoretical model was based on perceived risk theory. Perceived risk theory is important in the context of this study, as risks related to uneasiness and uncertainty can be expected in the development of responsible AI due to the volatile nature of intelligent applications. Our research provides some interesting findings which are presented in the discussion section.

Suggested Citation

  • Shivam Gupta & Shampy Kamboj & Surajit Bag, 2023. "Role of Risks in the Development of Responsible Artificial Intelligence in the Digital Healthcare Domain," Information Systems Frontiers, Springer, vol. 25(6), pages 2257-2274, December.
    • Handle: RePEc:spr:infosf:v:25:y:2023:i:6:d:10.1007_s10796-021-10174-0
    DOI: 10.1007/s10796-021-10174-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10796-021-10174-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10796-021-10174-0?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:spr:infosf:v:25:y:2023:i:6:d:10.1007_s10796-021-10174-0. 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.