IDEAS home Printed from https://ideas.repec.org/a/plo/pdig00/0000278.html
   My bibliography  Save this article

Bias in artificial intelligence algorithms and recommendations for mitigation

Author

Listed:
  • Lama H Nazer
  • Razan Zatarah
  • Shai Waldrip
  • Janny Xue Chen Ke
  • Mira Moukheiber
  • Ashish K Khanna
  • Rachel S Hicklen
  • Lama Moukheiber
  • Dana Moukheiber
  • Haobo Ma
  • Piyush Mathur

Abstract

The adoption of artificial intelligence (AI) algorithms is rapidly increasing in healthcare. Such algorithms may be shaped by various factors such as social determinants of health that can influence health outcomes. While AI algorithms have been proposed as a tool to expand the reach of quality healthcare to underserved communities and improve health equity, recent literature has raised concerns about the propagation of biases and healthcare disparities through implementation of these algorithms. Thus, it is critical to understand the sources of bias inherent in AI-based algorithms. This review aims to highlight the potential sources of bias within each step of developing AI algorithms in healthcare, starting from framing the problem, data collection, preprocessing, development, and validation, as well as their full implementation. For each of these steps, we also discuss strategies to mitigate the bias and disparities. A checklist was developed with recommendations for reducing bias during the development and implementation stages. It is important for developers and users of AI-based algorithms to keep these important considerations in mind to advance health equity for all populations.

Suggested Citation

  • Lama H Nazer & Razan Zatarah & Shai Waldrip & Janny Xue Chen Ke & Mira Moukheiber & Ashish K Khanna & Rachel S Hicklen & Lama Moukheiber & Dana Moukheiber & Haobo Ma & Piyush Mathur, 2023. "Bias in artificial intelligence algorithms and recommendations for mitigation," PLOS Digital Health, Public Library of Science, vol. 2(6), pages 1-14, June.
    • Handle: RePEc:plo:pdig00:0000278
    DOI: 10.1371/journal.pdig.0000278
    as

    Download full text from publisher

    File URL: https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0000278
    Download Restriction: no
    File URL: https://journals.plos.org/digitalhealth/article/file?id=10.1371/journal.pdig.0000278&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pdig.0000278?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
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hamish S Fraser & Alvin Marcelo & Mahima Kalla & Khumbo Kalua & Leo A Celi & Jennifer Ziegler, 2023. "Digital determinants of health: Editorial," PLOS Digital Health, Public Library of Science, vol. 2(11), pages 1-4, November.
    2. Marie-Laure Charpignon & Leo Anthony Celi & Marisa Cobanaj & Rene Eber & Amelia Fiske & Jack Gallifant & Chenyu Li & Gurucharan Lingamallu & Anton Petushkov & Robin Pierce, 2024. "Diversity and inclusion: A hidden additional benefit of Open Data," PLOS Digital Health, Public Library of Science, vol. 3(7), pages 1-17, July.

    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:plo:pdig00:0000278. 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: digitalhealth (email available below). General contact details of provider: https://journals.plos.org/digitalhealth .

    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.