IDEAS home Printed from https://ideas.repec.org/a/aza/ama000/y2020v6i1p37-45.html
   My bibliography  Save this article

Facebook and Pandora’s box: How using Big Data and Artificial Intelligence in advertising resulted in housing discrimination

Author

Listed:
  • Khatry, Sarah

    (Data Scientist, DataRobot, USA)

Abstract

In 2019, the US Department of Housing and Development charged Facebook with violating the Fair Housing Act 1968. This followed an investigation into the use of ethnically targeted advertising practices on Facebook. To understand Facebook’s targeting methods and the cause of the problematic outcomes, this paper follows the journey of an advertisement through Facebook’s platform. In this way, Facebook’s regulatory missteps can serve as a case study to illustrate how Big Data analytics can, when informed by human and machine bias, cross the line into discriminatory practices. This case study underscores how it is vital — in advertising as in other industries — not to treat advanced analytics like artificial intelligence as black boxes. Indeed, to inform the design and use of advanced analytics, it is essential for companies to consistently develop a comprehensive understanding of their data, in addition to the legal and ethical implications of their operations.

Suggested Citation

  • Khatry, Sarah, 2020. "Facebook and Pandora’s box: How using Big Data and Artificial Intelligence in advertising resulted in housing discrimination," Applied Marketing Analytics: The Peer-Reviewed Journal, Henry Stewart Publications, vol. 6(1), pages 37-45, June.
  • Handle: RePEc:aza:ama000:y:2020:v:6:i:1:p:37-45
    as

    Download full text from publisher

    File URL: https://hstalks.com/article/5693/download/
    Download Restriction: Requires a paid subscription for full access.

    File URL: https://hstalks.com/article/5693/
    Download Restriction: Requires a paid subscription for full access.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Keywords

    housing discrimination; Facebook; Big Data; AI; targeted advertising;
    All these keywords.

    JEL classification:

    • M3 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising

    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:aza:ama000:y:2020:v:6:i:1:p:37-45. 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: Henry Stewart Talks (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.