IDEAS home Printed from https://ideas.repec.org/a/aza/airwa0/y2022v1i4p342-349.html
   My bibliography  Save this article

Why automatic AI ethics evaluations are coming, and how they will work

Author

Listed:
  • Brusseau, James

    (Philosophy and Religious Studies Department, Pace University, One Pace Plaza, New York, NY 10038, USA)

  • Craveiro, Giovana Meloni

    (Graduate, University of São Paulo, Brazil)

Abstract

Ethics evaluations of companies that function with AI at their core are increasingly required by regulation and law in Europe and the US. Investors in artificial intelligence (AI)-intensive companies also seek ethics evaluations as part of the nonfinancial information they gather about corporate performance, especially as it relates to privacy and algorithmic fairness. The result is an increasing demand for the evaluations. The costs and time necessary to perform an AI ethics audit, however, are high, even prohibitive. To solve the problem, natural language processing (NLP) and machine learning (ML) can be employed to automate the process. The proposal is that much of the work of AI evaluating can be accomplished more efficiently by machines than by humans. To show how automated ethics reporting may work, this paper describes a project currently underway at Pace University in New York and the University of Trento in Italy. The project endeavours to apply AI to the task of producing AI ethics evaluations.

Suggested Citation

  • Brusseau, James & Craveiro, Giovana Meloni, 2022. "Why automatic AI ethics evaluations are coming, and how they will work," Journal of AI, Robotics & Workplace Automation, Henry Stewart Publications, vol. 1(4), pages 342-349, June.
  • Handle: RePEc:aza:airwa0:y:2022:v:1:i:4:p:342-349
    as

    Download full text from publisher

    File URL: https://hstalks.com/article/7196/download/
    Download Restriction: Requires a paid subscription for full access.

    File URL: https://hstalks.com/article/7196/
    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.

    Citations

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


    Cited by:

    1. Ahmed Izzidien, 2023. "Using the interest theory of rights and Hohfeldian taxonomy to address a gap in machine learning methods for legal document analysis," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-15, December.

    More about this item

    Keywords

    AI; AI ethics; ethical investing; AI human impact; fintech; natural language processing;
    All these keywords.

    JEL classification:

    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management
    • G2 - Financial Economics - - Financial Institutions and Services

    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:airwa0:y:2022:v:1:i:4:p:342-349. 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.