IDEAS home Printed from https://ideas.repec.org/a/tec/journl/v25y2021i1p115-125.html
   My bibliography  Save this article

The use of AI in formulating a criminological prognosis of an offender

Author

Listed:
  • Magdalena Kowalewska-Lukuc

    (Faculty of Law and Administration, University of Szczecin, Poland)

  • Konrad Burdziak

    (Faculty of Law and Administration, University of Szczecin, Poland)

Abstract

The article raise the issue of the use of AI (artificial intelligence) in formulating the criminological prognosis of an offender. The issue is analyzed in view of the institution of conditional early release from serving the rest of the imprisonment sentence. The authors point to several AI tools for making offender criminological predictions. An analysis of their application in various European countries shows that the question of whether their use should be considered ought to be replaced with the question of whether their use should be considered probably ought to be replaced with the question of how to use them, so that they can actually meet the objectives set for them.

Suggested Citation

  • Magdalena Kowalewska-Lukuc & Konrad Burdziak, 2021. "The use of AI in formulating a criminological prognosis of an offender," Technium Social Sciences Journal, Technium Science, vol. 25(1), pages 115-125, November.
    • Handle: RePEc:tec:journl:v:25:y:2021:i:1:p:115-125
    as

    Download full text from publisher

    File URL: https://techniumscience.com/index.php/socialsciences/article/view/4891/1735
    Download Restriction: no
    File URL: https://techniumscience.com/index.php/socialsciences/article/view/4891
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    AI; criminal law; criminological prognosis; conditional early release;
    All these keywords.

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    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:tec:journl:v:25:y:2021:i:1:p:115-125. 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: Tasente Tanase (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.