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Article

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Title

Towards automated recommendations for drunk driving penalties in Poland - a case study analysis in selected court

Authors

[ 1 ] Instytut Informatyki, Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | [ P ] employee

Scientific discipline (Law 2.0)

[2.3] Information and communication technology

Year of publication

2023

Published in

Foundations of Computing and Decision Sciences

Journal year: 2023 | Journal volume: vol. 48 | Journal number: no. 4

Article type

scientific article

Publication language

english

Keywords
EN
  • automation
  • sentencing guidelines
  • digitalization of justice
Abstract

EN Depending on the legal system, judges may have varying degrees of discretion in determining the type and extent of sentence that can be imposed for a particular offence. Nevertheless, it appears that even in systems traditionally considered discretionary, accepted patterns play a significant role in determining penalties, and judges utilize merely a limited spectrum of potential penalties in repetitive cases. Confirmation of the predictability of sentencing in certain categories of cases facilitates the possibility of automation. Utilising a computer program to assist judges in sentencing proposals based on input is feasible. This program can reflect the standard practice of sentencing penalties and punitive measures in a particular category of cases or rectify it, depending on the adopted sentencing policy. The objective of the article is to present findings from research that investigated whether a specific relation shapes the dimension of penalties and penal measures for cases concerning driving under the influence of alcohol in Poland, in the context of possible automation of the sentencing process. Another aim of this study is to provide an example of a straightforward mathematical recommendation model that tries to reflect both the discovered correlations in the data and the presumed intentions of legislators.

Pages (from - to)

425 - 451

DOI

10.2478/fcds-2023-0019

URL

https://sciendo.com/article/10.2478/fcds-2023-0019

License type

CC BY-NC-ND (attribution - noncommercial - no derivatives)

Open Access Mode

open journal

Open Access Text Version

final published version

Date of Open Access to the publication

at the time of publication

Ministry points / journal

70

Impact Factor

1,1 [List 2022]

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