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M-LAMAC: a model for linguistic assessment of mitigating and aggravating circumstances of criminal responsibility using computing with words.

Authors :
Rodríguez Rodríguez, Carlos Rafael
Amoroso Fernández, Yarina
Zuev, Denis Sergeevich
Peña Abreu, Marieta
Zulueta Veliz, Yeleny
Source :
Artificial Intelligence & Law; Sep2024, Vol. 32 Issue 3, p697-739, 43p
Publication Year :
2024

Abstract

The general mitigating and aggravating circumstances of criminal liability are elements attached to the crime that, when they occur, affect the punishment quantum. Cuban criminal legislation provides a catalog of such circumstances and some general conditions for their application. Such norms give judges broad discretion in assessing circumstances and adjusting punishment based on the intensity of those circumstances. In the interest of broad judicial discretion, the law does not establish specific ways for measuring circumstances' intensity. This gives judges more freedom and autonomy, but it also imposes on them more social responsibility and challenges them to manage the uncertainty and subjectivity inherent in this complex activity. This paper proposes a model to aid the linguistic assessment of circumstances' intensity and to provide linguistic and numerical recommendations to determine an appropriate punishment interval. M-LAMAC determines the collective evaluation of circumstances of the same type, determines the prevalence of a type of circumstance by means of a compensation function, recommends the required modification in the input interval, and finally recommends a numerical interval adjusted to the judges' initially expressed preferences. The model's applicability is demonstrated by means of several experiments on a fictitious case of bank document forgery. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09248463
Volume :
32
Issue :
3
Database :
Complementary Index
Journal :
Artificial Intelligence & Law
Publication Type :
Academic Journal
Accession number :
178778430
Full Text :
https://doi.org/10.1007/s10506-023-09365-8