Intelligent computer evaluation of offender's previous record

Uri J. Schild, Ruth Kannai

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

This paper considers the problem of how to evaluate an offender's criminal record. This evaluation is part of the sentencing process carried out by a judge, and may be complicated in the case of offenders with a heavy record. We give a comprehensive overview of the approach to an offender's past record in various (Western) countries, considering the two major approaches: desert-based and utilitarian. The paper describes the determination of the parameters involved in the evaluation, and the construction of a decision support system to be used by a judge about to pass sentence in a criminal case. The system may be used as a stand-alone system, but can also be integrated as a component of a general sentencing support system, e.g. a statistical sentencing information system. The system is a knowledge-based system. The knowledge base (in rule-form) was created primarily by eliciting knowledge from experts (judges, lawyers, academics and probation officers), but also by applying statutory law, case law and legal authoritative texts. It is flexible in the sense, that a user can introduce his1 own preferences (expressed as numerical coefficients) and thereby apply different sentencing principles. The prototype is at present undergoing testing by some of the participating judges.

Original languageEnglish
Pages (from-to)373-405
Number of pages33
JournalArtificial Intelligence and Law
Volume13
Issue number3-4
DOIs
StatePublished - 1 Dec 2005
Externally publishedYes

Keywords

  • Criminal sentencing
  • Decision support systems
  • Previous criminal record

ASJC Scopus subject areas

  • Artificial Intelligence
  • Law

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