ASSYST - computer support for guideline sentencing
ICAIL '89 Proceedings of the 2nd international conference on Artificial intelligence and law
Knowledge-based systems and legal applications
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Decision support for sentencing in a common law jurisdiction
ICAIL '95 Proceedings of the 5th international conference on Artificial intelligence and law
Machine Learning
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ICAIL '03 Proceedings of the 9th international conference on Artificial intelligence and law
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ISI'09 Proceedings of the 2009 IEEE international conference on Intelligence and security informatics
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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 his 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.