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Pretrial risk assessment instruments in the US criminal justice system—what lessons can be learned for the European Union
Abstract
This article explores the possibilities of using artificial intelligence (AI) in the European judicial area with a special emphasis on risk assessment instruments and the justification of their use in determining the likelihood that a defendant at large will seek to thwart the goal of criminal proceedings. In this regard, experiences in the application of various risk assessment instruments in US judicial practice are first analysed. Then the European normative framework established at the level of the Council of Europe and European Union (EU) law is considered with special emphasis on the ‘Proposal for a Regulation of the European Parliament and of the Council laying down harmonized rules on artificial intelligence’ as a key normative act that will determine the long-term preconditions for the application of the risk assessment instruments in the criminal proceedings of EU Member States. Finally, an attempt is made to give answers to some specific questions that arose from the implementation of AI in EU criminal justice systems taking into account the presumption of innocence, the right to an objective and impartial judge and the principle of proportionality.
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The high stakes of criminal justice make courts slow to adopt new technologies, and the state of the art in AI has little impact on criminal risk assessment.
“The high stakes of criminal justice make courts slow to adopt new technologies [52], and the state of the art in AI has little impact on criminal risk assessment.”
From Efficiency vs. Equity: A Structured Interdisciplinary Review of AI in Criminal Justice Risk Assessments (2026) · cites this paper as [52]
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Atkinson, G., & Casagrande, K. (2026) · Information · doi:10.3390/info17060574
Metadata
- Authors
- Novokmet, A., Tomičić, Z., & Vinković, Z.
- Venue
- International Journal of Law and Information Technology
- Publisher
- Oxford University Press (OUP)
- Published
- 2022-03-01
- Volume
- 30
- Issue
- 1
- Pages
- 1-22
- ISSN
- 0967-0769
- 1464-3693
- Cited by
- 9
- References
- 0
- Language
- en
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