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Man and machine: artificial intelligence and judicial decision making
Arthur Dyevre, Ahmad Shahvaroughi
Intelligence
Status: succeeded | Model: Gemma-4-26B-A4B | Prompt: intel-v1 | Confidence: 89%
Last extracted: 7/13/2026, 3:35:44 AM
Summary
This paper reviews the integration of artificial intelligence into judicial decision-making, focusing on criminal justice risk assessment. It analyzes the performance and fairness of AI tools, human judge biases, and the interaction between AI and humans, concluding that current AI impact is modest and highlighting gaps for future interdisciplinary research.
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Relation Signals (12)
Arthur Dyevre → authored → Man and machine: artificial intelligence and judicial decision making
confidence 100% · Authors:Arthur Dyevre, Ahmad Shahvaroughi
Ahmad Shahvaroughi → authored → Man and machine: artificial intelligence and judicial decision making
confidence 100% · Authors:Arthur Dyevre, Ahmad Shahvaroughi
Artificial Intelligence → appliedto → Judicial Decision Making
confidence 95% · The integration of artificial intelligence (AI) technologies into judicial decision-making
Artificial Intelligence → usedin → Criminal Justice Risk Assessment
confidence 90% · Using criminal justice risk assessment as a focal case
Criminal Justice Risk Assessment → contextfor → Pretrial
confidence 85% · particularly in pretrial, sentencing, and parole contexts
Criminal Justice Risk Assessment → contextfor → Parole
confidence 85% · particularly in pretrial, sentencing, and parole contexts
Criminal Justice Risk Assessment → contextfor → Sentencing
confidence 85% · particularly in pretrial, sentencing, and parole contexts
Criminology → contributesto → Judicial Decision Making Research
confidence 80% · Across the fields of computer science, economics, law, criminology... researchers have made significant progress
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Abstract
Abstract:The integration of artificial intelligence (AI) technologies into judicial decision-making - particularly in pretrial, sentencing, and parole contexts - has generated substantial concerns about transparency, reliability, and accountability. At the same time, these developments have brought the limitations of human judgment into sharper relief and underscored the importance of understanding how judges interact with AI-based decision aids. Using criminal justice risk assessment as a focal case, we conduct a synthetic review connecting three intertwined aspects of AI's role in judicial decision-making: the performance and fairness of AI tools, the strengths and biases of human judges, and the nature of AI+human interactions. Across the fields of computer science, economics, law, criminology and psychology, researchers have made significant progress in evaluating the predictive validity of automated risk assessment instruments, documenting biases in judicial decision-making, and, to a more limited extent, examining how judges use algorithmic recommendations. While the existing empirical evidence indicates that the impact of AI decision aid tools on pretrial and sentencing decisions is modest or inexistent, our review also reveals important gaps in the canvassed literatures. Further research is needed to evaluate the performance of AI risk assessment instruments, understand how judges navigate noisy decision making environments and how individual characteristics influence judges' responses to AI advice. We argue that AI vs Human comparisons have the potential to yield new insights into both algorithmic tools and human decision-makers and advocate greater interdisciplinary integration and cross-fertilization in future research.
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- Source: https://arxiv.org/abs/2603.19042v1
- Canonical: https://arxiv.org/abs/2603.19042v1
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Skip to main content arXiv is now an independent nonprofit! Learn more × Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Computer Science > Artificial Intelligence arXiv:2603.19042v1 (cs) [Submitted on 19 Mar 2026 (this version), latest version 14 Apr 2026 (v4)] Title:Man and machine: artificial intelligence and judicial decision making Authors:Arthur Dyevre, Ahmad Shahvaroughi View a PDF of the paper titled Man and machine: artificial intelligence and judicial decision making, by Arthur Dyevre and Ahmad Shahvaroughi View PDF Abstract:The integration of artificial intelligence (AI) technologies into judicial decision-making - particularly in pretrial, sentencing, and parole contexts - has generated substantial concerns about transparency, reliability, and accountability. At the same time, these developments have brought the limitations of human judgment into sharper relief and underscored the importance of understanding how judges interact with AI-based decision aids. Using criminal justice risk assessment as a focal case, we conduct a synthetic review connecting three intertwined aspects of AI's role in judicial decision-making: the performance and fairness of AI tools, the strengths and biases of human judges, and the nature of AI+human interactions. Across the fields of computer science, economics, law, criminology and psychology, researchers have made significant progress in evaluating the predictive validity of automated risk assessment instruments, documenting biases in judicial decision-making, and, to a more limited extent, examining how judges use algorithmic recommendations. While the existing empirical evidence indicates that the impact of AI decision aid tools on pretrial and sentencing decisions is modest or inexistent, our review also reveals important gaps in the canvassed literatures. Further research is needed to evaluate the performance of AI risk assessment instruments, understand how judges navigate noisy decision making environments and how individual characteristics influence judges' responses to AI advice. We argue that AI vs Human comparisons have the potential to yield new insights into both algorithmic tools and human decision-makers and advocate greater interdisciplinary integration and cross-fertilization in future research. Subjects: Artificial Intelligence (cs.AI) Cite as: arXiv:2603.19042 [cs.AI] (or arXiv:2603.19042v1 [cs.AI] for this version) https://doi.org/10.48550/arXiv.2603.19042 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Arthur Dyevre [view email] [v1] Thu, 19 Mar 2026 15:38:50 UTC (461 KB) [v2] Thu, 26 Mar 2026 10:56:37 UTC (473 KB) [v3] Tue, 31 Mar 2026 14:01:05 UTC (518 KB) [v4] Tue, 14 Apr 2026 09:49:54 UTC (509 KB) Full-text links: Access Paper: View a PDF of the paper titled Man and machine: artificial intelligence and judicial decision making, by Arthur Dyevre and Ahmad ShahvaroughiView PDF view license Current browse context: cs.AI < prev | next > new | recent | 2026-03 Change to browse by: cs References & Citations NASA ADSGoogle Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... 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