The New Actor: Artificial Intelligence in Criminology and Criminal Justice

This paper examines the emerging role of artificial intelligence (AI) as a unique “new actor” in criminology and criminal justice, challenging traditional frameworks that focus solely on perpetrators, victims, and the criminal justice system. Through a targeted literature synthesis drawing on source...

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Bibliographic Details
Main Author: Tong, Mingxi (Author)
Format: Electronic Article
Language:English
Published: 2025
In: Criminology, criminal justice, law & society
Year: 2025, Volume: 26, Issue: 2, Pages: 12-22
Online Access: Volltext (kostenfrei)
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Keywords:
Criminal Justice
Criminology
AI safety
AI misalignment
LLMs
AI-enabled crimes
AI-target attacks
AI-facilitated crimes
Description
Summary:This paper examines the emerging role of artificial intelligence (AI) as a unique “new actor” in criminology and criminal justice, challenging traditional frameworks that focus solely on perpetrators, victims, and the criminal justice system. Through a targeted literature synthesis drawing on sources from 2020-2024, the research analyzes AI’s multifaceted presence across the criminal landscape: as a sophisticated tool that enhances criminal capabilities, as a vulnerable target of exploitation, and, potentially, as an autonomous agent capable of independent criminal behavior. The methodology employs a purposive selective sampling selection approach, integrating diverse scholarly sources to examine AI-enabled criminal behavior, AI applications in criminal justice systems, and AI moral alignment frameworks. The findings reveal significant concerns about AI’s impact on criminal justice, especially the emergence of new criminal methodologies, and the philosophical and legal challenges of attributing criminal responsibility to AI systems. The research concludes that while AI-enabled crimes currently operate within existing criminological frameworks, the rapid evolution of AI capabilities necessitates proactive adaptation of theoretical models and investigative approaches, emphasizing prevention, detection, and system resilience over purely punitive measures.
ISSN:2332-886X
DOI:10.54555/CCJLS.13020.146572