AIMC Topic: Criminals

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The Impact of Biometric Surveillance on Reducing Violent Crime: Strategies for Apprehending Criminals While Protecting the Innocent.

Sensors (Basel, Switzerland)
In the rapidly evolving landscape of biometric technologies, integrating artificial intelligence (AI) and predictive analytics offers promising opportunities and significant challenges for law enforcement and violence prevention. This paper examines ...

Generative AI and criminology: A threat or a promise? Exploring the potential and pitfalls in the identification of Techniques of Neutralization (ToN).

PloS one
Generative artificial intelligence (AI) such as GPT-4 refers to systems able to understand and generate new coherent and relevant text by learning from existing data sets. The great opportunities that GPT-4 offers are accompanied by great risks. Inde...

Judges versus artificial intelligence in juror decision-making in criminal trials: Evidence from two pre-registered experiments.

PloS one
BACKGROUND: Artificial intelligence (AI) is anticipated to play a significant role in criminal trials involving citizen jurors. Prior studies have suggested that AI is not widely preferred in ethical decision-making contexts, but little research has ...

Predicting criminal offence in adolescents who exhibit antisocial behaviour: a machine learning study using data from a large randomised controlled trial of multisystemic therapy.

European child & adolescent psychiatry
INTRODUCTION: Accurate prediction of short-term offending in young people exhibiting antisocial behaviour could support targeted interventions. Here we develop a set of machine learning (ML) models that predict offending status with good accuracy; fu...

Interpretable algorithmic forensics.

Proceedings of the National Academy of Sciences of the United States of America
One of the most troubling trends in criminal investigations is the growing use of "black box" technology, in which law enforcement rely on artificial intelligence (AI) models or algorithms that are either too complex for people to understand or they ...

Differentiating Between Sexual Offending and Violent Non-sexual Offending in Men With Schizophrenia Spectrum Disorders Using Machine Learning.

Sexual abuse : a journal of research and treatment
Forensic psychiatric populations commonly contain a subset of persons with schizophrenia spectrum disorders (SSD) who have committed sex offenses. A comprehensive delineation of the features that distinguish persons with SSD who have committed sex of...

Identifying multilevel predictors of trajectories of psychopathology and resilience among juvenile offenders: A machine learning approach.

Development and psychopathology
Mental ill health is more common among juvenile offenders relative to adolescents in general. Little is known about individual differences in their long-term psychological adaptation and its predictors from multiple aspects of their life. This study ...

Key Information Extraction of Food Environmental Safety Criminal Judgment Documents Based on Deep Learning.

Journal of environmental and public health
Food has an impact on everyone's daily life, the long-term stability of the nation, human survival and development, people's lives and health, and the steady advancement of society. A food safety criminal judgment is a legal document used to record t...

Exploring Characteristics of Homicide Offenders With Schizophrenia Spectrum Disorders Via Machine Learning.

International journal of offender therapy and comparative criminology
The link between schizophrenia and homicide has long been the subject of research with significant impact on mental health policy, clinical practice, and public perception of people with psychiatric disorders. The present study investigates factors c...