Uniting Machine Intelligence, Brain and Behavioural Sciences to Assist Criminal Justice
Oliver Y. Ch\'en

TL;DR
This paper explores how machine intelligence, brain, and behavioral sciences can support criminal justice through predictive models, behavioral analysis, and brain decoding, highlighting current capabilities, limitations, and ethical concerns.
Contribution
It provides a comprehensive overview of recent advances and challenges in applying brain and behavior data for legal prediction and decision-making, emphasizing ethical and practical issues.
Findings
Brain and behavior data can support legal investigations and predictions.
Machine learning models are used to predict recidivism and human actions.
Current methods are promising but limited and require regulation.
Abstract
I discuss here three important roles where machine intelligence, brain and behaviour studies together may facilitate criminal law. First, predictive modelling using brain and behaviour data may support legal investigations by predicting categorical, continuous, and longitudinal legal outcomes of interests related to brain injury and mental illnesses. Second, psychological, psychiatric, and behavioural studies supported by machine learning algorithms may help predict human behaviour and actions, such as lies, biases, and visits to crime scenes. Third, machine learning models have been used to predict recidivism using clinical and criminal data whereas brain decoding is beginning to uncover one's thoughts and intentions based on brain imaging data. Having dispensed with achievements and promises, I examine concerns regarding the accuracy, reliability, and reproducibility of the brain- and…
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Taxonomy
TopicsNeuroethics, Human Enhancement, Biomedical Innovations · Deception detection and forensic psychology · Ethics and Social Impacts of AI
