Artificial Intelligence, Neuroprediction, and Criminal Liability: The Emergence of Algorithmic Culpability in Contemporary Criminal Justice

This article examines the emerging role of artificial intelligence, predictive analytics, and neuroscientific forecasting in reshaping contemporary understandings of criminal liability. As criminal justice systems increasingly integrate algorithmic risk assessment, behavioral prediction models, and brain-based forecasting tools, traditional doctrines of mens rea and individualized culpability face unprecedented epistemic challenges. The study argues that predictive systems do not replace normative legal judgment but create a new evidentiary layer that influences attribution of dangerousness, intent inference, sentencing calibration, and preventive detention. A doctrinal framework of algorithmic culpability is proposed to reconcile predictive technologies with due process, evidentiary reliability, and constitutional safeguards.