This study examines the role of artificial intelligence (AI) in predictive criminal psychology, focusing on its capabilities to analyze behavioural patterns, predict criminal tendencies, and assist law enforcement in crime prevention. Utilizing machine learning, natural language processing (NLP), and biometric data, AI models can assess risks and identify potential offenders. However, ethical challenges such as algorithmic bias, privacy violations, and profiling persist. This study critically examines AI's effectiveness and limitations in crime prediction, reviews ethical concerns, and discusses regulatory frameworks necessary to ensure accountability and fairness. A data-driven approach evaluates the relationships between crime predictors and outcomes, highlighting implications for future AI integration in criminal justice.
Artificial Intelligence (AI), Predictive Criminal Psychology, Machine Learning, Natural Language Processing (NLP), Biometric Analysis, Crime Prediction, Predictive Policing, Algorithmic Bias, Ethical Considerations, Facial Recognition, Behavioral Analysis, Crime Forecasting, Explainable AI (XAI), Data Privacy, Criminal Profiling, Recidivism Risk Assessment, Hotspot Mapping, Surveillance, Human Rights, AI Regulation