Artificial Intelligence (AI) in Forensic Psychology: An Umbrella Review of Potentials and Pitfalls

Abstract

Artificial intelligence (AI) is becoming increasingly embedded within forensic psychological practice, shaping how criminal risk, legal responsibility and public safety are assessed. AI tools are now used in recidivism prediction, behavioural analysis, deception detection and investigative support, high-stakes domains where errors can have profound consequences. Despite this rapid adoption, the existing literature remains fragmented, with most reviews confined to narrow subdomains and offering limited integrated synthesis of AI′s broader role in forensic psychology. Thus, this umbrella review addresses this gap by synthesising findings from 43 reviews obtained from five major databases, namely EBSCOhost ERIC, EBSCOhost PsycInfo, PubMed, Scopus and Web of Science. Across the reviewed literature, our umbrella review suggests that AI is positioned as offering several potential benefits for forensic psychological work, including improved predictive accuracy, real-time threat monitoring, more optimised resource allocation, enhanced analysis of complex behavioural data and more objective decision-making. At the same time, the present review highlights persistent pitfalls that may constrain the reliability and defensibility of current applications. These include the reinforcement of bias and disparities, limited transparency and explainability, over-reliance that may undermine human judgement, data constraints and overfitting, ethical and legal risks and substantial implementation and computational demands that may inhibit real-world application. Overall, this review underscores the need for rigorous safeguards to ensure that AI enhances rather than compromises forensic decision-making.