Threat of deepfakes to the criminal justice system: a systematic review

BackgroundThis systematic review explores the impact of deepfakes on the criminal justice system. Deepfakes, a sophisticated form of AI-generated synthetic media, have raised concerns due to their potential to compromise the integrity of evidence and judicial processes. The review aims to assess the extent of this threat, guided by a research question: (1) What threats do deepfakes pose to the criminal justice system?MethodsThe review was conducted using databases such as Web of Science, ProQuest, Scopus, and Google Scholar, focusing on publications from 2021 to 2022. Search terms were optimised for sensitivity and specificity, and articles were chosen based on criteria including relevance to deepfake threats and deepfake detection research. The methodology included rigorous screening processes using tools like Zotero and Rayyan.ai, with an emphasis on inter-rater reliability to ensure objective selection of studies.ResultsThe search initially identified 1355 articles, with 1200 articles screened for eligibility after duplicates were removed. For the threat of deepfakes to the criminal justice system, 110 studies were selected for full-text review, and 44 were included in the final analysis. Key findings include identification of primary crime categories linked to deepfakes, such as pornography, fraud, and information manipulation, alongside challenges like trust erosion in institutions and evidence falsification issues.ConclusionsDeepfakes significantly threaten the criminal justice system, highlighting the necessity for advanced detection methods. These findings underscore the importance of continued research and development in deepfake detection technologies and strategies for legal safeguards and broader implications on policy, national security, and democratic processes.