When algorithms testify: artificial intelligence-driven DNA analysis, evidentiary standards, and criminal justice reform.

Forensic DNA analysis has already influenced criminal justice, and serves as a powerful tool for both conviction and exoneration. Despite its scientific foundations and wide application, DNA evidence is vulnerable to interpretive errors, methodological limitations, and cognitive bias, as demonstrated by numerous wrongful convictions identified through the Innocence Project. Recent artificial intelligence (AI) methods, especially probabilistic genotyping, are used to support the interpretation of complex DNA samples, including mixed, low-template, and degraded profiles. However, the repeated utilization of AI-driven forensic analysis can lead to legal and ethical concerns, including procedural challenges in terms of its usability as direct evidence in the procedure. This article examines the implications of AI-based DNA interpretation for criminal justice, with particular attention to evidentiary reliability, due process, institutional accountability, and emerging policy responses in the US and Europe. It draws on parallels with clinical genomics and documented forensic applications of AI, and argues that AI can enhance forensic accuracy and fairness only if integrated within transparent, validated, and ethically governed frameworks that respect fundamental legal protections.