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Artificial intelligence in forensic genetics: applications and ethical challenges

Ranran Zhang · Journal of Translational Genetics and Genomics · 2025

Artificial intelligence (AI) is transforming forensic genetics through groundbreaking applications in (1) population structure analysis and biogeographical ancestry inference; (2) microbial detection and body fluid identification; (3) allele recognition and mixture interpretation; (4) age inference and phenotype prediction, (5) kinship analysis; and (6) other emerging domains, such as bloodstain deposition time and transcriptomic analysis. While promising efficiency and enhanced accuracy, its integration also raises ethical, legal, and social concerns. This opinion piece critically explores both the promise and perils of AI in forensic genetics, calling for urgent action to (1) build secure and trustworthy AI systems; (2) develop agile and effective regulatory frameworks; (3) uphold ethical integrity and human-centered design; and (4) foster global collaboration to meet cross-border challenges. Together, these principles are essential to ensuring that AI’s integration into forensic science advances both technological progress and the pursuit of justice.

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