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Finding truth in evidence: Computational intelligence
M. W. Perlin, "Finding truth in evidence: Computational intelligence", Artificial Intelligence in Court Dispositions of Violent Defendants and Juveniles, National Courts and Sciences Institute, Kansas City, Missouri, 23-Oct-2024.
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Abstract
The interpretation of complex DNA mixtures remains a central challenge in forensic science, where traditional human review methods often produce subjective, biased, and limited results. This presentation demonstrates how computational intelligence, specifically the TrueAllele® system, objectively extracts the full potential of DNA evidence to find the truth in legal contexts.
Using the New York v. John Wakefield case as a focal point, we illustrate how probabilistic genotyping can transform low-level, complex DNA mixtures into clear, interpretable results that withstand scientific scrutiny and legal challenges. TrueAllele objectively considers all genotype possibilities, quantitatively explains peak patterns, and calculates match statistics that show how much more likely a suspect or victim is in the evidence compared to an unrelated person. This method has been validated in over 40 peer-reviewed studies, shown to be accurate, sensitive, specific, and reproducible, and has been accepted in over 44 U.S. court rulings, including appellate and high court precedents.
Through demonstrated casework and validation data, the presentation will highlight how TrueAllele surpasses human interpretation by delivering reliable DNA mixture results that can statistically include or exclude individuals with transparency and scientific rigor. Participants will gain insight into how automated, objective DNA interpretation can advance justice by uncovering the truth in challenging evidence, illustrating a scalable model for integrating computational intelligence into forensic workflows.