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Duquesne Law Review

Abstract

Expert testimony continues to turn away from human-based skills to embrace machine-based evidence. Technology is used to identify and locate individuals, unlock encrypted devices, and even to evaluate criminal responsibility. Perhaps this is a positive change. The shortcomings of first-generation forensic identification specialties are substantial and include the inscrutability of its subjective comparisons. As such, this newer generation of evidence may well be an improvement. Yet the inscrutability problem adopts many forms. Machine-based evidence relies on hardware, software, algorithms, statistics, and engineering to reach results-ones created and interpreted by humans subject to bias and cognitive error; results the justice system often does not fully appreciate. Taking one example of machine evidence --- neuroimaging --- this Article examines its foundational reliability and complexity, explaining why such evidence is often inscrutable to courts and what might help courts to be better gatekeepers of such evidence.

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