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A comparative analysis of human and AI performance in forensic estimation of physical attributes

Human errors in criminal investigations have previously led to devastating miscarriages of justice. For example, flaws in forensic identification based on physical or photographic evidence are notoriously unreliable. The criminal justice system has, therefore, started to turn to artificial intellige...

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Detalles Bibliográficos
Autores principales: Barrington, Sarah, Farid, Hany
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10036317/
https://www.ncbi.nlm.nih.gov/pubmed/36959267
http://dx.doi.org/10.1038/s41598-023-31821-3
Descripción
Sumario:Human errors in criminal investigations have previously led to devastating miscarriages of justice. For example, flaws in forensic identification based on physical or photographic evidence are notoriously unreliable. The criminal justice system has, therefore, started to turn to artificial intelligence (AI) to improve the reliability and fairness of forensic identification. So as not to repeat history, it is critical to evaluate the appropriateness of deploying these new AI forensic tools. We assess the feasibility of measuring basic physical attributes in a photo using a state-of-the-art AI system, and compare performance with human experts and non-experts. Our results raise concerns as to the use of current AI-based forensic identification.