How forensic video analysis could have prevented hundreds of wrongful convictions
Dr. Karen Foster
Ph.D. Criminology, University of Michigan
Robert Delgado
J.D., Wrongful Conviction Litigation
Dr. Anil Gupta
Ph.D. Statistics, Data Science Lead, National Registry of Exonerations
Since the advent of DNA exoneration in the late 1980s, the criminal justice system has acknowledged that wrongful convictions are not rare anomalies but systemic failures. This research report examines a lesser-studied dimension of this crisis: the role that video evidence — or the failure to properly analyze it — plays in wrongful convictions and subsequent exonerations.
Drawing on data from the National Registry of Exonerations and original case file analysis of 340 exonerations where video evidence was available, this report quantifies the extent to which inadequate video analysis contributed to wrongful convictions. We find that in a significant percentage of these cases, exculpatory video evidence existed but was either not reviewed, improperly analyzed, or not disclosed to the defense — failures that modern forensic video analysis tools could have prevented.
The report presents a predictive model for identifying cases where video evidence reanalysis is most likely to reveal wrongful convictions, providing a data-driven framework for innocence organizations, public defenders, and policy advocates working to prevent and remedy miscarriages of justice.
A comprehensive analysis of resource disparity in criminal justice forensic technology
Ensuring attorney-client privilege through physically isolated analysis environments
A comprehensive methodology for systematic body-worn camera evidence review
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