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Elsevier have very kindly made this 2019 article free to download for 50 days until 28 December 2019

Davis, J. P., Maigut, A., & Forrest, C. L. D. (2019). The wisdom of the crowd: A case of post- to ante-mortem face matching by police super-recognisers. Forensic Science International. DOI: 10.1016/j.forsciint.2019.109910

This case report describes novel methodology used to identify a 43-year-old post-mortem photo of a drowned male recovered from the River Thames in the 1970s. Compared to police controls (n = 139), Metropolitan Police super-recognisers (n = 25), were more likely to confidently match the post-mortem photo to an ante-mortem photo of a man who was reported missing at about the same time. Effects were enhanced when drawing on the combined wisdom of police super-recogniser crowds. These findings supported additional case evidence allowing the coroner to rule that the deceased male and missing male were likely one and the same person. A description is provided of how similar super-recogniser wisdom of the crowd procedures could be applied to other visual image identification cases when no other method is feasible.

The authors were asked to assess this case when Andreea Maigut was volunteering one day a week with the Super-Recognisers Unit at New Scotland Yard. She also worked part-time for Josh Davis in a team with Charlotte Forrest at the University of Greenwich. The family associated with the case had been referred to the Metropolitan Police River Policing Unit based at Wapping Police Station (instigated as the Marine Police Force n 1798, pre-dating the Met, and possibly the first preventative police force in England).

The authors were blind to most of the case details in advance to ensure that they could not be influenced by any irrelevant facts, and it is hoped the coroner's judgement helped the family with closure. In a way, this was a unique opportunity to trial the Wisdom of the Police Super-Recogniser Crowd in a non-criminal investigation. Further research is required to assess method reliability in different circumstances, perhaps by combining human decisions with those derived from computerised face recognition systems.

Dr Josh P Davis, 9 November 2019, School of Human Sciences, University of Greenwich


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