Perhaps most notoriously, a few years ago, AI researchers Xiaolin Wu and Xi Zhang claimed to have trained an algorithm to identify criminals based on the shape of their faces, with an accuracy of 89.5 per cent. They didn’t go so far as to endorse some of the ideas about physiognomy and character that circulated in the 19th century, notably from the work of the Italian criminologist Cesare Lombroso: that criminals are underevolved, subhuman beasts, recognisable from their sloping foreheads and hawk-like noses. However, the recent study’s seemingly high-tech attempt to pick out facial features associated with criminality borrows directly from the ‘photographic composite method’ developed by the Victorian jack-of-all-trades Francis Galton – which involved overlaying the faces of multiple people in a certain category to find the features indicative of qualities like health, disease, beauty and criminality.
Algorithms associating appearance and criminality have a dark past. Catherine Stinson /
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