 Which is the least likely thing computers could pick up on from a photo?
"He literally couldn't look more like a paedophile," read one post – one of many to state a supposedly incontrovertible truth: that Savile's criminal tendencies could have been detected from the shape of his features, his eyes, his hair. If we knew nothing about their criminal history, some of their photos might even appear attractive. But the idea that someone's features betray their character is something rooted deep within us; it's the reason why certain photos perform well on dating apps, or why trustworthy-looking politicians might rack up votes. A recent paper, published by Xiaolin Wu and Xi Zhang of Shanghai's Jiao Tong University, claims to be the first to use machine learning and neural networks to attempt a fully automated inference of criminality from facial images, removing prejudice from the equation and testing the validity of our gut feelings. Through a study of 1,856 images ("controlled for race, gender, age and facial expression") they claim to have established the validity of "automated, face-induced inference on criminality, despite the historical controversy surrounding this line of enquiry." In other words, they believe that they've found a relationship between looking like a criminal and actually being one. The theories in della Porta's book were supported by dozens of detailed illustrations which, by comparing human faces to those of animals, suggested that they must surely share similar character traits. Many studies have been done into our psychological response to faces, and it's clear that a so-called halo effect will inevitably work its magic.
 An underlying capability of committing crime
 The impact of socioeconomic status on a person's character  An underlying capability of committing crime  The effect of wealth on someone's life  How social a person is likely to be