 What is the biggest effect when criminals are noted as having similar facial features to other wrongdoers?
Some blamed the BBC, some blamed those in Savile's immediate circle, but others blamed a simple error of human judgment. "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. We know that paedophiles, murderers and other violent criminals come in many shapes and sizes. 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. "What facial features influence the average Joe's impulsive and yet consensual judgments on social attributes?" they ask. 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.
 This perpetuates the belief in the area of study that should not be held up
 These sets of criminals are often shown to have similar socioeconomic backgrounds  This occurs when people are making judgements but not computers  This perpetuates the belief in the area of study that should not be held up  These coincidences are held under scrutiny and often disproved