 What is the purpose of the article?
Some blamed the BBC, some blamed those in Savile's immediate circle, but others blamed a simple error of human judgment. 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. Aristotle's pronouncement that "it is possible to infer character from features" led to a number of works relating to 'Physiognomica', a word derived from physis (nature), nomos (law) and (or) gnomon (judge or interpreter). All of Greek society, it was claimed, could benefit from this skill: it could assist with choosing an employee, a slave or a spouse, while its inherent vagueness made it intriguing to philosophers and useful for scientists who bent the theories to support their own beliefs. Theories of physiognomy, however, would persist beyond the Renaissance. In 1586, Italian scholar Giambattista della Porta published a book, De humana physiognomonia libri IIII, which established him as the 'father of Physiognomy'.
 To explain how physiognomy has evolved over time and affected society in harmful ways
 To explain how physiognomy has evolved over time and affected society in harmful ways  To provide an impartial historical account of physiognomy, a once popular branch of science  To predict how physiognomy could be manipulated to worsen current social inequities  To convince an audience of the benefits of physiognomy as a criminal justice tool