question:  Which of these is most true about physiognomy?
context: 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. Physiognomy, the 'science' of judging people by their appearance, was first theorised by the ancient Greeks in around the 5th century BC. 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'. Lavater's work was criticised for being ridden with bias (black faces rarely emerged well from his analyses) but he was right in one respect: "Whether they are or are not sensible of it," he wrote, "all men are daily influenced by physiognomy."
output:  People have been interested in this area for centuries but only recently applied technology to it
options:  If this were not an area of study, people would not be drawing false conclusions about people on trial  It has helped to put a number of important criminals behind bars  It is a brand new area of study that focuses on the application of machine learning to see how computers can help  People have been interested in this area for centuries but only recently applied technology to it