 Which is the best characterization of the overgeneralization hypotheses?
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." Theories of physiognomy, however, would persist beyond the Renaissance. Physiognomy ultimately stems from what Alexander Todorov, professor of psychology at Princeton University, calls an 'overgeneralisation hypothesis'.
 We are likely to attribute things to people based on people close to us who may look similar
 People are more likely to find others to be friendly based on their photos if they are surrounded by friendly people themselves  Computers are more likely to draw correct conclusions about people if they have larger pools of photos to draw from  We are likely to assume more photos are doctored than the number that actually are  We are likely to attribute things to people based on people close to us who may look similar