Common sense says no, right?
Two Chinese researchers from Shanghai Jiao Tong University, who wrote a paper titled "Automated Inference on Criminality using Face Images.", say differently.
The authors stated, "We are the first to study automated face-induced inference on criminality free of any biases of subjective judgments of human observers. By extensive experiments and vigorous cross validations, we have demonstrated that via supervised machine learning, data-driven face classifiers are able to make reliable inference on criminality."
...they used standard ID photographs (not mugshots) of Chinese males between the ages of 18 and 55. The men did not have facial hair,
("We stress that the criminal face images in Sc are normal ID photos not police mugshots," wrote the researchers.) MIT Technology Review picked up on their methods: "They then used 90 percent of these images to train a convolutional neural network to recognize the difference and then tested the neural net on the remaining 10 percent of the images." Results? They said that the classifiers performed "consistently well" and produced "evidence for the validity of automated face-induced inference on criminality."
MIT Technology Review's discussion of their findings in "Emerging Technology from the arXiv," said that the pair found that "the neural network could correctly identify criminals and noncriminals with an accuracy of 89.5 percent."
The MIT Conclusion
Of course, this work needs to be set on a much stronger footing. It needs to be reproduced with different ages, sexes, ethnicities, and so on. And on much larger data sets." Also, said the report, "All this heralds a new era of anthropometry, criminal or otherwise," and there is room for more research "as machines become more capable."