Put Away Your Machine Learning Hammer, Criminality Is Not A Nail

Earlier this month, researchers claimed to have found evidence that criminality can be predicted from facial features. In "Automated Inference on Criminality using Face Images," Xiaolin Wu and Xi Zhang describe how they trained classifiers using various machine learning techniques that were able to distinguish photos of criminals from photos of non-criminals with a high level of accuracy. The result these researchers found can be interpreted differently depending on what assumptions you bring to interpreting it, and what question you're interested in answering. The authors simply assume there's no bias in the criminal justice system, and thus that the criminals they have photos of are a representative sample of the criminals in the wider population (including those who have never been caught or convicted for their crimes). The question they're interested in is whether there's a correlation between facial features and criminality.