Automated Inference on Criminality Using Face Images
I thought this was a joke when I read the abstract, but it appears to be a genuine paper.<p>This paragraph in particular is one of the worst examples I&#x27;ve ever seen of researchers NOT UNDERSTANDING WHAT THEY ARE DOING:<p><i>Unlike a human examiner&#x2F;judge, a computer vision algorithm or classifier has absolutely no subjective baggages, having no emotions, no biases whatsoever due to past experience,  race,  religion,  political doctrine,  gender,  age,  etc., no  mental  fatigue,  no  preconditioning  of  a  bad  sleep  or meal.   The  automated  inference  on  criminality  eliminates the variable of meta-accuracy (the competence of the human  judge&#x2F;examiner)  all  together.</i><p>Please, read <i>Weapons of Math Destruction</i> and understand how excellent machine learning is at discovering and exploiting the biases in datasets.<p>Edit, no, sorry, it gets worse:<p><i>the  upper lip curvature is on average 23.4% larger for criminals than for  non-criminals.</i><p><i>the  distance d between two eye inner corners for criminals is slightly shorter (5.6%) than for non-criminals</i>