Training Computers to Find Future Criminals
I could not disagree more with these comments. Psychologists are just now starting to study the phenomenon of &quot;algorithm aversion&quot;, where people irrationally trust human judgement far more than algorithms. Even after watching an algorithm do far better in many examples.<p>The reality is humans are far worse. We are biased by all sorts of things. Unattractive people were found to get twice as long sentences as attractive ones. Judges were found to give much harsher sentences right before lunch time, when they were hungry. Doing interviews was found to decrease the performance of human judges, in domains like hiring and determining parolle. As opposed to just looking at the facts.<p>Even very simple statistical algorithms far outperform humans in almost every domain. As early as 1928, a simple statistical rule predicted recidivism better than prison psychologists. They predict the success of college students, job applicants, outcomes of medical treatment, etc, far better than human experts. Human experts never even beat the most basic statistical baseline.<p>You should never ever trust human judges. They are neither fair nor accurate. In such an important domain as this, where better predictions reduce the time people spend in prison and crime, there is no excuse not to use them. Anything that gets low risk people out of prison is good.<p>I believe that any rules that apply to algorithms should apply to humans too. We are algorithms too after all. If algorithms have to be blind to race and gender, so should human judges. If economic information is bad to use, humans should be blind to it also. If we have a right to see why an algorithm made a decision the way it did, we should be able to inspect human brains to. Perhaps put judges and parolle officers in an MRI.