To expand on your point to further strengthen your original argument, these models are trained on a smaller subset of observables and ideas we consider when we

To expand on your point to further strengthen your original argument, these models are trained on a smaller subset of observables and ideas we consider when we decide policy. Even then, the comparison between a matrix and a human brain is poor. Another issue I have is that we don't know is whether statistical bias exists in the metrics they train on, something they discuss in the paper. We already know for example blacks are arrested and convicted harsher than whites for some of the similar crimes[0]. The paper just says that COMPAS predicts likelihood of violent crime, not whether that means they'll be arrested of crime. Moreover while Table 1 talks about a prediction regarding violent crime, Figure 2 talks about recidivism with regards to all crime, so which is it? It still seems nebulous to me what COMPAS actually is for. I'd have to read it deeper than I have, but not sure how I feel about the paper. [0] http://www.politifact.com/truth-o-meter/statements/2016/feb/26/hillary-clinton/hillary-clinton-says-blacks-more-likely-be-arreste/ http://www.politifact.com/truth-o-meter/statements/2016/feb/...