Virtually all data used to predict crimes or recidivism is fraught with human bias, for example. Not sure that we want to reproduce the bias of criminal justice system in any prediction problem involving this type of data.
Read anything written by Solon Barocas: http://solon.barocas.org/
How is recidivism data biased? I'm sure that the information gleaned from parole officers and cops might be biased, but as long as the ML system is trained on whether or not someone actually reverted to committing crimes, it should be able to detect bias on the part of P.O.s and other functionaries and give a more accurate determination as to someone's chances of recidivism.
Which data are you referring to? In most cases, the training data isn't human-generated, and if it is, we usually want to match human behavior as close as possible.