  On the other hand the use of computers can constrain the ability of users to understand or consider the outcomes of their actions. These complex technologies, which are never fully free from errors, increasingly hide the automated processes behind the interface (Van den Hoven 2002). An example that illustrates how computer technologies can limit understanding of the outcomes are the controversial risk assessment tools used by judges in several states in the U.S. for parole decisions and sentencing. In 2016 a civil society organization found, based on an analysis of the risk scores of 7000 defendants produced by one particular algorithm, that the scores poorly reflected the actual recidivism rate and seemed to have a racial bias (Angwin et al. 2016). Regardless of whether its findings were correct, what is particularly relevant here is that the investigation also showed that judges did not have a full understanding of how the probabilities were calculated, because the algorithm was proprietary. The judges were basing their sentencing on the suggestion of an algorithm that they did not fully understand. This is the case for most computer technologies today. Users only see part of the many computations that a computer performs and are for the most part unaware of how it performs them; they usually only have a partial understanding of the assumptions, models and theories on which the information on their computer screen is based. 