I think one of the reasons that we have a higher standard for algorithmic decision making is the fact that algorithms are used at scale: For example, for a cla

I think one of the reasons that we have a higher standard for algorithmic decision making is the fact that algorithms are used at scale: For example, for a classification task we usually train an algorithm on labeled data (i.e. good debtor vs. bad debtor). When trained, we apply the algorithms to ALL future decisions on whom to give a credit. This makes algorithms so dangerous as compared to humans, because if 10 out of 1000 bankers are racist and discriminate against certain groups of people we still have 990 that don't. If our algorithm is trained on data that contains racism it will discriminate in every single case if it has the data to do so.