2017/138 - What Can I Do Now? Guiding Users in an World of Automated Decisions
More and more processes governing our lives use in some part an automatic decision step, where – based on a feature vector derived from an applicant -- an algorithm has the decision power over the final outcome. Here we present a simple idea which gives some of the power back to the applicant by providing her with alternatives which would make the decision algorithm decide differently. It is based on a formalization reminiscent of methods used for active learning and adversarial learning. This has been implemented for the specific case of decision forests (ensemble methods based on decision trees), mapping the problem to an iterative version of enumerating k-cliques.