A Study on Fairness and Trust Perceptions in Automated Decision Making
Abstract
Automated decision systems are increasingly used for consequential decision making -- for a variety of reasons. These systems often rely on sophisticated yet opaque models, which do not (or hardly) allow for understanding how or why a given decision was arrived at. This is not only problematic from a legal perspective, but non-transparent systems are also prone to yield undesirable (e.g., unfair) outcomes because their sanity is difficult to assess and calibrate in the first place. In this work, we conduct a study to evaluate different attempts of explaining such systems with respect to their effect on people's perceptions of fairness and trustworthiness towards the underlying mechanisms. A pilot study revealed surprising qualitative insights as well as preliminary significant effects, which will have to be verified, extended and thoroughly discussed in the larger main study.
Cite
@article{arxiv.2103.04757,
title = {A Study on Fairness and Trust Perceptions in Automated Decision Making},
author = {Jakob Schoeffer and Yvette Machowski and Niklas Kuehl},
journal= {arXiv preprint arXiv:2103.04757},
year = {2021}
}
Comments
Joint Proceedings of the ACM IUI 2021 Workshops, April 13--17, 2021, College Station, USA