A Study on Fairness and Trust Perceptions in Automated Decision Making

• DOI: 10.5445/ir/1000130551
• Publication Date: 2021-01-01
• Authors: Schöffer, Jakob; Machowski, Yvette; Kühl, Niklas
• Keywords: FOS: Computer and information sciences; info:eu-repo/classification/ddc/330; Fairness; 330; ddc:330; Economics; Computer Science - Artificial Intelligence; Explanation; Computer Science - Human-Computer Interaction; 02 engineering and technology; Trust; Transparency; Human-Computer Interaction (cs.HC); Machine Learning; Artificial Intelligence (cs.AI); 0202 electrical engineering, electronic engineering, information engineering; Automated Decision Making

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.<br/>Joint Proceedings of the ACM IUI 2021 Workshops, April 13--17, 2021, College Station, USA<br/>