Abstract
Data Analytics (DA) has been blamed for contributing to discriminatory managerial decisions in organizations. To date, most studies have focused on the technical antecedents of such discriminations. As a result, little is known about how to ameliorate the problem by focusing on the human aspects of decision making when using DA in organizational settings. This study represents an effort to address this gap. Drawing on the cognitive elaboration model of ethical decision-making, construal level theory, and the literature on moral intensity, this study investigates how the availability and the design of demographic transparency (a form of decisional guidance) can lower DA users’ likelihood of agreement with discriminatory recommendations of DA tools. In addition, this study examines the role of user’s mindfulness and organizational ethical culture on this process. This paper outlines an experimental methodology to empirically validate the proposed model and hypotheses and delineates potential contributions to theory and practice.
Recommended Citation
Ebrahimi, Sepideh and Hassanein, Khaled, "Demographic Transparency to Combat Data Analytics Discriminatory Recommendations" (2017). SIGHCI 2017 Proceedings. 5.
https://aisel.aisnet.org/sighci2017/5