Location
Grand Wailea, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
8-1-2019 12:00 AM
End Date
11-1-2019 12:00 AM
Description
Data Analytics (DA) has been criticized for contributing to discriminatory decisions in organizations. To date, several studies have investigated reasons for the generation of discriminatory recommendations by DA tools and how to ameliorate the issue. Nonetheless, recent studies by researchers, practitioners, and government agencies show that despite the progress made, the issue has not been eliminated. As a result, it is crucial for DA users to be vigilant about the danger of discriminatory recommendations generated by DA tools. This study represents an effort to provide empirical evidence about whether and to what extent decision makers will readily accept a discriminatory DA recommendation and about the cognition and attitudes that are associated with this behavior. The results obtained from an empirical study confirms that a majority of users readily accepted a discriminatory recommendation and sheds light on what factors influence this acceptance.
Can the Use of Data Analytics Tools Lead to Discriminatory Decisions?
Grand Wailea, Hawaii
Data Analytics (DA) has been criticized for contributing to discriminatory decisions in organizations. To date, several studies have investigated reasons for the generation of discriminatory recommendations by DA tools and how to ameliorate the issue. Nonetheless, recent studies by researchers, practitioners, and government agencies show that despite the progress made, the issue has not been eliminated. As a result, it is crucial for DA users to be vigilant about the danger of discriminatory recommendations generated by DA tools. This study represents an effort to provide empirical evidence about whether and to what extent decision makers will readily accept a discriminatory DA recommendation and about the cognition and attitudes that are associated with this behavior. The results obtained from an empirical study confirms that a majority of users readily accepted a discriminatory recommendation and sheds light on what factors influence this acceptance.
https://aisel.aisnet.org/hicss-52/os/dark_side/5