A new method of assessing bias in discriminatory decision-making

An extensive amount of literature has been written to better understand the formulation and processes behind both decision-making and discrimination. Over the last few decades and charged by research on dual process models and cognitive biases, these two distinct areas of research have become intertwined. Currently, the culmination of this synthesis has been the study of implicit bias and the development of the Implicit Association Test (IAT). However, there is heavy disagreement amongst researchers regarding the validity and utility of the IAT, with more recent work displaying a number of deficits that may preclude its use. In response to these claims, this study sought to test a new method to better assess biased behavior in the form of racial and gender discrimination. The Bias in Appraisal/Selection (BIAS) task was developed in order to accomplish this goal. The BIAS task appears to show some promise; results broadly identified discriminatory appraisal and selection across primarily moderate and low qualified candidates, as well as the composite scores altogether. Interestingly, these results showed that preference existed for Black and female candidates, opposite of what was expected. Implications for these and other findings are discussed. Overall, the advances in understanding the interplay between decision-making processes and discriminatory behavior have contributed to exciting but lacking developments. While more research is certainly needed, the BIAS task shows some promise as a theoretically-sound alternative approach to assessing discriminatory behavior.

Grantor dc:publisher

Wichita State University

Year dc:date.issued

2024

Author dc:creator

• Ballout, Mouhamad Houssein

Advisor dc:contributor.advisor

• Clark, C. Brendan

Statement dc:rights

• © Copyright 2024 by Mouhamad Houssein Naim Ballout All Rights Reserved

Language dc:language.iso

en_US

Dc Identifier Other

d24022

OAI record oai:identifier

https://soar.wichita.edu/oai/request?verb=GetRecord&metadataPrefix=dim&identifier=oai%3Anull%3A10057%2F28205