Applying XAI to an AI-based system for candidate management to mitigate bias and discrimination in hiring

Hofeditz, L (通讯作者),Univ Duisburg Essen, Forsthausweg 2, D-47057 Duisburg, Germany.
2022-12
Assuming that potential biases of Artificial Intelligence (AI)-based systems can be identified and controlled for (e.g., by providing high quality training data), employing such systems to augment human resource (HR)-decision makers in candidate selection provides an opportunity to make selection processes more objective. However, as the final hiring decision is likely to remain with humans, prevalent human biases could still cause discrimination. This work investigates the impact of an AI-based system's candidate recommendations on humans' hiring decisions and how this relation could be moderated by an Explainable AI (XAI) approach. We used a self-developed platform and conducted an online experiment with 194 participants. Our quantitative and qualitative findings suggest that the recommendations of an AI-based system can reduce discrimination against older and female candidates but appear to cause fewer selections of foreign-race candidates. Contrary to our expectations, the same XAI approach moderated these effects differently depending on the context.
ELECTRONIC MARKETS
卷号:32|期号:4|页码:2207-2233
ISSN:1019-6781|收录类别:SSCI
语种
英语
来源机构
University of Duisburg Essen; University of Paderborn
被引频次(WOS)
1
被引频次(其他)
1
180天使用计数
8
2013以来使用计数
8
EISSN
1422-8890
出版年
2022-12
DOI
10.1007/s12525-022-00600-9
关键词
Explainable AI Hiring Bias Discrimination Ethics
WOS学科分类
Business Management
学科领域
循证管理学 循证经济学