Ethics and discrimination in artificial intelligence-enabled recruitment practices

This study aims to address the research gap on algorithmic discrimination caused by AI-enabled recruitment and explore technical and managerial solutions. The primary research approach used is a literature review. The findings suggest that AI-enabled recruitment has the potential to enhance recruitm...

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Bibliographic Details
Published in:Humanities & social sciences communications Vol. 10; no. 1; pp. 567 - 12
Main Author: Chen, Zhisheng
Format: Journal Article
Language:English
Published: London Springer Nature B.V 01.12.2023
Springer Nature
Subjects:
Algorithms
Artificial intelligence
Bias
Discrimination
Employment
Ethics
Governance
Grounded theory
Hiring
Literature reviews
Personality
Personality traits
Race
Recruitment
Research methodology
Respondents
Transparency
ISSN:2662-9992, 2662-9992
Online Access:Get full text
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Summary:This study aims to address the research gap on algorithmic discrimination caused by AI-enabled recruitment and explore technical and managerial solutions. The primary research approach used is a literature review. The findings suggest that AI-enabled recruitment has the potential to enhance recruitment quality, increase efficiency, and reduce transactional work. However, algorithmic bias results in discriminatory hiring practices based on gender, race, color, and personality traits. The study indicates that algorithmic bias stems from limited raw data sets and biased algorithm designers. To mitigate this issue, it is recommended to implement technical measures, such as unbiased dataset frameworks and improved algorithmic transparency, as well as management measures like internal corporate ethical governance and external oversight. Employing Grounded Theory, the study conducted survey analysis to collect firsthand data on respondents’ experiences and perceptions of AI-driven recruitment applications and discrimination.
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ISSN:2662-9992
2662-9992
DOI:10.1057/s41599-023-02079-x