From Bias to Brilliance: The Impact of Artificial Intelligence Usage on Recruitment Biases in China
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F24%3A50021677" target="_blank" >RIV/62690094:18450/24:50021677 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/10634779" target="_blank" >https://ieeexplore.ieee.org/document/10634779</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TEM.2024.3442618" target="_blank" >10.1109/TEM.2024.3442618</a>
Alternative languages
Result language
angličtina
Original language name
From Bias to Brilliance: The Impact of Artificial Intelligence Usage on Recruitment Biases in China
Original language description
In the rapidly evolving landscape of human resources and talent acquisition, the impact of the usage of artificial intelligence (hereafter, AI) on recruitment biases has emerged as a pivotal and transformative subject of study. Therefore, this study aims to critically evaluate the impact of AI usage on recruitment biases, particularly in the context of China. The data were gathered through a survey of 423 respondents working in the manufacturing sector. We use a cross-sectional dataset and various diagnostics (i.e., reliability and collinearity tests). The empirical findings using multivariate regression techniques suggested that Al usage is reshaping the recruitment process by offering innovative solutions to tackle biases that have pervaded the hiring process for years. However, human involvement is indispensable in the recruitment process, alongside the use of AI. Although the use of AI can efficiently handle tasks such as resume screening and data analysis, human judgment brings essential qualities to the hiring process. Human recruiters possess the ability to assess a candidate's soft skills, cultural fit, and emotional intelligence, as these qualities are challenging for AI to comprehend. The policy implications of the study recommend that by combining the strengths of AI efficiency with human insight, organizations can create a recruitment process that is not only objective and efficient but also considerate, ethical, and aligned with the values and goals of the company.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
50204 - Business and management
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
ISSN
0018-9391
e-ISSN
1558-0040
Volume of the periodical
71
Issue of the periodical within the volume
August
Country of publishing house
US - UNITED STATES
Number of pages
13
Pages from-to
14155-14167
UT code for WoS article
001300990700006
EID of the result in the Scopus database
2-s2.0-85201305895