Background: The advent of big data in recruitment processes
has introduced more efficient, quicker, and scalable enhanced decision-making.
Big data technologies enable recruiters to analyse vast amounts of candidate
information, ostensibly improving the precision with which suitable candidates
are identified. However, this technological advance also presents significant
ethical challenges.
Aims: This study aims to explore the ethical challenges and
privacy concerns associated with the use of big data in recruitment processes,
focusing on algorithmic bias, data privacy, and fairness in hiring practices.
Methodology: The research employs a mixed-methods design,
integrating qualitative interviews with HR professionals and quantitative data
analysis to assess the implications of big data utilisation in recruitment. The
study was conducted across various organisations, focusing on their recruitment
practices, over six months. Qualitative interviews were conducted with HR
professionals to gather insights on real-world experiences related to ethical
challenges in recruitment. Additionally, a quantitative analysis of recruitment
algorithms was performed to identify prevalent biases and their impact on
hiring decisions, using statistical evidence to highlight significant findings.
By triangulating these methods, the research robustly examined how big data
applications alter recruitment landscapes, identifying ethical challenges and
laying a foundation for potential solutions.
Results: The findings reveal that algorithmic bias is a
profound issue in recruitment, with 62% of surveyed HR professionals
acknowledging its influence on hiring decisions. Moreover, significant concerns
regarding data privacy emerged, with 75% of respondents indicating that
handling sensitive candidate information lacks adequate safeguards, increasing
the risk of unauthorised access. Addressing ethical concerns in big data
recruitment necessitates the collaboration of multiple stakeholders, including
HR professionals, data scientists, and ethicists. Integrating fairness-aware
algorithms is a pivotal strategy, as they aim to rectify biases at different
stages of data processing, ensuring equitable decision-making. By encouraging
collaboration and implementing comprehensive strategies, organisations can
mitigate the ethical challenges associated with using big data in recruitment,
ultimately fostering a more inclusive and fair hiring environment.
Conclusion: The study concludes that while big data enhances
recruitment efficiency, it simultaneously raises critical ethical challenges
that must be addressed. Organisations need to implement robust frameworks to
ensure fairness and transparency, thereby safeguarding candidates' privacy and
fostering equitable hiring practices. These insights provide crucial guidance
for HR professionals seeking to navigate the complexities of big data in
recruitment.
Author(s) Details
Kevwe Onome-Irikefe
University of Rochester, United States.
Please see the book here:- https://doi.org/10.9734/bpi/mcsru/v6/5930
