What is it about?
Big Data in Recruitment: Ethical Challenges and Privacy Concerns
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Why is it important?
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. Study Design: The research employs a mixed-methods design, integrating qualitative interviews with HR professionals and quantitative data analysis to assess the implications of big data utilization in recruitment. Place and Duration of Study: The study was conducted across various organizations, focusing on their recruitment practices, over six months. Methodology: 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. 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 unauthorized access. Conclusion: The study concludes that while big data enhances recruitment efficiency, it simultaneously raises critical ethical challenges that must be addressed. Organizations 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.
Perspectives
This study is significant as it addresses one of the most pressing ethical concerns in modern human resource management, the responsible use of big data in recruitment. As organizations increasingly adopt data-driven and algorithmic tools to streamline hiring, the risk of unintended bias, privacy violations, and unfair treatment of candidates continues to grow. By systematically examining these challenges, this research provides critical insights into how technology, ethics, and human judgment intersect in contemporary recruitment practices. The mixed-methods approach, combining qualitative insights from HR professionals with quantitative analysis of recruitment algorithms, strengthens the study’s contribution by providing both empirical evidence and practical perspectives. The findings not only reveal the prevalence of algorithmic bias and inadequate data safeguards but also emphasize the need for fairness-aware frameworks that promote transparency, accountability, and inclusivity. Ultimately, this research contributes to academic, professional, and policy discussions on ethical AI and data governance in human resource management. It equips HR practitioners, data scientists, and organizational leaders with actionable strategies to mitigate bias, protect candidate privacy, and uphold ethical integrity in digital recruitment systems, ensuring that efficiency and fairness evolve hand in hand.
Kevwe Onome -Irikefe
Read the Original
This page is a summary of: Big Data in Recruitment: Ethical Challenges and Privacy Concerns, Journal of Advances in Mathematics and Computer Science, April 2025, Sciencedomain International,
DOI: 10.9734/jamcs/2025/v40i52000.
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