Global Journal of Human Resource Management (GJHRM)

Dehumanization

The Role of Artificial Intelligence in Human Resource Management in Ritman University, Ikot Ekpene, Akwa Ibom State (Published)

This study examined the role of Artificial Intelligence in Human Resource Management in Ritman University, Ikot Ekpene, Akwa Ibom State, with specific focus on the impact of dehumanization and discriminatory hiring practices on HRM outcomes. The rapid integration of AI technologies into HR functions has promised increased efficiency and data-driven decision-making; however, concerns have emerged regarding the potential loss of human connection and the perpetuation of algorithmic biases. Using the Technology Acceptance Model (TAM) as the theoretical framework, the study employed a cross-sectional survey design with a sample size of 98 respondents drawn from a population of 130 staff members. Data were collected using a structured questionnaire and analyzed using regression analysis via SPSS. The findings revealed that dehumanization has a negative and significant impact on human resource management (R² = 32.6%, Beta = -0.571, p < 0.05), indicating that AI-driven automation reduces empathy and personal connection in HR processes. Furthermore, discriminatory hiring practices were found to have a stronger negative and significant impact on HRM (R² = 70.1%, Beta = -0.837, p < 0.05), suggesting that biases embedded in AI algorithms undermine fairness, diversity, and inclusiveness in recruitment decisions. The study concludes that while AI offers operational benefits, its uncritical adoption in university HRM poses substantial risks to employee well-being and institutional equity. Recommendations include implementing hybrid AI-human HR models, establishing ethical oversight committees, conducting regular algorithmic audits, and investing in transparency and employee training to ensure responsible AI integration.

Keywords: Artificial Intelligence, Dehumanization, Human Resource Management, discriminatory hiring practices, technology acceptance model, university HRM

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