Book Title: Transformative Approaches in Multidisciplinary Research (TAMR)
Chief Editors: Dr. Meenakshi Kujur, and Dr. Hamidun Bunawan
Associate Editors: Mr. Gunjit Singhal, and Dr. Asma Farooque
Co-Editors: Dr. Suresh Kamarapu, and Dr. Souvik Sur
Chapter: 8
DOI: https://doi.org/10.59646/672/8
Author: Dr. S. Jayakani
Abstract
The continuous adoption of Artificial Intelligence (AI) in Human Resource (HR) management has greatly changed in the way organizations recruit, appraise, and manage employees. In this research paper, the author investigates AI ethics in HR and specifically how it affects the levels of trust and engagement of employees in organizations. The research paper will discuss the impact of AI-based HR systems on decision making, including recruiting, performance appraisal, promotion and monitoring employees. Mixed-method approach is used, which entails quantitative values based on organizational HR usage trends with qualitative values based on the analysis of the employee and HR professional perspectives based on existing studies. The results indicate that AI in HR is widely implemented in the various organizations based on the level of technology preparedness, the governance systems, and the level of ethical consciousness. Although AI is more efficient, in some situations, it minimizes bias, and promotes data-driven decision making, it also brings up ethical issues associated with transparency, algorithmic bias, privacy, and accountability. These issues directly affect the level of employee trust and some of the employees see AI systems as unbiased and effective, whereas others see it as a black box and, possibly, unjust. Moreover, the engagement of employees depends on the extent to which they trust AI systems since increased transparency and explainability results in increased acceptance and engagement, and a lack of any transparency decreases morale and commitment to the organization. Strategic/policy-based recommendations, including the creation of ethical AI governance systems, human-AI joint decision-making systems, and enhanced standards of transparency in HR technologies are also discussed in the paper. This work can be used to add to the accumulating literature on responsible AIs adoption in workplaces by emphasizing the ethical implications of AI in HR and offer useful insights to organizations, which wish to find a balance between innovation and employee trust and engagement.
Keywords: Artificial Intelligence, Human Resource Management, AI Ethics, Employee trust, Employee engagement, Algorithmic bias, HR technology, Workplace transparency, Digital HR, Responsible AI.
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