Talent management theoretical foundations: existing approaches analysis

Abstract

Introduction. Artificial intelligence (AI) technology development has introduced new ethical challenges into human resource management (HR). This research is relevant due to the growing use of AI for recruiting, performance evaluation, and employee monitoring, which improves HR process efficiency but also entails risks such as bias, privacy infringements, and the diminishing role of human agency. The study aims at providing a philosophical-ethical analysis of AI usage in HR, identifying and evaluating key ethical issues from the classical ethical theories standpoints.

Materials and methods. The study applies the methods of philosophical analysis and ethical reflection. The methodology is based on the synthesis of theoretical sources on AI ethics and human resource management, and case studies, with their interpretation in ethical categories.

Results and conclusions. The analysis revealed major ethical problems of applying AI in HR management: algorithmic bias leading to unfair decisions; threats to employee privacy under pervasive digital surveillance; erosion of human autonomy and diffused responsibility when algorithms make workplace decisions; and the impact of AI on the meaning of work and human subjectivity. A philosophical evaluation was given for each issue: from a utilitarian perspective, the trade-off between overall benefits and potential harm to minorities has been highlighted; from a deontological perspective, the inviolability of individual rights and dignity even in pursuit of efficiency has been affirmed; from a virtue ethics perspective, the importance of moral character in developers and HR managers using AI has been profoundly emphasized. The study’s novelty lies in its integrative consideration of AI in HR through classical ethical frameworks combined with contemporary ethical standards, which helps systematize knowledge of the moral risks of AI-driven HR technologies and relate them to fundamental ethical principles.

Discussion. The results underscore that successful AI integration in HR requires treating ethical considerations on par with technical efficiency. The practical significance of this work is in formulating principles for responsible AI use: preventing discrimination and bias, ensuring algorithmic transparency and explainability, preserving human oversight (the human-in-the-loop principle) and prioritizing employees’ rights. It is recommended that organizations should adopt ethical guidelines and conduct audits of AI systems; likewise, legislation is evolving in many countries to address these issues. Future research should further develop ethical frameworks for emerging HR technologies and examine AI’s impact on the values of work in a changing society.