LEVERAGING AI IN HUMAN RESOURCES ANALYTICS: ETHICAL AND SOCIAL SUSTAINABILITY STANDPOINT OF ATS (APPLICANT TRACKING SYSTEM) IN HUMAN RESOURCES OPERATION & RECRUITMENT PROCESS

Abstract

ABSTRACT

This research explores the ethical implications of AI-driven video interview technologies in recruitment, focusing on transparency, bias, inclusivity, and equity. Using thematic analysis of qualitative data from interviews with candidates and recruiters, the study identifies key ethical concerns and examines them through thear lenses of Jeremy Bentham’s utilitarian ethics and UNESCO’s Ethical AI Principles. Findings highlight significant challenges, including the lack of transparency in AI evaluation criteria, systemic biases disadvantaging underrepresented groups, and the impersonal nature of AI interactions. Additionally, governance gaps, such as risks of data misuse and accountability issues, underscore the need for robust safeguards. The study proposes a comprehensive business solution to address these challenges. Recommendations include enhancing transparency through clear communication and feedback mechanisms, mitigating biases with diverse training datasets and regular audits, and adopting hybrid recruitment models that balance AI efficiency with human empathy. Customizing AI systems to accommodate diverse candidate profiles and implementing governance frameworks, such as GDPR, further ensure ethical compliance and inclusivity. By aligning these solutions with utilitarian ethics, which emphasize maximizing societal benefits and minimizing harm, and UNESCO’s principles of accountability, inclusivity, and human agency, this research offers a roadmap for ethical AI deployment in recruitment. It concludes that a balanced approach integrating technical advancements and human oversight is essential for creating recruitment processes that are fair, transparent, and inclusive, ultimately fostering trust and enhancing the candidate experience.