Advances in Consumer Research
Issue:6 : 2659-2665
Original Article
AI in Recruitment: Challenges of Transparency, Accountability and Fairness
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1
Associate Professor, Department of MCA, RV Institute of Technology and Management, Bangalore, Karnataka- 560076.
2
Assistant Professor, Department of Commerce, BS Abdur Rahman Crescent institute of science and technology, Vandalur, Chennai-600048.
3
Associate Professor, School of Business and Management,CHRIST University, Nagasandra, Near Tumkur Road, Bangalore, Karnataka - 560073.
4
Associate Professor, School of Commerce, finance and Accountancy, Christ University, Delhi NCR Campus.
5
Assistant Professor-III, Department of Business Management, Amity University, Hyderabad.
6
HOD, Department of Business Administration, St. Thomas College of arts and science, koyambedu, Chennai-600107.
Abstract

Artificial Intelligence (AI) has rapidly transformed recruitment practices by automating candidate sourcing, screening, assessment, and selection. Organizations widely adopt AI tools to enhance efficiency, minimize hiring time, and improve decision-making. However, these technologies also raise profound concerns regarding transparency, accountability, and fairness. The black-box nature of many AI systems, the risk of bias in algorithmic decision-making, and unclear lines of responsibility create ethical and operational challenges that limit trust and acceptance. This article critically examines the challenges associated with AI-driven recruitment, focusing on transparency, accountability, and fairness. It also explores emerging regulatory responses, organizational strategies, and ethical frameworks that can help ensure a responsible and equitable adoption of AI in hiring. Tools such as fairness metrics, bias audits, and inclusive design practices help maintain impartiality. Ensuring fairness not only protects candidates’ rights but also enhances organizational diversity and strengthens employer reputation. Ultimately, fair AI systems support ethical recruitment by promoting equal opportunity for all applicants. The results imply that ethical considerations such as transparency, accountability, and data protection are viewed as universal concerns, cutting across gender lines. This uniformity may also reflect increased access to information, digital exposure, and similar levels of engagement with technology among both genders in the sample. Across all three factors—Transparency, Human Oversight and Privacy & Data Protection—the results consistently show no significant gender-based differences in opinion...

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