📄 Abstract
AI-based hiring tools, while enhancing recruitment efficiency, introduce critical ethical challenges, including algorithmic bias, lack of transparency ("black box" problem), and data privacy concerns. These systems risk perpetuating discrimination by trained on historical data, often disadvantaging minority groups and undermining diversity. The reliance on automated decisions reduces human oversight and empathy, highlighting the need for ethical frameworks, algorithmic accountability, and human-in-the-loop systems to ensure fairness. Artificial Intelligence (AI) is increasingly used by companies to help with hiring decisions. AI systems can quickly analyze resumes, rank candidates, and even conduct automated interviews. While these tools can save time and reduce costs, they also raise several ethical challenges. One major concern is bias, because AI systems learn from past data that may already contain human discrimination related to gender, race, or age. This can lead to unfair hiring decisions. Another issue is lack of transparency, since many AI systems work like a black box, making it difficult to understand how decisions are made. Privacy is also a concern because AI may collect and analyze large amounts of personal data from applicants.
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📚 How to Cite:
Yogathara D, Mrs. R. Anitha , ETHICAL CHALLENGES OF AI BASED HIRING DECISION , Volume 11 , Issue 3, March 2026, EPRA International Journal of Research & Development (IJRD) ,