The rapid growth of Artificial Intelligence (AI) in recruitment has transformed traditional hiring methods. This paper explores the design, development, and ethical considerations of an AI Resume Screener, a system that automates resume evaluation using Natural Language Processing (NLP) and Machine Learning (ML). The model efficiently matches resumes to job descriptions while minimizing human bias and improving decision accuracy. The study emphasizes fairness, transparency, and data privacy—three critical pillars for responsible AI adoption in Human Resource Management (HRM). Experimental findings indicate that AI-based screening enhances hiring efficiency by 65% and reduces unconscious bias in shortlisting by 40%. This research concludes that an AI-powered resume screener can significantly improve recruitment quality, fairness. Artificial Intelligence (AI) has revolutionized recruitment by automating the process of resume screening. This paper explores the concept of AI-powered resume screening systems, their architecture, principles, and their role in environmental studies. The study focuses on eliminate bias, and enhance selection processes in organizations and NGOs focused on environmental sustainability. The integration of AI in resume screening also supports reduces human workload, and ensures the selection of candidates with specialized knowledge in environmental fields.
AI in Recruitment, Ethical AI, Context-Aware Evaluation, LLMs, Resume Screening, Fair Hiring, Generative AI, Bias Mitigation.
IRE Journals:
Aafareen Sikandar Shaikh, Pradnya Pradip Sawant, Payal Ananta Pasalkar, Siddhi Hemant Pol, Sakshi Dipak Tanksale; Prof. P. A. Pawar "Smart AI Resume Screener For Environmental Studies" Iconic Research And Engineering Journals Volume 9 Issue 5 2025 Page 2430-2437 https://doi.org/10.64388/IREV9I5-1712464
IEEE:
Aafareen Sikandar Shaikh, Pradnya Pradip Sawant, Payal Ananta Pasalkar, Siddhi Hemant Pol, Sakshi Dipak Tanksale; Prof. P. A. Pawar
"Smart AI Resume Screener For Environmental Studies" Iconic Research And Engineering Journals, 9(5) https://doi.org/10.64388/IREV9I5-1712464