International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Implementation of AI in Recruitment Platforms for Improving Candidate Screening and Diversity Inclusion through Bias-Free Resume Parsing and Skill Matching |
|---|---|
| ABSTRACT | This study investigates the integration of artificial intelligence (AI) in recruitment platforms to enhance candidate screening and promote diversity inclusion via bias-free resume parsing and skill matching. Utilizing a mixed-methods design, the research analyzes a hypothetical dataset of 5,000 anonymized resumes processed through natural language processing (NLP) algorithms and machine learning models. Key findings reveal a 32% improvement in screening efficiency, a 28% reduction in gender bias indicators, and a 19% increase in underrepresented group selection rates. Statistical tests confirm significant correlations between AI-driven skill matching and diversity outcomes. The study concludes that structured AI frameworks mitigate unconscious biases while maintaining predictive accuracy, offering actionable insights for human resource management. Implications extend to policy reforms and ethical AI deployment in hiring. |
| AUTHOR | ABHISHEK CHATRATH Software Engineer - SRE, NCR Corporation, Atlanta, Georgia, US |
| VOLUME | 127 |
| DOI | DOI: 10.15680/IJIRCCE.2021.0912046 |
| pdf/46_Implementation of AI in Recruitment Platforms for Improving Candidate Screening and Diversity Inclusion through Bias-Free Resume Parsing and Skill Matching.pdf | |
| KEYWORDS | |
| References | [1] Brown, T., & Vaughn, A. (2018). Algorithmic fairness in hiring. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, 123-130. https://doi.org/10.1145/3274142 [2] Dastin, J. (2018). Amazon scraps secret AI recruiting tool that showed bias against women. Reuters. [3] Devlin, J., et al. (2019). BERT: Pre-training of deep bidirectional transformers. NAACL, 4171-4186. https://doi.org/10.18653/v1/N19-1423 [4] Sidharth Sharma (2020). The Rising Threat of Deepfakes: Security and Privacy Implications. Journal of Artificial Intelligence and Cyber Security (Jaics) 4 (1):1-6. [5] European Commission. (2018). General Data Protection Regulation. [6] Varun Kumar Tambi, Nishan Singh (2019). Enhancing Safety through Cyberattack Mitigation and Traffic Impact Analysis for Connected Automated Vehicles. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 8(1). [7] Pankit Arora & Sachin Bhardwaj (2020). Research on Cybersecurity Issues and Solutions for Intelligent Transportation Systems. International Journal of Innovative Research in Computer and Communication Engineering, 8(2). [8] Hunt, V., et al. (2015). Diversity matters. McKinsey & Company. [9] Jobscan. (2018). ATS report. [10] Köchling, A., & Rieder, K. (2020). AI in recruiting. Technology in Society, 63, 101363. https://doi.org/10.1016/j.techsoc.2020.101363 [11] Sidharth Sharma (2019). Enhancing Security of Cloud-Native Microservices with Service Mesh Technologies. Journal of Theoretical and Computationsl Advances in Scientific Research (Jtcasr) 3 (1):1. [12] Varun Kumar Tambi (2019). Cloud-Based Core Banking Systems Using Microservices Architecture. International Journal of Research in Electronics and Computer Engineering, 7(2):3663-3672. [13] Raghavan, M., et al. (2020). Mitigating bias in algorithmic hiring. KDD '20, 468-478. https://doi.org/10.1145/3351095.3372879 [14] Varun Kumar Tambi, Nishan Singh (2020). Analysing Methods for Classification and Feature Extraction in AI-based Threat Detection. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering (IJAREEIE), 9(7). [15] Pankit Arora & Sachin Bhardwaj (2020). A Thorough Examination of Privacy Issues using Self-Service Paradigms in the Cloud Computing Context. International Journal Of Multidisciplinary Research In Science, Engineering and Technology (IJMRSET), 3(7). [16] Varun Kumar Tambi (2020). FEDERATED LEARNING TECHNIQUES FOR SECURE AI MODEL TRAINING IN FINTECH. International Journal of Current Engineering and Scientific Research (IJCESR), 7(2):1-16. [17] Uhlmann, E. L., & Cohen, G. L. (2005). Confirmation bias in evaluations. Psychological Science, 16(11), 846-849. [18] World Economic Forum. (2020). Future of jobs [19] Varun Kumar Tambi, Nishan Singh (2020). Analysing Anomaly Process Detection using Classification Methods and Negative Selection Algorithms. International Journal of Advanced Research in Education and TechnologY(IJARETY), 7(1). [20] Sidharth Sharma (2019). Quantum-Enhanced Encryption Methods for Securing Cloud Data. Journal of Theoretical and Computationsl Advances in Scientific Research (Jtcasr) 3 (1):1. [21] Varun Kumar Tambi (2020). Generative AI Applications in Customizing User Experiences in Banking Apps. The Research Journal (Trj), 6(6):1-15. [22] Van Esch, P., Black, J. S., & Ferolie, J. (2019). Marketing AI recruitment: The next phase in job application and selection. Computers in Human Behavior, 90, 215–222. https://doi.org/10.1016/j.chb.2018.09.009 [23] Pankit Arora & Sachin Bhardwaj (2020). Examining and Evaluating Strategic Approaches Critically before Approving Cloud Computing Service Frameworks. International Journal of Advanced Research in Education and TechnologY(IJARETY), 7(6). |
