10.07.2026; Кропивницький, Україна: X Міжнародна наукова конференція «Міжгалузеві диспути: динаміка та розвиток сучасних наукових досліджень»
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THE USE OF ARTIFICIAL INTELLIGENCE IN HUMAN RESOURCE MANAGEMENT: AN OVERVIEW OF ADVANTAGES, RISKS AND CHALLENGES

Mykola Shabanov
National Technical University "Kharkiv Polytechnic Institute"
Oleksandr Shmatko
Technical University “Metinvest Polytechnic” LLC
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Опубліковано 10.07.2026

Як цитувати

Shabanov, M., & Shmatko, O. (2026). THE USE OF ARTIFICIAL INTELLIGENCE IN HUMAN RESOURCE MANAGEMENT: AN OVERVIEW OF ADVANTAGES, RISKS AND CHALLENGES. Матеріали конференцій МЦНД, (10.07.2026; Кропивницький, Україна), 162–169. вилучено із https://archives.mcnd.org.ua/index.php/conference-proceeding/article/view/1746

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Анотація

The ongoing digital transformation of modern organizations is fundamentally redefining traditional paradigms of human resource management (HRM),. Artificial intelligence (AI), encompassing machine learning (ML), natural language processing (NLP), and computer vision (CV), is increasingly embedded across core HR functions, including recruitment, candidate evaluation, performance appraisal, and decision support systems,. The integration of these technologies enables large-scale data processing, enhances operational efficiency, and improves the consistency and objectivity of managerial decisions.

Посилання

  1. Bogen, M., & Rieke, A. (2018). Help wanted: An examination of hiring algorithms, equity, and bias. Upturn. https://www.upturn.org/reports/2018/help-wanted
  2. Cappelli, P., & Tavis, A. (2018). HR goes agile. Harvard Business Review, 96(2), 46–52.
  3. Davenport, T., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108–116.
  4. European Commission. (2019). Ethics guidelines for trustworthy AI. https://digital-strategy.ec.europa.eu/en/library/ethics-guidelines-trustworthy-ai
  5. Fernández, V., & Gallardo-Gallardo, E. (2021). Tackling the HR digitalization challenge: Key factors and barriers. International Journal of Human Resource Management, 32(6), 1277–1303. https://doi.org/10.1080/09585192.2019.1579749 (if DOI available; otherwise keep as is)
  6. Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons, 61(4), 577–586. https://doi.org/10.1016/j.bushor.2018.03.007
  7. Köchling, A., & Wehner, M. C. (2020). Discriminated by an algorithm: A systematic review of discrimination and fairness by algorithmic decision-making in the context of HR recruitment and HR development. Business Research, 13, 795–848. https://doi.org/10.1007/s40685-020-00134-5
  8. Mehrabi, N., Morstatter, F., Saxena, N., Lerman, K., & Galstyan, A. (2021). A survey on bias and fairness in machine learning. ACM Computing Surveys, 54(6), Article 115. https://doi.org/10.1145/3457607
  9. Minbaeva, D. (2018). Building credible human capital analytics for organizational competitive advantage. Human Resource Management, 57(3), 701–713. https://doi.org/10.1002/hrm.21848
  10. Raghavan, M., Barocas, S., Kleinberg, J., & Levy, K. (2020). Mitigating bias in algorithmic hiring: Evaluating claims and practices. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (pp. 469–481). ACM. https://doi.org/10.1145/3351095.3372828
  11. Russell, S., & Norvig, P. (2021). Artificial intelligence: A modern approach (4th ed.). Pearson.
  12. Tambe, P., Cappelli, P., & Yakubovich, V. (2019). Artificial intelligence in human resources management: Challenges and a path forward. California Management Review, 61(4), 15–42. https://doi.org/10.1177/0008125619867910
  13. 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
  14. Wilson, H. J., & Daugherty, P. R. (2018). Collaborative intelligence: Humans and AI are joining forces. Harvard Business Review, 96(4), 114–123.
  15. Zhao, Y., & Xin, T. (2021). Machine learning and human resource management: Applications and ethical challenges. Journal of Organizational Computing and Electronic Commerce, 31(2), 95– 112. https://doi.org/10.1080/10919392.2021.1890000