Volume 38, Issue 3 (Autumn 2025)
JMDP 2025, 38(3): 94-125 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Khosravitanak M, Pourshafei H. (2025). Ethical Challenges of Using Artificial Intelligence in Human Resource Management: A Synthesis Study. JMDP. 38(3), 94-125.
URL: http://jmdp.ir/article-1-4923-en.html
URL: http://jmdp.ir/article-1-4923-en.html
1- Department of Education Sciences, Faculty of Education and Psychology, Birjand University, Iran. , mohamadkhosravitanak@birjand.ac.ir
2- Department of Education Sciences, Faculty of Education and Psychology, Birjand University, Iran.
2- Department of Education Sciences, Faculty of Education and Psychology, Birjand University, Iran.
Abstract: (243 Views)
Purpose: The present study aimed to identify and classify the ethical challenges arising from the application of artificial intelligence (AI) in human resource management (HRM). The focus of the research was on examining the relationship between AI-based technologies and the ethical dimensions of HRM.
Methodology: This study adopted a qualitative approach using the method of "research synthesis." Data were collected through documentary analysis, covering domestic studies from 2020 to 2025 (1399–1404 in the Iranian calendar) and international studies from 2020 to 2025. Keywords such as "ethical challenges," "artificial intelligence," and "human resource management" were searched in national and international databases. After screening, twenty eight final sources were selected for analysis, and data were examined using thematic analysis.
Findings: The results reveal four major ethical challenges, namely “bias and discrimination,” “privacy,” “transparency,” and “accountability.” The analysis indicates that successful and human-centered use of AI in HRM requires adherence to principles of justice, privacy protection, transparent decision-making, and organizational accountability.
Originality: By systematically categorizing the ethical challenges of AI in HRM, this study contributes theoretically, thereby extends the discussion on AI ethics within the human resource domain. From a practical perspective, the findings provide guidance for managers and policymakers to align their AI-driven decisions with ethical considerations.
Recommendations: Based on the findings, it is recommended that organizations develop clear and integrated ethical frameworks when applying AI in HRM.
Methodology: This study adopted a qualitative approach using the method of "research synthesis." Data were collected through documentary analysis, covering domestic studies from 2020 to 2025 (1399–1404 in the Iranian calendar) and international studies from 2020 to 2025. Keywords such as "ethical challenges," "artificial intelligence," and "human resource management" were searched in national and international databases. After screening, twenty eight final sources were selected for analysis, and data were examined using thematic analysis.
Findings: The results reveal four major ethical challenges, namely “bias and discrimination,” “privacy,” “transparency,” and “accountability.” The analysis indicates that successful and human-centered use of AI in HRM requires adherence to principles of justice, privacy protection, transparent decision-making, and organizational accountability.
Originality: By systematically categorizing the ethical challenges of AI in HRM, this study contributes theoretically, thereby extends the discussion on AI ethics within the human resource domain. From a practical perspective, the findings provide guidance for managers and policymakers to align their AI-driven decisions with ethical considerations.
Recommendations: Based on the findings, it is recommended that organizations develop clear and integrated ethical frameworks when applying AI in HRM.
Keywords: Artificial Intelligence, human Resource Management, Ethical Challenges, Ethics in Technology, Privacy, Transparency.
Type of Study: Research |
Subject:
Ethics & Administrative Integrity
Received: Oct 01 2025 | Accepted: Nov 02 2025 | ePublished: Feb 02 2026
Received: Oct 01 2025 | Accepted: Nov 02 2025 | ePublished: Feb 02 2026
References
1. Abbasi, R. and Esmaili, M. (2024). Artificial Intelligence and Digital Human Resource Processes: Applications and Challenges. Journal of Human Resource Management, 14(1), 116-140. (in Persian)
2. Abdkhodaei, Zohreh, Tohidi, Nasim, Karimi Vaghe, Narges, Barati, Mohammad. (2021). White Intelligence: From Machine Ethics to Moral Machine. Tehran: Institute of Cultural and Social Studies. (in Persian)
3. Agarwal, S., Gupta, A., & Roshani, P. (2023). Redefining HRM with artificial intelligence and machine learning. Emerald Publishing Limited, 11 (4). 1-13. [DOI:10.1108/978-1-80382-027-920231001]
4. Agbasiere, C. L., & Nze-Igwe, G. R. (2025). Algorithmic Fairness in Recruitment: Designing AI-Powered Hiring Tools to Identify and Reduce Biases in Candidate Selection. Path of Science, 11(4), 5001-5021. [DOI:10.22178/pos.116-10]
5. Akbari, A. R. and Tahmasebi, R. (2023). Identifying applications and requirements of artificial intelligence in the recruitment process. Organizational Culture Management, 21(1), 75-88. (in Persian)
6. Akter, S. (2025). AI's Impact on Talent Acquisition Strategies and Employee Engagement Methodologies: Ethical Considerations for Trustworthy AI-HRM Integration. Journal of Humanities and Social Sciences Studies, 7(8), 44-51. [DOI:10.32996/jhsss.2025.7.8.6]
7. Andrieux, P., Johnson, R. D., Sarabadani, J., & Van Slyke, C. (2024). Ethical considerations of generative AI-enabled human resource management. Organizational Dynamics, 53(1), 101032. [DOI:10.1016/j.orgdyn.2024.101032]
8. Anton, E., Aptyka, M., Oesterreich, T. D., & Teuteberg, F. (2024). The Moral Compass of Applicants: Ethical Decision Making Amidst AI-Driven Recruitment.
9. Bankins, S., The ethical use of artificial intelligence in human resource management: a decision-making framework. Ethics and Information Technology, 2021. 23(4): p. 841-854. [DOI:10.1007/s10676-021-09619-6]
10. Bhardwaj, G., S.V. Singh, and V. Kumar (2020) An empirical study of artificial intelligence and its impact on human resource functions. In the 2020 International Conference on Computation, Automation and Knowledge Management (ICCAKM). IEEE. [DOI:10.1109/ICCAKM46823.2020.9051544]
11. Bhise, P., Karekar, P., Nikam, R., & Ray, S. (2024). AI-HRM: Transforming Human Resource Management With Artificial Intelligence. Educational Administration: Theory and Practice, 30(5), 9208-9215.
12. Bolboli Qadikolaei, S. and Parsania, H. (2023). A systematic review of the ethical implications of using artificial intelligence in digital technologies and its relationship with the ethics of flourishing. Socio-Cultural Strategy, 12(3), 771-798. (in Persian)
13. Bujold, A., Roberge-Maltais, I., Parent-Rocheleau, X., Boasen, J., Sénécal, S. & Léger, P. M. (2024). Responsible artificial intelligence in human resources management: a review of the empirical literature. AI and Ethics, 4(4), 1185-1200. [DOI:10.1007/s43681-023-00325-1]
14. Capasso, M., Arora, P., Sharma, D., & Tacconi, C. (2024). On the Right to Work in the Age of Artificial Intelligence: Ethical Safeguards in Algorithmic Human Resource Management. Business and Human Rights Journal, 9(3), 346-360. [DOI:10.1017/bhj.2024.26]
15. Cebulla, A., Szpak, Z., Howell, C., Knight, G. & Hussain, S. (2023). Applying ethics to AI in the workplace: the design of a scorecard for Australian workplace health and safety. AI & society, 38(2), 919-935. [DOI:10.1007/s00146-022-01460-9] [https://www.ncbi.nlm.nih.gov/pubmed/35582329]
16. Chang, K. (2024). Ethical and operational challenges in AI-empowered employee recruitment: Insights and suggestions for the managers and managerial practitioners. Innovations in Business and Strategic Management, 2(1), 29-32. [DOI:10.61577/ibsm.2024.100005]
17. Chen, Z. (2023). Ethics and discrimination in artificial intelligence-enabled recruitment practices. Humanities and Social Sciences Communications, 10(1), 1-12. [DOI:10.1057/s41599-023-02079-x]
18. Chowdhury, S., Budhwar, P., & Wood, G. (2024). Generative artificial intelligence in business: towards a strategic human resource management framework. British Journal of Management, 35(4), 1680-1691. [DOI:10.1111/1467-8551.12824]
19. Chowdhury, S., Dey, P., Joel-Edgar, S., Bhattacharya, S., & Truong, L. (2023). Unlocking the value of artificial intelligence in human resource management through an AI capability framework. Human Resource Management Review, 33(1), 880-899. [DOI:10.1016/j.hrmr.2022.100899]
20. Czarnitzki, D., Fernández, G. P. & Rammer, C. (2023). Artificial intelligence and firm-level productivity. Journal of Economic Behavior & Organization, 211, 188-205. [DOI:10.1016/j.jebo.2023.05.008]
21. Du, J. (2024). Exploring Gender Bias and Algorithm Transparency: Ethical Considerations of AI in HRM. Journal of Theory and Practice of Management Science, 4(03), 36-43. [DOI:10.53469/jtpms.2024.04(03).06]
22. Dutta, B. M. (2018). The ethics of artificial intelligence in legal decision making: an empirical study. Psychology and Education Journal, 55(1).
23. Etemadi, M., Chitsaz, E., Koushki, S., & Jafari, S. M. (2024). Artificial Intelligence (AI) vs. Human-Led Approaches in Human Resource Recruitment Assessment: A Meta-Synthesis of Advantages and Disadvantages. Journal of Sustainable Human Resource Management, 6(11), 214-191. (in Persian).
24. Fathi-Livari R, Hamidizadeh A, Sanoubar N, Zareei-Matin H. (2019). Designing and Validating the Ethical Leadership Model in Organizations. JMDP. 31(4), 37-62.
25. Fernández-Martínez, C. & Fernández, A. (2020). AI and recruiting software: Ethical and legal implications. Paladyn, Journal of Behavioral Robotics, 11(1), 199-216. [DOI:10.1515/pjbr-2020-0030]
26. Garg, S., Sinha, S., Kar, A. K., & Mani, M. (2022). A review of machine learning applications in human resource management. International Journal of Productivity and Performance Management, 71(5), 1590-1610. [DOI:10.1108/IJPPM-08-2020-0427]
27. Gil de Zúñiga, H., Goyanes, M., & Durotoye, T. (2024). A scholarly definition of artificial intelligence (AI): Advancing AI as a conceptual framework in communication research. Political communication, 41(2), 317-334. [DOI:10.1080/10584609.2023.2290497]
28. Gong, Q., Fan, D., & Bartram, T. (2025). Integrating artificial intelligence and human resource management: a review and future research agenda. The International Journal of Human Resource Management, 36(1), 103-141. [DOI:10.1080/09585192.2024.2440065]
29. Haight, A. M. & Johnson, E. S. (2023). Coping with Ethical Challenges in AI Recruiting (Master's thesis, Handelshøyskolen BI).
30. Hamani, R., & Mokhtari, M. (2025). Formulating an Ideal Model for the Relationship Between Ethics and Artificial Intelligence: Emphasizing the Ethical Foundations of Allama Misbah Yazdi. Journal of Moral Studies, 8(1), 89-112.
31. Hamouche, S., Rofa, N., & Parent-Lamarche, A. (2025). Systematic bibliometric review of artificial intelligence in human resource development: insights for HRD researchers, practitioners, and policymakers. European Journal of Training and Development, 49(1/2), 43-62. [DOI:10.1108/EJTD-10-2023-0152]
32. Hemalatha, A., Kumari, P. B., Nawaz, N., & Gajenderan, V. (2021). Impact of Artificial Intelligence on Recruitment and Selection of Information Technology Companies. In Proceedings - International Conference on Artificial Intelligence and Smart Systems, ICAIS 2021 (pp. 60-66). [DOI:10.1109/ICAIS50930.2021.9396036]
33. Huang, X., Yang, F., Zheng, J., Feng, C., & Zhang, L. (2023). Personalized human resource management via HR analytics and artificial intelligence: Theory and implications. Asia Pacific Management Review, 28(4), 598-610. [DOI:10.1016/j.apmrv.2023.04.004]
34. Hunkenschroer, A. L. & Kriebitz, A. (2023). Is AI recruiting (un) ethical? A human rights perspective on the use of AI for hiring. AI and Ethics, 3(1), 199-213. [DOI:10.1007/s43681-022-00166-4] [https://www.ncbi.nlm.nih.gov/pubmed/35909984]
35. Hunkenschroer, A.L., Luetge, C (2022). Ethics of AI-Enabled Recruiting and Selection: A Review and Research Agenda. J Bus Ethics 178, 977-1007. [DOI:10.1007/s10551-022-05049-6]
36. Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1(9), 389-399. [DOI:10.1038/s42256-019-0088-2]
37. Jowarder, R. A. (2025). The Ethics of AI Decision-Making: Balancing Automation, Explainable AI, and Human Oversight. International Journal of Science and Research Archive, 14(3), 435-443. [DOI:10.30574/ijsra.2025.14.3.0677]
38. Karslı, N. (2025). Ethical and Theological Problems Related to Artificial Intelligence. Eskişehir Osmangazi Üniversitesi İlahiyat Fakültesi Dergisi, 12(Din ve Yapay Zeka), 1-19. [DOI:10.51702/esoguifd.1583408]
39. Khair, M. A., Mahadasa, R., Tuli, F. A., & Ande, J. R. P. K. (2020). Beyond human judgment: exploring the impact of artificial intelligence on HR decision-making efficiency and fairness. Global Disclosure of Economics and Business, 9(2), 163-176. [DOI:10.18034/gdeb.v9i2.730]
40. Kimseng, T., Javed, A., Jeenanunta, C. & Kohda, Y. (2020). Applications of fuzzy logic to reconfigure human resource management practices for promoting product innovation in formal and non-formal R&D firms. Journal of Open Innovation: Technology, Market, and Complexity, 6(2), 38. [DOI:10.3390/joitmc6020038]
41. 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. Business Research, 13(3), 795-848. [DOI:10.1007/s40685-020-00134-w]
42. Kumar, C. (2025). From Automation to Ethics: Responsible AI in Human Resource Management across Industries with Insights from the Power Sector. RESEARCH REVIEW International Journal of Multidisciplinary, 10(4), 63-81. [DOI:10.31305/rrijm.2025.v10.n4.009]
43. Laudon, K.C., Laudon, J.P. (2014). Management Information Systems: Managing the Digital Firm (13/e), Prentice Hall, NJ.
44. Leicht-Deobald, U., Busch, T., Schank, C., Weibel, A., Schafheitle, S., Wildhaber, I., & Kasper, G. (2019). The challenges of algorithm-based HR decision-making for personal integrity. Journal of Business Ethics, 160(2), 377-392. [DOI:10.1007/s10551-019-04204-w] [https://www.ncbi.nlm.nih.gov/pubmed/31814653]
45. Mariani, M. M., Perez‐Vega, R. & Wirtz, J. (2022). AI in marketing, consumer research, and psychology: A systematic literature review and research agenda. Psychology & Marketing, 39(4), 755-776. [DOI:10.1002/mar.21619]
46. Mariani, M.M., Machado, I., Magrelli, V., Dwivedi, Y.K. (2023). Artificial intelligence in innovation research: A systematic review, conceptual framework, and future research directions. Technovation, 122: 102623. [DOI:10.1016/j.technovation.2022.102623]
47. Mendy, J., Jain, A., & Thomas, A. (2024). Artificial intelligence in the workplace-challenges, opportunities and HRM framework: a critical review and research agenda for change. Journal of Managerial Psychology, 8(6), 109-121. [DOI:10.1108/JMP-05-2024-0388]
48. Michailidis, M. P. (2018). The challenges of AI and blockchain on HR recruiting practices. Cyprus Review, 30(2), 169-180.
49. Mohapatra, L. M., Kamesh, A. V. S., & Roul, J. (2023). Challenges and Path Ahead for Artificial Intelligence-aided Human Resource Management. In The Adoption and Effect of Artificial Intelligence on Human Resources Management, Part A (pp. 107-121). Emerald Publishing Limited. [DOI:10.1108/978-1-80382-027-920231006]
50. Mori, M., Sassetti, S., Cavaliere, V., & Bonti, M. (2024). A systematic literature review on artificial intelligence in recruiting and selection: a matter of ethics. Personnel Review, 54(3), 854-878. [DOI:10.1108/PR-03-2023-0257]
51. Mujtaba, D. F., & Mahapatra, N. R. (2024). Fairness in AI-driven recruitment: Challenges, metrics, methods, and future directions. arXiv preprint arXiv:2405.19699.
52. Naik, N., Hameed, B. M., Shetty, D. K., Swain, D., Shah, M., Paul, R., ... & Somani, B. K. (2022). Legal and ethical considerations in artificial intelligence in healthcare: who takes responsibility? Frontiers in Surgery, 9, 862322. [DOI:10.3389/fsurg.2022.862322] [https://www.ncbi.nlm.nih.gov/pubmed/35360424]
53. Olson, C. & Levy, J. (2018). Transforming marketing with artificial intelligence. Applied Marketing Analytics, 3(4), 291-297. [DOI:10.69554/YDWT3570]
54. Onome-Irikefe, Kevwe. 2025. "Big Data in Recruitment: Ethical Challenges and Privacy Concerns". Journal of Advances in Mathematics and Computer Science 40 (5):96-104. [DOI:10.9734/jamcs/2025/v40i52000]
55. Orhan, A., & Kurnaz, S. (2025). Artificial Intelligence in Human Resource Management Training. In Economic Innovations and Technological Developments in HRM (pp. 405-444). IGI Global. [DOI:10.4018/979-8-3693-4412-5.ch016]
56. Oswald, F. L., Behrend, T. S., Putka, D. J., & Sinar, E. (2020). Big data in industrial-organizational psychology and human resource management: Forward progress for organizational research and practice. Annual Review of Organizational Psychology and Organizational Behavior, 7, 505-533. [DOI:10.1146/annurev-orgpsych-032117-104553]
57. Patole, S., Carpenter, R. E., & McWhorter, R. (2024). Exploring artificial intelligence and ethical use of data in HRD. In the Academy of Human Resource Development 2024 International Research Conference in the Americas.
58. Pedrami, M. and Nargesia, A. (2025). Identification and Meta-synthesis Analysis of Artificial Intelligence Ethical Challenges in Human Resource Management: A Conceptual Framework. Journal of Human Resource Management, 15(Special Issue on Artificial Intelligence and Digital Transformation in Human Resource Management), 143-166. (in Persian)
59. Priyanka, R., Ravindran, K., Sankaranarayanan, B. & Ali, S. M. (2023). A fuzzy DEMATEL decision modeling framework for identifying key human resources challenges in start-up companies: Implications for sustainable development. Decision Analytics Journal, 6, 100192. [DOI:10.1016/j.dajour.2023.100192]
60. Rabenu, E., & Baruch, Y. (2025). Cyborging HRM theory: from evolution to revolution-the challenges and trajectories of AI for the future role of HRM. Personnel Review, 54(1), 174-198. [DOI:10.1108/PR-02-2024-0111]
61. 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). [DOI:10.1145/3351095.3372828]
62. Rahimiaghdam S, Salehpoor P, Namvar R. (2025). Ethical Challenges of Adopting AI in HRM. Ethics in Science and Technology; 19 (4):142-149. (in Persian)
63. Ravin, J. (2017). HR's new role: Rethinking and enabling digital engagement. Strategic HR Review, 16(2). [DOI:10.1108/SHR-01-2017-0009]
64. Rydén, P. & El Sawy, O. (2022). Real-time management: When AI goes fast and flows. In Platforms and Artificial Intelligence: The Next Generation of Competences (pp. 225-243). Cham: Springer International Publishing. [DOI:10.1007/978-3-030-90192-9_11]
65. Sachan, V. S., Katiyar, A., Somashekher, C., Chauhan, A. S. & Bhima, C. K. (2024). The Role Of Artificial Intelligence In HRM: Opportunities, Challenges, And Ethical Considerations. Educational Administration: Theory and Practice, 30(4), 7427-7435.
66. Schultz, R. 2005. Contemporary issues in ethics and information technology.: IRM press. [DOI:10.4018/978-1-59140-779-9]
67. Setiawati, R., Kusmara, A., & Kuusk, T. (2025). Managing Transparency, Fairness Accountability in AI for Sustainable Human Resource Management. In 2025 4th International Conference on Creative Communication and Innovative Technology (ICCIT) (pp. 1-7). IEEE. [DOI:10.1109/ICCIT65724.2025.11166968]
68. Sharifzadeh, R. (2022). Information Technology, Moral Dilemmas, and Decision-Making. Iranian Journal of Information Processing and Management, 38(2), 5-34. (in Persian)
69. Siau, K., & Wang, W. (2020). Artificial intelligence (AI) ethics: ethics of AI and ethical AI. Journal of Database Management (JDM), 31(2), 74-87. [DOI:10.4018/JDM.2020040105]
70. Singh, L., Randhelia, A., Jain, A., & Choudhary, A. K. (2025). Ethical and Regulatory Compliance Challenges of Generative AI in Human Resources. Generative Artificial Intelligence in Finance: Large Language Models, Interfaces, and Industry Use Cases to Transform Accounting and Finance Processes, 199-214. [DOI:10.1002/9781394271078.ch11]
71. Sýkorová, Z., Hague, D., Dvouletý, O., & Procházka, D. A. (2024). Incorporating artificial intelligence (AI) into recruitment processes: ethical considerations. Vilakshan-XIMB Journal of Management, (ahead-of-print). [DOI:10.1108/XJM-02-2024-0039]
72. Tilmes, N. (2022). Disability, fairness, and algorithmic bias in AI recruitment. Ethics and Information Technology, 24(2), 21. [DOI:10.1007/s10676-022-09633-2]
73. Varsha, P. S., Dr. (2023). How can we manage biases in artificial intelligence systems - A systematic literature review. International Journal of Information Management Data Insights, 3(1), Article 100165. [DOI:10.1016/j.jjimei.2023.100165]
74. Waheed, A., Miao, X., Waheed, S., Ahmad, N., & Majeed, A. (2019). How new HRM practices, organizational innovation, and innovative climate affect the innovation performance in the IT industry: A moderated-mediation analysis. Sustainability, 11 (3), 621. [DOI:10.3390/su11030621]
75. Wang, J., & Pashmforoosh, R. (2024). A new framework for ethical artificial intelligence: keeping HRD in the loop. Human Resource Development International, 27(3), 428-451. [DOI:10.1080/13678868.2024.2346492]
76. Wang, X.-L., Lei, N., & Hou, Y.-Z. (2020). How does human resource department's client relationship management affect sustainable enterprise performance in the context of artificial intelligence? International Journal of Technology Management, 84(1-2), 50-69. [DOI:10.1504/IJTM.2020.112139]
77. Wiradendi Wolor, C. (2020). Implement talent management to improve the organization's performance in Indonesia to fight Industrial Revolution 4.0. International Journal of Scientific & Technology Research.
78. Yang, C., Yang, P. & Feng, Y. (2021). Effect of achievement-related gamification on brand attachment. Industrial Management & Data Systems, 122(1), 251- 271. [DOI:10.1108/IMDS-02-2021-0088]
79. Yazdani, H., & hakiminia, M. (2024). Identifying the challenges and opportunities of using artificial intelligence in Human resource management with a meta-synthesis approach. Journal of Sustainable Human Resource Management, 6(10), 139-113. (in Persian)
80. Yorks, L., & Jester, M. Y. (2024). Applying generative AI ethically in HRD practice. Human Resource Development International, 27(3), 410-427. [DOI:10.1080/13678868.2024.2337963]
81. Rajaei, Z., noferesti, F., heidarnia, Z., mohemmi, Z. (2024). Application of artificial intelligence in human resource management, Journal of Naja Human Resources, 17(73), 39-70. (in Persian)
82. Zahra, Y. (2024). Ethical and Legal Implications of AI in Decision-Making. Jurnal Sistem Informasi dan Teknik Informatika (JAFOTIK), 2(2), 49-54. [DOI:10.70356/jafotik.v2i2.42]
83. Strohmeier, S. (2020). Digital human resource management: A conceptual clarification. German Journal of Human Resource Management, 34(3), 345-365. [DOI:10.1177/2397002220921131]
84. 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. [DOI:10.1177/0008125619867910]
85. Schultz, R. A. (Ed.). (2005). Contemporary issues in ethics and information technology. IGI Global. [DOI:10.4018/978-1-59140-779-9]
86. Walsh, D., & Downe, S. (2005). Meta-synthesis method for qualitative research: A literature review. Journal of Advanced Nursing, 50(2), 204-211. [DOI:10.1111/j.1365-2648.2005.03380.x] [https://www.ncbi.nlm.nih.gov/pubmed/15788085]
87. Sandelowski, M., & Barroso, J. (2007). Handbook for Synthesizing Qualitative Research. Springer.
88. Rao, S., & Zhao, T. (2025). Ethical AI in HR: A Case Study of Tech Hiring. Journal of Computer Information Systems, 1-18. [DOI:10.1080/08874417.2024.2446954]
89. Andreas NB (2024), "Ethics in international HRD: examining conversational AI and HR chatbots". Strategic HR Review, Vol. 23 No. 3 pp. 121-125. [DOI:10.1108/SHR-03-2024-0018]
90. Ajonbadi, H.A., Khan, S., Owolewa, M. (2024). Before It Goes South: The Ethical Dilemma of Artificial Intelligence in Human Resource Management-The Bangladesh Workplace Experience HRM, Artificial Intelligence and the Future of Work. Palgrave Macmillan, Cham. [DOI:10.1007/978-3-031-62369-1_8]
91. Du, J. (2024). Ethical and Legal Challenges of AI in Human Resource Management. Journal of Computing and Electronic Information Management, 13(2), 71-77. [DOI:10.54097/83j64ub9]
92. Hamilton, R.H., Davison, H.K. Legal and Ethical Challenges for HR in Machine Learning. Employ Respons Rights J 34, 19-39 (2022). [DOI:10.1007/s10672-021-09377-z]
93. Yanamala, K. K. (2023). Transparency, Privacy, and Accountability in AI-Enhanced HR Processes. Journal of Advanced Computing Systems, 3(3), 10-18. [DOI:10.69987/JACS.2023.30302]
94. Bar-Gil, O., Ron, T., & Czerniak, O. (2024). AI for the people? Embedding AI ethics in HR and people analytics projects. Technology in Society, 77, 102527. [DOI:10.1016/j.techsoc.2024.102527]
95. Khan, M. I., Parahyanti, E., & Hussain, S. (2024). The Role Generative AI in Human Resource Management: Enhancing Operational Efficiency, Decision-Making, and Addressing Ethical Challenges. Asian Journal of Logistics Management, 3(2), 104-125. [DOI:10.14710/ajlm.2024.24671]
96. Lungu, DC., Grigorescu, A., Yousaf, Z. (2024). The Ethical Concerns of AI Technologies in Human Resources. (eds) Europe in the New World Economy: Opportunities and Challenges. ESPERA 2023. Springer Proceedings in Business and Economics. Springer, Cham. [DOI:10.1007/978-3-031-71329-3_14]
97. Ayari, A., Ammar, A. (2024). AI Accountability, Ethics, and Human Resource Implications. In: Ammar, A., Bernstein, M. (eds) Ethical Challenges for the Future of Neurosurgery. Springer, Cham. [DOI:10.1007/978-3-031-71477-1_4]
98. Mask, E., & Pearl, J. (2024). Artificial intelligence in human resources: Ethical implications and performance enhancement.
99. Porkodi, S., & Cedro, T. L. (2025). The Ethical Role of Generative Artificial Intelligence in Modern HR Decision-Making: A Systematic Literature Review. European Journal of Business and Management Research, 10(1), 44-55. [DOI:10.24018/ejbmr.2025.10.1.2535]
100. Javaid, B & Pearl, J. (2024). Ethical Challenges of Artificial Intelligence Implementation in Human Resources: Implications for Job Performance Evaluation.
101. Raza, S & Guibas, Ls. (2024). Artificial Intelligence in Human Resources: Ethical Implications and Job Performance Analysis.
102. Onome-Irikefe, K. (2025). Ethical Challenges and Privacy Concerns Associated with Big Data in the Hiring Process: A Mixed-Methods Study. Available at SSRN 5639551. [DOI:10.9734/bpi/mcsru/v6/5930] [https://doi.org/10.2139/ssrn.5639551]
103. Martin, L. (2018). How to retain motivated employees in their jobs? Economic and Industrial Democracy, 41(4), 910-953. [DOI:10.1177/0143831X17741528]
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution 4.0 International License. |
