Ethical Risks and Mitigation Strategies Arising from AI-Enabled Human Resource Management in the Public Sector

Authors

  • Aoran Wang
  • Dan Jiang

DOI:

https://doi.org/10.54097/nw9wzq94

Keywords:

Artificial Intelligence; Public Sector; Human Resource Management; Algorithmic Governance; Digital Ethics.

Abstract

Artificial intelligence technologies are reshaping human resource management (HRM) processes in the public sector through intelligent algorithms and big data analytics. Their applications in three key scenarios—talent recruitment, performance evaluation, and training—play increasingly critical roles. This study identifies major ethical risks: challenges to decision-making fairness caused by algorithmic black boxes, ambiguity in accountability attribution within human-machine collaboration, and power imbalances resulting from data monopolization. To address these, we propose a "Tripartite Governance Framework for Technology": establishing algorithmic auditing mechanisms, refining ethical standards for human-AI collaboration, and fostering a digital governance culture. This framework provides actionable pathways for the digital transformation of public sector HRM in the AI era.

Downloads

Download data is not yet available.

References

[1] Li Deyi. Introduction to Artificial Intelligence[M]. Beijing: China Science and Technology Press, 2021.74.

[2] General Office . Guiding Opinions on Accelerating the Standardization, Regularization, and Facilitation of Government Services[Z]. 2022-02-07.

[3] Weng Yiqin. New Vision of Intelligent Creative Editing Training[J].Cultural Industry,2025,(17):22-24.

[4] Wang Fang, Zhang Yu. Ethical dilemmas of digital transformation in public sector human resource management[J]. Chinese Administrative Management, 2023(5): 45-52.

[5] World Economic Forum. The Future of Jobs Report 2023[R]. Geneva: WEF, 2023.

[6] Suzhou Industrial Park Management Committee. Construction Plan for Suzhou Industrial Park Smart Training Platform[R]. Suzhou: Suzhou Industrial Park Management Committee, 2021.

[7] Singapore Government Technology Agency. White Paper on the Civil Servant Learning Manager (SGLearn) System[R].Singapore: Singapore Government Science and Technology Agency, 2022.

[8] Russell S. Human Compatible: Artificial Intelligence and the Problem of Control[M]. London: Penguin Books, 2019: 89-102.

[9] Yan Bing, Zheng Xia, Wang Bo. "Data Element ×" Scenario-Driven Citizen Green and Low-Carbon Action Operation Guide System V1.0[CP]. 2023SR1234567. Beijing: 2025.

[10] European Commission. Ethics Guidelines for Trustworthy AI[EB/OL]. https://digital-strategy.ec.europa.eu/en/library/ethics-guidelines-trustworthy-ai, 2021-04-08.

[11] Osborne D, Gabbler T. Ditching Bureaucracy: Five Strategies for Reinventing Government [M]. Translated by Zhou Dunren, et al. Shanghai: Shanghai Translation Publishing House, 2006: 112-135.

Downloads

Published

06-11-2025

Issue

Section

Articles

How to Cite

Wang, A., & Jiang, D. (2025). Ethical Risks and Mitigation Strategies Arising from AI-Enabled Human Resource Management in the Public Sector. Journal of Innovation and Development, 13(1), 45-53. https://doi.org/10.54097/nw9wzq94