Mathematical methods of the digitalization of HR processes in public administration

Oleksandr Oliinyk; Damir Bikulov; Olha Holovan; Svitlana Markova; Olha Veritova

doi:10.26906/EiR.2025.4(99).4169

Authors

Oleksandr Oliinyk Zaporizhzhia National University https://orcid.org/0000-0003-0511-7681
Damir Bikulov Zaporizhzhia National University https://orcid.org/0000-0001-9188-7310
Olha Holovan Zaporizhzhia National University https://orcid.org/0000-0002-9410-3830
Svitlana Markova Zaporizhzhia National University https://orcid.org/0000-0003-0675-0235
Olha Veritova Zaporizhzhia National University https://orcid.org/0000-0001-7365-701X

DOI:

https://doi.org/10.26906/EiR.2025.4(99).4169

Keywords:

public administration, artificial intelligence in personnel selection, algorithmic bias, algorithmic discrimination, high-risk HR systems, EU «AI Act», data audit, mathematical methods

Abstract

The study analyzes the dual effect of AI in public sector recruitment: it increases productivity but risks structural inequalities and algorithmic discrimination, undermining public authority. Current approaches to fairness remain fragmented, creating gaps between efficiency and societal perception. Bias emerges at all recruitment stages. Under the EU “AI Act”, such systems are classified as high-risk technologies requiring mandatory audits. To address this, a composite fairness and non-discrimination index is proposed, integrating technical, ethical, and legal metrics into a unified assessment system. This model enables the identification of vulnerabilities and supports evidence-based decisions. It is substantiated that digitalization requires a systemic methodology for ensuring fairness as a key condition for trust in government algorithms.

Author Biographies

Oleksandr Oliinyk, Zaporizhzhia National University

Candidate of Philosophical Sciences, Associate Professor of the Department of Business Administration and Management of Foreign Economic Activity

Damir Bikulov, Zaporizhzhia National University

Doctor of Public Administration, Professor of the Department of Business Administration and Management of Foreign Economic Activity

Olha Holovan, Zaporizhzhia National University

Candidate of Physical and Mathematical Sciences, Associate Professor of the Department of Business Administration and Management of Foreign Economic Activity

Svitlana Markova, Zaporizhzhia National University

Doctor of Economic Sciences, Professor of the Department of Business Administration and Management of Foreign Economic Activity

Olha Veritova, Zaporizhzhia National University

Candidate of Pedagogical Sciences, Senior Lecturer of the Department of Business Administration and Management of Foreign Economic Activity

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