THE PROBLEM OF DISCRIMINATION IN THE APPLICATION OF AI IN PUBLIC SERVICE MANAGEMENT

Abstract

Purpose: The aim of the study is to identify and analyse the mechanisms leading to discrimination as a result of the use of AI systems in public service management, as well as to identify possible solutions to reduce these phenomena. Need for the study: With the rapid development of AI technologies, they are increasingly being used by public institutions to make decisions in areas such as welfare, education, security or employment. However, the lack of transparency of algorithms, biased input data and insufficient oversight mechanisms can lead to the reproduction and exacerbation of existing social inequalities, resulting in discrimination against specific groups of citizens. Methodology: The analysis was based on a literature review, reports from public institutions, case studies and current examples of AI implementation in the public sector. Ethical and legal aspects were also taken into account, based on regulatory documents and recommendations on the use of AI in public administration. Findings: The use of AI without proper oversight and awareness of risks can lead to the automation of discriminatory practices, especially towards ethnic minorities, people with low socio-economic status or people with disabilities. In practice, there is also often a lack of clear procedures regarding accountability for decisions made by algorithms and mechanisms for audit and correction. Practical Implications: The results of the study point to the need to create a transparent and ethical regulatory framework, to ensure diversity in training data, and to implement algorithmic audits and accountability mechanisms. It also recommends public participation in the design and implementation of AI systems in public services to ensure fairness and equity.

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