Artificial intelligence in the public sector offers numerous opportunities to enhance the efficiency and quality of public services, as well as supporting the adoption of more comprehensive, data-driven policies. This work aimed to review practices and identify the challenges of using artificial intelligence in the European and Slovenian public sectors, while also highlighting the limitations stemming from legal and ethical norms and guidelines. This topic was chosen due to the growing importance of artificial intelligence in the delivery of public services and the risks it entails.
A review of several examples of artificial intelligence use was carried out, alongside an analysis of relevant legal and ethical acts in the public sector. We observed the use of artificial intelligence in practice within the European and Slovenian public sectors and conducted a normative analysis of the public sector’s role in regulations and guidelines, in order to define key challenges and propose good practice recommendations.
Our findings demonstrate that artificial intelligence can significantly improve the quality of public services and enable data-driven decision-making that more accurately reflects real-world circumstances. However, artificial intelligence systems in the public sector are often classified as high-risk, requiring stricter legal and ethical standards. Key challenges include a lack of awareness of obligations, the absence of established procedures and policies, and a shortage of qualified personnel.
This work contributes to raising awareness within the public sector of legal obligations and ethical principles in the use of artificial intelligence. Its practical value lies in recognising the importance of the responsible use of artificial intelligence, promoting the adoption of internal policies, fostering interdisciplinary cooperation, and systematically managing risks. Its societal contribution is strengthening legal certainty and promoting responsible AI use, benefiting citizens, policymakers and society as a whole.
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