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Ethical integration in public sector AI: the case of algorithmic systems in the public employment service in Germany

  • This article addresses the ethical design of artificial intelligence (AI) in the public sector, with a particular focus on Public Employment Services (PES). While AI is increasingly employed to streamline administrative processes and improve service delivery, its application in employment mediation raises fundamental concerns regarding fairness, accountability, and democratic legitimacy. The EU Artificial Intelligence Act has further underscored the urgency of addressing these challenges by classifying employment-related AI systems as high-risk, thereby mandating robust safeguards to prevent discrimination and ensure transparency. The central aim of this study is to examine how ethical and social considerations can be systematically embedded in the development and implementation of public sector AI. Using the German PES as a case study, we introduce the “Embedded Ethics and Social Sciences” approach (EE), which integrates ethical reflection and practitioner involvement from the outset.This article addresses the ethical design of artificial intelligence (AI) in the public sector, with a particular focus on Public Employment Services (PES). While AI is increasingly employed to streamline administrative processes and improve service delivery, its application in employment mediation raises fundamental concerns regarding fairness, accountability, and democratic legitimacy. The EU Artificial Intelligence Act has further underscored the urgency of addressing these challenges by classifying employment-related AI systems as high-risk, thereby mandating robust safeguards to prevent discrimination and ensure transparency. The central aim of this study is to examine how ethical and social considerations can be systematically embedded in the development and implementation of public sector AI. Using the German PES as a case study, we introduce the “Embedded Ethics and Social Sciences” approach (EE), which integrates ethical reflection and practitioner involvement from the outset. Qualitative insights from interviews with caseworkers highlight the socio-technical challenges of implementation, particularly the need to reconcile efficiency with citizen trust. Building on these insights, we propose concrete design elements emerging from the integration of ethical and social considerations into system development. In this context, we discuss issues of data ethics and bias, fairness, and the role of explainable AI (XAI). Our analysis demonstrates that this framework not only supports compliance with new regulatory requirements but also strengthens human oversight and agency, and shared decision-making. More broadly, the findings suggest that ethically grounded design can enhance fairness, transparency, and legitimacy across diverse domains of public administration, thereby contributing to more accountable and citizen-centered governance in the digital era.show moreshow less

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Metadaten
Author:Bernhard BauerORCiDGND, Sabrina Mühlbauer, Kerstin Schloegl-FlierlORCiDGND, Enzo Weber, Paula ZiethmannORCiDGND
URN:urn:nbn:de:bvb:384-opus4-1270898
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/127089
ISSN:2195-2663OPAC
Publisher:Institute for Employment Research
Place of publication:Nürnberg
Type:Working Paper
Language:English
Year of first Publication:2025
Publishing Institution:Universität Augsburg
Release Date:2025/12/17
Page Number:32
Series:IAB-Discussion Paper ; 12/2025
DOI:https://doi.org/10.48720/IAB.DP.2512
Institutes:Katholisch-Theologische Fakultät
Fakultät für Angewandte Informatik
Katholisch-Theologische Fakultät / Systematische Theologie
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Software & Systems Engineering
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Softwaretechnik
Katholisch-Theologische Fakultät / Systematische Theologie / Lehrstuhl für Moraltheologie
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Softwaretechnik / Professur Softwaremethodik für verteilte Systeme
Dewey Decimal Classification:3 Sozialwissenschaften / 30 Sozialwissenschaften, Soziologie / 300 Sozialwissenschaften
Licence (German):CC-BY-SA 4.0: Creative Commons: Namensnennung - Weitergabe unter gleichen Bedingungen