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. 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.