@inproceedings{10.1145/3715275.3732103,
Author = {Abdenebaoui, Larbi and Aljuneidi, Saja and Horstmannshoff, Fynn and Meyer, Jochen and Boll, Susanne},
Title = {Value-Driven Design for Public Administration: Insights from a Generative Chatbot in a Housing Application Case Study},

Year = {2025},
Pages = {1554–1564},
Month = {},
Publisher = {Association for Computing Machinery},
Series = {FAccT '25},
Booktitle = {Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency},
Doi = {10.1145/3715275.3732103},
type = {inproceedings},
Abstract = {Artificial intelligence holds significant potential to transform public administration by streamlining complex processes and improving service delivery. However, its adoption is hindered by concerns regarding its alignment with public values e.g., ensuring that all citizens are treated equitably. This study addresses these challenges through a value-driven design approach, focusing on a generative chatbot to assist citizens with the Housing Entitlement Certificate application, a service enabling low-income households to access subsidized housing in Germany. Through two participatory workshops with citizens and public administration employees, the research highlights a tension between significant benefits, such as improved accessibility and streamlined processes, and challenges, including reduced human interaction and dependency on technology. To navigate these tensions, the study proposes actionable requirements, including escalation pathways to human representatives and robust data protection measures. By providing a real-world example, this work illustrates how value-based design can guide the responsible and impactful integration of AI in public administration. The findings underscore the importance of balancing the potential of generative chatbots with societal and ethical considerations, offering a replicable framework for aligning AI systems with public values in diverse service contexts.}
}
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