Why Do Civil Servants Delegate Empathic Engagement with Clients to Artificial Intelligence Systems? Insights from a Discrete Choice Experiment

Pascal König and Kristina Sabrina Weißmüller
Additional contact information
Kristina Sabrina Weißmüller: Vrije Universiteit Amsterdam

No v9nj3_v1, SocArXiv from Center for Open Science

Abstract: What factors lie behind bureaucrats’ readiness to delegate client interactions that commonly involve human empathy to artificial intelligence (AI) systems? Such delegation entails a crucial trade-off as it may reduce workload but simultaneously introduces inauthentic empathic engagement in citizen-state relations, which may undermine the moral integrity of public administration (PA). Drawing on bureaucratic legitimacy theory, this study tests the impact of efficiency gains, AI features, and organizational norms on civil servants’ willingness to delegate citizen engagement to AI. Findings from a pre-registered discrete choice experiment conducted with 300 active German civil servants (Obs.=3,000) show that while efficiency gains and norms do have some impact, utilitarian considerations concerning AI’s ability to serve clients well are clearly the most important motivator. The findings show that the acceptability of delegating empathic engagement with citizens to AI can be tied to key dimensions of bureaucratic legitimacy, and provide novel evidence that the delegation of counselling to AI in PA is more strongly linked with public service motivation rather than self-serving efficiency gains. These insights advance theory and inform responsible and client-centered use of AI in public bureaucracies.

Date: 2025-11-21
New Economics Papers: this item is included in nep-ain and nep-exp
References: Add references at CitEc
Citations:

Downloads: (external link)
https://osf.io/download/691f5422495579815777070c/

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:v9nj3_v1

DOI: 10.31219/osf.io/v9nj3_v1

Access Statistics for this paper

More papers in SocArXiv from Center for Open Science
Bibliographic data for series maintained by OSF ().