Balancing Automation and Discretion: How Decision Stakes and Human-AI Collaboration Affect Citizen Perceptions in Public Administration

The growing use of AI in public administration improves efficiency, yet its use in discretionary decisions raises concerns about fairness and legitimacy. While prior research examined decision stakes and Human–AI decision-making configurations separately, their combined effect on citizens’ perceptions of fairness and adoption remains underexplored. We conducted a mixed-method Wizard-of-Oz study (n=43) using an Intelligent-Self-Service-Kiosk. Participants completed a low-stakes (ID-renewal) and a high-stakes (social-housing) task under one of three decision-making configurations: AI alone, AI with human-supervision, and human with AI advice or recommendation. Quantitative analysis found no significant effects, highlighting the limits of standard metrics. However, qualitative interviews revealed that citizens valued human involvement, requiring meaningful over symbolic oversight. They emphasized interactive dialogue before decisions to capture their circumstances and after, to facilitate appeals. We contribute evidence of tensions between citizens’ desire for efficiency and need for human-control and fairness. We provide guidance for designing citizen-centered AI systems that align with democratic values.