The impact of public agency representation on citizen perception in the face of technological discrimination
Bibliographic Data
| ID | 21723639 |
|---|---|
| Authors | Younghyun Cho (0009-0007-6899-3271, Florida State University, Tallahassee, FL, United States, corresponding author), James E Wright (0000-0002-6896-563X, Arizona State University, Phoenix, United States), Gregory A Porumbescu (0000-0001-8595-6068, Rutgers University-Newark, Newark, United States) |
| Year | 2026 |
| Pages | 1-29 |
| Publication date | 2026-06-28 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Public Management Review (JOURNAL) |
| Journal identifiers | ISSN: 1471-9037 • E-ISSN: 1471-9045 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/14719037.2026.2692614 |
| OpenAlex | W7166468453 |
| Language | EN |
| References cited | 48 |
This study explores how public agency representation and expertise shape citizen perceptions of algorithmic discrimination. Using theories of representative bureaucracy and Human-In-The-Loop (HITL), an experimental design with a general population and an African American sample examines how algorithmic correction approaches influence trust, legitimacy, and perceived performance. Expert involvement increases positive perceptions across samples, with stronger effects observed in the African American sample. Awareness of inclusion boosts trust among the African American sample but has mixed results for the general population. Findings suggest that while technical expertise is crucial, representative inclusion is vital for rebuilding trust within communities historically impacted by discrimination
Bureaucracy · Perception · E-Government and Public Services · Ethics and Social Impacts of AI · Social Media and Politics
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| Highly cited | No |
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