The impact of public agency representation on citizen perception in the face of technological discrimination
通过实验研究公共机构代表性和专家参与如何影响公民对算法歧视的感知，发现专家参与提升信任，代表性包容对受歧视群体尤为重要。
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.