Representative Bureaucracy and Attitudes Toward Automated Decision Making

• 成果类型: Article
• 署名作者: Miller, Susan M.; Keiser, Lael R.
• 署名单位: University of South Carolina System; University of South Carolina Columbia; University of Missouri System; University of Missouri Columbia
• 刊物名称: JOURNAL OF PUBLIC ADMINISTRATION RESEARCH AND THEORY
• ISSN/ISSBN: 1053-1858
• DOI: 10.1093/jopart/muaa019
• 发表日期: 2021
• 页码: 150-165
• 关键词: law-enforcement; Public support; racial threat; perceptions; police; black; RACE; trust; CITIZENS; safety

摘要

The theory of representative bureaucracy posits that citizens will view policy and service delivery more favorably if public servants share their background characteristics. However, automation is changing public service delivery, limiting human involvement in the process. We examine attitudes toward automated decision making through the lens of representative bureaucracy, generating expectations about how a lack of passive representation will affect views toward automated versus human decision making in government. Using a survey experiment, we find evidence that black citizens are more likely to rate automated decision making higher, compared with police officers, on fairness and preference when exposed to a lack of passive representation in a police agency. We do not find evidence of this relationship for white citizens. Our findings provide insight into the way in which passive representation conditions minority citizens' views toward automation, highlighting the importance of considering representation, or lack thereof, as governments contemplate the adoption of automated services.