Algorithmization of Bureaucratic Organizations: Using a Practice Lens to Study How Context Shapes Predictive Policing Systems

• 成果类型: Article
• 署名作者: Meijer, Albert; Lorenz, Lukas; Wessels, Martijn
• 署名单位: Utrecht University; Netherlands Organization Applied Science Research
• 刊物名称: PUBLIC ADMINISTRATION REVIEW
• ISSN/ISSBN: 0033-3352
• DOI: 10.1111/puar.13391
• 发表日期: 2021
• 页码: 837-846
• 关键词: street-level; TECHNOLOGY; COMMUNICATION; INFORMATION; DISCRETION

摘要

The current scientific debate on algorithms in the public sector is dominated by a focus on technology rather than organizational patterns. This paper extends our understanding of these patterns by studying the algorithmization of bureaucratic organizations, which is the process in which an organization rearranges its working routines around the use of algorithms. To explore the algorithmization of bureaucratic organizations, we conducted a comparative empirical analysis of predictive policing in Berlin (Germany) and Amsterdam (Netherlands) through in-depth qualitative research. Our study identified two emergent patterns: the 'algorithmic cage' (Berlin, more hierarchical control) and the 'algorithmic colleague' (Amsterdam, room for professional judgment). These patterns result from administrative cultures and reinforce existing patterns of organization. The study highlights that two patterns of algorithmization of government bureaucracy can be identified and that these patterns depend on dominant social norms and interpretations rather than the technological features of algorithmic systems.