Algorithms in the public sector. Why context matters

• 成果类型: Article
• 署名作者: Wenzelburger, Georg; Koenig, Pascal D.; Felfeli, Julia; Achtziger, Anja
• 署名单位: Saarland University; Harvard University; Zeppelin University
• 刊物名称: PUBLIC ADMINISTRATION
• ISSN/ISSBN: 0033-3298
• DOI: 10.1111/padm.12901
• 发表日期: 2024
• 页码: 40-60
• 关键词: artificial-intelligence; decision-making; TRANSPARENCY; acceptance; trust; INFORMATION; MODEL

摘要

Algorithms increasingly govern people's lives, including through rapidly spreading applications in the public sector. This paper sheds light on acceptance of algorithms used by the public sector emphasizing that algorithms, as parts of socio-technical systems, are always embedded in a specific social context. We show that citizens' acceptance of an algorithm is strongly shaped by how they evaluate aspects of this context, namely the personal importance of the specific problems an algorithm is supposed to help address and their trust in the organizations deploying the algorithm. The objective performance of presented algorithms affects acceptance much less in comparison. These findings are based on an original dataset from a survey covering two real-world applications, predictive policing and skin cancer prediction, with a sample of 2661 respondents from a representative German online panel. The results have important implications for the conditions under which citizens will accept algorithms in the public sector.