Digitization or equality: When government automation covers some, but not all citizens

Abstract

This paper presents an empirical study of automation in government digital systems. Previous studies have found that automated systems are not suited to cover all citizens equally and may cause administrative burdens on excluded citizens. The case presented in this study is the automated system for awarding child benefits in Norway. Based on data from the national registry, most recipients are awarded the benefit automatically. However, some citizens are not covered by the automation and must apply manually. The theoretical framing of the study combines modern and classic views of how citizens access public services by combining theory from recent literature on administrative burdens and the older theory of access. The data analysis is done with process mining, an innovative method of sorting and understanding data. The findings support previous findings of how registry data and automated computer systems in government can create inequality in service quality. Furthermore, the findings also show that low-income citizens are disproportionally required to apply manually. The study addresses questions concerning why automated systems fail to cover all citizens and the potential challenges generated by this exclusion when governments rely on computer systems in delivering welfare programmes. These are important considerations, as government digitalisation is increasingly innovating with automated systems to deliver public services.