Governments worldwide are increasingly deploying algorithmic systems that influence citizens’ rights, benefits, and opportunities. These systems often resemble social scoring systems (SSSs) in functionality and societal impact. While extensively studied in China and the United States, SSS remain underexplored in other regions, and no systematization to compare SSS projects within and across regions exists. Moreover, the gap extends to the lack of a comprehensive overview of broader issues triggered by SSS, such as digital dignity, which go beyond the issues of accuracy and non-discrimination. This study addresses these gaps by focusing on existing systems in Switzerland and in developing a replicable codebook able to categorize their features, functionalities, and societal implications. Using a combination of document analysis and iterative coding, 51 systems were identified and analysed across different dimensions, such as dignity, privacy, and social equality. The findings reveal that public administration and law enforcement entities are the primary actors deploying these systems, often leveraging personal data, big data, and historical records. While these systems aim to enhance efficiency and public safety, they also raise ethical concerns, particularly regarding invasive data practices, privacy violations, and the erosion of digital dignity. A key contribution of this research is the identification of underexplored dimensions of digital dignity, including agency, compassionate decision-making, individual and cultural sense of identity, and the dynamic nature of human beings. Through the developed codebook and the provided visualization tool, this study equips stakeholders to better assess and mitigate the risks of SSS in terms of equity, accountability, and fundamental rights.
Reveilhac et al. (Tue,) studied this question.