“Unprecedented Injustice”: Network Determinism in the Dutch Digital Welfare State

Automated decision-making systems in the welfare state have produced discriminatory outcomes at scale, as critical schol arship has extensively documented. This article examines the mechanisms through which such outcomes are produced by tracing the cultural, institutional, and technical determinants embedded in their design and use. Drawing on qualitative research conducted in the Netherlands between 2023 and 2024, it combines semi-structured interviews, ethnographic observation, and documentary analysis across three cases: SyRI, the childcare benefits scandal (Toeslagenaffaire), and Rotterdam’s welfare fraud detection system. Rather than asking whether automated systems discriminate, the article asks how discriminatory social classifications become translated into algorithmic risk and acquire the authority of seemingly objective decisions. The analysis identifies four recurring mechanisms: manual pre-selection of groups for scrutiny, the use of records of past suspicion as training data, proxy substitution for sensitive attributes, and the cumulative, intersec tional layering of risk indicators. To conceptualize these dynamics, the article develops the notion of network determin ism: the practical closure produced when administrative institutions, databases, policy objectives, statistical categories, organizational routines, and computational systems repeatedly reinforce one another, turning contingent classifications into effectively deterministic outcomes for those subjected to them. The findings show that discrimination cannot be attributed to algorithms alone, but emerges from chains of human and institutional choices that distribute both decision-making and responsibility. The Dutch cases therefore demonstrate why technical or legal corrections are insufficient without addressing the socio-cultural assumptions that automated systems are built to operationalize.