M.F. Enbergs
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Unsafe Social Welfare Systems
A System Safety Analysis of the Dutch Childcare Benefit Scandal
The introduction of algorithmic decision-making in the social welfare domain has contributed to the emergence and amplification of harm to citizens. In several cases, the use of algorithmic decision-support systems has led to the formation of so-called “digital cages”; administrative exclusion by digital information architectures. To date we still lack comprehensive theoretical concepts to describe and analyze the systemic hazards introduced by algorithmic systems. Our study illustrates the affordances of system-theoretic concepts and methods, drawing on system safety, to understand and analyze algorithmically induced hazards in public governance. We show, on example of the Dutch Childcare Benefit Scandal, that the system safety discipline offers powerful concepts and tools to understand, prevent, and address algorithmically induced system hazards in social welfare. By applying system safety concepts, our study contributes to the development of sociotechnical assessment approaches for algorithmic systems in public governance.
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The introduction of algorithmic decision-making in the social welfare domain has contributed to the emergence and amplification of harm to citizens. In several cases, the use of algorithmic decision-support systems has led to the formation of so-called “digital cages”; administrative exclusion by digital information architectures. To date we still lack comprehensive theoretical concepts to describe and analyze the systemic hazards introduced by algorithmic systems. Our study illustrates the affordances of system-theoretic concepts and methods, drawing on system safety, to understand and analyze algorithmically induced hazards in public governance. We show, on example of the Dutch Childcare Benefit Scandal, that the system safety discipline offers powerful concepts and tools to understand, prevent, and address algorithmically induced system hazards in social welfare. By applying system safety concepts, our study contributes to the development of sociotechnical assessment approaches for algorithmic systems in public governance.