Domain Atlas / Public benefits & eligibility
Rotterdam welfare-fraud risk model
An independent audit of Rotterdam's welfare-fraud risk model documented scores skewed against already-vulnerable groups, and the city suspended the system's use following the scrutiny.[4]
What happened
Rotterdam used a machine-learning model (originally built with Accenture) to score welfare recipients for fraud-investigation priority. Journalists at Lighthouse Reports and partners obtained the model and training data, and their audit documented that risk scores skewed against already-vulnerable groups — women, parents, people with limited Dutch — with individual features like language skill acting as proxies. The city suspended the system's use following the scrutiny.
The sociotechnical reading
Rotterdam is the Atlas's clearest case of the audit-as-actor: the control that finally bound the system came from investigative access to the model itself, which is exactly what vendor opacity usually prevents. It also illustrates selection harms that live outside output accuracy — the model decided who got investigated, and investigation is itself a burden. Governance that only measures "was the flag correct" misses the question "who bears the process". The equity-measurement patterns in the Practice Library exist for this distinction.
The concepts used in this reading are defined in the Field Guide; the governance responses live in the Practice Library.