Domain Atlas / Child welfare & family services
Gladsaxe model
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Gladsaxe's early-detection project (DTO) was a decision-tree model over about 44 risk indicators, meant to score, for every child aged 0 to 6 rather than only families already receiving help, the estimated probability that the child was living in vulnerability; per a university-run Danish public-sector AI catalogue it was to be trained on roughly 173,000 notifications the authorities received between April 2016 and December 2017, but only about 117 usable historical cases existed, and it was halted in its development phase in 2019 without ever running on live decisions, after a national media storm and an unrelated data breach that exposed about 20,000 citizens' personal identification numbers.[5]
What happened
Gladsaxe, a Copenhagen-suburb municipality of about 70,000 people, built an in-house early-detection project (formally Dataunderstoettet Tidlig Opsporing af udsatte boern, or DTO) after a case review found children in distress were typically first identified only around age 8–12, even though different municipal departments had each noted earlier warning signs that were never connected into one picture. The design was a decision-tree model over roughly 44 risk indicators drawn from about nine cross-register data sources, meant to score — for every child aged 0–6 rather than only families already receiving help — the estimated probability that the child was living in vulnerability. Per a university-run Danish public-sector AI catalogue, only about 117 usable historical cases of vulnerable young children existed, too few to train on reliably, and the model was never completed. Contrary to durable public memory, the municipality and the peer-reviewed case study state it was not a "points system" that summed weighted points per risk factor; the widely quoted point values trace to media framing of the municipality's application. Human discretion was designed to remain decisive: a specialist adviser made the preliminary assessment and, without family consent, the case was to be deleted. The project sought legal cover first through a December 2017 "free municipality" exemption — denied by the Ministry of Economy and Interior — and then hoped for a basis in the new Data Protection Act, which did not, in the end, enable it. It became entangled in the national "ghetto" package and GDPR debates, and a March 2018 media storm compared it to surveillance states. After an unrelated December 2018 theft of four laptops exposed a spreadsheet with about 20,000 citizens' personal identification numbers, a governing coalition party withdrew support; the project was put on hold in January 2019 and ended in its development phase that year, never deployed on live decisions.
The sociotechnical reading
Most cases in this Atlas turn on what a deployed system did; Gladsaxe turns on what a system was never permitted to do. Its decisive controls all sat upstream of the model: a legal authorization it never obtained (a free-municipality exemption, then a data-protection legal basis, neither granted), a deployment sign-off, the whole-population scope of its data (it was to profile every young child, not only families already receiving help — a broader reach than the benefits-gated tools it was modeled on), and the institution's data-security capacity (a part-time data-protection officer against an estimated need of ten to seventeen). The model's own dynamics — the memory loop, the deference loop — barely got a chance to run. The case study's diagnosis is a "decoupled" governance chain: councillors approved the purpose but were not close enough to the method to explain or defend it when a media storm and an unrelated data breach collapsed the political support the project depended on. The lesson is that legitimacy, legal basis, and security capacity are load-bearing controls in their own right — a tool can be stopped by the failure of any one of them long before its accuracy is ever tested. It is also the Atlas's clearest "double ethics" case: the same reading that flags whole-population profiling has to weigh the documented cost of not connecting signals that left vulnerable children unseen until age eight.
The concepts used in this reading are defined in the Field Guide; the governance responses live in the Practice Library. The model organization for this case can be stress-tested in the PAN Lab.