Warning on the use of risk profiling to detect crime, fraud and debt
Local authorities are increasingly using algorithms to try to identify potential violators such as criminal gangs and benefit fraudsters, according to a survey by NOS.
At least 25 municipalities use systems that create “risk profiles” for offenses that impact council funding, as well as to identify people at risk of serious debt.
The tax authorities have been criticized for using dual citizenship as an indicator of risk in families suspected of fraud in the family allowance scandal, which led to the resignation of the cabinet last month. A series of investigations found that many people were wrongly targeted and blacklisted for making small administrative mistakes.
Last year, a court ordered the government to stop using its algorithm-based fraud detection system, SyRI, which used risk profiling to compile lists of people suspected of housing or social security fraud. .
Judges ruled that the system, created by officials from the Social Affairs Ministry in 2014, violated EU human rights and privacy laws because it branded people as potential fraudsters without any evidence.
Anton Ekker, one of the lawyers who challenged the government’s use of SyRI in court, said the proliferation of algorithms was concerning. “The cabinet promised that there would be no repeat of the child care allowance scandal, but there is no clear picture of what all municipalities are doing,” he said. declared to NOS.
Simple algorithms are used widely across government – for example, to calculate how much a driver should be fined for exceeding the speed limit. But more sophisticated systems carry a risk of discrimination if they focus on particular social groups or neighborhoods.
Amsterdam uses algorithms to try to detect illegal vacation rentals in an attempt to limit Airbnb-style rentals in residential areas, as well as people at risk of high debt.
Brielle in Nissewaard, near Rotterdam, uses “smart modeling” to identify potential benefit fraud by highlighting distinctive patterns of behavior. Breda, in Brabant, assesses the effect of proposed construction or demolition projects on neighborhoods using machine learning.
Leudal in Maastricht, Limburg is evaluating construction and real estate documents to try to spot patterns indicating the presence of criminal gangs.
Ekker told NOS that the use of artificial intelligence could lead to other situations such as the benefits scandal. “I’m not sure the local authorities have enough internal expertise to do it the right way,” he said. “They are often very dependent on external IT vendors.
“If this threatens to go wrong again, we cannot rule out a lawsuit.”
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