A flawed algorithm that determines the social security benefits received by people in the UK is causing hunger, debt, and psychological distress, Human Rights Watch has warned.
The model calculates the benefits people are entitled to each month based on changes in their earnings. But Human Rights Watch discovered a defect in the system.
The algorithm only analyzes the wages people receive within a calendar month, and ignores how often they’re paid. This means that people who receive multiple paychecks in a month — a common occurrence in irregular and low-paid work — can have their earnings overestimated and their payments dramatically shrunk.
Human Rights Watch says the system could be improved by using shorter periods of income assessment or averaged earnings over longer periods of time. While the government evaluates these proposals, the watchdog has called for urgent measures to be implemented, such as one-off grants for applicants.
“The government has put a flawed algorithm in charge of deciding how much money to give people to pay rent and feed their families,” said Amos Toh, senior AI and human rights researcher at Human Rights Watch. “The government‘s bid to automate the benefits system – no matter the human cost – is pushing people to the brink of poverty.”
The algorithm is a core part of Universal Credit, a revamp of the UK‘s welfare system that combines six benefits into one monthly sum.
The system was designed to streamline payments, but has been widely criticized since its launch in 2016. Anyone who applies for it has to wait for five weeks before they receive their first payment, and people with limited digital skills or internet access have struggled to manage the online system.
The algorithm the UK uses reflects a global trend to automate social security systems. Last October, a UN human rights expert said these programs were often designed to slash welfare, ramp up government surveillance, and generate profits for corporate interests.
Human Rights Watch wants the UK government to take a more human-centered approach. But problems with the algorithm shouldn’t let the policymakers off the hook.
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