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DWP bring in discriminatory AI to detect ‘fraud’

The most senior civil servant in the Department for Work and Pensions (DWP) has told MPs that he hopes the DWP’s use of artificial intelligence in detecting fraud among benefit claimants will not repeat the Post Office Horizon scandal.

Peter Schofield was questioned by the Commons Work and Pensions Committee last Wednesday on his department’s decision to spend £70 million on so-called machine learning1 in the three years to 2024-25.

DWP’s annual report and accounts revealed last year that it was using machine learning to prioritise which universal credit claims to review for potential fraud.

However, the National Audit Office reported in that document that using machine learning in this way creates “an inherent risk that the algorithms are biased towards selecting claims for review from certain vulnerable people or groups with protected characteristics”.

The disabled people’s organisation, Greater Manchester Coalition of Disabled People, continues working with the tech justice campaign group Foxglove over concerns that the algorithm could be “over-picking” disabled people for its benefit fraud investigations.

Schofield told the work and pensions committee yesterday that machine learning “helps us to target our resources, helps us to target our people, to investigate more effectively those sort of cases where there’s most likely to be fraud.”

He said there was always a human being who made the final decision on whether to launch a fraud investigation and that the system also “enables us to identify those people who might be vulnerable customers.”

But Conservative MP Sir Desmond Swayne asked whether there were “shades of Horizon” over its use of such technology, and Schofield said, “I really hope not.”

His response came in the week that an ITV drama based on the Horizon scandal, which saw more than 700 sub-postmasters wrongly charged with fraud and theft due to faulty software provided by Japanese multinational Fujitsu, pressured the government into rushing out plans to exonerate those wrongfully convicted.

The SNP’s Peter Grant, a member of the public accounts committee, pointed out that if the algorithm used by DWP to detect possible cases of fraud has any “unintended inclination towards bias” around particular groups of claimants, that would put DWP in breach of the law.

Neil Couling, the DWP director-general responsible for universal credit, told Grant: “The systems do have biases; it’s whether they are biases that are not allowed in the law.”

He said the machine learning systems need to have “bias” so the department can “catch fraudsters”, but he said that DWP checks for “unintended bias” at three separate stages.

He said DWP would report in this year’s annual report and account for whether “particular groups with different protected characteristics were impacted unintentionally by this kind of activity.”

But he admitted that other countries had “got themselves into quite a bit of a pickle” when they have “tried to use this sort of technique.”

He said: “I’m determined that in the UK, we don’t do that, so as I said to the public accounts committee back in September, we are taking this very carefully.”

This article first appeared in

  1. A type of artificial intelligence that provides computers with a set of instructions to process large quantities of historical data and identify patterns in that data ↩︎

Image: David J / CC BY 2.0 Deed / AI artwork

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