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Department for Work and Pensions AI failures

Every documented AI failure involving Department for Work and Pensions on the AI Failure Index, classified by the mechanism that broke.

Failures
4
Highest severity
High
Span
2021 to 2024
Failure modes
3
FI-0537Public SectorHigh
Policy Violation

DWP AI fraud detection system found to be biased against vulnerable groups

An AI system used by the UK's Department for Work and Pensions to detect fraud in Universal Credit advance claims was found to be biased. An internal fairness analysis revealed that the system disproportionately flagged certain demographic groups for investigation.

Confidence
Medium (multi-source)
Department for Work and Pensions3 sourcesPressPublicDec 2024
FI-0486Public SectorHigh
Agentic Action Error

DWP algorithm criticised for bias and wrongful disability fraud referrals

Campaigners, journalists and researchers raised concerns that the Department for Work and Pensions' (DWP) General Matching Service algorithm used to detect benefit fraud was opaque and biased, and sought legal remedies to force disclosure. Subsequent reporting and FOI material showed the system wrongly flagged large numbers of claimants and internal analyses reported statistically significant bias by disability, age and nationality.

Confidence
High (multi-source, primary)
United Kingdom , Department for Work and Pensions (DWP)5 sourcesPrimaryPublicFeb 2022
FI-0672Public SectorHigh
Brand & Safety Incident

DWP fraud detection algorithm targets disabled claimants

The UK DWP used a secretive algorithm to flag Universal Credit claimants for fraud investigations. The system was found to disproportionately target disabled people, which led to a legal challenge and a public admission of bias by the DWP.

Confidence
Medium (multi-source)
Department for Work and Pensions (DWP)2 sourcesPressPublicDec 2021
FI-0248Public SectorMedium
Brand & Safety Incident

UK DWP Universal Credit fraud model shows bias in age and nationality referrals

An internal assessment found statistically significant bias in the UC Advances model, disproportionately flagging non-UK nationals and certain age groups for fraud investigations without a corresponding gain in correct identifications.

Confidence
High (multi-source, primary)
Department for Work and Pensions (DWP)3 sourcesPrimaryPublicFeb 2024

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