Skip to Content
logologo
AI Incident Database
Open TwitterOpen RSS FeedOpen FacebookOpen LinkedInOpen GitHub
Open Menu
Découvrir
Envoyer
  • Bienvenue sur AIID
  • Découvrir les incidents
  • Vue spatiale
  • Vue de tableau
  • Vue de liste
  • Entités
  • Taxonomies
  • Soumettre des rapports d'incident
  • Classement des reporters
  • Blog
  • Résumé de l’Actualité sur l’IA
  • Contrôle des risques
  • Incident au hasard
  • S'inscrire
Fermer
Découvrir
Envoyer
  • Bienvenue sur AIID
  • Découvrir les incidents
  • Vue spatiale
  • Vue de tableau
  • Vue de liste
  • Entités
  • Taxonomies
  • Soumettre des rapports d'incident
  • Classement des reporters
  • Blog
  • Résumé de l’Actualité sur l’IA
  • Contrôle des risques
  • Incident au hasard
  • S'inscrire
Fermer

Incident 738: Department for Work and Pensions (DWP) Algorithm Wrongly Flags 200,000 for Housing Benefit Fraud

Description: A Department for Work and Pensions (DWP) algorithm wrongly flagged over 200,000 UK housing benefit claims as high risk, resulting in unnecessary investigations. Two-thirds of these flagged claims were legitimate, causing wasted public funds and stress for claimants. Despite initial success in a pilot, the algorithm's real-world performance fell short. This incident highlights the risks of overreliance on automated systems in welfare administration.

Outils

Nouveau rapportNouveau rapportNouvelle RéponseNouvelle RéponseDécouvrirDécouvrirVoir l'historiqueVoir l'historique

Entités

Voir toutes les entités
Présumé : Un système d'IA développé et mis en œuvre par Department for Work and Pensions (DWP), a endommagé UK general public et UK housing benefit claimants.

Statistiques d'incidents

ID
738
Nombre de rapports
5
Date de l'incident
2024-06-23
Editeurs
Daniel Atherton
Applied Taxonomies
MIT

Classifications de taxonomie MIT

Machine-Classified
Détails de la taxonomie

Risk Subdomain

A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
 

1.3. Unequal performance across groups

Risk Domain

The Domain Taxonomy of AI Risks classifies risks into seven AI risk domains: (1) Discrimination & toxicity, (2) Privacy & security, (3) Misinformation, (4) Malicious actors & misuse, (5) Human-computer interaction, (6) Socioeconomic & environmental harms, and (7) AI system safety, failures & limitations.
 
  1. Discrimination and Toxicity

Entity

Which, if any, entity is presented as the main cause of the risk
 

AI

Timing

The stage in the AI lifecycle at which the risk is presented as occurring
 

Post-deployment

Intent

Whether the risk is presented as occurring as an expected or unexpected outcome from pursuing a goal
 

Unintentional

Rapports d'incidents

Chronologie du rapport

+1
L'algorithme DWP signale à tort 200 000 personnes pour d'éventuelles fraudes et erreurs
+2
DWP algorithm 'wrongly flags' 200,000 people for fraud
DWP wrongly suspects hundreds of thousands of benefits claimants of fraud
L'algorithme DWP signale à tort 200 000 personnes pour d'éventuelles fraudes et erreurs

L'algorithme DWP signale à tort 200 000 personnes pour d'éventuelles fraudes et erreurs

theguardian.com

DWP algorithm 'wrongly flags' 200,000 people for fraud

DWP algorithm 'wrongly flags' 200,000 people for fraud

uk.news.yahoo.com

DWP algorithm wrongly forces over 200,000 people through benefit fraud investigations

DWP algorithm wrongly forces over 200,000 people through benefit fraud investigations

thecanary.co

DWP Algorithm Mistakenly Identifies 200,000 Individuals as Potential Fraud Cases

DWP Algorithm Mistakenly Identifies 200,000 Individuals as Potential Fraud Cases

en.econostrum.info

DWP wrongly suspects hundreds of thousands of benefits claimants of fraud

DWP wrongly suspects hundreds of thousands of benefits claimants of fraud

walesonline.co.uk

L'algorithme DWP signale à tort 200 000 personnes pour d'éventuelles fraudes et erreurs
theguardian.com · 2024
Traduit par IA

Plus de 200 000 personnes ont fait l’objet d’une enquête à tort pour fraude et erreur en matière d’aide au logement après que les performances d’un algorithme gouvernemental se soient révélées bien en deçà des attentes, peut révéler le Guar…

DWP algorithm 'wrongly flags' 200,000 people for fraud
uk.news.yahoo.com · 2024

200,000 Department for Work and Pensions claimants have been warned they have "wrongly" been triggered for "fraud and error". The DWP algorithm has "wrongly flagged" 200,000 people for possible fraud and error, according to the Guardian new…

DWP algorithm wrongly forces over 200,000 people through benefit fraud investigations
thecanary.co · 2024

The Canary has previously reported how the Department for Work and Pensions (DWP) reliance on AI and algorithmic technology for benefit fraud detection could put disabled and chronically ill claimants at risk. Now, new data obtained by a ca…

DWP Algorithm Mistakenly Identifies 200,000 Individuals as Potential Fraud Cases
en.econostrum.info · 2024

According to the Guardian, more than 200,000 people have been wrongfully investigated for housing benefit fraud and error after a government algorithm failed to operate as expected.

Two-thirds of claims marked as potentially high risk by a …

DWP wrongly suspects hundreds of thousands of benefits claimants of fraud
walesonline.co.uk · 2024

More than 200,000 people have been wrongly investigated for housing benefit fraud and error. Over the last three years two-thirds of claims flagged as potentially high risk by a Department for Work and Pensions (DWP) automated system were a…

Variantes

Une "Variante" est un incident qui partage les mêmes facteurs de causalité, produit des dommages similaires et implique les mêmes systèmes intelligents qu'un incident d'IA connu. Plutôt que d'indexer les variantes comme des incidents entièrement distincts, nous listons les variations d'incidents sous le premier incident similaire soumis à la base de données. Contrairement aux autres types de soumission à la base de données des incidents, les variantes ne sont pas tenues d'avoir des rapports en preuve externes à la base de données des incidents. En savoir plus sur le document de recherche.

Incidents similaires

Selected by our editors
UK Government AI Allegedly Targets Disproportionate Numbers of Certain Nationals for Fraud Review

MP raises concern over Bulgarian nationals’ UK benefit suspensions

Dec 2021 · 13 rapports
Par similarité textuelle

Did our AI mess up? Flag the unrelated incidents

Opaque Fraud Detection Algorithm by the UK’s Department of Work and Pensions Allegedly Discriminated against People with Disabilities

DWP urged to reveal algorithm that ‘targets’ disabled for benefit fraud

Oct 2019 · 6 rapports
ETS Used Allegedly Flawed Voice Recognition Evidence to Accuse and Assess Scale of Cheating, Causing Thousands to be Deported from the UK

The English test that ruined thousands of lives

Jan 2014 · 1 rapport
Facial Recognition Trial Performed Poorly at Notting Hill Carnival

Don’t Believe the Algorithm

Aug 2017 · 4 rapports
Incident précédentProchain incident

Incidents similaires

Selected by our editors
UK Government AI Allegedly Targets Disproportionate Numbers of Certain Nationals for Fraud Review

MP raises concern over Bulgarian nationals’ UK benefit suspensions

Dec 2021 · 13 rapports
Par similarité textuelle

Did our AI mess up? Flag the unrelated incidents

Opaque Fraud Detection Algorithm by the UK’s Department of Work and Pensions Allegedly Discriminated against People with Disabilities

DWP urged to reveal algorithm that ‘targets’ disabled for benefit fraud

Oct 2019 · 6 rapports
ETS Used Allegedly Flawed Voice Recognition Evidence to Accuse and Assess Scale of Cheating, Causing Thousands to be Deported from the UK

The English test that ruined thousands of lives

Jan 2014 · 1 rapport
Facial Recognition Trial Performed Poorly at Notting Hill Carnival

Don’t Believe the Algorithm

Aug 2017 · 4 rapports

Recherche

  • Définition d'un « incident d'IA »
  • Définir une « réponse aux incidents d'IA »
  • Feuille de route de la base de données
  • Travaux connexes
  • Télécharger la base de données complète

Projet et communauté

  • À propos de
  • Contacter et suivre
  • Applications et résumés
  • Guide de l'éditeur

Incidents

  • Tous les incidents sous forme de liste
  • Incidents signalés
  • File d'attente de soumission
  • Affichage des classifications
  • Taxonomies

2024 - AI Incident Database

  • Conditions d'utilisation
  • Politique de confidentialité
  • Open twitterOpen githubOpen rssOpen facebookOpen linkedin
  • ecd56df