Descripción: Researchers have argued that the Department for Work and Pensions' Universal Credit system disproportionately impacts single mothers. Automated processes in the system, designed to determine eligibility and detect fraud, are reported to have introduced biases, leading to financial instability and hardship. The algorithms allegedly miscalculate earnings and delay childcare reimbursements, in turn exacerbating income volatility and debt among single mothers.
Entidades
Ver todas las entidadesPresunto: un sistema de IA desarrollado e implementado por Department for Work and Pensions (DWP), perjudicó a Single mothers y British single mothers.
Estadísticas de incidentes
Risk Subdomain
A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
1.1. Unfair discrimination and misrepresentation
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.
- 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
Informes del Incidente
Cronología de Informes
The Universal Credit system is disproportionately impacting working single mothers, it has been claimed.
Universal Credit is managed by the Department for Work and Pensions (DWP) and is the most common UK benefit with 6.7million people clai…
Variantes
Una "Variante" es un incidente que comparte los mismos factores causales, produce daños similares e involucra los mismos sistemas inteligentes que un incidente de IA conocido. En lugar de indexar las variantes como incidentes completamente separados, enumeramos las variaciones de los incidentes bajo el primer incidente similar enviado a la base de datos. A diferencia de otros tipos de envío a la base de datos de incidentes, no se requiere que las variantes tengan informes como evidencia externa a la base de datos de incidentes. Obtenga más información del trabajo de investigación.
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