Incidente 162: translated-es-ETS Used Allegedly Flawed Voice Recognition Evidence to Accuse and Assess Scale of Cheating, Causing Thousands to be Deported from the UK
Descripción: translated-es- International testing organization ETS admits voice recognition as evidence of cheating for thousands of previous TOEIC test-takers that reportedly included wrongfully accused people, causing them to be deported without an appeal process or seeing their incriminating evidence.
Entidades
Ver todas las entidadesPresunto: un sistema de IA desarrollado e implementado por ETS, perjudicó a UK ETS past test takers , UK ETS test takers y UK Home Office.
Clasificaciones de la Taxonomía CSETv1
Detalles de la TaxonomíaIncident Number
The number of the incident in the AI Incident Database.
162
Risk Subdomain
A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
7.3. Lack of capability or robustness
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.
- AI system safety, failures, and limitations
Entity
Which, if any, entity is presented as the main cause of the risk
Human
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
Intentional
Informes del Incidente
Cronología de Informes
Una investigación de la BBC ha generado nuevas dudas sobre la evidencia utilizada para expulsar a miles de personas del Reino Unido por presuntamente hacer trampa en una prueba de inglés.
El testimonio de los denunciantes y los documentos o…
Variantes
Una "Variante" es un incidente de IA similar a un caso conocido—tiene los mismos causantes, daños y sistema de IA. En lugar de enumerarlo por separado, lo agrupamos bajo el primer incidente informado. A diferencia de otros incidentes, las variantes no necesitan haber sido informadas fuera de la AIID. Obtenga más información del trabajo de investigación.
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