Registro de citas para el Incidente 83

Description: Gmail, Yahoo, Outlook, GMX, and LaPoste email inbox sites showed racial and content-based biases when AlgorithmWatch tested their spam box filtering algorithms.

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Presunto: un sistema de IA desarrollado e implementado por Gmail , Outlook , Yahoo , GMX y LaPoste, perjudicó a email users.

Estadísticas de incidentes

ID
83
Cantidad de informes
1
Fecha del Incidente
2020-10-15
Editores
Sean McGregor, Khoa Lam

Clasificaciones de la Taxonomía CSETv0

Detalles de la Taxonomía

Full Description

Gmail, Yahoo, Outlook, GMX, and LaPoste email inbox sites showed racial and content-based biases when AlgorithmWatch tested their spam box filtering algorithms. AlgorithmWatch sent hundreds of emails to 10 email accounts on the listed sites, and noticed emails would be filtered into the spam box if certain words were within the body of the email. A Nigerian students internship application was marked spam, but when the word "Nigeria" was removed it was delivered to the inbox. The same applied to a "sex education" email that was forwarded to inbox after removing "sex". A Joe Biden speech went through when the words "loan, investment, billion" were removed.

Short Description

Gmail, Yahoo, Outlook, GMX, and LaPoste email inbox sites showed racial and content-based biases when AlgorithmWatch tested their spam box filtering algorithms.

Severity

Unclear/unknown

Harm Distribution Basis

Race, National origin or immigrant status

Harm Type

Harm to civil liberties

AI System Description

Machine learning algorithms used to filter spam emails out of inboxes

System Developer

Gmail, Outlook, Yahoo, GMX, LaPoste

Sector of Deployment

Information and communication

Relevant AI functions

Perception, Cognition, Action

AI Techniques

Language recognition, content filtering

AI Applications

spam filtering

Named Entities

Gmail, Yahoo, Outlook, GMX, LaPoste, SpamAssassin, AlgorithmWatch

Technology Purveyor

Gmail, Yahoo, Outlook

Beginning Date

2020-10-22

Ending Date

2020-10-22

Near Miss

Unclear/unknown

Intent

Unclear

Lives Lost

No

Infrastructure Sectors

Communications

Data Inputs

inbound emails

Informes del Incidente

Los filtros de spam son eficientes y no controversiales. Hasta que los miras.
algorithmwatch.org · 2020

Un experimento revela que Microsoft Outlook marca los mensajes como spam basándose en una sola palabra, como "Nigeria". Los filtros de spam en gran parte no están auditados y podrían discriminar injustamente.

En un experimento, AlgorithmWat…

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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