Description: AlgorithmWatch tested spam filtering algorithms across Gmail, Yahoo, Outlook, GMX, and LaPoste. Their findings reportedly showed that Microsoft Outlook’s spam filter flagged emails based on specific keywords that led to racial and content-based biases blocking legitimate communications. Emails mentioning Nigeria or containing certain financial and sexual health terms were found to be disproportionately marked as spam.
Entidades
Ver todas las entidadesAlleged: Yahoo , LaPoste , GMX , Microsoft y Google developed an AI system deployed by Yahoo , Outlook , LaPoste , GMX y Gmail, which harmed Yahoo! Mail users , Microsoft Outlook users , LaPoste users , GMX users y Gmail Users.
Sistemas de IA presuntamente implicados: Yahoo! Mail's spam filter , SpamAssassin , Microsoft Outlook's spam filter , LaPoste Mail's spam filter , GMX Mail's spam filter y Gmail's spam filter
Clasificaciones de la Taxonomía CSETv0
Detalles de la TaxonomíaProblem Nature
Indicates which, if any, of the following types of AI failure describe the incident: "Specification," i.e. the system's behavior did not align with the true intentions of its designer, operator, etc; "Robustness," i.e. the system operated unsafely because of features or changes in its environment, or in the inputs the system received; "Assurance," i.e. the system could not be adequately monitored or controlled during operation.
Specification, Robustness
Physical System
Where relevant, indicates whether the AI system(s) was embedded into or tightly associated with specific types of hardware.
Software only
Level of Autonomy
The degree to which the AI system(s) functions independently from human intervention. "High" means there is no human involved in the system action execution; "Medium" means the system generates a decision and a human oversees the resulting action; "low" means the system generates decision-support output and a human makes a decision and executes an action.
Unclear/unknown
Nature of End User
"Expert" if users with special training or technical expertise were the ones meant to benefit from the AI system(s)’ operation; "Amateur" if the AI systems were primarily meant to benefit the general public or untrained users.
Amateur
Public Sector Deployment
"Yes" if the AI system(s) involved in the accident were being used by the public sector or for the administration of public goods (for example, public transportation). "No" if the system(s) were being used in the private sector or for commercial purposes (for example, a ride-sharing company), on the other.
No
Data Inputs
A brief description of the data that the AI system(s) used or were trained on.
inbound emails
Clasificaciones de la Taxonomía CSETv1
Detalles de la TaxonomíaIncident Number
The number of the incident in the AI Incident Database.
83
Informes del Incidente
Cronología de Informes
algorithmwatch.org · 2020
- Ver el informe original en su fuente
- Ver el informe en el Archivo de Internet
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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