Skip to Content
logologo
AI Incident Database
Open TwitterOpen RSS FeedOpen FacebookOpen LinkedInOpen GitHub
Open Menu
Descubrir
Enviar
  • Bienvenido a la AIID
  • Descubrir Incidentes
  • Vista espacial
  • Vista Tabular
  • Vista de lista
  • Entidades
  • Taxonomías
  • Enviar Informes de Incidentes
  • Ranking de Reportadores
  • Blog
  • Resumen de noticias de IA
  • Control de Riesgos
  • Incidente aleatorio
  • Registrarse
Colapsar
Descubrir
Enviar
  • Bienvenido a la AIID
  • Descubrir Incidentes
  • Vista espacial
  • Vista Tabular
  • Vista de lista
  • Entidades
  • Taxonomías
  • Enviar Informes de Incidentes
  • Ranking de Reportadores
  • Blog
  • Resumen de noticias de IA
  • Control de Riesgos
  • Incidente aleatorio
  • Registrarse
Colapsar

Incidente 82: #LekkiMassacre: Why Facebook labelled content from October 20 incident ‘false’

Descripción: Facebook incorrectly labels content relating to an incident between #EndSARS protestors and the Nigerian army as misinformation.

Herramientas

Nuevo InformeNuevo InformeNueva RespuestaNueva RespuestaDescubrirDescubrirVer HistorialVer Historial

Entidades

Ver todas las entidades
Presunto: un sistema de IA desarrollado e implementado por Facebook, perjudicó a Facebook users y Facebook users interested in the Lekki Massacre incident.

Estadísticas de incidentes

ID
82
Cantidad de informes
1
Fecha del Incidente
2020-10-21
Editores
Sean McGregor, Khoa Lam
Applied Taxonomies
CSETv0, CSETv1, GMF, MIT

Clasificaciones de la Taxonomía CSETv0

Detalles de la Taxonomía

Problem 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

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.
 

Medium

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.
 

user content (textposts, images, videos)

Clasificaciones de la Taxonomía CSETv1

Detalles de la Taxonomía

Incident Number

The number of the incident in the AI Incident Database.
 

82

Clasificaciones de la Taxonomía MIT

Machine-Classified
Detalles de la Taxonomía

Risk Subdomain

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

3.1. False or misleading information

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. Misinformation

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

Incident Occurrence#LekkiMassacre: ¿Por qué Facebook etiquetó el contenido del incidente del 20 de octubre como "falso"?
#LekkiMassacre: ¿Por qué Facebook etiquetó el contenido del incidente del 20 de octubre como "falso"?

#LekkiMassacre: ¿Por qué Facebook etiquetó el contenido del incidente del 20 de octubre como "falso"?

techpoint.africa

#LekkiMassacre: ¿Por qué Facebook etiquetó el contenido del incidente del 20 de octubre como "falso"?
techpoint.africa · 2020
Traducido por IA

El miércoles 21 de octubre de 2020, varios contenidos que contenían imágenes relacionadas con el desafortunado incidente ocurrido el martes en la puerta de peaje de Lekki en Lagos, Nigeria, se marcaron como información errónea en Facebook e…

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.

Incidentes Similares

Por similitud de texto

Did our AI mess up? Flag the unrelated incidents

Deepfake Video of Ukrainian President Yielding to Russia Posted on Ukrainian Websites and Social Media

Russian War Report: Hacked news program and deepfake video spread false Zelenskyy claims

Mar 2022 · 9 informes
Facebook translates 'good morning' into 'attack them', leading to arrest

Facebook translates 'good morning' into 'attack them', leading to arrest

Oct 2017 · 26 informes
Indian Political App Tek Fog Allegedly Hijacked Trends and Manipulated Public Opinion on Other Social Media Platforms

India’s Tek Fog Shrouds an Escalating Political War

Apr 2020 · 3 informes
Incidente AnteriorSiguiente Incidente

Incidentes Similares

Por similitud de texto

Did our AI mess up? Flag the unrelated incidents

Deepfake Video of Ukrainian President Yielding to Russia Posted on Ukrainian Websites and Social Media

Russian War Report: Hacked news program and deepfake video spread false Zelenskyy claims

Mar 2022 · 9 informes
Facebook translates 'good morning' into 'attack them', leading to arrest

Facebook translates 'good morning' into 'attack them', leading to arrest

Oct 2017 · 26 informes
Indian Political App Tek Fog Allegedly Hijacked Trends and Manipulated Public Opinion on Other Social Media Platforms

India’s Tek Fog Shrouds an Escalating Political War

Apr 2020 · 3 informes

Investigación

  • Definición de un “Incidente de IA”
  • Definición de una “Respuesta a incidentes de IA”
  • Hoja de ruta de la base de datos
  • Trabajo relacionado
  • Descargar Base de Datos Completa

Proyecto y Comunidad

  • Acerca de
  • Contactar y Seguir
  • Aplicaciones y resúmenes
  • Guía del editor

Incidencias

  • Todos los incidentes en forma de lista
  • Incidentes marcados
  • Cola de envío
  • Vista de clasificaciones
  • Taxonomías

2024 - AI Incident Database

  • Condiciones de uso
  • Política de privacidad
  • Open twitterOpen githubOpen rssOpen facebookOpen linkedin
  • ecd56df