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Incidente 93: HUD charges Facebook with enabling housing discrimination

Descripción: In March 2019 the U.S. Department of Housing and Urban Development charged Facebook with violating the Fair Housing Act by allowing real estate sellers to target advertisements in a discriminatory manner.

Herramientas

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Entidades

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Presunto: un sistema de IA desarrollado e implementado por Facebook, perjudicó a Facebook users of minority groups , non-American-born Facebook users , non-Christian Facebook users , Facebook users interested in accessibility y Facebook users interested in Hispanic culture.

Estadísticas de incidentes

ID
93
Cantidad de informes
4
Fecha del Incidente
2018-08-13
Editores
Sean McGregor, Khoa Lam
Applied Taxonomies
CSETv0, CSETv1, GMF, MIT

Clasificaciones de la Taxonomía CSETv1

Detalles de la Taxonomía

Incident Number

The number of the incident in the AI Incident Database.
 

93

Notes (special interest intangible harm)

Input any notes that may help explain your answers.
 

HUD alleged that Facebook restricted who saw ads based on users' age, gender, zip code, religion, citizenship, and more.

Special Interest Intangible Harm

An assessment of whether a special interest intangible harm occurred. This assessment does not consider the context of the intangible harm, if an AI was involved, or if there is characterizable class or subgroup of harmed entities. It is also not assessing if an intangible harm occurred. It is only asking if a special interest intangible harm occurred.
 

yes

Date of Incident Year

The year in which the incident occurred. If there are multiple harms or occurrences of the incident, list the earliest. If a precise date is unavailable, but the available sources provide a basis for estimating the year, estimate. Otherwise, leave blank. Enter in the format of YYYY
 

2019

Date of Incident Month

The month in which the incident occurred. If there are multiple harms or occurrences of the incident, list the earliest. If a precise date is unavailable, but the available sources provide a basis for estimating the month, estimate. Otherwise, leave blank. Enter in the format of MM
 

03

Estimated Date

“Yes” if the data was estimated. “No” otherwise.
 

No

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 Facebook activity, user social network data

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
 

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.
 
  1. 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

Incident Occurrence+1
HUD acusa a Facebook de permitir la discriminación en la vivienda
HUD contra FacebookEl Departamento de Justicia obtiene un innovador acuerdo de conciliación con Meta Platforms, antes conocido como Facebook, para resolver las acusaciones de publicidad discriminatoria
HUD acusa a Facebook de permitir la discriminación en la vivienda

HUD acusa a Facebook de permitir la discriminación en la vivienda

thehill.com

HUD está demandando a Facebook por discriminación en la vivienda

HUD está demandando a Facebook por discriminación en la vivienda

forbes.com

HUD contra Facebook

HUD contra Facebook

nafcu.org

El Departamento de Justicia obtiene un innovador acuerdo de conciliación con Meta Platforms, antes conocido como Facebook, para resolver las acusaciones de publicidad discriminatoria

El Departamento de Justicia obtiene un innovador acuerdo de conciliación con Meta Platforms, antes conocido como Facebook, para resolver las acusaciones de publicidad discriminatoria

justice.gov

HUD acusa a Facebook de permitir la discriminación en la vivienda
thehill.com · 2019
Traducido por IA

El Departamento de Vivienda y Desarrollo Urbano (HUD) acusó el jueves a Facebook de alentar y permitir la discriminación en la vivienda a través de sus prácticas publicitarias dirigidas.

HUD está acusando a Facebook de violar la Ley de Vivi…

HUD está demandando a Facebook por discriminación en la vivienda
forbes.com · 2019
Traducido por IA

El gobierno federal está demandando a Facebook por acusaciones de discriminación en la vivienda en la plataforma de publicidad de la red social.

El Departamento de Vivienda y Desarrollo Urbano de EE. UU. anunció el jueves que está acusando …

HUD contra Facebook
nafcu.org · 2019
Traducido por IA

La semana pasada vi un seminario web (costo adicional) que está disponible en el Centro de capacitación en línea de NAFCU titulado [Banderas rojas para préstamos justos] (https://onlinetrainingcenter.nafcu.org/KD/training_menu.cfm?pg=tm_mod…

El Departamento de Justicia obtiene un innovador acuerdo de conciliación con Meta Platforms, antes conocido como Facebook, para resolver las acusaciones de publicidad discriminatoria
justice.gov · 2022
Traducido por IA

El Departamento de Justicia anunció hoy que obtuvo un acuerdo de conciliación que resuelve las acusaciones de que Meta Platforms Inc., anteriormente conocida como Facebook Inc., se ha involucrado en publicidad discriminatoria en violación d…

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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