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Incident 93: HUD charges Facebook with enabling housing discrimination

Description: 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.

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Entities

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Alleged: Facebook developed and deployed an AI system, which harmed Facebook users of minority groups , non-American-born Facebook users , non-Christian Facebook users , Facebook users interested in accessibility and Facebook users interested in Hispanic culture.

Incident Stats

Incident ID
93
Report Count
4
Incident Date
2018-08-13
Editors
Sean McGregor, Khoa Lam
Applied Taxonomies
CSETv0, CSETv1, GMF, MIT

CSETv1 Taxonomy Classifications

Taxonomy Details

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

CSETv0 Taxonomy Classifications

Taxonomy Details

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

MIT Taxonomy Classifications

Machine-Classified
Taxonomy Details

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

Incident Reports

Reports Timeline

Incident Occurrence+1
HUD charges Facebook with enabling housing discrimination
HUD v. FacebookJustice Department Secures Groundbreaking Settlement Agreement with Meta Platforms, Formerly Known as Facebook, to Resolve Allegations of Discriminatory Advertising
HUD charges Facebook with enabling housing discrimination

HUD charges Facebook with enabling housing discrimination

thehill.com

HUD Is Suing Facebook For Housing Discrimination

HUD Is Suing Facebook For Housing Discrimination

forbes.com

HUD v. Facebook

HUD v. Facebook

nafcu.org

Justice Department Secures Groundbreaking Settlement Agreement with Meta Platforms, Formerly Known as Facebook, to Resolve Allegations of Discriminatory Advertising

Justice Department Secures Groundbreaking Settlement Agreement with Meta Platforms, Formerly Known as Facebook, to Resolve Allegations of Discriminatory Advertising

justice.gov

HUD charges Facebook with enabling housing discrimination
thehill.com · 2019

The Department of Housing and Urban Development (HUD) on Thursday charged Facebook with encouraging and enabling housing discrimination through its targeted advertising practices.

HUD is charging Facebook with violating the Fair Housing Act…

HUD Is Suing Facebook For Housing Discrimination
forbes.com · 2019

The federal government is suing Facebook over allegations of housing discrimination in the social network's advertising platform.

The U.S. Department of Housing and Urban Development on Thursday announced that it is charging Facebook with v…

HUD v. Facebook
nafcu.org · 2019

Last week I watched a webinar (additional cost) that is available on the NAFCU Online Training Center titled Red Flags for Fair Lending. The webinar was presented live in March of this year on the same day that the United States Department …

Justice Department Secures Groundbreaking Settlement Agreement with Meta Platforms, Formerly Known as Facebook, to Resolve Allegations of Discriminatory Advertising
justice.gov · 2022

The Department of Justice announced today that it has obtained a settlement agreement resolving allegations that Meta Platforms Inc., formerly known as Facebook Inc., has engaged in discriminatory advertising in violation of the Fair Housin…

Variants

A "variant" is an incident that shares the same causative factors, produces similar harms, and involves the same intelligent systems as a known AI incident. Rather than index variants as entirely separate incidents, we list variations of incidents under the first similar incident submitted to the database. Unlike other submission types to the incident database, variants are not required to have reporting in evidence external to the Incident Database. Learn more from the research paper.

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