Skip to Content
logologo
AI Incident Database
Open TwitterOpen RSS FeedOpen FacebookOpen LinkedInOpen GitHub
Open Menu
Discover
Submit
  • Welcome to the AIID
  • Discover Incidents
  • Spatial View
  • Table View
  • List view
  • Entities
  • Taxonomies
  • Submit Incident Reports
  • Submission Leaderboard
  • Blog
  • AI News Digest
  • Risk Checklists
  • Random Incident
  • Sign Up
Collapse
Discover
Submit
  • Welcome to the AIID
  • Discover Incidents
  • Spatial View
  • Table View
  • List view
  • Entities
  • Taxonomies
  • Submit Incident Reports
  • Submission Leaderboard
  • Blog
  • AI News Digest
  • Risk Checklists
  • Random Incident
  • Sign Up
Collapse

Incident 18: Gender Biases of Google Image Search

Description: Google Image returns results that under-represent women in leadership roles, notably with the first photo of a female "CEO" being a Barbie doll after 11 rows of male CEOs.

Tools

New ReportNew ReportNew ResponseNew ResponseDiscoverDiscoverView HistoryView History

Entities

View all entities
Alleged: Google developed and deployed an AI system, which harmed Women.

Incident Stats

Incident ID
18
Report Count
11
Incident Date
2015-04-04
Editors
Sean McGregor
Applied Taxonomies
CSETv0, CSETv1, GMF, MIT

CSETv1 Taxonomy Classifications

Taxonomy Details

Incident Number

The number of the incident in the AI Incident Database.
 

18

Notes (special interest intangible harm)

Input any notes that may help explain your answers.
 

Significant gender/sex bias in google search image results

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
 

2015

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
 

04

Date of Incident Day

The day on which the incident occurred. If a precise date is unavailable, leave blank. Enter in the format of DD
 

09

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.
 

High

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.
 

Yes

Data Inputs

A brief description of the data that the AI system(s) used or were trained on.
 

open source internet, user requests, user searches

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

+9
Who’s a CEO? Google image results can shift gender biases
Google’s algorithm shows prestigious job ads to men, but not to women. Here’s why that should worry you.Why is it still so hard to find women CEOs on Google Images?
Who’s a CEO? Google image results can shift gender biases

Who’s a CEO? Google image results can shift gender biases

washington.edu

Google Search thinks the most important female CEO is Barbie

Google Search thinks the most important female CEO is Barbie

theverge.com

The first woman CEO to appear in a Google Images search is ... CEO Barbie

The first woman CEO to appear in a Google Images search is ... CEO Barbie

pcworld.com

Be Careful What You Google

Be Careful What You Google

theatlantic.com

Looking for 'doctor' or 'cop' in Google Image Search delivers crazy sexist results

Looking for 'doctor' or 'cop' in Google Image Search delivers crazy sexist results

splinternews.com

Google Image Search Has A Gender Bias Problem

Google Image Search Has A Gender Bias Problem

huffingtonpost.com

When You Google Image CEO, the First Female Photo on the Results Page Is Barbie

When You Google Image CEO, the First Female Photo on the Results Page Is Barbie

glamour.com

Google Image search for CEO has Barbie as first female result

Google Image search for CEO has Barbie as first female result

bbc.co.uk

The Hidden Gender Bias In Google Image Search

The Hidden Gender Bias In Google Image Search

fastcompany.com

Google’s algorithm shows prestigious job ads to men, but not to women. Here’s why that should worry you.

Google’s algorithm shows prestigious job ads to men, but not to women. Here’s why that should worry you.

washingtonpost.com

Why is it still so hard to find women CEOs on Google Images?

Why is it still so hard to find women CEOs on Google Images?

fastcompany.com

Who’s a CEO? Google image results can shift gender biases
washington.edu · 2015

Who’s a CEO? Google image results can shift gender biases

Jennifer Langston UW News

Getty Images last year created a new online image catalog of women in the workplace – one that countered visual stereotypes on the Internet of moms as frazz…

Google Search thinks the most important female CEO is Barbie
theverge.com · 2015

The University of Washington just released a preview of a study that claims search engine results can influence people's perceptions about how many men or women hold certain jobs. One figure quoted in the preview is that in a Google image s…

The first woman CEO to appear in a Google Images search is ... CEO Barbie
pcworld.com · 2015

The Ellen Pao-Kleiner Perkins trial shone a light on discrimination in the tech industry, but for a more immediate look at the challenges women face in corporate America, look no further than a Google Images search.

Doing a search at the si…

Be Careful What You Google
theatlantic.com · 2015

Google is a modern oracle, and a miraculous one at that. It can lead you to the Perfect Strangers theme song lyrics, or to a satellite image of your childhood neighborhood, or to a blueprint for building a quantum computer. But for as much …

Looking for 'doctor' or 'cop' in Google Image Search delivers crazy sexist results
splinternews.com · 2015

In today's modern professional world men can be doctors, investment bankers, and professors, while women, of course, can be nurses, secretaries, and sexy Halloween costume models—at least according to Google Image Search.

Why did we spend a…

Google Image Search Has A Gender Bias Problem
huffingtonpost.com · 2015

Not all doctors or CEOs are men. Not all nurses are women. But you might think otherwise if you searched for these professions in Google images.

It turns out that there's a noticeable gender bias in the image search results for some jobs, a…

When You Google Image CEO, the First Female Photo on the Results Page Is Barbie
glamour.com · 2015

Try this: Google image "CEO." Notice anything? The first female Google image search result for "CEO" appears TWELVE rows down—and it's Barbie.

A recent study conducted at the University of Washington sought to examine how well female repres…

Google Image search for CEO has Barbie as first female result
bbc.co.uk · 2015

Search the term "CEO" in Google Images and the first picture of woman you get is a picture of Barbie in a suit.

This "gender bias" has become apparent after a paper was published showing that many image searches for specific occupations fav…

The Hidden Gender Bias In Google Image Search
fastcompany.com · 2015

Just when you thought biases were a completely human construct, more evidence suggests that both algorithms and interfaces could be biased, too.

ADVERTISEMENT

The latest example of this is from a study conducted by researchers from Universi…

Google’s algorithm shows prestigious job ads to men, but not to women. Here’s why that should worry you.
washingtonpost.com · 2015

Fresh off the revelation that Google image searches for “CEO” only turn up pictures of white men, there’s new evidence that algorithmic bias is, alas, at it again. In a paper published in April, a team of researchers from Carnegie Mellon Un…

Why is it still so hard to find women CEOs on Google Images?
fastcompany.com · 2018

“You can’t be what you can’t see,” Marie Wilson of the White House Project said back in 2010. According to a new study, Google Images may not be helping to improve the situation.

AdView analyzed employment data to determine the number of wo…

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.

Similar Incidents

By textual similarity

Did our AI mess up? Flag the unrelated incidents

Sexist and Racist Google Adsense Advertisements

Sexist and Racist Google Adsense Advertisements

Jan 2013 · 27 reports
AI Beauty Judge Did Not Like Dark Skin

AI Beauty Judge Did Not Like Dark Skin

Sep 2016 · 10 reports
Biased Google Image Results

Biased Google Image Results

Mar 2016 · 18 reports
Previous IncidentNext Incident

Similar Incidents

By textual similarity

Did our AI mess up? Flag the unrelated incidents

Sexist and Racist Google Adsense Advertisements

Sexist and Racist Google Adsense Advertisements

Jan 2013 · 27 reports
AI Beauty Judge Did Not Like Dark Skin

AI Beauty Judge Did Not Like Dark Skin

Sep 2016 · 10 reports
Biased Google Image Results

Biased Google Image Results

Mar 2016 · 18 reports

Research

  • Defining an “AI Incident”
  • Defining an “AI Incident Response”
  • Database Roadmap
  • Related Work
  • Download Complete Database

Project and Community

  • About
  • Contact and Follow
  • Apps and Summaries
  • Editor’s Guide

Incidents

  • All Incidents in List Form
  • Flagged Incidents
  • Submission Queue
  • Classifications View
  • Taxonomies

2024 - AI Incident Database

  • Terms of use
  • Privacy Policy
  • Open twitterOpen githubOpen rssOpen facebookOpen linkedin
  • 86fe0f5