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Incident 103: Twitter’s Image Cropping Tool Allegedly Showed Gender and Racial Bias

Description: Twitter's photo cropping algorithm was revealed by researchers to favor white and women faces in photos containing multiple faces, prompting the company to stop its use on mobile platform.

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Alleged: Twitter developed and deployed an AI system, which harmed Twitter Users , Twitter non-white users and Twitter non-male users.

Incident Stats

Incident ID
103
Report Count
5
Incident Date
2020-09-18
Editors
Sean McGregor, Khoa Lam
Applied Taxonomies
GMF, CSETv1, MIT

CSETv1 Taxonomy Classifications

Taxonomy Details

Incident Number

The number of the incident in the AI Incident Database.
 

103

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

Notes (AI special interest intangible harm)

If for 5.5 you select unclear or leave it blank, please provide a brief description of why. You can also add notes if you want to provide justification for a level.
 

The cropping neutral network would crop the preview image in way that focused more on individuals with lighter completions, younger, female, or without disabilities.

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
 

2020

GMF Taxonomy Classifications

Taxonomy Details

Known AI Goal Snippets

One or more snippets that justify the classification.
 

(Snippet Text: Twitter‘s algorithm for automatically cropping images attached to tweets often doesn’t focus on the important content in them. , Related Classifications: Image Cropping)

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

+1
Why Twitter’s image cropping algorithm appears to have white bias
+1
Twitter's Photo Crop Algorithm Favors White Faces and Women
Twitter launches bug bounty contest to detect algorithmic biasTwitter's AI bounty program reveals bias toward young, pretty white people
Why Twitter’s image cropping algorithm appears to have white bias

Why Twitter’s image cropping algorithm appears to have white bias

thenextweb.com

Twitter's Photo Crop Algorithm Favors White Faces and Women

Twitter's Photo Crop Algorithm Favors White Faces and Women

wired.com

Sharing learnings about our image cropping algorithm

Sharing learnings about our image cropping algorithm

blog.twitter.com

Twitter launches bug bounty contest to detect algorithmic bias

Twitter launches bug bounty contest to detect algorithmic bias

engadget.com

Twitter's AI bounty program reveals bias toward young, pretty white people

Twitter's AI bounty program reveals bias toward young, pretty white people

engadget.com

Why Twitter’s image cropping algorithm appears to have white bias
thenextweb.com · 2020

Twitter‘s algorithm for automatically cropping images attached to tweets often doesn’t focus on the important content in them. A bother, for sure, but it seems like a minor one on the surface. However, over the weekend, researchers found th…

Twitter's Photo Crop Algorithm Favors White Faces and Women
wired.com · 2021

A study of 10,000 images found bias in what the system chooses to highlight. Twitter has stopped using it on mobile, and will consider ditching it on the web.

LAST FALL, CANADIAN student Colin Madland noticed that Twitter’s automatic croppi…

Sharing learnings about our image cropping algorithm
blog.twitter.com · 2021

In October 2020, we heard feedback from people on Twitter that our image cropping algorithm didn’t serve all people equitably. As part of our commitment to address this issue, we also shared that we'd analyze our model again for bias. Over …

Twitter launches bug bounty contest to detect algorithmic bias
engadget.com · 2021

Twitter has laid out plans for a bug bounty competition with a difference. This time around, instead of paying researchers who uncover security issues, Twitter will reward those who find as-yet undiscovered examples of bias in its image-cro…

Twitter's AI bounty program reveals bias toward young, pretty white people
engadget.com · 2021

Twitter's first bounty program for AI bias has wrapped up, and there are already some glaring issues the company wants to address. CNET reports that grad student Bogdan Kulynych has discovered that photo beauty filters skew the Twitter sali…

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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