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Incident 115: Genderify’s AI to Predict a Person’s Gender Revealed by Free API Users to Exhibit Bias

Description: A company's AI predicting a person's gender based on their name, email address, or username was reported by its users to show biased and inaccurate results.

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Alleged: Genderify developed and deployed an AI system, which harmed Genderify customers and gender minority groups.

Incident Stats

Incident ID
115
Report Count
3
Incident Date
2020-07-28
Editors
Sean McGregor, Khoa Lam
Applied Taxonomies
CSETv1, GMF, MIT

CSETv1 Taxonomy Classifications

Taxonomy Details

Incident Number

The number of the incident in the AI Incident Database.
 

115

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.
 

no

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.
 

There is no evidence or indication that the system led to any special interest intangible harms through its use or deployment.

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

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
 

07

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
 

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 OccurrenceService that uses AI to identify gender based on names looks incredibly biased+1
AI-Powered ‘Genderify’ Platform Shut Down After Bias-Based Backlash
Service that uses AI to identify gender based on names looks incredibly biased

Service that uses AI to identify gender based on names looks incredibly biased

theverge.com

AI-Powered ‘Genderify’ Platform Shut Down After Bias-Based Backlash

AI-Powered ‘Genderify’ Platform Shut Down After Bias-Based Backlash

syncedreview.com

Someone made an AI that predicted gender from email addresses, usernames. It went about as well as expected

Someone made an AI that predicted gender from email addresses, usernames. It went about as well as expected

theregister.com

Service that uses AI to identify gender based on names looks incredibly biased
theverge.com · 2020

Some tech companies make a splash when they launch, others seem to bellyflop.

Genderify, a new service that promised to identify someone’s gender by analyzing their name, email address, or username with the help AI, looks firmly to be in th…

AI-Powered ‘Genderify’ Platform Shut Down After Bias-Based Backlash
syncedreview.com · 2020

Just hours after making waves and triggering a backlash on social media, Genderify — an AI-powered tool designed to identify a person’s gender by analyzing their name, username or email address — has been completely shut down.

Launched last…

Someone made an AI that predicted gender from email addresses, usernames. It went about as well as expected
theregister.com · 2020

The creators of a controversial tool that attempted to use AI to predict people's gender from their internet handle or email address have shut down their service after a huge backlash.

The Genderify app launched this month, and invited peop…

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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