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Incident 409: Facial Recognition Researchers Used YouTube Videos of Transgender People without Consent

Description: YouTube videos of transgender people used by researchers to study facial recognition during gender transitions were used and distributed without permission.

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Entities

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Alleged: University of North Carolina Wilmington , Karl Ricanek and Gayathri Mahalingam developed and deployed an AI system, which harmed Transgender YouTubers and transgender people.

Incident Stats

Incident ID
409
Report Count
3
Incident Date
2013-09-13
Editors
Khoa Lam
Applied Taxonomies
CSETv1, MIT

CSETv1 Taxonomy Classifications

Taxonomy Details

Incident Number

The number of the incident in the AI Incident Database.
 

409

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
 

2013

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
 

Estimated Date

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

Yes

Multiple AI Interaction

“Yes” if two or more independently operating AI systems were involved. “No” otherwise.
 

no

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
 

2.1. Compromise of privacy by obtaining, leaking or correctly inferring sensitive information

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. Privacy & Security

Entity

Which, if any, entity is presented as the main cause of the risk
 

Human

Timing

The stage in the AI lifecycle at which the risk is presented as occurring
 

Pre-deployment

Intent

Whether the risk is presented as occurring as an expected or unexpected outcome from pursuing a goal
 

Intentional

Incident Reports

Reports Timeline

Incident OccurrenceTransgender YouTubers had their videos grabbed to train facial recognition software+1
Prominent facial recognition researcher scraped videos of trans people, left dataset exposed
Transgender YouTubers had their videos grabbed to train facial recognition software

Transgender YouTubers had their videos grabbed to train facial recognition software

theverge.com

Prominent facial recognition researcher scraped videos of trans people, left dataset exposed

Prominent facial recognition researcher scraped videos of trans people, left dataset exposed

biometricupdate.com

How a flawed biometrics research project singled out LGBTQ+ individuals

How a flawed biometrics research project singled out LGBTQ+ individuals

venturebeat.com

Transgender YouTubers had their videos grabbed to train facial recognition software
theverge.com · 2017

About five or six years ago, one of Karl Ricanek’s students showed him a video on YouTube. It was a time lapse of a person undergoing hormone replacement therapy, or HRT, in order to transition genders. “At the time, we were working on faci…

Prominent facial recognition researcher scraped videos of trans people, left dataset exposed
biometricupdate.com · 2022

New research finds that a controversial facial recognition dataset of trans people remained available online for years after the initial controversy of its existence, reports AlgorithmWatch. The academic responsible is a U.S. government adv…

How a flawed biometrics research project singled out LGBTQ+ individuals
venturebeat.com · 2022

Last year was a grim, record-setting year for violence against transgender individuals, and the Human Rights Campaign is tracking data that shows 2022 is on a similar pace. Outside of physical violence, other forms of attacks can harm these…

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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