Description: FaceApp’s algorithm was reported by a user to have predicted different genders for two mostly identical facial photos with only a slight difference in eyebrow thickness.
Entities
View all entitiesAlleged: FaceApp developed and deployed an AI system, which harmed FaceApp non-binary presenting users , FaceApp transgender users and FaceApp users.
Incident Stats
Incident ID
273
Report Count
1
Incident Date
2020-12-24
Editors
Khoa Lam
Applied Taxonomies
CSETv1 Taxonomy Classifications
Taxonomy DetailsIncident Number
The number of the incident in the AI Incident Database.
273
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
CSETv1_Annotator-1 Taxonomy Classifications
Taxonomy DetailsIncident Number
The number of the incident in the AI Incident Database.
273
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
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
12
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
24
Estimated Date
“Yes” if the data was estimated. “No” otherwise.
No
Incident Reports
Reports Timeline
twitter.com · 2020
- View the original report at its source
- View the report at the Internet Archive
I’d like to talk a little bit about algorithms, dysphoria, and dysmorphia.
I’ve struggled with algorithms. I’ll often take a picture and run it through FaceApp to get gendered.
I recently noticed that when my eyebrows are thin, it says I am…
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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