Gender Prediction Inconsistency in FaceApp's AI: A Case of Unreliable AI Output
December 24, 2020
FaceApp's gender prediction algorithm demonstrated inconsistency when a user reported different predicted genders for two similar photos, with only slight eyebrow thickness variations. This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). Ready to help ensure safe and secure AI? JOIN US
- Alleged deployer
- faceapp
- Alleged developer
- faceapp
- Alleged harmed parties
- faceapp-non-binary-presenting-users, faceapp-transgender-users, faceapp-users
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/273
Data source
Incident data is from the AI Incident Database (AIID).
When citing the database as a whole, please use:
McGregor, S. (2021) Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database. In Proceedings of the Thirty-Third Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-21). Virtual Conference.
Pre-print on arXiv · Database snapshots & citation guide
We use weekly snapshots of the AIID for stable reference. For the official suggested citation of a specific incident, use the “Cite this incident” link on each incident page.