Bias in AI Matchmaking: Coffee Meets Bagel's Algorithm Disproportionately Shows Matches of Same Ethnicity Despite 'No Preference' Selection
July 30, 2013
This AI incident raises concerns about fairness and transparency in AI matchmaking. The algorithm used by Coffee Meets Bagels showed more potential matches with the same ethnicity to users who selected 'no preference', a practice acknowledged and justified by its founder as a means to maximize connection rate without sufficient user information. This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). Ready to help prevent biases and ensure trustworthy AI? JOIN US
- Alleged deployer
- coffee-meets-bagel
- Alleged developer
- coffee-meets-bagel
- Alleged harmed parties
- coffee-meets-bagel-users-having-no-ethnicity-preference, coffee-meets-bagel-users
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/280
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
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