Google researchers labeled gender categories in their smile-detection model as 'Gender 1' and 'Gender 2' specifically to reduce the risk of introducing unconscious societal bias.
Notes on verification
Confirmed directly by the primary source (Google's arXiv paper) which explicitly states the rationale for using generic labels, corroborated by independent tech press coverage (The Register). [tier=gold indep_score=0.867 clusters=3 claim_tier=notable]
Sources
- Google’s New AI Smile Detector Shows How Embracing Race and Gender Can Reduce Bias (seed:technology_and_ai)
- https://www.theregister.com/software/2017/12/06/google-learns-to-smile-because-ais-bad-at-it/798222 (corroboration)
- https://arxiv.org/pdf/1712.00193 (corroboration)
- https://research.google/pubs/pub46513/ (corroboration)
- https://ar5iv.labs.arxiv.org/html/1712.00193 (corroboration)