Google Translate's Implicit Gender Bias: A Case Study on Responsible AI Harm Prevention
April 13, 2017
Learn about a 2016 Cornell University study that revealed Google Translate's pattern of gender assignment, demonstrating implicit bias against women in the context of occupations. This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). Ready to help shape responsible AI and prevent such biases? JOIN US
- Alleged deployer
- Alleged developer
- Alleged harmed parties
- women
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/59
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.