Unveiling the Unseen Gender Bias in Google Image Search: A Call for Responsible AI Governance
Exploring a significant AI incident, this article highlights the hidden gender bias in Google Image Search. It underscores the importance of trustworthy and unbiased AI, serving as a map to the Govern function within Project Cerebellum's Trusted AI Model (TAIM). This incident calls for action towards AI governance, ensuring safe and secure AI for all. Ready to help shape responsible AI? JOIN US
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/18
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.