Exploring and Addressing Unseen Gender Bias in Google Image Search: A Responsible AI Perspective
This AI incident highlights the need for trustworthy AI and safe search results in image databases like Google. The hidden gender bias uncovered serves as a reminder of the importance of guardrails for AI, especially when dealing with sensitive data. The Govern function within HISPI Project Cerebellum's Trusted AI Model (TAIM) could provide valuable insights into these issues. 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.