Bias in Google Image Search: A Harmful Consequence of Unregulated AI

Recent studies have uncovered a shocking disparity in Google's image search results when querying 'Three Black Teenagers' versus 'Three White Teenagers'. This incident underscores the urgent need for responsible AI governance and trustworthy AI models to prevent such harmful biases. HISPI Project Cerebellum TAIM, our robust AI incident database, maps, measures, and manages such incidents to ensure safe and secure AI usage. Engage with us through JOIN US to learn more about harm prevention and the role you can play in creating a trustworthy digital future.

Matched TAIM controls

Suggested mapping from embedding similarity (not a formal assessment). Browse all TAIM controls

GOVERN 3.1 — similarity 0.493, rank 1. TAIM detail and related incidents →
MAP 1.6 — similarity 0.493, rank 2. TAIM detail and related incidents →
MAP 4.1 — similarity 0.484, rank 3. TAIM detail and related incidents →

Source

Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/53

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.