Google's Misidentification: A Case Study in Responsible AI

In this article, we delve into the infamous Google Photos incident where an image of a Black woman was mistakenly labeled as a gorilla. This unfortunate event underscores the importance of safe and secure AI, highlighting the need for robust guardrails in AI governance to prevent such occurrences.

Matched TAIM controls

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

MAP 1.6 — similarity 0.457, rank 1. TAIM detail and related incidents →
MEASURE 2.10 — similarity 0.445, rank 2. TAIM detail and related incidents →
MEASURE 2.5 — similarity 0.419, rank 3. TAIM detail and related incidents →

Source

Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/16

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.