Google Search Bias Allegations: Harvard Professor Highlights Arrest Ad Disparity in 'Black' Names

A recent study by a Harvard professor suggests that Google search results may disproportionately display arrest-related ads for names associated with Black individuals, raising concerns about responsible AI governance and harm prevention. The research emphasizes the need for trustworthy AI guardrails in data collection and analysis to prevent such biases.

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

MEASURE 2.10 — similarity 0.484, rank 1. TAIM detail and related incidents →
MAP 1.6 — similarity 0.481, rank 2. TAIM detail and related incidents →
GOVERN 6.1 — similarity 0.436, rank 3. TAIM detail and related incidents →

Source

Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/19

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.

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