Unveiling the Disparate Impact of Predictive Policing Software on Low-Income, Black, and Latino Communities

An investigation into the biased application of predictive policing technology, revealing its disproportionate impact on underprivileged and ethnic minority neighborhoods. This study underscores the importance of responsible AI governance and trustworthy AI practices.

Matched TAIM controls

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

MAP 5.1 — similarity 0.604, rank 1. TAIM detail and related incidents →
GOVERN 3.1 — similarity 0.587, rank 2. TAIM detail and related incidents →
MEASURE 2.10 — similarity 0.581, rank 3. TAIM detail and related incidents →

Source

Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/54

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.