Examining Crime Prediction Software: Uncovering Potential Bias or a Promising Tool for Public Safety

In an era where data-driven decision making is increasingly prominent, the use of software to predict crime has garnered attention. Proponents tout it as a potential 'holy grail' in public safety, streamlining resource allocation and potentially preventing crimes. However, concerns have been raised about its fairness and impact on minority communities, specifically whether it could be biased against them.

Matched TAIM controls

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

MEASURE 2.11 — similarity 0.554, rank 1. TAIM detail and related incidents →
MAP 5.1 — similarity 0.552, rank 2. TAIM detail and related incidents →
MEASURE 2.5 — similarity 0.548, 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.