Flawed Criminal Sentencing AI as Inaccurate as Public Opinion

A recent investigation reveals a criminal sentencing algorithm, used by several jurisdictions in the US, is no more accurate than random guesses made by internet users. The faulty model's decisions could potentially lead to miscarriages of justice, highlighting the urgent need for responsible AI governance.

Matched TAIM controls

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

MEASURE 2.5 — similarity 0.509, rank 1. TAIM detail and related incidents →
MEASURE 1.3 — similarity 0.504, rank 2. TAIM detail and related incidents →
MEASURE 3.2 — similarity 0.497, rank 3. TAIM detail and related incidents →

Source

Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/40

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.