Virginia Courts’ Algorithmic Recidivism Risk Assessment Failed to Lower Incarceration Rates

July 1, 2003

Research has questioned the effectiveness of algorithmic predictions of future offending risks used by Virginia courts, revealing racial and age disparities in risk scores and application. The tool neither worsened nor improved historical racial differences in sentencing, raising concerns about responsible AI governance.

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

MEASURE 2.6 — similarity 0.668, rank 1. TAIM detail and related incidents →
MEASURE 3.1 — similarity 0.665, rank 2. TAIM detail and related incidents →
MEASURE 1.1 — similarity 0.663, rank 3. TAIM detail and related incidents →

Alleged deployer: virginia-courts
Alleged developer: virginia-department-of-criminal-justice-services
Alleged harmed parties: virginia-convicted-felons, virginia-black-offenders, virginia-young-offenders

Source

Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/274

Data source

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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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