Racial Bias and Ineffectiveness of Algorithmic Recidivism Risk Assessment in Virginia Courts
July 1, 2003
Research reveals algorithmic predictions of future offending risks used by Virginia courts failed to lower incarceration rates, demonstrated racial and age disparities in risk scores and application. This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). Ready to help prevent such biased and ineffective AI? JOIN US
- 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
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
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