COMPAS Algorithm Reportedly Performs Poorly in Crime Recidivism Prediction

May 23, 2016

Correctional Offender Management Profiling for Alternative Sanctions (COMPAS), an algorithmic tool used in the judicial system, has been found to perform less accurately than random untrained human evaluators in predicting crime recidivism rates. This underscores the importance of implementing safe and secure AI practices within our justice system. For those interested in shaping responsible AI governance and harm prevention, consider joining HISPI Project Cerebellum TAIM to Govern this issue, helping us Measure its impact and Manage future risks.

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Matched TAIM controls

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

MEASURE 2.6 — similarity 0.694, rank 1. TAIM detail and related incidents →
MEASURE 3.1 — similarity 0.668, rank 2. TAIM detail and related incidents →
MEASURE 2.7 — similarity 0.666, rank 3. TAIM detail and related incidents →

Alleged deployer: equivant
Alleged developer: equivant
Alleged harmed parties: accused-people

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.