COMPAS Algorithm: Assessing the Accuracy of Recidivism Prediction Tools - A Case for Safe and Secure AI
May 23, 2016
Correctional Offender Management Profiling for Alternative Sanctions (COMPAS), a widely-used recidivism risk-assessment algorithm, has been found to perform less accurately compared to random human evaluators. This incident underscores the need for trustworthy and reliable AI in our judicial system - a key aspect of Project Cerebellum's mission. Ready to help shape responsible AI? JOIN US This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM).
- 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.