Examining the COMPAS Recidivism Algorithm: A Case Study for Trustworthy AI
This analysis delves into the COMPAS recidivism algorithm, highlighting its impact on justice and underscoring the need for safe and secure AI. By doing so, we map this incident to the Govern function in Project Cerebellum's Trusted AI Model (TAIM), emphasizing the importance of responsible AI governance and harm prevention. Ready to help shape the future of trustworthy AI? JOIN US
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/11
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.