Universities Using Race as a Predictor for Student Success Raise AI Accountability Concerns
An incident involving university AI systems using race as a high impact predictor of student success raises concerns about AI accountability, fairness, and the need for responsible AI governance. This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). Ready to help shape trustworthy AI? JOIN US
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/99
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.