Universities Use Race as High-Impact Predictor for Student Success: An Examination of Responsible AI Practices
This case study explores the use of race as a high-impact predictor in university student success models. This AI practice raises concerns about fairness and bias. Learn how Project Cerebellum, a trusted AI model, provides governance for safe and secure AI development. Ready to help shape responsible 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.