Race Used in AI Tools Predicting Student Success at Major Universities: A Question of Responsible AI Governance
January 1, 2012
Several major universities have implemented an AI tool that incorporates race as a factor for predicting student success. This practice, if unchecked, could lead to potential harm and bias. Join us in promoting safe and secure AI by contributing to the Project Cerebellum AI incident database, aiding in the development of guardrails for AI. This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). JOIN US
- Alleged deployer
- university-of-massachusetts-amherst, university-of-wisconsin-milwaukee, university-of-houston, texas-aandm-university, georgia-state-university, more-than-500-colleges
- Alleged developer
- eab
- Alleged harmed parties
- black-college-students, latinx-college-students, indigenous-students
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.