Race Used as High-Impact Predictor in AI Systems at Major Universities: Potential for Biased Outcomes
This incident raises concerns about the fairness of AI in education, highlighting the use of race as a 'high impact predictor' of student success. Such practices can lead to biased outcomes and undermine trustworthy AI principles. This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). Ready to help prevent harm and establish guardrails for 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.