Exam Monitoring Software Disparities Impact BIPOC Students at the University of Toronto - Highlighting AI Incident Mapping to Govern Function in HISPI Project Cerebellum Trusted AI Model (TAIM)
This incident sheds light on biased AI application in exam monitoring software, causing disadvantages for Black, Indigenous, and students of color at the University of Toronto. Understanding and addressing these disparities is essential for trustworthy AI and preventing harm. Join us in promoting safe, secure, and responsible AI governance through Project Cerebellum's AI incident database.JOIN US
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/140
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.