Exam Monitoring Software Disadvantages Impact BIPOC Students at the University of Toronto: A Case Study in Safe and Secure AI
This incident highlights potential disadvantages faced by BIPOC students using exam monitoring software at the University of Toronto. It underscores the importance of responsible AI governance, emphasizing the need for safe and secure AI that prioritizes fairness and avoids bias. 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/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.