University of Toronto's Exam Monitoring Software: Potential Biases Impacting BIPOC Students

A recent investigation has highlighted concerns regarding the impact of exam monitoring software on BIPOC students at the University of Toronto. The software, designed to detect cheating, may inadvertently disadvantage these students due to racial biases, potentially leading to academic disparities.

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Suggested mapping from embedding similarity (not a formal assessment). Browse all TAIM controls

MEASURE 2.10 — similarity 0.520, rank 1. TAIM detail and related incidents →
MEASURE 1.3 — similarity 0.513, rank 2. TAIM detail and related incidents →
MEASURE 2.8 — similarity 0.512, rank 3. TAIM detail and related incidents →

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.

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