Remote Learning Software's Facial Recognition Failure: A Case Study in Bias
February 1, 2021
A Black student encountered issues with facial recognition during a remote-proctored lab quiz, resulting in excessive environment changes to ensure the software functioned correctly. This incident highlights the need for safe and secure AI, emphasizing harm prevention and the importance of responsible AI governance. JOIN US This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM).
- Alleged deployer
- unknown
- Alleged developer
- unknown
- Alleged harmed parties
- amaya-ross, black-students, black-test-takers
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/158
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.