Teachers Plan Widespread Appeals Against Unfair AI-Based Evaluations: Emphasizing the Need for Safe, Trustworthy AI
This incident involving teachers' appeals of allegedly unfair evaluations highlights the critical role of trustworthy AI in education. The AI system under scrutiny has reportedly made biased decisions. To prevent such incidents and foster responsible AI, it is crucial to adopt safe and secure AI practices, such as those offered by Project Cerebellum's AI governance framework. By joining our community, you can help shape the future of AI incident prevention and contribute to the implementation of effective guardrails for AI, ensuring a safer and fairer digital learning environment. This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). JOIN US
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/9
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.