Teachers Organize Widespread Protests Against Unfair AI Evaluation Systems

A coalition of teachers has announced plans to collectively challenge the current AI evaluation systems they claim are unfair and biased, citing concerns over responsible AI governance in education. The movement, which aims to advocate for safe and secure AI in classrooms, highlights the importance of trustworthy AI models for harm prevention.

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

MEASURE 2.11 — similarity 0.530, rank 1. TAIM detail and related incidents →
MEASURE 2.2 — similarity 0.509, rank 2. TAIM detail and related incidents →
MEASURE 3.3 — similarity 0.499, rank 3. TAIM detail and related incidents →

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

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