Teachers Plan Widespread Appeal for Addressing 'Unfair' AI Evaluations in Education - Harm Prevention and Responsible AI

This incident highlights the importance of trustworthy AI in education, particularly fair evaluations. Teachers are planning widespread appeals due to perceived unfairness in AI-based assessment systems. Join us in ensuring safe and secure AI through Project Cerebellum, our AI incident database and governance platform. 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

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