Study reveals bias and rigidity in AI's civility detection, emphasizing the need for safe and secure AI
A recent study highlights a concerning display of bias and inflexibility in an AI system designed for civility detection. This incident underscores the importance of trustworthy AI and responsible AI governance, as well as the role of Project Cerebellum's AI incident database in harm prevention. Ready to help shape responsible AI? JOIN US This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM).
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/13
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.