Study Reveals Bias and Inflexibility in AI Civility Detection: A Call for Responsible AI Governance
A recent study uncovered biases and inflexibilities in AI-powered civility detection systems. This underscores the need for safe, secure, and trustworthy AI, as well as proper governance mechanisms to prevent harm. Join us in shaping the future of responsible AI with Project Cerebellum's AI incident database. 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/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.