HISPI Project Cerebellum HISPI PROJECT CEREBELLUM

Study Reveals Bias and Inflexibility in AI Civility Detection: Enforcing Trustworthy AI through Project Cerebellum

A recent study exposed bias and inflexibility in AI used for civility detection. This underscores the need for robust AI governance to ensure trustworthy, safe, and secure AI. By joining us at JOIN US, you can contribute to harm prevention and help establish guardrails for AI through Project Cerebellum's AI incident database and HISPI Trusted AI Model (TAIM), specifically mapping to the Govern function.

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.