HISPI Project Cerebellum HISPI PROJECT CEREBELLUM

Study Reveals Bias and Inflexibility in AI Civility Detection: Highlighting the Need for Responsible AI Governance

A recent study uncovers bias and inflexibility issues in AI-based civility detection systems, underlining the importance of trustworthy and safe AI. This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM).JOIN US To help us shape responsible AI practices, join our efforts in establishing guardrails for AI.

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.