HISPI Project Cerebellum HISPI PROJECT CEREBELLUM

Study Reveals Bias and Lack of Flexibility in AI Civility Detection: Addressing Harm Prevention through Responsible AI

A recent study highlights the potential for AI systems to exhibit bias and inflexibility in civility detection, underlining the need for robust AI governance. By understanding these challenges, we can work towards creating trustworthy and safe AI solutions. 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.