HISPI Project Cerebellum HISPI PROJECT CEREBELLUM

Investigating Racial Bias in AI Systems: Harm Prevention and Guardrails for Trustworthy AI

Uncovering the root causes of racial bias in AI systems is crucial for safe and secure AI. This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). By analyzing incidents like this, we can establish stronger guardrails for AI, promoting trustworthy AI development. Ready to help shape responsible AI? JOIN US

Source

Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/43

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.