Understanding and Mitigating Machine Bias: A Crucial Step Towards Trustworthy AI
Delve into the critical issue of machine bias, a key challenge in AI governance. This incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). By understanding and addressing such biases, we can contribute to safe and secure AI and prevent harm. Ready to help shape responsible AI? JOIN US
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/54
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.