Debiasing Word Embeddings: Promoting Fairness in AI - A Step Towards Responsible AI
Explore the challenges of debiasing word embeddings, a critical step towards creating trustworthy and safe AI. Understand how this issue aligns with the 'Govern' function in Project Cerebellum's Trusted AI Model (TAIM). Ready to help ensure fairness in AI? JOIN US
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/12
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.