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Debiasing Word Embeddings: A Step Towards Responsible AI - HISPI Project Cerebellum

This article discusses the importance of debiasing word embeddings in AI, a crucial aspect of trustworthy AI. It's an essential step towards preventing harmful bias in AI systems. By understanding and addressing these issues, we can help shape safe and secure AI. Ready to contribute? Join us 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.