Examining Allegations of Gender Bias in LinkedIn's Algorithm - Ensuring Trustworthy AI
An investigation into claims of gender bias within LinkedIn's algorithmic system highlights the need for responsible AI governance and safe, secure AI. This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). Stay informed on our AI incident database and help us promote harm prevention by joining us.JOIN US
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/47
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.