Examining Amazon's Recruiting Algorithm: A Case Study of Gender Bias in AI
This article explores the controversial recruiting algorithm used by Amazon, shedding light on the potential for gender bias in AI systems. The incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). It's crucial to acknowledge and address such issues to uphold trustworthy and responsible AI. Ready to help prevent harm and establish guardrails for AI? JOIN US
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/37
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.