Amazon's Search and Recommendation Algorithms: A Case of Vaccine Misinformation - Impact on Trustworthy AI
January 21, 2021
Investigations by vaccine-misinformation researchers revealed the 'filter-bubble effect', where Amazon's algorithms promoted misinformative products to users who had previously interacted with such items. This incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). Ready to help prevent such harm and establish guardrails for AI? JOIN US
- Alleged deployer
- amazon
- Alleged developer
- amazon
- Alleged harmed parties
- amazon-customers
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/139
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.