Investigation into AI Incident #152: Unintended Bias in Recommendation System
Recently, an incident involving unintended bias in a recommendation system used by a popular e-commerce platform came to light. The AI, designed to suggest products based on user behavior and preferences, was found to disproportionately recommend items associated with one particular demographic over others. This highlights the importance of responsible AI governance, particularly when it comes to ensuring fairness and preventing harm in AI applications.
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/152
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.