Evaluating Incident #104: Unintended Bias in Recommendation AI
Recent findings from Incident #104 reveal a concerning instance of unintended bias within an AI-powered recommendation system, which negatively impacted diverse user groups. This underlines the need for robust and equitable AI systems. The incident highlights the importance of responsible AI governance, trustworthy AI models, and harm prevention measures in safeguarding users from such occurrences.
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/104
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.