Exploring Controversies in Spam Filter AI: A Crucial Step Towards Trustworthy AI
Understand the intricate workings of spam filters, often overlooked AI applications. Their efficiency hides potential controversies that challenge responsible AI governance. Join us in advocating for harm prevention and implementing guardrails for AI, contributing to the Govern function in Project Cerebellum's Trusted AI Model (TAIM). This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). JOIN US
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/83
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.