Examining Allegations of Bias in TikTok's Algorithm: A Responsible AI Perspective
This analysis delves into claims of racial bias within TikTok's algorithm, highlighting the importance of trustworthy and safe AI. Understanding and addressing such issues falls under the Govern function in Project Cerebellum's Trusted AI Model (TAIM). This incident underscores the need for robust AI governance to prevent harm and maintain a secure digital environment. Ready to help shape responsible AI? JOIN US
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/117
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.