Examining Bias in TikTok's Algorithm: A Closer Look

A recent study suggests that TikTok's algorithm may disproportionately promote content from certain racial and ethnic groups, raising concerns about fairness and accountability in AI-driven platforms. It's crucial to ensure responsible AI governance and safe and secure AI practices, especially when it comes to guardrails for popular social media apps like TikTok.

Matched TAIM controls

Suggested mapping from embedding similarity (not a formal assessment). Browse all TAIM controls

MEASURE 2.11 — similarity 0.487, rank 1. TAIM detail and related incidents →
MEASURE 2.10 — similarity 0.469, rank 2. TAIM detail and related incidents →
MAP 1.6 — similarity 0.467, rank 3. TAIM detail and related incidents →

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.