Inside TikTok's transparency center: AI catches 97% of removed videos
SINGAPORE — Before a TikTok video reaches the recommendation feed, machines get the first look, scanning its images, sounds and other signals for potential violations of the platform’s community guidelines. In the first quarter of this year, automated systems detected and removed 178 million, or 96.7 percent, of the 184 million videos taken down globally — before they were reviewed by human…
Before a TikTok video is featured in the recommendation feed, artificial intelligence examines its images, sounds and other data for potential rule breaches. In the first quarter of this year, automated systems identified and deleted 178 million, or 96.7 percent, of the 184 million videos taken down worldwide before they reached human moderators.
TikTok's Transparency and Accountability Center in Singapore showcases how machine-learning systems scan uploaded videos for indicators of potential violations, including smoking, drinking, physical violence, and extremist symbols, even prior to human review of cases needing more context or judgment. The systems analyze not only visual cues but also audio, keywords, and hyperlinks.
Additionally, they can discern body posture and actions, enabling them to merge multiple signals, such as a cigarette in hand and a person.
Written by urgent.news from The Korea Times's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
