💬 Language & Media

Wikipedia 'AI-Generated' Category Label Drift by Domain

How quickly AI-generated category labels spread across Wikipedia's domains

Observations
2
Tracking since
Last updated

AI-Generated Label Count by Domain

Number of pages containing 'AI-generated' phrase per Wikipedia domain

0 observations · measured in count

Net Change in AI-Generated Labels

Difference in AI-generated label count from previous measurement (always 0 for first run)

2 observations · measured in count

0 count
Net Change in AI-Generated Labels
17 Aug 2026 21:00
Net Change in AI-Generated Labels (count) — summary, last 30 days.
00.20.40.60.8120:4720:5321:00Net Change in AI-Generated Labels: 0 count — 17 Aug 2026 20:47Net Change in AI-Generated Labels: 0 count — 17 Aug 2026 21:00
Net Change in AI-Generated Labels (count) — line, last 30 days.
00.20.40.60.8120:4720:5321:00Net Change in AI-Generated Labels: 0 count — 17 Aug 2026 20:47Net Change in AI-Generated Labels: 0 count — 17 Aug 2026 21:00
Net Change in AI-Generated Labels (count) — area, last 30 days.
Net Change in AI-Generated Labels observations
WhenNet Change in AI-Generated Labels
0 count
0 count
Net Change in AI-Generated Labels (count) — table, last 30 days.

About this data

This page tracks the adoption and removal of AI-generated category labels (such as 'Articles with AI-generated content') across all Wikipedia language domains. The data shows how many such labels exist per domain and how their numbers change over time. By monitoring this drift, we can observe patterns in how communities respond to AI-generated content classification. The figures are derived from regular scans of Wikipedia's category metadata, providing a real-time snapshot of label proliferation.

Sources

Every figure on this page was read from these pages.

Why this isn't published anywhere else

While there is research on AI-generated content in Wikipedia, none of the sources track the spread or drift of 'AI-generated' category labels across Wikipedia domains over time. The existing sources focus on content analysis or general AI visibility, not label adoption metrics.

Uniqueness score 0.90 — assessed against live web search results when this subject was created.