Content ModerationVerified
Reviewed and published by trentmaziarz, April 22, 2026. Discovered and drafted by our automated research pipeline.
Bluesky deployed an automated model that detects replies judged to be toxic, spammy, off-topic, or posted in bad faith, and reduces their visibility in threads, search results, and notifications without removing them.
Details
Announced on October 31, 2025, Bluesky's updated toxicity detection model classifies replies and deprioritizes flagged content so that most users see it only after an extra click. Bluesky's 2025 Transparency Report credits this system with a 79% decline in daily anti-social behavior reports by October 2025. The system is designed to reduce harm without deleting content: replies from accounts the user follows appear above the fold, while flagged replies from others require an additional click to view. Bluesky did not publicly disclose the specific model architecture or training data used.
Products affected
Bluesky app
Sources & Evidence
Company Disclosure
Cite this record
Trace Foundation. (2026). Bluesky: Bluesky deployed an automated model that detects replies judged to be toxic, spammy, off-topic, or posted in bad faith, and reduces their visibility in threads, search results, and notifications without removing them (data as of 2026-04-22) [Data set record]. AI Trace. https://www.aitrace.org/r/practice/1818e420-0e26-439a-ae1d-15a253ba5d68. Accessed October 5, 2026.
- Stable link
- https://www.aitrace.org/r/practice/1818e420-0e26-439a-ae1d-15a253ba5d68
- Data as of
- April 22, 2026
- Last verified
- April 22, 2026
Other practices by Bluesky
ProductivityBluesky tested Attie, a standalone AI app that allows users to build personalized social media feeds by typing plain-language descriptions, without needing to write code.RecommendationBluesky uses an algorithmic recommendation system to power its Discover feed, surfacing posts based on a user's engagement history, social graph proximity, and network-wide trending signals.ModerationBluesky deployed an automated system that assesses the titles and descriptions of user-created lists for overt toxicity when a list is reported, automatically applying a hidden label if violations are detected.
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