LinkedIn implements new measures to curb AI-generated slop

๐กLearn how major platforms are fighting back against AI-generated content saturation.
โก 30-Second TL;DR
What Changed
Targeting AI-generated content that lacks human insight
Why It Matters
This shift forces content creators and marketers to rethink AI-assisted workflows, moving away from mass-produced content toward more nuanced, human-centric strategies.
What To Do Next
Audit your content automation pipeline to ensure your posts include unique, human-verified insights rather than generic LLM outputs.
Key Points
- โขTargeting AI-generated content that lacks human insight
- โขAlgorithm adjustments to favor high-quality, authentic user interactions
- โขEffort to improve overall feed readability and user experience
๐ง Deep Insight
Web-grounded analysis with 22 cited sources.
๐ Enhanced Key Takeaways
- โขLinkedIn is deploying "AI solving AI" systems to specifically identify and suppress generic posts, bot comments, and "attention-bait videos" rather than outright removing them, thereby reducing their distribution beyond immediate networks.
- โขThe platform's new core algorithm, named "360Brew," utilizes a 150-billion-parameter AI model that evaluates content based on its substance, author credibility, and "dwell time" (how long users spend on a post), moving beyond traditional engagement metrics like likes.
- โขLinkedIn's measures also directly target and penalize "engagement pods" and automated commenting tools, which were previously used to artificially boost post visibility and engagement.
- โขThis initiative comes despite LinkedIn itself offering built-in generative AI tools for users to enhance profiles and draft content, highlighting a distinction between AI assistance for quality and AI replacement for insight.
๐ ๏ธ Technical Deep Dive
- LinkedIn is employing "AI solving AI" systems, which are newly built technical systems trained with an in-house editorial team.
- These systems are designed to differentiate content that offers original perspective, context, or expertise from that which is generic, repetitive, or lacks substance.
- Classifiers are being developed to identify low-quality AI comments by analyzing language patterns and the volume/frequency of posts.
- The new algorithm, referred to as "360Brew," is an AI system with 150 billion parameters that evaluates the actual text of posts, not just user reactions.
- It assesses content substance, formatting signals, and author credibility as part of its quality classifier, which operates within minutes of publication.
- Early tests of the new systems showed a 94% accuracy rate in correctly tagging generic content.
- The system aims to learn over time by analyzing user engagement patterns and identifying language that adds perspective versus regurgitating existing ideas.
๐ฎ Future ImplicationsAI analysis grounded in cited sources
โณ Timeline
๐ Sources (22)
Factual claims are grounded in the sources below. Forward-looking analysis is AI-generated interpretation.
- entrepreneur.com
- fastcompany.com
- botdog.co
- martech.org
- digitalapplied.com
- freshfield.com
- socialmediatoday.com
- channelnews.com.au
- the-decoder.com
- jdsupra.com
- technewsworld.com
- upwork.com
- trendhunter.com
- socialmediatoday.com
- favola.co.uk
- originality.ai
- researchgate.net
- liseller.com
- good2bsocial.com
- helpnetsecurity.com
- socialmediatoday.com
- forbes.com
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Original source: The Next Web (TNW) โ



