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AI slop is LinkedIn's term for low-effort, likely AI-generated content that may sound polished but lacks a clear point of view, unique perspective or substance, and that feels generic, repetitive, recycled or built to game attention123. LinkedIn says classifiers spot slop and limit how widely it is shown, and Hari Srinivasan said in August 2026 that members were seeing 40% fewer views on what LinkedIn classifies as AI slop than a few weeks earlier1456. Members can tap the More menu on a post or comment and choose "Seems like AI slop," and an author may see a message in Post Analytics when a post gets enough community feedback12. Laura Lorenzetti wrote in May 2026 that using AI to help you write is fine if your posts and comments represent your voice, and LinkedIn's Help Center advises telling others if you relied heavily on AI and that is not obvious27.
What counts as AI slop and what does not
LinkedIn's Help Center says its focus is on whether content adds value, not on how it was created, and that content which feels generic or repetitive, or lacks a clear point of view, is less likely to be shown to many people2. LinkedIn's Pressroom says AI can help refine language, but overuse, especially in large volumes and in an automated way, dilutes the insights that real human conversations spark4. Hari Srinivasan wrote in July 2026 that AI and slop are not the same, because many people refine their thoughts with AI8. The definition also reaches comments: LinkedIn's Pressroom names comments posted in large volumes with automation tools and little or no human involvement, and responses that only restate the original post4.
How LinkedIn finds and reduces slop
LinkedIn finds AI slop with classifiers that were built with its editorial team and learn over time to tell content that adds perspective, context or expertise from content that feels generic or repetitive, even when it looks polished47. Tim Jurka wrote in October 2026 that feedback from expert reviewers creates a continuous learning loop that helps refine LinkedIn's policies and models5. He explained that the AI tools producing generic content keep changing, so LinkedIn needs systems that adapt quickly and work in large volumes5. For that it uses a teacher-student setup, in which larger programs identify new slop patterns and label examples, and smaller, faster programs learn from those labeled examples5. Jurka added that the same AI systems LinkedIn uses to show members insightful conversations also help it identify and reduce generic content5. Srinivasan said the classifiers are meant to reduce the slop members see in suggested content and in content from outside their network8.
Member feedback and what creators see
Member feedback on AI slop helps inform LinkedIn's classifiers13. The option can also be chosen after tapping X on a post or choosing Hide posts by a member's name, and it is currently available for posts and comments in the feed23. LinkedIn's Help Center says the feedback informs its content quality work, and that it does not indicate a policy violation or trigger a reporting flow3. Srinivasan gave two reasons for showing creators private feedback in their analytics: they want to know when they sound inauthentic, and members should get feedback from real humans, not an AI detector that might get it wrong8. In August 2026 he said no single piece of feedback determines how widely a post is shown, because LinkedIn looks at many factors together and has built safeguards against feedback being used to unfairly target other members6.
How it has changed
- 2026
May
Laura Lorenzetti announced steps to crack down on automation tools, dial back generic content and strengthen authenticity, including systems built with LinkedIn's editorial team to recognize signals of AI slop7.
July
Hari Srinivasan said LinkedIn was ramping up new classifiers for AI slop and low-quality posts, was ramping up the ability for members to flag slop, and would test a private flag in analytics for authors8.
August
LinkedIn launched the "Seems like AI slop" option in the three-dot menu of posts and comments, and over a million people used it in the first two weeks6.
August
Hari Srinivasan said authors may see a message in Post Analytics when a post receives enough community feedback6.
October
Tim Jurka wrote that LinkedIn's classifiers now cover all posts distributed beyond a member's immediate network, with 94% precision at detecting AI slop5.
What you can do
- Avoid posting comments at scale using automation tools with little or no human involvement, and add something new rather than restating the original post4.
- If you advertise, read the LinkedIn Marketing Solutions Help Center article "AI slop feedback option for ads on the LinkedIn feed" to see how the feedback option works for ads3.