LinkedIn adds a button to report AI-generated 'slop'
Source: Sarah Perez, TechCrunch · 2026-07-30
LinkedIn is taking aim at the “AI slop” — low-quality, artificially generated content — filling its feed. On Thursday, the company announced that it’s adding a new feature to let users click a “seems like AI slop” button when someone’s post appears to have been written with AI.
The move reflects a broader shift across online publishing platforms to cut back on AI content, as people have grown frustrated with the computer-written, inauthentic posts filling the web.
Last week, for instance, newsletter platform Substack added a tool to help users identify when the content they’re reading on its site was written by AI, through a partnership with Pangram. Meanwhile, Pangram this week announced $9 million in new funding to tackle the problems of AI content flooding the internet. The problem is also impacting new startups, as Digg had to shut down its Reddit competitor in March, saying it couldn’t get a handle on the number of bots flooding its site.
Internet infrastructure firm Cloudflare says the problem is just getting worse, as there is now more bot traffic on the web than human-generated requests — a milestone that was reached faster than it had previously predicted.
In a post on LinkedIn, the company’s chief product officer, Hari Srinivasan, admitted the Microsoft-owned social network is facing similar problems. “AI slop is a top priority for all of us. We really care about this. People come to LinkedIn to connect with real people and share their real perspectives, ideas, and expertise,” he said.
The exec explained that the new “Seems like AI slop” button is now one of several measures LinkedIn is using to reduce the amount of low-quality, AI-generated content on its platform. The company is also investing in automation defenses, where it now blocks “hundreds of thousands” of automated comment attempts daily, and millions of other automation attempts in just the past couple of months.
Srinivasan said LinkedIn is also introducing new classifiers to identify if a post is AI slop or other low-quality content, which would reduce the amount of slop you’d see in suggested content recommendations from outside your network. (The button ties into this measure, as it will provide a source of signal that will allow LinkedIn to tune its AI models to better identify slop.)
Plus, LinkedIn will begin privately flagging in users’ dashboards when people believe their content is coming off as inauthentic due to heavy use of AI. The company believes that this will help posters improve their writing, in the case that they’re simply using AI technology to refine their own work, rather than when they’re posting what’s considered full-on “slop” content.
Notably, the company is pulling its own “enhance your post” feature that had used AI to help you write. It’s replacing it with a feature that proofreads your words, instead of changing your voice.
Other improvements include expanding access to profile and page verification tools and adding an option to block comments from company pages you no longer want to see, Srinivasan said.
Lines of inquiry this paper opens 24
Research framings built by reading the notes related to this paper — the questions it feeds into.
How does AI-generated content create social proof without authentic interaction?- How often does LinkedIn wrongly flag legitimate posts as AI-generated?
- How does LinkedIn's verification system affect what content appears in feeds?
- How does LinkedIn's approach differ from other AI content moderation systems?
- Do members who flag AI posts actually see fewer AI-generated posts afterward?
- How much of LinkedIn's feed is genuinely AI-generated versus human-written content?
- What triggers LinkedIn's detection of inauthentic content from heavy AI use?
- Why do AI posts collect likes without generating replies on social media?
- How does LinkedIn's platform response address detected AI-generated content?
- Does flagging AI content change engagement and distribution like downvoting does?
- How does LinkedIn's comment-versus-post AI split compare to Reddit's?
- How accurate is the detector labeling these posts?
- What happens to reach when a post gets flagged incorrectly?
- Why are Technology and Software Development categories highest on Medium?
- Why is machine-generated text concentrated in certain Reddit communities?
- Why do accusations focus on gatekeeping rather than detecting AI?
- Does improving detection accuracy change how slop accusations function socially?
- What signals do AI text detectors actually measure in their classification?
- Can AI-rewritten text still be detected as machine-modified?
- Can user feedback flags rival AI detector accuracy for identifying AI slop?
- How accurate is Originality.ai's detector at identifying AI-written content?
- Can readers distinguish machine-generated text from human-written comments?