LinkedIn Adds "Seems Like AI Slop" Button to Target Automated Feed Spam

LinkedIn added a user-reporting feature allowing members to flag feed posts as machine-generated spam.
The new option appears inside the three-dot menu at the top of individual posts on desktop and mobile applications.
When a user selects the new option, LinkedIn removes the flagged post from the feed and displays a confirmation message.
"Thanks for letting us know. Your feedback helps improve the feed."
Tech publication 404 Media first reported the interface update after testing the option on posts containing repetitive formatting, takeaway lists, and heavy emoji use.
LinkedIn Chief Product Officer Hari Srinivasan confirmed the feature rollout.
"AI slop is a top priority for all of us."
"We are ramping the ability for members to tell us if they believe a post or comment seems like AI slop."
"Slop is hard to define and the definition changes; this lets us tune our models and make better feeds."
The platform update follows data from AI-detection firm Pangram, which showed that 41% of long-form posts on LinkedIn registered as fully machine-written.
LinkedIn uses the user flags to train automated detection algorithms on backend systems.
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| Credit: LinkedIn |
The company also deploys automated classifiers designed to filter low-quality content before posts enter member feeds.
LinkedIn blocks hundreds of thousands of automated comment attempts daily.
Alongside the reporting button, LinkedIn is altering its internal content editing tools.
The platform is retiring its "enhance your post" generative AI tool.
In its place, LinkedIn is introducing a basic proofreader that checks spelling and grammar while preserving the writer's original voice.
Srinivasan addressed the distinction between machine-written text and general AI assistance.
"AI and slop are not the same thing."
To address accounts that produce excessive synthetic text, LinkedIn plans to test private alerts within author analytics dashboards.
Writers who receive multiple reader flags will see notifications indicating their writing came across as inauthentic.
