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You know the type: a polished LinkedIn post filled with inspirational lessons, immaculate structure, and more em dashes than most people use in a month.
LinkedIn is now introducing a new way for users to report what it calls "AI slop," making it easier for users to call out the flood of low-quality AI-generated posts popping up across the platform. This is a strong indicator that social platforms are shifting from encouraging generative AI adoption to drawing a line between AI used to refine a person’s ideas and automated content that adds little value.
The Microsoft-owned professional network announced Thursday that users can select a new “Seems like AI slop” option to report posts they consider low-quality, inauthentic, or excessively automated. LinkedIn said those reports will provide an additional signal for systems that rank and moderate content.
Concerns about AI-generated spam have continued growing across social media, where businesses, recruiters, marketers, and professionals increasingly rely on authentic content to build credibility. Now, after spending the past few years incorporating AI-powered writing tools, companies are dealing with the unintended consequences of those same technologies as AI-generated content becomes harder to ignore.
LinkedIn is relying on both users and AI to clean up the feed
Don’t expect all AI to be wiped from your feeds just yet. The new reporting option is only one element in LinkedIn's strategy to improve content quality rather than remove all posts that mention AI.
In a public announcement LinkedIn post, Chief Product Officer Hari Srinivasan said the company is rolling out new classifiers designed to identify AI-generated and other low-quality posts before they spread through content recommendations. LinkedIn hopes that reports from users will serve as another signal to help those systems become more accurate over time.
LinkedIn is also stepping up its investment in automated abuse detection. According to Srinivasan, the platform now blocks hundreds of thousands of automated comment attempts every day and has stopped billions of additional automation attempts over the past couple of months, including large-scale posting activity.
AI use isn't the problem, LinkedIn says
According to Srinivasan, many professionals use AI tools to organize, refine their ideas, or improve the readability of their writing, rather than generate entire posts. The company says there's a difference between using AI as an editing tool and publishing fully AI-generated or low-quality content.
Mirroring that distinction, LinkedIn will begin testing a private analytics feature that notifies users when other members believe their content sounds inauthentic or overly AI-generated.
The feedback will only be visible to the author, giving users a chance to adjust their writing style instead of facing public moderation.
That idea is also influencing LinkedIn's own AI writing tools. The company is getting rid of its existing "enhance your post" feature, which rewrote user content using AI. Instead, it is shifting to become more of a proofreading tool that corrects grammar and clarity while leaving the original author's voice intact.
The changes reflect LinkedIn’s new emphasis on authenticity over automation, with an effort to encourage AI-assisted editing without changing a user's voice.
The AI content problem isn't unique to LinkedIn
Like many things in the tech world, this challenge has been a trend experienced by numerous companies in the social platform scene as they try to handle an influx of AI-generated content.
Research cited by Fortune from AI detection company Pangram found that 41% of long-form LinkedIn posts and 30% of short-form posts were identified as fully AI-generated. AI detection tools certainly aren’t perfect, but these findings suggest AI-generated content has become increasingly common on LinkedIn.
Other platforms are responding in their own ways. Substack recently partnered with Pangram to help identify AI-generated writing. Meanwhile, Snapchat announced it would stop recommending fully AI-generated videos in its Spotlight feed unless they were created using Snapchat's own AI creative tools and appropriately labeled. Earlier this year, YouTube said cutting “AI slop” was a top priority.
Still, Meta has taken an alternative approach by continuing to expand its AI-generated media capabilities, including its recently introduced Muse Image and Muse Video, which let users generate AI-created images and videos, while adding watermarking technology intended to identify AI-generated media.
Why it matters
LinkedIn isn’t like other social media sites; it occupies a unique role, seeing as its content directly influences hiring decisions, professional networking, executive thought leadership, and B2B marketing. But as AI-generated content becomes more common, maintaining authenticity is the new big challenge.
LinkedIn is taking a nuanced approach using community reporting, automated detection, bot prevention, creator feedback, and updated writing tools.
It’s interesting how, after spending the past several years racing to integrate generative AI into products, companies are increasingly investing in tools that distinguish useful AI assistance from low-value automated content.
LinkedIn's latest update offers enterprise organizations and business professionals an early indication of how platforms may manage AI adoption as generative content proliferates online.
Other News: Substack is facing backlash from writers over its new Pangram-powered AI detection tool, with critics warning it could produce false positives and unfairly undermine trust in human-written content.