LinkedIn is taking aim at one of the biggest problems facing professional networks: the explosion of low-quality, AI-generated content designed to appear insightful, authoritative, and useful, but often delivering little more than recycled information dressed up as expertise.
The platform has introduced a new “Seems like AI slop” reporting option, allowing users to flag posts they believe rely heavily on artificial intelligence and contribute to the growing wave of generic content overwhelming online discussions.
For years, LinkedIn has positioned itself as a place where professionals share knowledge, build relationships and exchange industry insights.
However, the growing use of generative AI has created a new class of content creators who can produce thousands of posts without necessarily understanding the subjects they are discussing.
In a post on LinkedIn, chief product officer Hari Srinivasan acknowledged the scale of the problem, saying the company considers AI slop a major priority.
“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.” Srinivasan said.
“We continue to improve and invest in our automation defenses. On comments alone, everyday we are now catching hundreds of thousands of automated comment attempts, and have blocked billions of other automation attempts (posting at scale, slop) in the last couple months alone..” he said.
The significance of the move is that LinkedIn is no longer relying solely on behind-the-scenes moderation systems. It is asking users to help identify content that damages the quality of professional conversations.
The platform is also expanding its automated defences, blocking hundreds of thousands of automated comment attempts every day and millions of other suspicious automation attempts in recent months.
New detection systems are being developed to identify AI slop and low-value content before it reaches recommendation feeds, while reports submitted through the new feature will provide additional data to improve these models.
However, the problem goes beyond AI-generated text.
The deeper issue is the growing number of online personalities, influencers and digital marketing operators who have built professional reputations around repeating information they have little experience or understanding of.
Across the digital marketing industry, countless freelancers and agencies have turned content creation into a production line. Articles are rewritten, repackaged and redistributed with minor wording changes, often giving the appearance of expertise without adding any new analysis, research or original thought.
The result is a professional internet increasingly filled with people commenting on industries they do not understand, promoting strategies they have never tested and presenting basic summaries as specialist knowledge.
For legitimate journalists, researchers and experienced professionals, this creates a serious credibility problem.
Expertise is not created by publishing hundreds of posts. It is built through experience, investigation, accountability and the ability to provide information that others cannot easily find.
Generative AI has made it far easier for people to imitate those qualities.
A person with limited knowledge of cybersecurity, marketing, technology or business can now generate convincing-looking articles, social media posts and industry commentary within minutes. The writing may appear polished, but the underlying knowledge may be shallow or completely absent.
The problem is not the technology itself, but how easily it can be used to imitate expertise.
Using AI as a tool to improve grammar, structure research or assist with editing is very different from using it to manufacture a false impression of authority.
LinkedIn’s changes could help expose this growing problem by making authenticity, originality and expertise more important signals than simply posting frequently.
The company is also planning to privately notify users when their content appears overly dependent on AI-generated writing. The goal is not to punish professionals who use AI responsibly, but to encourage users to maintain their own voice and perspective.
As part of the changes, LinkedIn is removing its previous “enhance your post” AI writing feature and replacing it with a proofreading tool designed to fix errors without rewriting a person’s style.
The battle over AI slop is not limited to LinkedIn.
Newsletter platform Substack recently partnered with Pangram to help identify when content may have been created using AI. Pangram has also raised $9 million to develop technology focused on detecting AI-generated material across the internet.
Smaller platforms are facing similar challenges. Digg shut down its Reddit competitor after struggling to control the number of bots flooding the service.
Cloudflare has warned the problem is accelerating, reporting that bot traffic across the internet has now surpassed human-generated requests — a milestone the company said arrived sooner than expected.
The challenge for platforms is no longer simply stopping spam. It is protecting the value of genuine knowledge in an environment where anyone can create the appearance of expertise.
If LinkedIn’s approach works, it could become an important filter against the growing economy of fake authority, recycled opinions and automated professional branding.
The future of online credibility may depend on a simple question: did a real person with real experience create this, or is it just another piece of content created to feed an algorithm?
