Keeping conversations real on LinkedIn
Source: Laura Lorenzetti, LinkedIn · 2026-05-20
At a time when more people need help navigating work, it's more important than ever that people can learn from real voices, authentic perspectives, and lived expertise.
But lately, keeping that human element front and center is becoming a balancing act. While AI can be a helpful tool for refining language, we're seeing a rise in what many call "AI slop," content that is low-effort, AI-generated content that may sound polished on the surface but lacks any real unique perspective or substance.
When AI is overused, especially at scale and in an automated way, it dilutes the valuable insights that real human conversations can spark. It's ok to use AI to help you write, but your posts and comments need to represent your voice and your perspectives. The ultimate value comes from the human behind the tool.
To address this, we're taking meaningful steps to crack down on automation tools, dial back on generic content, and strengthen authenticity.
This includes technology systems built in partnership with our editorial team that have been trained to recognize signals of AI slop and learn over time by identifying content that adds perspective, context, or expertise and content that feels generic or repetitive, even if it appears polished on the surface. Beyond posts, this also will recognize and take action:
When content appears to be generated by AI and lacks clear perspective, it is less likely to be widely distributed beyond a person's immediate network, which helps keep space for more thoughtful contributions.
Early results are encouraging. In our initial testing, we're correctly identifying generic content 94% of the time. That means this kind of content is far less likely to spread beyond someone's immediate network, and you'll see less of it from outside your network in your feed. Members have shared they are already seeing fewer of these types of posts in their feeds, and we expect that to continue over time.
Lastly, bots and fake AI profiles ruin genuine engagement. While our teams work around the clock to kick them off the platform, AI is getting smarter. That's exactly why verification matters. To help you cut through the noise, you can now filter for our 100M+ verified members across almost everywhere you engage with people on LinkedIn: profile views, job applications, and now comments and conversations in the feed.
Valuable conversations happen when professionals share their unique perspectives. A single insight shared at the right time can spark a conversation, open a door, or create a new opportunity. These updates are designed to protect the experience on LinkedIn so when you're engaging, you're interacting with real people offering their real point-of-view.
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?
- 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?
- How does LinkedIn's platform response address detected AI-generated content?
- How does LinkedIn's comment-versus-post AI split compare to Reddit's?
- Does AI-assisted writing dilute the conversational value of social media?
- Does detecting AI authorship actually improve social media feed quality?
- How do polished AI posts gain social proof without inviting discussion?
- Why do AI posts collect likes without generating replies on social media?
- Do AI-generated posts get more engagement than human-written ones?
- Do AI posts on social media actually achieve engagement without replies?
- Do AI-generated summaries reduce user engagement with original content sites?
- Do AI-generated articles receive less search traffic than human writing?
- Do audiences penalize AI-written posts through visible callouts at scale?
- How does Reddit's AI prevalence compare to the broader internet?
- Do writers edit AI assistance enough to fool content filters?
- Can collaboration with GenAI preserve long-term skill development in writing work?
- Does ownership of AI text lead users to rely more on suggestions?