LinkedIn to Curb Low-Quality AI Posts to Improve Professional Feeds: what changed

LinkedIn plans to deploy systems to detect and reduce low-value AI-generated posts, comments, attention‑bait videos, and large — scale automation, using an iterative “AI solving AI” approach while retaining useful machine — generated content.

LinkedIn said it will roll out systems to reduce the presence of low-quality, AI-generated content in users’ feeds, aiming to keep professionals from being distracted by generic or promotional material. The company framed the effort as a response to months of rising low-value AI output and internal shorthand for the problem — “AI slop. the focus is on removing the subset of machine — produced material that lowers feed quality rather than eliminating automated content wholesale.

LinkedIn described its technical approach as “AI solving AI” but provided few public details about the detection systems themselves. The company said the cleanup will be iterative rather than a single, platform — wide switch: new tools will be rolled out gradually, adjusted over time, and refined as enforcement begins. That staged deployment reflects both the technical complexity of distinguishing useful from low-value AI content and the company’s caution about unintended consequences for legitimate creators.

For its initial enforcement work, LinkedIn identified three priority categories the systems will target: generic AI-generated posts and comments that offer little substantive value; attention‑bait videos designed primarily to game feed engagement; and automation tools that generate or distribute AI content at scale. The firm singled these classes out as the most immediately harmful to feed quality and the top priorities for early action.

The initiative follows several months of growing complaints from users and creators as experimentation with AI shifted toward engagement — seeking posts. Because LinkedIn has released limited public detail about detection methods and enforcement thresholds, the precise impact on creators, publishers, and vendors of automation tools remains uncertain. The company cautioned that meaningful reductions in visible “AI slop” may take time-it could be several months before most users notice a clear improvement in feed quality.