LinkedIn and Snapchat adjust algorithms to prioritize human-led content
Major social platforms are introducing reporting tools and changing recommendation logic to mitigate the volume of automated posts and focus on authentic authorship.
Julian Reeve
Jul 30, 2026 · 1 min read
A new reporting mechanism on LinkedIn now allows users to flag content as inauthentic, part of a structural effort by the Microsoft-owned network to reduce the visibility of automated posts. The initiative is a response to the increasing volume of low-quality synthetic content—often termed slop—that occupies professional feeds. By collecting these user signals, LinkedIn intends to refine the internal classifiers that determine which posts are recommended to users outside their immediate professional circles.
The platform is also reversing its approach to generative features. LinkedIn has removed its automated post-enhancement tool, which used AI to draft entire updates, and replaced it with a proofreading feature designed to preserve a user’s original voice. This change reflects a broader realization within the industry that the ease of generating content has led to a saturation of the web. Data from Cloudflare indicates that bot traffic now accounts for more than half of all internet requests, a threshold reached sooner than infrastructure analysts had projected.
Snapchat is taking a similar stance by adjusting the eligibility criteria for its Spotlight recommendations. The company will no longer offer financial rewards for videos that are entirely machine-generated, moving to ensure that its discovery engine favors original perspectives and human storytelling. While both platforms continue to offer AI-powered creative tools for editing and effects, the shift in policy marks a clear distinction between using technology as a support and using it as a primary author. The objective is to stabilize the quality of the user experience by rewarding human creativity over automated output.