LinkedIn introduces 'Seems Like AI Slop' reporting button to combat synthetic feed spam

Responding to growing user frustration over automated corporate posts and synthetic engagement bait, LinkedIn has officially rolled out a dedicated feed tool allowing members to directly flag content labeled as "Seems like AI slop." The feature arrives as Microsoft's professional networking platform steps up backend enforcement against low-quality, machine-generated spam across its global network.

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Direct Feed Flagging and Algorithm Tuning

The new reporting option is accessible via the standard three-dot context menu on individual posts and comments, and lets users instantly remove suspicious content from their personal view while submitting telemetry to LinkedIn's trust and safety teams. Rather than quietly masking posts, the platform explicitly utilizes the colloquial term "AI slop" within the interface menu.

According to LinkedIn Chief Product Officer Hari Srinivasan, user reporting will serve as real-time training data to refine the site's machine learning classifiers. "Slop is hard to define and the definition changes; this lets us tune our models and make better feeds," Srinivasan noted in a public update, adding that authentic human perspective remains the core focus of the professional platform.

Sunset of 'Enhance Post' in Favor of Voice-Preserving Tools

Alongside the user-facing flag, LinkedIn is scaling back several of its own native generative AI features. The platform is officially retiring its automated "Enhance your post" feature, which previously offered to rephrase draft text using AI models. In its place, the company is introducing a basic proofreading tool designed strictly to catch spelling and grammatical errors while retaining the author's original tone and writing style.

Additionally, LinkedIn is expanding its backend detection algorithms to restrict the reach of unoriginal, automated content, particularly when it is recommended to users outside an author's immediate network. Creators whose posts receive frequent AI slop flags will receive private notifications within their personal analytics dashboard to encourage more authentic contributions.

Mounting Data on Network Automation

The strategic pivot follows recent independent research highlighting the scale of automated content across professional social channels. A study conducted by AI detection firm Pangram estimated that upwards of 41% of long-form text posts on LinkedIn show characteristics of machine generation.

By combining crowdsourced user reporting, stricter backend classifiers, and expanded account verification, LinkedIn aims to stem the tide of synthetic content and restore genuine professional discourse across its feed.