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    LinkedIn launched a user reporting tool that allows members to flag feed content as "Seems like AI slop" to combat machine-generated spam.The platform is officially retiring its AI-driven post enhancement feature and introducing a proofreading tool that preserves the original author's voice.New backend classifiers and profile verification rollouts aim to clean up the professional network after reports showed massive spikes in automated posts.

    LinkedIn is officially pushing back against the flood of machine-generated feed spam. The professional networking platform rolled out a new reporting button that allows users to flag content specifically as "Seems like AI slop." Tucked inside the standard three-dot menu on any post, the tool lets human readers police the timeline. The move marks a direct response to a growing cultural frustration with synthetic engagement bait that has increasingly dominated the site.Chief Product Officer Hari Srinivasan announced the measures directly, noting that authentic human connection remains the core focus for the company. To support the user-facing reporting button, LinkedIn is ramping up backend classifiers designed to detect low-quality automation before it hits the feed. The system is already working overtime. According to Srinivasan, the platform currently blocks hundreds of thousands of automated comment attempts daily and has thwarted billions of broad automation actions over the past few months alone.The company is also walking back some of its own previous AI integrations. LinkedIn is removing a tool that offered to "enhance" user posts with artificial intelligence. In its place, the platform will introduce a standard proofreading feature built to check spelling and grammar while preserving the original voice of the author. For creators, the backend analytics dashboard will soon test a private flagging system. If multiple users report a specific post as inauthentic or heavily reliant on AI, the original author will receive a quiet notification.The anti-slop campaign arrives just as third-party data paints a stark picture of the network's current state. A recent study by AI detection firm Pangram revealed that 41 percent of long-form posts on LinkedIn registered as completely machine-written. By crowdsourcing the identification process, the platform aims to better train its internal models to recognize the constantly evolving aesthetics of automated spam. Expanding profile and company page verifications will also play a role in ensuring real humans are behind the screens.

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