Platforms are taking different paths on AI-generated content. LinkedIn’s new reporting tool is drawing skepticism, while Substack opts for transparency. Writers worry about fairness and the risk of misuse.
Content professionals are watching closely as major platforms introduce new tools to address AI-generated writing. LinkedIn’s recent rollout of a “Seems like AI slop” button has sparked debate among creators and industry experts, who question whether such features could unfairly target legitimate writers and stifle professional expression.
Since the early days of the web, publishing online has been largely unregulated, with few universal standards for what content is allowed. Today, each platform sets its own policies, but enforcement varies and audiences often determine what gains traction through engagement. Despite growing concerns about low-quality or AI-generated material, there is still no single code of ethics governing online publishing.
Jennifer Stack, an award-winning content practitioner and adjunct professor, argues that transparency should be the priority for platforms and governments when it comes to generative AI. She notes that while some users may choose to publish AI-generated content frequently, it is not the role of others to police their choices. Instead, Stack believes that technical definitions and platform-level transparency are more effective than relying on user reports or public votes to determine content authenticity.
Substack recently introduced an AI detection tool designed to give readers more information about how posts are created. The platform encouraged authors to disclose their use of AI, but left it up to readers to engage with the tool or ignore it. Substack also published its perspective on AI-generated content and later shared feedback from its community, signaling a commitment to open dialogue and transparency.
In contrast, LinkedIn’s new reporting feature was launched with little public explanation. The “Seems like AI slop” button began appearing for North American users on July 30, but the company did not issue a formal announcement or provide detailed guidance on how reports would be handled. Chief product officer Hari Srinivasan stated that addressing AI slop was a priority, but many LinkedIn “Top Voices” and subject-matter experts have expressed skepticism about the tool’s rigor and potential for abuse.
Some creators worry that the feature could be misused to target posts based on personal bias or misunderstanding, especially since LinkedIn has previously offered AI writing assistance within its post composer. The platform is now retiring its AI enhancement tool while simultaneously inviting users to flag content they suspect is AI-generated, raising questions about the message this sends to professionals building their online presence.
Stack emphasizes that individuals should have the freedom to present themselves as they choose on social media, and that collective taste should not dictate what qualifies as acceptable content. She argues that a lack of engagement already serves as feedback for creators, and that additional reporting mechanisms risk introducing negativity and gatekeeping into online communities.
As platforms experiment with different approaches to AI disclosure and content moderation, the debate continues over how best to balance transparency, fairness, and user autonomy. The conversation echoes broader industry discussions about the impact of AI on publishing, such as the challenges faced by advertisers in maintaining brand safety while leveraging new technologies, as explored in this analysis of contextual AI in advertising.
