AI companies begin cleaning up AI slop to protect model performance.

Platforms and AI firms are tightening content quality controls to limit AI-generated “slop,” which the article reports can degrade model performance; reported responses include takedowns, algorithm updates, and new hires focused on content expertise.

AI companies and major platforms are reported to be increasing efforts to reduce low-quality AI-generated content, often called "AI slop." The article frames these efforts as driven by concerns for information quality and by the risk that model-generated content could degrade future model performance. Industry leaders and platforms have been cited taking visible steps, and companies are also changing hiring priorities to emphasize content expertise. The shift is presented as both a product-quality and data-quality concern. Key reported developments: - YouTube CEO Neal Mohan is reported to have named managing AI slop a top priority for 2026, and the platform removed channels in December 2025 for publishing fake AI-generated trailers. - The article cites research published in Nature that reports indiscriminate training on model-generated content can cause defects in resulting models. - Google's December 2025 core update is reported to have tightened E-E-A-T requirements, with visibility declines for sites showing weak expertise signals. - The article reports increased hiring and new content roles at major AI firms and platforms, emphasizing human authorship and subject-matter expertise. Summary: Reportedly, platforms and AI developers are aligning policies, takedowns, algorithm changes, and hiring to reduce the prevalence of AI-generated low-quality content because they view it as a risk to model performance and the quality of future training data. Undetermined at this time.