Copyright CNET
If you've scrolled through social media lately and thought, "this feels off," you're not imagining things. The internet is filling up with something called AI slop -- a wave of machine-made junk content that's cheap, endless and hard to escape. The term started as online slang a few years ago but quickly became shorthand for the growing flood of low-effort AI-generated material. Think of it as spam for the social media age. Bad email scams have been replaced by bland blog posts, fake news clips and surreal videos and stock photos that, frankly, should never see the light of day. What AI slop actually means Slop used to describe animal feed made from leftovers. In today's context, it captures that same sense of cheap filler. AI slop is content generated quickly and carelessly, with no originality or factual accuracy. You'll find AI slop across every platform, from YouTube videos with robotic narration over stolen footage, to "news" websites copying each other's AI-written articles and TikTok clips featuring voices that resemble Siri trying to sound human. Even search results are starting to feel sloppier, with AI-generated how-tos and product reviews ranking above legitimate customer reporting. The problem isn't that AI is inherently bad at creating. It's that too many people use it to flood the internet with content that looks informative but isn't. Even John Oliver dedicated a whole segment to AI slop on his show. Sean King O'Grady, the creator of the docuseries Suspicious Minds and an award-winning filmmaker, gave me some hope in the younger generations. His 10-year-old took one look at a hyper-real Sora clip of Marc Cuban that O'Grady created and immediately called it out as fake and said, "Get that AI slop out of my face." But in some cases, AI is very good and confidently fools people. That content gets shared, reposted and monetized before anyone checks if it's real, as we have often seen on social media. How AI slop differs from deepfakes and hallucinations AI slop isn't the same as a deepfake or a hallucination, even though the three often blur. The difference is intent and quality. Deepfakes are precision forgeries that use AI to generate or alter realistic video and audio, making someone appear to do or say something they never did. The goal is deception, from fake political speeches to voice clones used in scams. Deepfakes target individuals, and their danger lies in how convincing they can be. AI hallucinations are technical errors. A chatbot might cite a study that doesn't exist or invent a legal case from thin air. The model isn't trying to mislead -- hallucinations happen when it predicts the next likely word and gets it wrong. AI slop is broader and more careless. It happens when people use AI to mass-produce content such as articles, videos, music and art without checking accuracy or coherence. It clogs feeds, boosts ad revenue and fills search results with repetitive or nonsensical material. Its inaccuracy comes from neglect, not deceit or error. In short, deepfakes deceive on purpose, hallucinations fabricate by accident and AI slop floods the internet out of indifference, often fueled by greed for a quick buck. Where is all the AI slop coming from? Part of the reason AI slop spread so fast is that AI technology became powerful and cheap. AI companies created these models in the hopes that it would reduce the barrier of entry to people who have great ideas but lack the talent or finances to create things. What ended up happening is that people are asking AI tools to churn out text and images by the thousands for clicks or ad revenue. It's a volume game. If a video performs well, more just like it are created, so we end up with digital clutter and uncanny online iterations. Once tools like ChatGPT, Gemini and Claude made it possible to generate readable text, images and videos in seconds, especially with newer AI generators like Sora and Veo -- content farms jumped in. They realized they could fill websites, social feeds and YouTube with AI content faster than any human team could write, edit or film. For example, despite having only four videos, this YouTube channel has amassed 4.2 million subscribers and hundreds of millions of views: Platforms have played a role, too. Algorithms often reward quantity and engagement, not quality. The more you post, the more attention you grab, even if what you post is nonsense (mukbang much?). AI makes it trivial to scale that strategy. There's also money involved. Some creators pump out fake celebrity news or clickbait videos stuffed with ads. Others repurpose AI content to trick recommendations and drive traffic to low-effort sites. The goal isn't to inform or entertain. It's to make a fraction of a cent per view, multiplied by millions. O'Grady has watched the evolution of AI slop over the years but says, "The novelty of a lot of this new slop will also wear off extremely quickly." How AI slopification is ruining the internet At first glance, slop looks harmless -- a few bad posts in your feed and maybe you get a laugh or two out of it. But volume changes everything and fatigues the audience. As more junk circulates, it pushes credible sources down in search results and crowds out human creators. It also blurs the line between truth and fabrication. When half of what you see looks like a simulation, it's harder to trust the rest. That erosion of trust has real consequences. Misinformation spreads faster when no one knows what's real. Scammers weaponize AI to build convincing fake brands or impersonate people and even officials. Advertisers are struggling because their campaigns sometimes appear alongside AI slop on platforms like YouTube, damaging brand credibility by association. There's a deeper cultural cost. O'Grady sees a long arc of numbness online giving the example of Bob Ross punching Stephen Hawking. "I think the internet, in a strange way, has desensitized all of us to violence in a pretty horrible way," he tells CNET. "I wonder what does that say about our humanity when violent or grotesque AI mashups go viral?" The thought of where we're going as a culture and what we do with these tools scares O'Grady more than thinking about the economic consequences of generative AI videos. What can we do about AI slop? No one has a perfect fix yet, but some companies are trying. Platforms like Spotify have started labeling AI-generated media and adjusting algorithms to downrank low-quality output. Google, TikTok and OpenAI have promised watermarking systems to help you tell human content apart from synthetic material. Though those methods are still easy to evade if someone screenshots an image, re-encodes the video or rewrites AI text. Some of the fixes rely on a framework called C2PA, short for Coalition for Content Provenance and Authenticity. It's an industry standard backed by companies like Adobe, Amazon, Microsoft and Meta that embeds metadata directly into digital files to show when and how they were created and edited. If it works as intended, C2PA will help you trace whether an image, video or article came from a verified human source or an AI generator. The challenge is adoption, since metadata can be stripped or ignored and most platforms do not enforce it consistently. O'Grady is skeptical about labels alone, worried that even authentic videos of serious events, such as a politician committing a crime, could be easily dismissed as fake with a false AI watermark. "I might be pessimistic on this front, but I don't think labeling will do much," he says. "I think the watermarks could be also used to de-authenticate things that were authentically real." Creators are pushing back in their own way, too. Many journalists and artists emphasize human craft. Some writers include a simple note, "no AI was used," to reassure readers that a person, not a prompt, made the work. Can AI slop be stopped? Probably not completely. Once mass production of words and images became nearly free and fairly easy, the floodgates opened. AI doesn't care about truth, taste or originality. It cares about probability. And that's exactly what makes slop so easy to make and so hard to escape. But bringing awareness helps. People are learning to spot patterns, the same phrasing ("tapestry," "in the era of," "not only but also," are some of the common ones), the same empty language that feels human but lands hollow. However, AI tools are advancing rapidly and whatever AI model is currently out is the worst as it will ever be. The cognitive cost is real. "I think all of this is probably very bad for your brain, the same way that junk food is," O'Grady says. "Your mind is what you put into it. If it's what we're consuming all day, because it's all that's out there, I think that's pretty dangerous." Instead of leading to the predicted "galactic techno-utopia," as O'Grady calls it, or singularity where consciousnesses merge, he says the current trend of AI suggests our future might just be an endless, senseless universe of Bob Ross memes, "shrimp Jesus" and other absurd slop. For now, the best defense is our attention. Slop thrives on automation and on scrolling or sharing without thinking -- something we've all been guilty of doing. Slow down, check sources, reward creators who still put in real effort. It may not fix this mess overnight, but it's a start. The internet has been here before. We fought spam, clickbait, dis- and misinformation. AI slop is the next version of the same story, faster and slicker but harder to detect. Whether the web keeps its integrity depends on how much we still value human work over machine output.
