Charlie Kirk was assassinated on Wednesday in Utah, and even before the ink on the traditional news obituaries dried, Amazon was already filling up with AI-generated books in memoriam. The Kindle store carried titles that promised to give readers “the full story” of his death and “the quick arrest of the Charlie Kirk shooter”, though the suspect hadn’t been identified at that point, much less caught.

One particular $7.99 e-book raised eyebrows: The Shooting of Charlie Kirk: A Comprehensive Account of the Utah Valley University Attack, the Aftermath, and America’s Response. Social media users noted that the author — a phantom named Anastasia J. Casey — had apparently published the book before the event took place. By Thursday evening, Amazon removed the books and calmed nerves by clarifying that The Shooting of Charlie Kirk was actually published on 10 September, following the shooting.

The speed with which Kirk’s death was monetized is jarring, but it is hardly an anomaly. It is a glimpse of a cultural ecosystem which generative AI has quietly colonized. The fact that a major marketplace could be flooded with instant hagiographies, written by no one, about an event that hadn’t fully concluded, is a stark reminder that the AI slop machine doesn’t sleep: it digests the news cycle in real time and spits it back out as a product for consumption.

Publishing is the canary in the coal mine. Over the last year or two, Amazon’s Kindle store has been inundated with AI-written novels — so many that the Authors Guild and the Romance Writers of America have raised alarms about “spam farmers”. The YA-friendly “romantasy” genre, one of publishing’s few growth sectors, has been targeted with slapdash ChatGPT concoctions that mimic bestselling series.

In January, a prolific romance author writing under the pseudonym K.C. Crowne published a Russian mafia-romance novel called Dark Obsession. Soon, screenshots began circulating showing what appeared to be a raw AI prompt embedded in the middle of the book: “Certainly! Here’s an enhanced version of your passage, making Elena more relatable and injecting additional humor while providing a brief, sexy description of Grigori.” A ChatGPT help ticket found in the text of a bodice-ripper was a smoking gun that reveals just how seamlessly AI junk is creeping into the mainstream.

Music has fared no better. On Spotify, a fake AI band named Velvet Sundown racked up over a million plays before it was discovered that their music, promo photos, and backstory were all computer-generated. Most listeners may never even know they are nodding along to a ghost band. Streaming-farm economics incentivize slop: churn out endless ambient tracks with fake artist names, collect fractions of pennies, and repeat.

Film is next. OpenAI this week unveiled its first animated feature, Critterz, to be released in 2026, an experiment in letting a text-to-video model churn out entire cinematic sequences for a massive discount. Hollywood’s striking writers were right to be nervous: if a studio can type “Pixar-style movie about a talking kangaroo who learns about climate change” and get back 90 minutes of content, why pay a screenwriter? The Writers Guild extracted some contractual protections, but the industry logic points in only one direction toward cheap synthetic content.

Even journalism has been compromised. News outlets from CNET to Sports Illustrated have published AI-generated stories without clear disclosure, often riddled with errors. In February, I posted a short video of an anti-Trump No Kings protest at the Pennsylvania Capitol building, and an AI-powered news service called Storyful quickly turned it into a news story picked up as far away as Australia.

The dystopian future taking shape is not one where robots replace all artists outright, but where genuine human work becomes a boutique niche, like vinyl records in the age of Spotify. A hand-crafted novel, a carefully reported investigation, or a band sweating on stage will still exist, but they will be treated as artisanal luxuries, consumed by connoisseurs. For everyone else, there will be the slop: AI-written Charlie Kirk biographies, Spotify filler, Netflix-style auto-cartoons, and news stories composed by bots.

In fairness, culture has always had its pulp, its hacks, and its kitsch. And even before the advent of generative AI, the last generation has witnessed a flattening of cultural life: art and entertainment have been dumbed down by algorithmic incentives, corporate risk aversion, and a cultural climate that prizes literalism over nuance. Performative politics has given us products designed to be ideologically legible rather than genuinely challenging, while declining media literacy has left younger audiences ill-equipped to handle ambiguity or satire. The “slopification” was already underway; AI simply turns up the speed and scale. What was once a slow drift toward homogenized, shallow, disposable content is now a flood.

If Kirk’s instant posthumous canon is any indication, that future isn’t arriving tomorrow. It’s already here.

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Ryan Zickgraf is a columnist for UnHerd, based in Pennsylvania.

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China is trying to catch up with America on artificial intelligence. The Wall Street Journal has reported that Zhipu AI — one of China’s six “AI tiger” LLMs — has released a new model that can rival leading US systems, including Anthropic’s Mythos, in cybersecurity tasks such as pinpointing security bugs. While this marks a milestone in China’s drive to catch up with Western AI capabilities, strong performance on a single benchmark does not mean it has taken the lead. Chinese models still lag behind their Western counterparts in broader capabilities, such as autonomous operation. Skepticism is therefore warranted before resorting to hysterical conclusions, but complacency about the geopolitical implications of China’s AI advances would be an even greater mistake.

On the infrastructure side, Chinese AI is still constrained by access to advanced chips, with American labs way ahead in computing capacity as well as investment. Analysis from earlier this year suggests that Chinese models are likely to be at least a few months behind those in the US. But they are still continuing to make progress, or that the geopolitical importance of AI will be decided only by whose LLM has ventured deeper into the technological frontier. The practical applications of AI, countries’ to capture foreign markets, and the application of AI into the real economy will matter just as much.

Here, China may hold an advantage. As with its dominance across many critical supply chains, Beijing may not need to produce the most advanced AI systems — only those that are affordable and widely deployable. In doing so, it could consolidate global influence by supplying functional, low-cost AI at scale.

Beijing seems to be pursuing exactly that path, developing an AI “open-source” strategy that offers affordable, widely available AI models for companies and individuals to use and modify as they wish. The production of the DeepSeek AI model, which matched the performance of Silicon Valley tools such as ChatGPT at a fraction of the cost for users, created goodwill among Chinese models with developers.

The four most popular models on OpenRouter, an AI hardware platform for developers, are now all Chinese. The goal for China is not only to win the frontier-model race, but to make its systems the default layer of AI adoption across industries and global markets. For most economies, the choice is increasingly between an affordable tool they can deploy now and a more robust one that may be out of reach.

And while the countries adopting Chinese models may be exposed to political pressure and cyber threats from Beijing, safer and more capable alternatives matter little if they are unaffordable. American AI companies are already under pressure to monetize products whose operating costs are rising. If Chinese open-source models become the cheap default for startups, universities, governments and businesses across the developing world, then America’s AI lead will be eroded from below.

Perhaps more concerning for America in the long run is how AI can give Chinese manufacturing even more strength, through the ongoing integration of AI as a general-purpose technology. China’s new Five-Year Plan mentioned AI more than 50 times and includes an “AI+” action plan aimed at spreading AI across the economy.

Beijing has been pioneering automation of its critical infrastructure for years, with promising recent results in increasing warplane production capacity. In that regard, China’s open-model strategy and manufacturing dominance will reinforce each other. Cheap, adaptable models accelerate deployment across the real economy while those deployments generate real-world data and use cases that can feed back into further model improvement.

The United States should not dismiss the importance of its lead in the AI race. That lead worries Beijing, not least because a more automated Chinese economy would also become more vulnerable to AI-generated cyber threats. But nor should Washington assume that China cannot catch up with American capabilities over time.

This AI competition represents part of a broader struggle over tech supply chains and geopolitical influence. Decisions over whether to adopt US or Chinese models could produce a more fragmented global reality, with different regions relying on different cloud providers, chips and security structures. The result will likely be a global economy which is divided into competing spheres, rather than one which produces a single winner.

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Miquel Vila is a political and geopolitical risk consultant focusing on industrial strategy, critical infrastructure and global supply chains.

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