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Why is the Intellectual Dark Web at war with itself?

Civil war in 'Podcastistan' should not surprise us. Credit: The Joe Rogan Experience/YouTube

Civil war in ‘Podcastistan’ should not surprise us. Credit: The Joe Rogan Experience/YouTube

22 April 2025 - 6:45pm

The Intellectual Dark Web is at war. Douglas Murray has been fighting with Joe Rogan and comedian Dave Smith over Palestine and Second World War revisionism. In response, Triggernometry host Konstantin Kisin has published a video and article defending Murray’s arguments from expertise and personal experience. Kisin cites the increasingly poor quality of public debate as evidence that he was mistaken in the core “anti-woke” contention that open debate always tends toward truth. Bret Weinstein has since weighed in, lamenting that Murray and Kisin have become what they once opposed.

So with Kisin counter-signalling open debate, and Murray arguing from authority, is the IDW giving up on its core precepts? What does all of this mean, beyond the trivial insight that commentators don’t always agree among themselves? In brief: that the battle to defend the print-era worldview against its digital successor is over — and print lost.

The IDW is a nexus of commentators that emerged in the 2010s to challenge the solidifying “woke” consensus on topics such as gender and academic freedom. Usually emphasising rationality, open debate and free speech, this caucus sought to defend the classical liberal worldview in an increasingly censorious and “post-truth” climate. But this typically did not include much consideration of the enabling terms of thought or discussion itself — least of all, of the media within which these take place.

And yet these have long been understood to play a crucial role in public life. Among the IxDW commentators, Kisin appears most attuned to this reality, citing Marshall McLuhan’s “the medium is the message” in his video. The reference is apt: of all 20th-century writers on technology, McLuhan is among those most attuned to its mind-altering effects. But in this context, a still more salient voice is surely the literary theorist Walter J. Ong.

In 1982’s Orality and Literacy, Ong theorised that literacy is so profoundly mind-altering that it “restructures consciousness”. Confined to a relatively small elite until the late Middle Ages, following the invention of the printing press this consciousness revolution spread, by degrees, to a majority of Western populations. As documented by historian Elizabeth Eisenstein, this had far-reaching disruptive consequences including the Reformation, the Thirty Years’ War, the modern nation-state settlement, and the scientific and industrial revolutions.

Taken together, these changes have tended to be narrated in hindsight as self-evidently positive, irreversible progress — what the historian Herbert Butterfield called “Whig history”. This settlement is also, broadly speaking, what IDW advocates gesture at when they use terms such as “classical liberalism” and “Western civilisation”.

But Whig history’s “moral progress” can also be seen as a paradigm dependent on print. Early commentators on the digital revolution tended to assume that this would simply accelerate the existing trajectory of the print revolution, and thus continue Whig history. Yet Kisin is right to express a newfound ambivalence about that core print-era value, free debate, for the simple reason that existing evidence suggests the digital revolution is not extending but reversing many aspects of the print paradigm.

In 1982 Ong posited the emergence, with television and radio, of “secondary orality”: that is, people who can read but choose not to. However, this secondary orality emerged fully not with TV and radio in the 20th century, but with the digital revolution of the 21st: a reality with far-reaching effects already noted by educators and intelligence researchers . Its effects are also already political, as the November 2024 “podcast election” attests.

Kisin is on the right track with the title of his essay: “Podcastistan”. This implies a polity of spoken-word rather than written debate; in other words, one of secondary orality. And we can expect such a polity to hew more closely in character and outlook to oral than to literate cultures. For example, as Ong puts it, whereas writing “separates the knower from the known and thus sets up conditions for ‘objectivity’”, in an oral culture “learning or knowing means achieving close, empathetic, communal identification with the known”. Or, as Kisin says of podcast politics, “words do not have meanings, they have feelings”.

The problem for IDW members is that their core paradigm always presupposed the culture enabled and propagated by mass print literacy. But that culture has essentially been killed off by the digital medium within which many (now arguably ex-)IDW figures such as Kisin and Murray continue to thrive, along with sense-makers native to the new secondary orality, such as Rogan.

The tragedy of the IDW is that what its members stood for was, at the time of the group’s formation, already in the process of disappearing. This spate of infighting reveals which of its members have grasped this — and which are still defending a position whose ground is dissolving beneath them.


Mary Harrington is a contributing editor at UnHerd.

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China is threatening America in the AI race

Reports sugget Zhipu AI  has released a new model that can rival leading US systems. Credit: Getty

Reports sugget Zhipu AI has released a new model that can rival leading US systems. Credit: Getty

1 July 2026 - 10:18am

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.


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

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