from the prepare-for-everything-to-get-very-stupid-and-racist dept
You might recall how the press and a bipartisan coalition of lawmakers suffered a four-year embolism about the purported privacy and national security threat of TikTok, before “fixing” the problem by ultimately offloading TikTok to Trump’s billionaire friends. You know, the exact sort of authoritarian-friendly people keen on doing everything critics had previously accused ByteDance and the Chinese of.
The politics, policy, and press coverage of that entire saga were a profound embarrassment. And it’s hard to think of a bigger tech policy own goal by Democrats anytime in the last half century.
Countless news outlets and politicians endlessly overstated the TikTok threat, and downplayed how the “ban” and subsequent sale had nothing to do with protecting national security or consumer privacy, and everything to do with basically stealing a company that U.S. tech couldn’t out-compete, in the process coddling companies like Facebook that can’t innovate their way out of a paper bag.
It was lazy, corrupt protectionism with no shortage of xenophobia, and a variation of that same effort is about to be repeated across AI. Except much bigger, much louder, and much, much dumber.
Worried that cheaper, open source, and on-device Chinese models could disrupt U.S. efforts to dominate, enshittify, and over-charge for walled-garden AI, the Trump administration is already signaling that they’re gearing up to wage war on overseas and open source AI models after they failed to block China’s access to next-generation chipsets:
“The Trump administration is showing signs it could ban cutting-edge Chinese AI models — a momentous move that could lock in dominance by OpenAI and Anthropic.”
Of course it won’t stop there. It will be a hop, skip, and a jump from banning more powerful Chinese AI models to trying to outlaw open source alternatives, models from smaller overseas non-Chinese competitors, on-device models, and anything that might challenge the walled-garden hegemony of U.S. tech giants.
U.S. AI isn’t profitable. It’s nowhere close. It may never be. U.S. tech companies sunk hundred of billions of dollars into costly and ultra-energy intensive AI models that for many companies, like Microsoft, people don’t actually even want to use. Nobody outside of the Musk fashy cult likes Grok. OpenAI is potentially poised to implode. And even more popular companies like Anthropic are contemplating a price war when they already don’t make money.
U.S. tech companies had been busy jacking up the cost of model access to try and claw their way toward profitability (unsuccessfully), resulting in a lot of companies (like Uber) publicly stating they’re paying too much money for too little actual utility. That’s caused many U.S. companies, like DoorDash, to flock to cheaper Chinese models:
“DoorDash, which, according to a post on X on Wednesday by co-founder and CTO Andy Fang, will be launching DoorDash CLI, an experimental tool in limited beta that will allow users to order DoorDash through an AI agent, or even directly from the terminal. Earlier this month, Fang said using a model from Chinese startup Moonshot AI is “better quality” and comes at a “cheaper cost.”
Enter the protectionists, who talk a good game about “free market competition” and forging innovative products in the hot irons of competition, but turn into gargantuan, blubbering crybabies the second Chinese products come into frame (see: TikTok, EVs, 5G, and now AI). This performative gyration always comes with a fake concern for U.S. privacy and national security by people too lazy and corrupt to genuinely protect either (see the ongoing U.S. failure to pass even a baseline internet-era privacy law).
Not only are many Chinese AI models cheaper and improving in quality, they’re often “open-weight,” meaning their parameters or values are entirely visible to the user, which appeals to enterprises that want deeper insights under the hood. As models like China’s Kimi K3 see surging demand, it’s resulting in a rising freak out in the U.S. about what to do about the Chinese threat (sound of thundering timpani drums):
It shouldn’t be too long before the Trump administration, with enthusiastic Democrat support, steps in to try to not only ban higher-power Chinese AI models but also to force Americans to use more expensive U.S. walled garden efforts from our biggest domestic giants.
That’s of course not going to magically stop the rest of the world from adopting cheaper Chinese AI. Or protect U.S. markets from a potential bubble collapse. And it’s not going to magically and suddenly make U.S. AI profitable or well-liked, since many Americans have inextricably tethered their anger at AI to the endless bad decisions by U.S. techno-fascists and domestic enshittification merchants who demand to be shielded from competition and regulatory accountability in equal measure.
You could open the door to international competition, but ensure your well-staffed regulators create a safe and level playing field across privacy, national security, labor, and consumer rights. We don’t want to do that because that might cause domestic U.S. companies to lose money. So instead we’re going to try and ban cheaper overseas alternatives, leveraging a lot of bad faith rhetoric on privacy and NatSec along the way.
That’s then going to be parroted by a lot of lazy news outlets too feckless to explain that Trump policy architects are neither competent nor operating in good faith when it comes to AI.
Things are moving so quickly that it’s hard to parse out exactly what this new era of AI protectionism will look like, but if the TikTok ban was anything to go by, you can be absolutely sure our next steps in domestic U.S. AI policy will be very stupid, filled with a lot of people talking endlessly out of their ass on NatSec and privacy, and tinged with no shortage of gross xenophobia.
Filed Under: ai, china, competition, local ai, open source, open weight, protectionism
Companies: alibaba, anthropic, moonshot, openai, z.ai
Comments on “The Corrupt, Xenophobic Hysteria Behind The ‘TikTok Ban’ Will Soon Be Mirrored Across U.S. AI Policy”
The great irony was that OpenAI was supposed to be a non-commercial entity. And then the grifter-in-chief Sam Altman started dragging it over to the commercial space.
Also, it’s hard to turn AI into a walled garden – there’s just no lock-in mechanism. People aren’t invested in specific LLMs, they just want results, and once they get those results there’s no incentive to keep them using it aside from the quality of the model itself. AI models offer no benefit to walled garden ecosystems. If a model becomes unappealing for any reason people will just use a different one. Neither Apple, Google or Microsoft have managed to create an AI monopoly on any of their devices.
Facts Only
* U.S. lawmakers and press advocated for a TikTok ban based on privacy and national security concerns.
* The TikTok ban resulted in the company being offloaded to U.S.-based buyers.
* The Trump administration has signaled potential bans on cutting-edge Chinese AI models.
* OpenAI and Anthropic are U.S.-based AI companies.
* DoorDash CTO Andy Fang stated that a model from Chinese startup Moonshot AI offers better quality at a lower cost.
* Kimi K3 is a Chinese AI model experiencing increased demand.
* Many Chinese AI models utilize "open-weight" parameters.
* U.S. AI companies, including Microsoft and OpenAI, have invested hundreds of billions of dollars into AI models.
* Uber has publicly stated it pays too much for too little utility regarding current AI access costs.
* The U.S. has not passed a baseline internet-era privacy law.
Executive Summary
U.S. AI policy is currently trending toward protectionism, mirroring previous legislative actions taken against TikTok. There is an emerging conflict between the high-cost, "walled-garden" business models of U.S. giants like OpenAI and Anthropic and the cheaper, often open-weight alternatives emerging from China, such as Moonshot AI and Kimi K3. This shift is driven by the inability of domestic AI firms to achieve profitability despite massive capital investments, leading some U.S. enterprises to seek more cost-effective overseas models.
The Trump administration is signaling a willingness to ban advanced Chinese AI to preserve domestic dominance. While framed as a matter of national security and privacy, these moves are viewed by critics as a means to shield U.S. companies from competition they cannot out-innovate. The situation remains uncertain as to whether these bans will extend to open-source models or non-Chinese overseas competitors, and whether such policies will actually protect the U.S. market or simply accelerate the adoption of foreign AI globally.
Full Take
The strongest version of this narrative is that U.S. "national security" rhetoric is often a facade for economic protectionism, used to bail out domestic monopolies that have failed to innovate or maintain a price advantage. By framing competition as a security threat, the state can legally mandate a captive market for domestic firms.
The argument relies heavily on the "Protectionist Playbook," utilizing a pattern of emotional provocation and framing the struggle as one between "corrupt billionaires" and "open-source innovation." It employs a strategy of historical parallel—linking the TikTok saga to current AI policy—to suggest an inevitable cycle of failure. By characterizing the U.S. AI industry as a bubble on the verge of collapse, the narrative pushes the reader toward a conclusion of systemic incompetence.
Patterns detected: ARC-0012 Emotional Exploitation, ARC-0002 Distortion
This narrative is driven by a "pro-competition/anti-corporate" paradigm. It assumes that market efficiency and open-source availability are the primary moral and economic goods, while ignoring the genuine geopolitical complexities of dual-use AI technology. The implication is that human agency is currently being throttled by "techno-fascists" who prioritize rent-seeking over utility.
If this were a coordinated influence campaign, the playbook would involve eroding trust in domestic institutions by painting them as both incompetent and malicious, while simultaneously promoting the reliability and superiority of foreign (Chinese) technical infrastructure to weaken national cohesion. The content aligns with this pattern by aggressively delegitimizing U.S. policy architects while praising the quality and cost of Chinese alternatives.
Bridge Questions:
1. Is there a measurable technical difference between "national security threats" in social media (data harvesting) and LLMs (algorithmic influence/capabilities)?
2. Would a baseline U.S. privacy law eliminate the need for these bans, or are the concerns rooted in something else entirely?
3. At what point does "open-weight" transparency become a security liability rather than a corporate advantage?
Sentinel — Human
The text functions as polemical opinion journalism, using historical parallels to argue a political thesis about the future of AI regulation, displaying a strong personal voice rather than objective reporting.
