TikTok After Xi’s Qiushi Article: Why China’s Security Laws Are the Whole Ballgame

Xi Jinping’s new article in Qiushi (the Chinese Communist Party Central Committee’s flagship theoretical public policy journal) repackages a familiar message: China will promote the “healthy and high-quality development” of the private economy, but under the leadership of the Chinese Communist Party. This is expressed in China’s statutory law as the “Private Economy Promotion Law.”  And of course we have to always remember that under the PRC “constitution,” statutes are primarily designed to safeguard the authority and interests of the Chinese Communist Party (CCP) rather than to protect the rights and privileges of individuals—because individuals don’t really have any protections against the CCP.  

For U.S. policymakers weighing what to do about TikTok, this is not reassuring rhetoric in my view. It is instead a reminder that, in China, private platforms ultimately operate within a legal-and-political framework that gives state-security organs binding powers over companies, the Chinese people, and their data.

According to the South China Morning Post:

In another show of support for China’s private sector, Beijing has released the details of a speech from President Xi Jinping which included vows the country would guarantee a level playing field for private firms, safeguard entrepreneurs’ lawful rights and interests, and step up efforts to solve their long-standing challenges, including overdue payments.

The full address, delivered in February to a group of China’s leading entrepreneurs, had not been made available to the public before Friday, when Qiushi – the ruling Communist Party’s theoretical journal – posted a transcript on its website.

“The policies and measures to promote the development of the private economy must be implemented in a solid and thorough manner,” Xi said in February. “Whatever the party Central Committee has decided must be resolutely carried out – without ambiguity, delay, or compromise

I will try to explain why the emphasis of Xi’s policy speech matters, and why the divest-or-ban logic for TikTok under US law (and it is a law) remains intact regardless of what may seem like “friendly” language about private enterprise.  It’s also worth remembering that whatever the result of the TikTok divestment may be, it’s just another stop along the way in the Sino-American struggle­—or something more kinetic.  As Clausewitz wrote in his other famous quotation, the outcomes produced by war are never final. (See Book I Chapter 1 aka the good stuff.)  Even the most decisive battlefield victory may have no lasting political achievement.  As we have seen time and again, the termination of one conflict often produces the necessary conditions for future conflict.

What Xi’s piece actually signals

Xi’s article combines pro-private-sector language (property-rights protection, market access, financing support) with an explicit call for Party leadership and ideological guidance in the private economy. In other words, the promise is growth within control, and not just any control but the control of the Party. There is no carve‑out from national-security statutes, no “TikTok exemption,” and no suggestion that private firms can decline cooperation when state-security laws apply consistent with China’s “unrestricted warfare” doctrine.

Recall that the CCP has designated the TikTok algorithm as a strategic national asset, and “national” in this context and the context of Xi’s article means the Chinese Communist Party of which Xi is President-for-Life.  This brother is not playing.

The laws that define the TikTok Divestment risk (not the press releases)

The core concern about TikTok is jurisdiction, or the CCP’s extra-territorial jurisdiction, a concept we don’t fully comprehend. Xi’s Qiushi article promises support for private firms under Party leadership. That means that the National Intelligence Law, Cybersecurity Law, Counter‑Espionage Law, and China’s data‑export regime remain in force and are controlling authority over companies like TikTok. For U.S. reviewers like CIFIUS, that means ByteDance‑controlled TikTok is, by design, subject to compelled, confidential cooperation with state‑security organs. 

As long as the TikTok platform and algorithm is ultimately controlled by a company subject to the CCP’s security laws, U.S. reviewers correctly assume those laws can reach the service, even if operations are partly localized abroad. MTP readers will recall the four pillars of China’s statutory security regime that matter most in this context, being:

National Intelligence Law (2017). Requires all organizations and citizens to support, assist, and cooperate with state intelligence work, and to keep that cooperation secret. Corporate policies and NDAs do not trump statutory duties, especially in the PRC.

Cybersecurity Law (2017). Obligates “network operators” to provide technical support and assistance to public‑security and state‑security organs, and sets the baseline for security reviews and Multi‑Level Protection (MLPS) obligations.

Counter‑Espionage Law (2023 amendment). Broadens the scope of what counts as “espionage” to include data, documents, and materials related to national security or the “national interest,” increasing the zone where requests can be justified.

Data regime (Data Security Law (DSL), Personal Information Protection Law (PIPL), and the Cyberspace Administration of China (CAC) regulatory measures). Controls cross‑border transfers through security assessments or standard contracts and allows denials on national‑security grounds. Practically, many datasets can’t leave China without approval—and keys/cryptography used onshore must follow onshore rules.

None of the above is changed by the Private Economy Promotion Law or by Xi’s supportive tone toward entrepreneurs. The laws remain superior in any conflict such as the TikTok divest-or-ban law.

It is these laws that are at the bottom of U.S. concerns about TikTok’s data scraping–it is, after all, spyware with a soundtrack.  There’s a strong case to be made that U.S. artists, songwriters, creators and fans are all dupes of TikTok as a data collection tool  in a country that requires its companies to hand over to the Ministry of State Security all it needs to support the intelligence mission (MSS is like the FBI and CIA in one agency with a heavy ration of FSB).

Zhang Yiming, founder of ByteDance and former public face of TikTok, stepped down as CEO in 2021 but remains Chairman and key shareholder. He controls more than half of the company’s voting rights and retains about a 21% stake. That also makes him China’s richest man. Though low-profile publicly, he is actively guiding ByteDance’s AI strategy and long-term direction. Mr. Zhang does not discuss this part.  It should come as no surprise–according to his Wikipedia page, Mr. Zhang understands what happens when you don’t toe the Party line:

ByteDance’s first app, Neihan Duanzi, was shut down in 2018 by the National Radio and Television Administration. In response, Zhang issued an apology stating that the app was “incommensurate with socialist core values“, that it had a “weak” implementation of Xi Jinping Thought, and promised that ByteDance would “further deepen cooperation” with the ruling Chinese Communist Party to better promote its policies.

ByteDance’s AI strategy is built on aggressive large-scale data scraping including from TikTok. Its proprietary crawler, ByteSpider, dominates global web-scraping traffic, collecting vast amounts of content at speeds far beyond rivals like OpenAI. This raw data fuels TikTok’s recommendation engine and broader generative AI development, giving ByteDance rapid adaptability and massive training inputs. Unlike OpenAI, which emphasizes curated datasets, ByteDance prioritizes scale, velocity, and real-time responsiveness, integrating insights from TikTok user behavior and the wider internet. This approach positions ByteDance as a formidable AI competitor, leveraging its enormous data advantage to strengthen consumer products, expand generative AI capabilities, and consolidate global influence.

I would find it very, very hard to believe that Mr. Zhang is not a member of the Chinese Communist Party, but in any event he understands very clearly what his role is under the National Intelligence Law and related statutes.  Do you think that standing up to the MSS to protect the data privacy of American teenagers is consistent with “Xi Jinping Thought”?

Why this makes TikTok’s case harder, not easier

For Washington, the TikTok problem is not market access or entrepreneurship. It’s the data governance chain. Xi’s article underscores that private firms are expected to align with the Party Center’s decisions and to embed Party structures. Combine that political expectation with the statutory duties described above, and you get a simple inference: if China’s security services want something—from data access to algorithmic levers—ByteDance and its affiliates are obliged to give it to them or at least help, and are often barred from disclosing that help.

That’s why divestiture has become the U.S. default: the only durable mitigation against TikTok is to place ownership and effective control outside PRC legal reach, with clean technical and organizational separation (code, data, keys, staffing, and change control). Anything short of that leaves the fundamental risk untouched.

Where the U.S. law and process fit

Congress’s divest‑or‑ban statute requires TikTok to be controlled by an entity not subject to PRC direction, on terms approved by U.S. authorities. Beijing’s export‑control rules on recommendation algorithms make a full transfer difficult if not impossible; that’s why proposals have floated a U.S. “fork” with separate code, ops, and data. But Xi’s article doesn’t move the ball: it simply reinforces that CCP jurisdiction over private platforms is a feature, not a bug, of the system.

Practical implications (policy and product)

For policymakers: Treat Xi’s article as confirmation that political control and security statutes are baked in. Negotiated “promises” won’t outweigh legal duties to assist intelligence work. Any compliance plan that assumes voluntary transparency or a “hands‑off” approach is fragile by design.

For platforms: If you operate in China, assume compelled and confidential cooperation is possible and in this case almost a certainty if it hasn’t already happened. Architect China operations as least‑privilege, least‑data environments; segregate code and keys; plan for outbound data barrrers as a normal business condition.

For users and advertisers: The risk discussion is about governance and jurisdiction, not whether a particular management team “would never do that.” They would.  Corporate intent can’t override state legal authority particularly when the Party’s Ministry of State Security is doing the asking.

Now What?

Xi’s article does not soften TikTok’s regulatory problem in the United States. If anything, it sharpens it by reiterating that the private economy advances under the Party’s direction, never apart from it. When you combine Mr. Zhang’s role with Bytedance in China’s AI national champions, it’s pretty obvious whose side TikTok is on.

Wherever the divest-or-ban legislation ends up, it will inevitably set the stage for the next conflict.  If I had to bet today, my bet is that Xi has no intention of making a deal with the US that involves giving up the TikTok algorithm in violation of the Party’s export-control rules and access to US user data for AI training.

From Fictional “Looking Backward” to Nonfiction Silicon Valley: Will Technologists Crown the New Philosopher‑Kings?

More than a century ago, writers like Edward Bellamy and Edward Mandell House asked a question that feels as urgent in 2025 as it did in their era: Should society be shaped by its people, or designed by its elites? Both grappled with this tension in fiction. Bellamy’s Looking Backward (1888) imagined a future society run by rational experts — technocrats and bureaucrats centralizing economic and social life for the greater good. House’s Philip Dru: Administrator (1912) went a step further, envisioning an American civil war where a visionary figure seizes control from corrupt institutions to impose a new era of equity and order.  Sound familiar?

Today, Silicon Valley’s titans are rehearsing their own versions of these stories. In an era dominated by artificial intelligence, climate crisis, and global instability, the tension between democratic legitimacy and technocratic efficiency is more pronounced than ever.

The Bellamy Model: Eric Schmidt and Biden’s AI Order

President Biden’s sweeping Executive Order on AI issued in late 2023 feels like a chapter lifted from Looking Backward. Its core premise is unmistakable: Trust our national champion “trusted” technologists to design and govern the rules for an era shaped by artificial intelligence. At the heart of this approach is Eric Schmidt, former CEO of Google and a key advisor in shaping the AI order at least according to Eric Schmidt. 

Schmidt has long advocated for centralizing AI policymaking within a circle of vetted, elite technologists — a belief reminiscent of Bellamy’s idealistic vision. According to Schmidt, AI and other disruptive technologies are too pivotal, too dangerous, and too impactful to be left to messy democratic debates. For people in Schmidt’s cabal, this approach is prudent: a bulwark against AI’s darker possibilities. But it doesn’t do much to protect against darker possibilities from AI platforms.  For skeptics like me, it raises a haunting question posed by Bellamy himself: Are we delegating too much authority to a technocratic elite?

The Philip Dru Model: Musk, Sacks, and Trump’s Disruption Politics

Meanwhile, across the aisle, another faction of Silicon Valley is aligning itself with Donald Trump and making a very different bet for the future. Here, the nonfiction playbook is closer to the fictional Philip Dru. In House’s novel, an idealistic and forceful figure emerges from a broken system to impose order and equity. Enter Elon Musk and David Sacks, both positioning themselves as champions of disruption, backed by immense platforms, resources, and their own venture funds. 

Musk openly embraces a worldview wherein technologists have both the tools and the mandate to save society by reshaping transportation, energy, space, and AI itself. Meanwhile, Sacks advocates Silicon Valley as a de facto policymaker, disrupting traditional institutions and aligning with leaders like Trump to advance a new era of innovation-driven governance—with no Senate confirmation or even a security clearance. This competing cabal operates with the implicit belief that traditional democratic institutions, inevitiably bogged down by process, gridlock, and special interests can no longer solve society’s biggest problems. To Special Government Employees like Musk and Sacks, their disruption is not a threat to democracy, but its savior.

A New Gilded Age? Or a New Social Contract?

Both threads — Biden and Schmidt’s technocratic centralization and Musk, Sacks, and Trump’s disruption-driven politics — grapple with the legacy of Bellamy and House. In the Gilded Age that inspired those writers, industrial barons sought to justify their dominance with visions of rational, top-down progress. Today’s Silicon Valley billionaires carry a similar vision for the digital era, suggesting that elite technologists can govern more effectively than traditional democratic institutions like Plato’s “guardians” of The Republic.

But at what cost? Will AI policymaking and its implementation evolve as a public endeavor, shaped by citizen accountability? Or will it be molded by corporate elites making decisions in the background? Will future leaders consolidate their role as philosopher-kings and benevolent administrators — making themselves indispensable to the state?

The Stakes Are Clear

As the lines between Silicon Valley and Washington continue to blur, the questions posed by Bellamy and House have never been more relevant: Will technologist philosopher-kings write the rules for our collective future? Will democratic institutions evolve to balance AI and climate crisis effectively? Will the White House of 2025 (and beyond) cede authority to the titans of Silicon Valley? In this pivotal moment, America must ask itself: What kind of future do we want — one that is chosen by its citizens, or one that is designed for its citizens? The answer will define the character of American democracy for the rest of the 21st century — and likely beyond.

Shilling Like It’s 1999: Ars, Anthropic, and the Internet of Other People’s Things

Ars Technica just ran a piece headlined “AI industry horrified to face largest copyright class action ever certified.”

It’s the usual breathless “innovation under siege” framing—complete with quotes from “public interest” groups that, if you check the Google Shill List submitted to Judge Alsup in the Oracle case and Public Citizen’s Mission Creep-y, have long been in the paid service of Big Tech. Judge Alsup…hmmm…isn’t he the judge in the very Anthropic case that Ars is going on about?

Here’s what Ars left out: most of these so-called advocacy outfits—EFF, Public Knowledge, CCIA, and their cousins—have been doing Google’s bidding for years, rebranding corporate priorities as public interest. It’s an old play: weaponize the credibility of “independent” voices to protect your bottom line.

The article parrots the industry’s favorite excuse: proving copyright ownership is too hard, so these lawsuits are bound to fail. That line would be laughable if it weren’t so tired; it’s like elder abuse. We live in the age of AI deduplication, manifest checking, and robust content hashing—technologies the AI companies themselves use daily to clean, track, and optimize their training datasets. If they can identify and strip duplicates to improve model efficiency, they can identify and track copyrighted works. What they mean is: “We’d rather not, because it would expose the scale of our free-riding.”

That’s the unspoken truth behind these lawsuits. They’re not about “stifling innovation.” They’re about holding accountable an industry that’s built its fortunes on what can only be called the Internet of Other People’s Things—a business model where your creative output, your data, and your identity are raw material for someone else’s product, without permission, payment, or even acknowledgment.

Instead of cross-examining these corporate talking points like you know…journalists…Ars lets them pass unchallenged, turning what could have been a watershed moment for transparency into a PR assist. That’s not journalism—it’s message laundering.

The lawsuit doesn’t threaten the future of AI. It threatens the profitability of a handful of massive labs—many backed by the same investors and platforms that bankroll these “public interest” mouthpieces. If the case succeeds, it could force AI companies to abandon the Internet of Other People’s Things and start building the old-fashioned way: by paying for what they use.

Come on, Ars. Do we really have to go through this again? If you’re going to quote industry-adjacent lobbyists as if they were neutral experts, at least tell readers who’s paying the bills. Otherwise, it’s just shilling like it’s 1999.

AI’s Manhattan Project Rhetoric, Clearance-Free Reality

Every time a tech CEO compares frontier AI to the Manhattan Project, take a breath—and remember what that actually means.  Master spycatcher James Jesus Angleton is rolling in his grave. (aka Matt Damon in The Good Shepherd.). And like most elevator pitch talking points, that analogy starts to fall apart on inspection.

The Manhattan Project wasn’t just a moonshot scientific collaboration. It was the most tightly controlled, security-obsessed R&D operation in American history. Every physicist, engineer, and janitor involved had a federal security clearance. Facilities were locked down under military command of General Leslie Groves. Communications were monitored. Access was compartmentalized. And still—still—the Soviets penetrated it.  See Klaus Fuchs.  Let’s understand just how secret the Manhattan Project was—General Curtis LeMay had no idea it was happening until he was asked to set up facilities for the Enola Gay on his bomber base on Tinian a few months before the first nuclear bomb.  You want to find out about the details of any frontier lab, just pick up the newspaper.  Not nearly the same thing. There were no chatbots involved and there were no Special Government Employees with no security clearance.

Oppie Sacks

So when today’s AI executives name-drop Oppenheimer and invoke the gravity of dual-use technologies, what exactly are they suggesting? That we’re building world-altering capabilities without any of the safeguards that even the AI Whiz Kids admit are historically necessary by their Manhattan Project talking point in the pitch deck?

These frontier labs aren’t locked down. They’re open-plan. They’re not vetting personnel. They’re recruiting from Discord servers. They’re not subject to classified environments. They’re training military-civilian dual-use models on consumer cloud platforms. And when questioned, they invoke private sector privilege and push back against any suggestion of state or federal regulation.  And here’s a newsflash—requiring a security clearance for scientific work in the vital national interest is not regulation.  (Neither is copyright but that’s another story.)

Meanwhile, they’re angling for access to Department of Energy nuclear real estate, government compute subsidies, and preferred status in export policy—all under the justification of “national security” because, you know, China.  They want the symbolism of the Manhattan Project without the substance. They want to be seen as indispensable without being held accountable.

The truth is that AI is dual-use. It can power logistics and surveillance, language learning and warfare. That’s not theoretical—it’s already happening. China openly treats AI as part of its military-civil fusion strategy. Russia has targeted U.S. systems with information warfare bots. And our labs? They’re scraping from the open internet and assuming the training data hasn’t been poisoned with the massive misinformation campaigns on Wikipedia, Reddit and X that are routine.

If even the Manhattan Project—run under maximum secrecy—was infiltrated by Soviet spies, what are the chances that today’s AI labs, operating in the wide open are immune?  Wouldn’t a good spycatcher like Angleton assume these wunderkinds have already been penetrated?

We have no standard vetting for employees. No security clearances. No model release controls. No audit trail for pretraining data integrity. And no clear protocol for foreign access to model weights, inference APIs, or sensitive safety infrastructure. It’s not a matter of if. It’s a matter of when—or more likely, a matter of already.

Remember–nobody got rich out of working on the Manhattan Project. That’s another big difference. These guys are in it for the money, make no mistake.

So when you hear the Manhattan Project invoked again, ask the follow-up question: Where’s the security clearance?  Where’s the classification?  Where’s the real protection?  Who’s playing the role of Klaus Fuchs?

Because if AI is our new Manhattan Project, then running it without security is more than hypocrisy. It’s incompetence at scale.

AI Frontier Labs and the Singularity as a Modern Prophetic Cult

It gets rid of your gambling debts 
It quits smoking 
It’s a friend, it’s a companion 
It’s the only product you will ever need
From Step Right Up, written by Tom Waits

The AI “frontier labs” — OpenAI, Anthropic, DeepMind, xAI, and their constellation of evangelists — often present themselves as the high priests of a coming digital transcendence. This is sometimes called “the singularity” which refers to a hypothetical future point when artificial intelligence surpasses human intelligence, triggering rapid, unpredictable technological growth. Often associated with self-improving AI, it implies a transformation of society, consciousness, and control, where human decision-making may be outpaced or rendered obsolete by machines operating beyond our comprehension. 

But viewed through the lens of social psychology, the AI evangelists increasingly resembles that of cognitive dissonance cults, as famously documented in Dr. Leon Festinger and team’s important study of a UFO cult (a la Heaven’s Gate), When Prophecy Fails.  (See also The Great Disappointment.)

In that social psychology foundational study, a group of believers centered around a woman named “Marian Keech” predicted the world would end in a cataclysmic flood, only to be rescued by alien beings — but when the prophecy failed, they doubled down. Rather than abandoning their beliefs, the group rationalized the outcome (“We were spared because of our faith”) and became even more committed. They get this self-hypnotized look, kind of like this guy (and remember-this is what the Meta marketing people thought was the flagship spot for Meta’s entire superintelligence hustle):


This same psychosis permeates Singularity narratives and the AI doom/alignment discourse:
– The world is about to end — not by water, but by unaligned superintelligence.
– A chosen few (frontier labs) hold the secret knowledge to prevent this.
– The public must trust them to build, contain, and govern the very thing they fear.
– And if the predicted catastrophe doesn’t come, they’ll say it was their vigilance that saved us.

Like cultic prophecy, the Singularity promises transformation:
– Total liberation or annihilation (including liberation from annihilation by the Red Menace, i.e., the Chinese Communist Party).
– A timeline (“AGI by 2027”, “everything will change in 18 months”).
– An elite in-group with special knowledge and “Don’t be evil” moral responsibility.
– A strict hierarchy of belief and loyalty — criticism is heresy, delay is betrayal.

This serves multiple purposes:
1. Maintains funding and prestige by positioning the labs as indispensable moral actors.
2. Deflects criticism of copyright infringement, resource consumption, or labor abuse with existential urgency (because China, don’t you know).
3. Converts external threats (like regulation) into internal persecution, reinforcing group solidarity.

The rhetoric of “you don’t understand how serious this is” mirrors cult defenses exactly.

Here’s the rub: the timeline keeps slipping. Every six months, we’re told the leap to “godlike AI” is imminent. GPT‑4 was supposed to upend everything. That didn’t happen, so GPT‑5 will do it for real. Gemini flopped, but Claude 3 might still be the one.

When prophecy fails, they don’t admit error — they revise the story:
– “AI keeps accelerating”
– “It’s a slow takeoff, not a fast one.”
– “We stopped the bad outcomes by acting early.”
– “The doom is still coming — just not yet.”

Leon Festinger’s theories seen in When Prophecy Fails, especially cognitive dissonance and social comparison, influence AI by shaping how systems model human behavior, resolve conflicting inputs, and simulate decision-making. His work guides developers of interactive agents, recommender systems, and behavioral algorithms that aim to mimic or respond to human inconsistencies, biases, and belief formation.   So this isn’t a casual connection.

As with Festinger’s study, the failure of predictions intensifies belief rather than weakening it. And the deeper the believer’s personal investment, the harder it is to turn back. For many AI cultists, this includes financial incentives, status, and identity.

Unlike spiritual cults, AI frontier labs have material outcomes tied to their prophecy:
– Federal land allocations, as we’ve seen with DOE site handovers.
– Regulatory exemptions, by presenting themselves as saviors.
– Massive capital investment, driven by the promise of world-changing returns.

In the case of AI, this is not just belief — it’s belief weaponized to secure public assets, shape global policy, and monopolize technological futures. And when the same people build the bomb, sell the bunker, and write the evacuation plan, it’s not spiritual salvation — it’s capture.

The pressure to sustain the AI prophecy—that artificial intelligence will revolutionize everything—is unprecedented because the financial stakes are enormous. Trillions of dollars in market valuation, venture capital, and government subsidies now hinge on belief in AI’s inevitable dominance. Unlike past tech booms, today’s AI narrative is not just speculative; it is embedded in infrastructure planning, defense strategy, and global trade. This creates systemic incentives to ignore risks, downplay limitations, and dismiss ethical concerns. To question the prophecy is to threaten entire business models and geopolitical agendas. As with any ideology backed by capital, maintaining belief becomes more important than truth.

The Singularity, as sold by the frontier labs, is not just a future hypothesis — it’s a living ideology. And like the apocalyptic cults before them, these institutions demand public faith, offer no accountability, and position themselves as both priesthood and god.

If we want a secular, democratic future for AI, we must stop treating these frontier labs as prophets — and start treating them as power centers subject to scrutiny, not salvation.

Schrödinger’s Training Clause: How Platforms Like WeTransfer Say They’re Not Using Your Files for AI—Until They Are

Tech companies want your content. Not just to host it, but for their training pipeline—to train models, refine algorithms, and “improve services” in ways that just happen to lead to new commercial AI products. But as public awareness catches up, we’ve entered a new phase: deniable ingestion.

Welcome to the world of the Schrödinger’s training clause—a legal paradox where your data is simultaneously not being used to train AI and fully licensed in case they decide to do so.

The Door That’s Always Open

Let’s take the WeTransfer case. For a brief period this month (in July 2025), their Terms of Service included an unmistakable clause: users granted them rights to use uploaded content to “improve the performance of machine learning models.” That language was direct. It caused backlash. And it disappeared.

Many mea culpas later, their TOS has been scrubbed clean of AI references. I appreciate the sentiment, really I do. But—and there’s always a but–the core license hasn’t changed. It’s still:

– Perpetual

– Worldwide

– Royalty-free

– Transferable

– Sub-licensable

They’ve simply returned the problem clause to its quantum box. No machine learning references. But nothing that stops it either.

 A Clause in Superposition

Platforms like WeTransfer—and others—have figured out the magic words: Don’t say you’re using data to train AI. Don’t say you’re not using it either. Instead, claim a sweeping license to do anything necessary to “develop or improve the service.”

That vague phrasing allows future pivots. It’s not a denial. It’s a delay. And to delay is to deny.

That’s what makes it Schrödinger’s training clause: Your content isn’t being used for AI. Unless it is. And you won’t know until someone leaks it, or a lawsuit makes discovery public.

The Scrape-Then-Scrub Scenario

Let’s reconstruct what could have happened–not saying it did happen, just could have–following the timeline in The Register:

1. Early July 2025: WeTransfer silently updates its Terms of Service to include AI training rights.

2. Users continue uploading sensitive or valuable content.

3. [Somebody’s] AI systems quickly ingest that data under the granted license.

4. Public backlash erupts mid-July.

5. WeTransfer removes the clause—but to my knowledge never revokes the license retroactively or promises to delete what was scraped. In fact, here’s their statement which includes this non-denial denial: “We don’t use machine learning or any form of AI to process content shared via WeTransfer.” OK, that’s nice but that wasn’t the question. And if their TOS was so clear, then why the amendment in the first place?

Here’s the Potential Legal Catch

Even if WeTransfer removed the clause later, any ingestion that occurred during the ‘AI clause window’ is arguably still valid under the terms then in force. As far as I know, they haven’t promised:

– To destroy any trained models

– To purge training data caches

– Or to prevent third-party partners from retaining data accessed lawfully at the time

What Would ‘Undoing’ Scraping Require?

– Audit logs to track what content was ingested and when

– Reversion of any models trained on user data

– Retroactive license revocation and sub-license termination

None of this has been offered that I have seen.

What ‘We Don’t Train on Your Data’ Actually Means

When companies say, “we don’t use your data to train AI,” ask:

– Do you have the technical means to prevent that?

– Is it contractually prohibited?

– Do you prohibit future sublicensing?

– Can I audit or opt out at the file level?

If the answer to those is “no,” then the denial is toothless.

How Creators Can Fight Back

1. Use platforms that require active opt-in for AI training.

2. Encrypt files before uploading.

3. Include counter-language in contracts or submission terms:

   “No content provided may be used, directly or indirectly, to train or fine-tune machine learning or artificial intelligence systems, unless separately and explicitly licensed for that purpose in writing” or something along those lines.

4. Call it out. If a platform uses Schrödinger’s language, name it. The only thing tech companies fear more than litigation is transparency.

What is to Be Done?

The most dangerous clauses aren’t the ones that scream “AI training.” They’re the ones that whisper, “We’re just improving the service.”

If you’re a creative, legal advisor, or rights advocate, remember: the future isn’t being stolen with force. It’s being licensed away in advance, one unchecked checkbox at a time.

And if a platform’s only defense is “we’re not doing that right now”—that’s not a commitment. That’s a pause.

That’s Schrödinger’s training clause.

From Plutonium to Prompt Engineering: Big Tech’s Land Grab at America’s Nuclear Sites–and Who’s Paying for It?

In a twist of post–Cold War irony, the same federal sites that once forged the isotopes of nuclear deterrence are now poised to fuel the arms race of artificial intelligence under the leadership of Special Government Employee and Silicon Valley Viceroy David Sacks. Under a new Department of Energy (DOE) initiative, 16 legacy nuclear and lab sites — including Savannah River, Idaho National Lab, and Oak Ridge Tennessee — are being opened to private companies to host massive AI data centers. That’s right–Tennessee where David Sacks is riding roughshod over the ELVIS Act.

DOE Giveaway 2025-05936Download

But as this techno-industrial alliance gathers steam, one question looms large: Who benefits — and how will the American public be compensated for leasing its nuclear commons to the world’s most powerful corporations? Spoiler alert: We won’t.

A New Model, But Not the Manhattan Project

This program is being billed in headlines as a “new Manhattan Project for AI.” But that comparison falls apart quickly. The original Manhattan Project was:
– Owned by the government
– Staffed by public scientists
– Built for collective defense

Today’s AI infrastructure effort is:
– Privately controlled
– Driven by monopolies and venture capital
– Structured to avoid transparency and public input
– Uses free leases on public land with private nuclear reactors

Call it the Manhattan Project in reverse — not national defense, but national defense capture.

The Art of the Deal: Who gets what?

What Big Tech Is Getting

– Access to federal land already zoned, secured, and wired
– Exemption from state and local permitting
– Bypass of grid congestion via nuclear-ready substations
– DOE’s help fast-tracking nuclear microreactors (SMRs)
– Potential sovereign AI training enclaves, shielded from export controls and oversight

And all of it is being made available to private companies called the “Frontier labs”: Microsoft, Oracle, Amazon, OpenAI, Anthropic, xAI — the very firms at the center of the AI race.

What the Taxpayer Gets (Maybe)

Despite this extraordinary access, almost nothing is disclosed about how the public is compensated. No known revenue-sharing models. No guaranteed public compute access. No equity. No royalties.

Land lease payments? Not disclosed. Probably none.
Local tax revenue? Minimal (federal lands exempt)
Infrastructure benefit sharing? Unclear or limited

It’s all being negotiated quietly, under vague promises of “national competitiveness.”

Why AI Labs Want DOE Sites

Frontier labs like OpenAI and Anthropic — and their cloud sponsors — need:
– Gigawatts of energy
– Secure compute environments
– Freedom from export rules and Freedom of Information Act requests
– Permitting shortcuts and national branding

The DOE sites offer all of that — plus built-in federal credibility. The same labs currently arguing in court that their training practices are “fair use” now claim they are defenders of democracy training AI on taxpayer-built land.

This Isn’t the Manhattan Project — It’s the Extraction Economy in a Lab Coat

The tech industry loves to invoke patriotism when it’s convenient — especially when demanding access to federal land, nuclear infrastructure, or diplomatic cover from the EU’s AI Act. But let’s be clear:

This isn’t the Manhattan Project. Or rather we should hope it isn’t because that one didn’t end well and still hasn’t.
It’s not public service.
It’s Big Tech lying about fair use, wrapped in an American flag — and for all we know, it might be the first time David Sacks ever saw one.

When companies like OpenAI and Microsoft claim they’re defending democracy while building proprietary systems on DOE nuclear land, we’re not just being gaslit — we’re being looted.

If the AI revolution is built on nationalizing risk and privatizing power, it’s time to ask whose country this still is — and who gets to turn off the lights.

When Viceroy David Sacks Writes the Tariffs: How One VC Could Weaponize U.S. Trade Against the EU

David Sacks is a “Special Government Employee”, Silicon Valley insider and a PayPal mafioso who has become one of the most influential “unofficial” architects of AI policy under the Trump administration. No confirmation hearings, no formal role—but direct access to power.

He:
– Hosts influential political podcasts with Musk and Thiel-aligned narratives.
– Coordinates behind closed doors with elite AI companies who are now PRC-style “national champions” (OpenAI, Anthropic, Palantir).
– Has reportedly played a central role in shaping the AI Executive Orders and industrial strategy driving billions in public infrastructure to favored firms.

Under 18 U.S.C. § 202(a), a Special Government Employee is:

  • Temporarily retained to perform limited government functions,
  • For no more than 130 days per year (which for Sacks ends either April 14 or May 30, 2025), unless reappointed in a different role,
  • Typically serves in an advisory or consultative role, or
  • Without holding actual decision-making or operational authority over federal programs or agencies.

SGEs are used to avoid conflict-of-interest entanglements for outside experts while still tapping their expertise for advisory purposes. They are not supposed to wield sweeping executive power or effectively run a government program. Yeah, right.

And like a good little Silicon Valley weasel, Sacks supposedly is alternating between his DC side hustle and his VC office to stay under 130 days. This is a dumbass reading of the statute which says “‘Special Government employee’ means… any officer or employee…retained, designated, appointed, or employed…to perform…temporary duties… for not more than 130 days during any period of 365 consecutive days.” That’s not the same as “worked” 130 days on the time card punch. But oh well.

David Sacks has already exceeded the legal boundaries of his appointment as a Special Government Employee (SGE) both in time served but also by directing the implementation of a sweeping, whole-of-government AI policy, including authoring executive orders, issuing binding directives to federal agencies, and coordinating interagency enforcement strategies—actions that plainly constitute executive authority reserved for duly appointed officers under the Appointments Clause. As an SGE, Sacks is authorized only to provide temporary, nonbinding advice, not to exercise operational control or policy-setting discretion across the federal government. Accordingly, any executive actions taken at his direction or based on his advisement are constitutionally infirm as the unlawful product of an individual acting without valid authority, and must be deemed void as “fruit of the poisonous tree.”

Of course, one of the states that the Trump AI Executive Orders will collide with almost immediately is the European Union and its EU AI Act. Were they 51st? No that’s Canada. 52nd? Ah, right that’s Greenland. Must be 53rd.

How Could David Sacks Weaponize Trade Policy to Help His Constituents in Silicon Valley?

Here’s the playbook:

Engineer Executive Orders

Through his demonstrated access to Trump and senior White House officials, Sacks could promote executive orders under the International Emergency Economic Powers Act (IEEPA) or Section 301 of the Trade Act, aimed at punishing countries (like EU members) for “unfair restrictions” on U.S. AI exports or operations.

Something like this: “The European Union’s AI Act constitutes a discriminatory and protectionist measure targeting American AI innovation, and materially threatens U.S. national security and technological leadership.” I got your moratorium right here.

Leverage the USTR as a Blunt Instrument

The Office of the U.S. Trade Representative (USTR) can initiate investigations under Section 301 without needing new laws. All it takes is political will—and a nudge from someone like Viceroy Sacks—to argue that the EU’s AI Act discriminates against U.S. firms. See Canada’s “Tech Tax”. Gee, I wonder if Viceroy Sacks had anything to do with that one.

Redefine “National Security”

Sacks and his allies can exploit the Trump administration’s loose definition of “national security” claiming that restricting U.S. AI firms in Europe endangers critical defense and intelligence capabilities.

Smear Campaigns and Influence Operations

Sacks could launch more public campaigns against the EU like his attacks on the AI diffusion rule. According to the BBC, “Mr. Sacks cited the alienation of allies as one of his key arguments against the AI diffusion plan”. That’s a nice ally you got there, be a shame if something happened to it.

After all, the EU AI Act does what Sacks despises like protects artists and consumers, restricts deployment of high-risk AI systems (like facial recognition and social scoring), requires documentation of training data (which exposes copyright violations), and applies extraterritorially (meaning U.S. firms must comply even at home).

And don’t forget, Viceroy Sacks actually was given a portfolio that at least indirectly includes the National Security Council, so he can use the NATO connection to put a fine edge on his “industrial patriotism” just as war looms over Europe.

When Policy Becomes Personal

In a healthy democracy, trade retaliation should be guided by evidence, public interest, and formal process.

But under the current setup, someone like David Sacks can short-circuit the system—turning a private grievance into a national trade war. He’s already done it to consumers, wrongful death claims and copyright, why not join war lords like Eric Schmidt and really jack with people? Like give deduplication a whole new meaning.

When one man’s ideology becomes national policy, it’s not just bad governance.

It’s a broligarchy in real time.

Beyond Standard Oil: How the AI Action Plan Made America a Command Economy for Big Tech That You Will Pay For

When the White House requested public comments earlier this year on how the federal government should approach artificial intelligence, thousands of Americans—ranging from scientists to artists, labor leaders to civil liberties advocates—responded with detailed recommendations. Yet when America’s AI Action Plan was released today, it became immediately clear that those voices were largely ignored. The plan reads less like a response to public input and more like a pre-written blueprint drafted in collaboration with the very corporations it benefits. The priorities, language, and deregulatory thrust suggest that the real consultations happened behind closed doors—with Big Tech executives, not the American people.

In other words, business as usual.

By any historical measure—Standard Oil, AT&T, or even the Cold War military-industrial complex—the Trump Administration’s “America’s AI Action Plan” represents a radical leap toward a command economy built for and by Big Tech. Only this time, there are no rate regulations, no antitrust checks, and no public obligations—just streamlined subsidies, deregulation, and federally orchestrated dominance by a handful of private AI firms.

“Frontier Labs” as National Champions

The plan doesn’t pretend to be neutral. It picks winners—loudly. Companies like OpenAI, Anthropic, Meta, Microsoft, and Google are effectively crowned as “national champions,” entrusted with developing the frontier of artificial intelligence on behalf of the American state.

– The National AI Research Resource (NAIRR) and National Science Foundation partnerships funnel taxpayer-funded compute and talent into these firms.
– Federal procurement standards now require models that align with “American values,” but only as interpreted by government-aligned vendors.
– These companies will receive priority access to compute in a national emergency, hard-wiring them into the national security apparatus.
– Meanwhile, so-called “open” models will be encouraged in name only—no requirement for training data transparency, licensing, or reproducibility.

This is not a free market. This is national champion industrial policy—without the regulation or public equity ownership that historically came with it.

Infrastructure for Them, Not Us

The Action Plan reads like a wishlist from Silicon Valley’s executive suites:

– Federal lands are being opened up for AI data centers and energy infrastructure.
– Environmental and permitting laws are gutted to accelerate construction of facilities for private use.
– A national electrical grid expansion is proposed—not to serve homes and public transportation, but to power hyperscaler GPUs for model training.
– There’s no mention of public access, community benefit, or rural deployment. This is infrastructure built with public expense for private use.

Even during the era of Ma Bell, the public got universal service and price caps. Here? The public is asked to subsidize the buildout and then stand aside.

Deregulation for the Few, Discipline for the Rest

The Plan explicitly orders:
– Rescission of Biden-era safety and equity requirements.
– Reviews of FTC investigations to shield AI firms from liability.
– Withholding of federal AI funding from states that attempt to regulate the technology for safety, labor, or civil rights purposes.

Meanwhile, these same companies are expected to supply the military, detect cyberattacks, run cloud services for federal agencies, and set speech norms in government systems.

The result? An unregulated cartel tasked with executing state functions.

More Extreme Than Standard Oil or AT&T

Let’s be clear: Standard Oil was broken up. AT&T had to offer regulated universal service. Lockheed, Raytheon, and the Cold War defense contractors were overseen by procurement auditors and GAO enforcement.

This new AI economy is more privatized than any prior American industrial model—yet more dependent on the federal government than ever before. It’s an inversion of free market principles wrapped in American flags and GPU clusters.

Welcome to the Command Economy—For Tech Oligarchs

There’s a word for this: command economy. But instead of bureaucrats in Soviet ministries, we now have a handful of unelected CEOs directing infrastructure, energy, science, education, national security, and labor policy—all through cozy relationships with federal agencies.

If we’re going to nationalize AI, let’s do it honestly—with public governance, democratic accountability, and shared benefit. But this halfway privatized, fully subsidized, and wholly unaccountable structure isn’t capitalism. It’s capture.

AI Needs Ever More Electricity—And Google Wants Us to Pay for It

Uncle Sugar’s “National Emergency” Pitch to Congress

At a recent Congressional hearing, former Google CEO Eric “Uncle Sugar” Schmidt delivered a message that was as jingoistic as it was revealing: if America wants to win the AI arms race, it better start building power plants. Fast. But the subtext was even clearer—he expects the taxpayer to foot the bill because, you know, the Chinese Communist Party. Yes, when it comes to fighting the Red Menace, the all-American boys in Silicon Valley will stand ready to fight to the last Ukrainian, or Taiwanese, or even Texan.

Testifying before the House Energy & Commerce Committee on April 9, Schmidt warned that AI’s natural limit isn’t chips—it’s electricity. He projected that the U.S. would need 92 gigawatts of new generation capacity—the equivalent of nearly 100 nuclear reactors—to keep up with AI demand.

Schmidt didn’t propose that Google, OpenAI, Meta, or Microsoft pay for this themselves, just like they didn’t pay for broadband penetration. No, Uncle Sugar pushed for permitting reform, federal subsidies, and government-driven buildouts of new energy infrastructure. In plain English? He wants the public sector to do the hard and expensive work of generating the electricity that Big Tech will profit from.

Will this Improve the Grid?

And let’s not forget: the U.S. electric grid is already dangerously fragile. It’s aging, fragmented, and increasingly vulnerable to cyberattacks, electromagnetic pulse (EMP) weapons, and even extreme weather events. Pouring public money into ultra-centralized AI data infrastructure—without first securing the grid itself—is like building a mansion on a cracked foundation.

If we are going to incur public debt, we should prioritize resilience, distributed energy, grid security, and community-level reliability—not a gold-plated private infrastructure buildout for companies that already have trillion-dollar valuations.

Big Tech’s Growing Appetite—and Private Hoarding

This isn’t just a future problem. The data center buildout is already in full swing and your Uncle Sugar must be getting nervous about where he’s going to get the money from to run his AI and his autonomous drone weapons. In Oregon, where electricity is famously cheap thanks to the Bonneville Power Administration’s hydroelectric dams on the Columbia River, tech companies have quietly snapped up huge portions of the grid’s output. What was once a shared public benefit—affordable, renewable power—is now being monopolized by AI compute farms whose profits leave the region to the bank accounts in Silicon Valley.

Meanwhile, Microsoft is investing in a nuclear-powered data center next to the defunct Three Mile Island reactor—but again, it’s not about public benefit. It’s about keeping Azure’s training workloads running 24/7. And don’t expect them to share any of that power capacity with the public—or even with neighboring hospitals, schools, or communities.

Letting the Public Build Private Fortresses

The real play here isn’t just to use public power—it’s to get the public to build the power infrastructure, and then seal it off for proprietary use. Moats work both ways.

That includes:
– Publicly funded transmission lines across hundreds of miles to deliver power to remote server farms;
– Publicly subsidized generation capacity (nuclear, gas, solar, hydro—you name it);
– And potentially, prioritized access to the grid that lets AI workloads run while the rest of us face rolling blackouts during heatwaves.

All while tech giants don’t share their models, don’t open their training data, and don’t make their outputs public goods. It’s a privatized extractive model, powered by your tax dollars.

Been Burning for Decades

Don’t forget: Google and YouTube have already been burning massive amounts of electricity for 20 years. It didn’t start with ChatGPT or Gemini. Serving billions of search queries, video streams, and cloud storage events every day requires a permanent baseload—yet somehow this sudden “AI emergency” is being treated like a surprise, as if nobody saw it coming.

If they knew this was coming (and they did), why didn’t they build the power? Why didn’t they plan for sustainability? Why is the public now being told it’s our job to fix their bottleneck?

The Cold War Analogy—Flipped on Its Head

Some industry advocates argue that breaking up Big Tech or slowing AI infrastructure would be like disarming during a new Cold War with China. But Gail Slater, the Assistant Attorney General leading the DOJ’s Antitrust Division, pushed back forcefully—not at a hearing, but on the War Room podcast.

In that interview, Slater recalled how AT&T tried to frame its 1980s breakup as a national security threat, arguing it would hurt America’s Cold War posture. But the DOJ did it anyway—and it led to an explosion of innovation in wireless technology.

“AT&T said, ‘You can’t do this. We are a national champion. We are critical to this country’s success. We will lose the Cold War if you break up AT&T,’ in so many words. … Even so, [the DOJ] moved forward … America didn’t lose the Cold War, and … from that breakup came a lot of competition and innovation.”

“I learned that in order to compete against China, we need to be in all these global races the American way. And what I mean by that is we’ll never beat China by becoming more like China. China has national champions, they have a controlled economy, et cetera, et cetera.

We win all these races and history has taught by our free market system, by letting the ball rip, by letting companies compete, by innovating one another. And the reason why antitrust matters to that picture, to the free market system is because we’re the cop on the beat at the end of the day. We step in when competition is not working and we ensure that markets remain competitive.”

Slater’s message was clear: regulation and competition enforcement are not threats to national strength—they’re prerequisites to it. So there’s no way that the richest corporations in commercial history should be subsidized by the American taxpayer.

Bottom Line: It’s Public Risk, Private Reward

Let’s be clear:

– They want the public to bear the cost of new electricity generation.
– They want the public to underwrite transmission lines.
– They want the public to streamline regulatory hurdles.
– And they plan to privatize the upside, lock down the infrastructure, keep their models secret and socialize the investment risk.

This isn’t a public-private partnership. It’s a one-way extraction scheme. America needs a serious conversation about energy—but it shouldn’t begin with asking taxpayers to bail out the richest companies in commercial history.