Tag: technology

TikTok’s Divestment Ouroboros: How the “Sale” Changed the Optics but Not the Leverage

When the TikTok USDS deal was announced under the Protecting Americans from Foreign Adversary Controlled Applications Act, it was framed as a clean resolution to years of national-security concerns expressed by many in the US. TikTok was to be reborn as a U.S. company, with U.S. control, and foreign influence neutralized. But if you look past the press language and focus on incentives, ownership, and law, a different picture emerges.

TikTok’s “forced sale” under the PAFACA (not to be confused with COVFEFE) traces back to years of U.S. national-security concern that TikTok’s owner ByteDance—one of the People’s Republic of China’s biggest tech companies founded by Zhang Yiming among China’s richest men and a self-described member of the ruling Chinese Communist Party—could be compelled under PRC law to share data or to allow the CCP to influence the platform’s operations. TikTok and its lobbyists repeatedly attempted to deflect the attention of regulators through measures like U.S. data localization and third-party oversight (e.g., “Project Texas”). However, lawmakers concluded that aggressive structural separation—not promises which nobody was buying—was needed. Congress then passed, and President Biden signed, legislation requiring either divestiture of “foreign adversary controlled” apps like TikTok or face a total a U.S. ban. Facing app-store and infrastructure cutoff risk, TikTok and ByteDance pursued a restructuring to keep U.S. operations alive and maintain an exit to US financial markets.

Lawmakers’ concerns were real and obvious. By trading on social media addiction, TikTok can compile rich behavioral profiles—especially on minors—by combining what users watch, like, share, search, linger on, and who they interact with, along with device identifiers, network data, and (where permitted) location signals. At scale, that kind of telemetry can be used to infer vulnerabilities and target susceptibility. For the military, the concern is not only “TikTok tracks troop movements,” but also that social media posts, aggregated location and social-graph signals across hundreds of millions of users could reveal patterns around bases, deployments, routines, or sensitive communities—hence warnings that harvested information could “possibly even reveal troop movements,” hence TikTok’s longstanding bans on government-issued devices.

These concerns shot through government circles while the Tok became ubiquitous and carefully engineered social media addiction gripped the US, and indeed the West. (TikTok just this week settled out of the biggest social media litigation in history.) Congress was very concerned and with good reason—Rep. Mike Gallagher demanded that TikTok “Break up with the Chinese Communist Party (CCP) or lose access to your American users.”  Rep. Cathy McMorris Rodgers said the bill would “prevent foreign adversaries, such as China, from surveilling and manipulating the American people.” Sen. Pete Ricketts warned “If the Chinese Communist Party is refusing to let ByteDance sell TikTok… they don’t want [control of] those algorithms coming to America.” 

And of course, who can forget a classic Marsha line from Senator Marsha Blackburn. I don’t know how to say “Bless your heart” in Mandarin, but in English it’s “we heard you were opening a TikTok headquarters in Nashville and what you’re probably going to find is that the welcome mat isn’t going to be rolled out for you in Nashville.”

So there’s that.

TikTok can compile rich behavioral profiles—especially on minors—by combining what users post, watch, like, share, search, linger on, and who they interact with, along with device identifiers, network data, and location signals. At scale, that kind of telemetry can be used to infer vulnerabilities and targeting susceptibility. These exploits have real strategic value. With the CCP’s interest in undermining US interests and especially blunting the military, the concern is not necessarily that “the CCP tracks troop movements” directly (although who really knows), but that aggregated location and social-graph signals could reveal patterns around bases, deployments, routines, or sensitive communities—hence warnings that harvested information could “possibly even reveal troop movements,” and the TikTok’s longstanding bans on government-issued devices.  You know, kind of like if you flew a balloon across the CONUS. military bases.

It must also be said that when you watch TikTok’s poor performance before Congress at hearings, it really came down to a simple question of trust. I think nobody believed a word they said and the TikTok witnesses exuded a kind of arrogance that simply does not work when Congress has a bit in the teeth. Full disclosure, I have never believed a word they said and have always been troubled that artists were unwittingly leading their fans to the social media abattoir.

I’ve been writing about TikTok for years, and not because it was fashionable or politically easy. After a classic MTP-style presentation at the MusicBiz conference in 2020 where I laid out all the issues with TikTok and the CCP, somehow I never got invited back. Back in 2020, I warned that “you don’t need proof of misuse to have a national security problem—you only need legal leverage and opacity.” I also argued that “data localization doesn’t solve a governance problem when the parent company [Bytedance] remains subject to foreign national security law,” and that focusing on the location of data storage missed “the more important question of who controls the system that decides what people see.” The forced sale didn’t vindicate any one prediction so much as confirm the basic point: structure matters more than assurances, and control matters more than rhetoric. I still have that concern after all the sound and fury.

There is also a legitimate constitutional concern with PAFACA: a government-mandated divestiture risks resembling a Fifth Amendment taking if structured to coerce a sale without just compensation. PAFACA deserved serious scrutiny even given the legitimate national security concerns. Had the dust settled with the CCP suing the U.S. government under a takings theory, it would have been both too cute by half and entirely on-brand—an example of the CCP’s “unrestricted warfare” approach to lawfare, exploiting Western legal norms strategically. (The CCP’s leading military strategy doctrine, Unrestricted Warfare poses terrorism (and “terror-like” economic and information attacks such as TikTok’s potential use) as part of a spectrum of asymmetric methods that can weaken a technologically superior power like the US.)

Indeed, TikTok did challenge the divest-or-ban statute in the Supreme Court and mounted a SOPA-style campaign that largely failed. TikTok argued that a government-mandated forced sale violated the First Amendment rights of its users and exceeded Congress’s national-security authority. The Supreme Court upheld (unanimously) the PAFACA law, concluding that Congress permissibly targeted foreign-adversary control for national-security reasons rather than suppressing speech, and that the resulting burden on expression did not violate the First Amendment. The case ultimately underscored how far national-security rationales can narrow judicial appetite to second-guess political branches in foreign-adversary disputes no matter how many high-priced lawyers, lobbyists and spin doctors line up at your table. And, boy, did they have them. I think at one point close to half the shilleries in DC were on the PRC payroll.

In that sense, the TikTok deal itself may prove to be another illustration of Master Sun’s maxim about winning without fighting, i.e., achieving strategic advantage not through open confrontation, but by shaping the terrain, the rules, and the opponent’s choices in advance—and perhaps most importantly in this case…deception.

But the deal we got is the deal we have so let’s see what we actually have achieved (or how bad we got hosed this time). As I often say, it’s a damn good thing we never let another MTV build a business on our backs.

The Three Pillars of TikTok

TikTok USDS is the U.S.-domiciled parent holding company for TikTok’s American operations, created to comply with the divest-or-ban law. It is majority owned by U.S. investors, with ByteDance retaining a non-controlling minority stake (reported around 19.9%) and licensing core recommendation technology to the U.S. business. (Under U.S. GAAP, 20%+ ownership is a common rebuttable presumption of “significant influence,” which can trigger less favorable accounting and more scrutiny of the relationship. Staying below 20% helps keep the stake looking purely passive which is kind of a joke considering Byte still owns the key asset. And we still have to ask if BD (or CCP) has any special voting rights (“golden share”), board control, dual-class stock, etc.)

The deal appears to rest on three pillars—and taken together, they point to something closer to an ouroboros than a divestment: the structure consumes itself, leaving ByteDance, and by extension the PRC, in a position that is materially different on paper but strikingly similar in practice.

Pillar One: ByteDance Keeps the Crown Jewel

The first and most important point is the simplest: ByteDance retains ownership of TikTok’s recommendation algorithm.

That algorithm is not an ancillary asset. It is TikTok’s product. Engagement, ad pricing, cultural reach, and political concern all flow from it. Selling TikTok without selling the algorithm is like selling a car without the engine and calling it a divestiture because the buyer controls the steering wheel.

Public reporting strongly suggests the solution was not a sale of the algorithm, but a license or controlled use arrangement. TikTok USDS may own U.S.-specific “tweaks”—content moderation parameters, weighting adjustments, compliance filters—but those sit on top of a core system ByteDance still owns and controls.

That distinction matters, because ownership determines who ultimately controls:

  • architectural changes,
  • major updates,
  • retraining methodology,
  • and long-term evolution of the system.

In other words, the cap table changed, but the switch did not necessarily move.

Pillar Two: IPO Optionality Without Immediate Disclosure

The second pillar is liquidity. ByteDance did not fight this battle simply to keep operating TikTok in the U.S.; it fought to preserve access to an exit in US financial markets.

The TikTok USDS structure clearly keeps open a path to an eventual IPO. Waiting a year or two is not a downside. There is a crowded IPO pipeline already—AI platforms, infrastructure plays, defense-adjacent tech—and time helps normalize the structure politically and operationally.

But here’s the catch: an IPO collapses ambiguity.

A public S-1 would have to disclose, in plain English:

  • who owns the algorithm,
  • whether TikTok USDS owns it or licenses it,
  • the material terms of any license,
  • and the risks associated with dependence on a foreign related party.

This is where old Obama-era China-listing tricks no longer work. Based on what I’ve read, TikTok USDS would likely be a U.S. issuer with a U.S.-inspectable auditor. ByteDance can’t lean on the old HFCAA/PCAOB opacity playbook, because HFCAA is about audit access—not about shielding a related-party licensor from scrutiny.

ByteDance surely knows this. Which is why the structure buys time, not relief from transparency. The IPO is possible—but only when the market is ready to price the risk that the politics are currently papering over.

Pillar Three: PRC Law as the Ultimate Escape Hatch

The third pillar is the quiet one, but it may be the most consequential: PRC law as an external constraint. As long as ByteDance owns the algorithm, PRC law is always waiting in the wings. Those laws include:

Export-control rules on recommendation algorithms.
Data security and cross-border transfer regimes.
National security and intelligence laws that impose duties on PRC companies and citizens.

Together, they form a universal answer to every hard question:

  • Why can’t the algorithm be sold? PRC export controls.
  • Why can’t certain technical details be disclosed? PRC data laws.
  • Why can’t ByteDance fully disengage? PRC legal obligations.

This is not hypothetical. It’s the same concern that animated the original TikTok controversy, just reframed through contracts instead of ownership.

So while TikTok USDS may be auditable, governed by a U.S. board, and compliant with U.S. operational rules, the moment oversight turns upstream—toward the algorithm, updates, or technical dependencies—PRC law reenters the picture.

The result is a U.S. company that is transparent at the edges and opaque at the core. My hunch is that this sovereign control risk is clearly spelled out in any license document and will get disclosed in an IPO.

Putting It Together: Divestment of Optics, Not Control

Taken together, the three pillars tell a consistent story:

  • ByteDance keeps the algorithm.
  • ByteDance gets paid and retains an exit.
  • PRC law remains available to constrain transfer, disclosure, or cooperation.
  • U.S. regulators oversee the wrapper, not the engine.

That does not mean ByteDance is in exactly the same legal position as before. Governance and ownership optics have changed. Some forms of U.S. oversight are real. But in terms of practical control leverage, ByteDance—and by extension Beijing—may be uncomfortably close to where they started.

The foreign control problem that launched the TikTok saga was never just about equity. It was about who controls the system that shapes attention, culture, and information flow. If that system remains owned upstream, the rest is scaffolding.

The Ouroboros Moment

This is why Congress is likely to be furious once the implications sink in.

The story began with concerns about PRC control.
It moved through years of negotiation and political theater.
It ends with an “approved structure” that may leave PRC leverage intact—just expressed through licenses, contracts, and sovereign law rather than a majority stake.

The divestment eats its own tail.

Or put more bluntly: the sale may have changed the paperwork, but it did not necessarily change who can say no when it matters most. And that’s control.

As we watch the People’s Liberation Army practicing its invasion of Taiwan, it’s not rocket science to ask how all this will look if the PRC invades Taiwan tomorrow and America comes to Taiwan’s defense. In a U.S.–PRC shooting war, TikTok USDS would likely face either a rapid U.S. distribution ban on national-security grounds (already blessed by SCOTUS), a forced clean-room severance from ByteDance’s algorithm and services, or an operational breakdown if PRC law or wartime measures disrupt the licensed technology the platform depends on.

The TikTok “sale” looks less like a divestiture of control than a divestiture of optics. ByteDance may have reduced its equity stake and ceded governance formalities, but if it retained ownership of the recommendation algorithm and the U.S. company remains dependent on ByteDance by license, then ByteDance’s—and by extension the CCP’s—legal leverage over ByteDance—can remain in a largely similar control position in practice.

TikTok USDS may change the cap table, but it doesn’t necessarily change the sovereign. As long as ByteDance owns the algorithm and PRC law can be invoked to restrict transfer, disclosure, or cooperation without CCP approval, the end state risks looking eerily familiar: a U.S.-branded wrapper around a system Beijing can still influence at the critical junctions. The whole saga starts with bitter complaints in Congress about “foreign control,” ends with “approved structure,” but largely lands right back where it began—an ouroboros of governance optics swallowing itself.

Surely I’m missing something.

Grassroots Revolt Against Data Centers Goes National: Water Use Now the Flashpoint

Over the last two weeks, grassroots opposition to data centers has moved from sporadic local skirmishes to a recognizable national pattern. While earlier fights centered on land use, noise, and tax incentives, the current phase is more focused and more dangerous for developers: water.

Across multiple states, residents are demanding to see the “water math” behind proposed data centers—how much water will be consumed (not just withdrawn), where it will come from, whether utilities can actually supply it during drought conditions, and what enforceable reporting and mitigation requirements will apply. In arid regions, water scarcity is an obvious constraint. But what’s new is that even in traditionally water-secure states, opponents are now framing data centers as industrial-scale consumptive users whose needs collide directly with residential growth, agriculture, and climate volatility.

The result: moratoria, rezoning denials, delayed hearings, task forces, and early-stage organizing efforts aimed at blocking projects before entitlements are locked in.

Below is a snapshot of how that opposition has played out state by state over the last two weeks.

State-by-State Breakdown

Virginia  

Virginia remains ground zero for organized pushback.

Botetourt County: Residents confronted the Western Virginia Water Authority over a proposed Google data center, pressing officials about long-term water supply impacts and groundwater sustainability.  

Hanover County (Richmond region): The Planning Commission voted against recommending rezoning for a large multi-building data center project.  

State Legislature: Lawmakers are advancing reform proposals that would require water-use modeling and disclosure.

Georgia  

Metro Atlanta / Middle Georgia: Local governments’ recruitment of hyperscale facilities is colliding with resident concerns.  

DeKalb County: An extended moratorium reflects a pause-and-rewrite-the-rules strategy.  

Monroe County / Forsyth area: Data centers have become a local political issue.

Arizona  

The state has moved to curb groundwater use in rural basins via new regulatory designations requiring tracking and reporting.  

Local organizing frames AI data centers as unsuitable for arid regions.

Maryland  

Prince George’s County (Landover Mall site): Organized opposition centered on environmental justice and utility burdens.  

Authorities have responded with a pause/moratorium and a task force.

Indiana  

Indianapolis (Martindale-Brightwood): Packed rezoning hearings forced extended timelines.  

Greensburg: Overflow crowds framed the fight around water-user rankings.

Oklahoma  

Luther (OKC metro): Organized opposition before formal filings.

Michigan  

Broad local opposition with water and utility impacts cited.  

State-level skirmishes over incentives intersect with water-capacity debates.

North Carolina  

Apex (Wake County area): Residents object to strain on electricity and water.

Wisconsin & Pennsylvania 

Corporate messaging shifts in response to opposition; Microsoft acknowledged infrastructure and water burdens.

The Through-Line: “Show Us the Water Math”

Lawrence of Arabia: The Well Scene

Across these states, the grassroots playbook has converged:

Pack the hearing.  

Demand water-use modeling and disclosure.  

Attack rezoning and tax incentives.  

Force moratoria until enforceable rules exist.

Residents are demanding hard numbers: consumptive losses, aquifer drawdown rates, utility-system capacity, drought contingencies, and legally binding mitigation.

Why This Matters for AI Policy

This revolt exposes the physical contradiction at the heart of the AI infrastructure build-out: compute is abstract in policy rhetoric but experienced locally as land, water, power, and noise.

Communities are rejecting a development model that externalizes its physical costs onto local water systems and ratepayers.

Water is now the primary political weapon communities are using to block, delay, and reshape AI infrastructure projects.

Read the local news:

America’s AI Boom Is Running Into An Unplanned Water Problem (Ken Silverstein/Forbes)

Residents raise water concerns over proposed Google data center (Allyssa Beatty/WDBJ7 News)

How data centers are rattling a Georgia Senate special election (Greg Bluesetein/Atlanta Journal Constitution)

A perfect, wild storm’: widely loathed datacenters see little US political opposition (Tom Perkins/The Guardian) 

Hanover Planning Commission votes to deny rezoning request for data center development (Joi Fultz/WTVR)

Microsoft rolls out initiative to limit data-center power costs, water use impact (Reuters)

Grass‑Roots Rebellion Against Data Centers and Grid Expansion

A grass‑roots “data center and electric grid rebellion” is emerging across the United States as communities push back against the local consequences of AI‑driven infrastructure expansion. Residents are increasingly challenging large‑scale data centers and the transmission lines needed to power them, citing concerns about enormous electricity demand, water consumption, noise pollution, land use, declining property values, and opaque approval processes. What were once routine zoning or utility hearings are now crowded, contentious events, with citizens organizing quickly and sharing strategies across counties and states.



This opposition is no longer ad hoc. In Northern Virginia—often described as the global epicenter of data centers—organized campaigns such as the Coalition to Protect Prince William County have mobilized voters, fundraised for local elections, demanded zoning changes, and challenged approvals in court. In Maryland’s Prince George’s County, resistance has taken on a strong environmental‑justice framing, with groups like the South County Environmental Justice Coalition arguing that data centers concentrate environmental and energy burdens in historically marginalized communities and calling for moratoria and stronger safeguards.



Nationally, consumer and civic groups are increasingly coordinated, using shared data, mapping tools, and media pressure to argue that unchecked data‑center growth threatens grid reliability and shifts costs onto ratepayers. Together, these campaigns signal a broader political reckoning over who bears the costs of the AI economy.

Global Data Centers

Here’s a snapshot of grass roots opposition in Texas, Louisiana and Nevada:

Texas

Texas has some of the most active and durable local opposition, driven by land use, water, and transmission corridors.

  • Hill Country & Central Texas (Burnet, Llano, Gillespie, Blanco Counties)
    Grass-roots groups formed initially around high-voltage transmission lines (765 kV) tied to load growth, now explicitly linking those lines to data center demand. Campaigns emphasize:
    • rural land fragmentation
    • wildfire risk
    • eminent domain abuse
    • lack of local benefit
      These groups are often informal coalitions of landowners rather than NGOs, but they coordinate testimony, public-records requests, and local elections.
  • DFW & North Texas
    Neighborhood associations opposing rezoning for hyperscale facilities focus on noise (backup generators), property values, and school-district tax distortions created by data-center abatements.
  • ERCOT framing
    Texas groups uniquely argue that data centers are socializing grid instability risk onto residential ratepayers while privatizing upside—an argument that resonates with conservative voters.

Louisiana

Opposition is newer but coalescing rapidly, often tied to petrochemical and LNG resistance networks.

  • North Louisiana & Mississippi River Corridor
    Community groups opposing new data centers frame them as:
    • “energy parasites” tied to gas plants
    • extensions of an already overburdened industrial corridor
    • threats to water tables and wetlands
      Organizers often overlap with environmental-justice and faith-based coalitions that previously fought refineries and export terminals.
  • Key tactic: reframing data centers as industrial facilities, not “tech,” triggering stricter land-use scrutiny.

Nevada

Nevada opposition centers on water scarcity and public-land use.

  • Clark County & Northern Nevada
    Residents and conservation groups question:
    • water allocations for evaporative cooling
    • siting near public or BLM-managed land
    • grid upgrades subsidized by ratepayers for private AI firms
  • Distinct Nevada argument: data centers compete directly with housing and tribal water needs, not just environmental values.

The Data Center Rebellion is Here and It’s Reshaping the Political Landscape (Washington Post)

Residents protest high-voltage power lines that could skirt Dinosaur Valley State Park (ALEJANDRA MARTINEZ AND PAUL COBLER/Texas Tribune)

US Communities Halt $64B Data Center Expansions Amid Backlash (Lucas Greene/WebProNews)

Big Tech’s fast-expanding plans for data centers are running into stiff community opposition (Marc Levy/Associated Press)

Data center ‘gold rush’ pits local officials’ hunt for new revenue against residents’ concerns (Alander Rocha/Georgia Record)

You Can’t Prosecute Smuggling NVIDIA chips to CCP and Authorize Sales to CCP at the Same Time

The Trump administration is attempting an impossible contradiction: selling advanced NVIDIA AI chips to China while the Department of Justice prosecutes criminal cases for smuggling the exact same chips into China.

According to the DOJ:

“Operation Gatekeeper has exposed a sophisticated smuggling network that threatens our Nation’s security by funneling cutting-edge AI technology to those who would use it against American interests,” said Ganjei. “These chips are the building blocks of AI superiority and are integral to modern military applications. The country that controls these chips will control AI technology; the country that controls AI technology will control the future. The Southern District of Texas will aggressively prosecute anyone who attempts to compromise America’s technological edge.”

That divergence from the prosecutors is not industrial policy. That is incoherence. But mostly it’s just bad advice, likely coming from White House AI Czar David Sacks, Mr. Trump’s South African AI policy advisor who may have a hard time getting a security clearance in the first place..

On one hand, DOJ is rightly bringing cases over the illegal diversion of restricted AI chips—recognizing that these processors are strategic technologies with direct national-security implications. On the other hand, the White House is signaling that access to those same chips is negotiable, subject to licensing workarounds, regulatory carve-outs, or political discretion.

You cannot treat a technology as contraband in federal court and as a commercial export in the West Wing.

Pick one.

AI Chips Are Not Consumer Electronics

The United States does not sell China F-35 fighter jets. We do not sell Patriot missile systems. We do not sell advanced avionics platforms and then act surprised when they show up embedded in military infrastructure. High-end AI accelerators are in the same category.

NVIDIA’s most advanced chips are not merely commercial products. They are general-purpose intelligence infrastructure or what China calls military-civil fusion. They train surveillance systems, military logistics platforms, cyber-offensive tools, and models capable of operating autonomous weapons and battlefield decision-making pipelines with no human in the loop.

If DOJ treats the smuggling of these chips into China as a serious federal crime—and it should—there is no coherent justification for authorizing their sale through executive discretion. Except, of course, money, or in Mr. Sacks case, more money.

Fully Autonomous Weapons—and Selling the Rope

China does not need U.S. chips to build consumer AI. It wants them for military acceleration.Advanced NVIDIA AI chips are not just about chatbots or recommendation engines. They are the backbone of fully autonomous weapons systems—autonomous targeting, swarm coordination, battlefield logistics, and decision-support models that compress the kill chain beyond meaningful human control.

There is an old warning attributed to Vladimir Lenin—that capitalists would sell the rope by which they would later be hanged. Apocryphal or not, it captures this moment with uncomfortable precision.

If NVIDIA chips are powerful enough to underpin autonomous weapons systems for allied militaries, they are powerful enough to underpin autonomous weapons systems for adversaries like China. Trump’s own National Security Strategy statement clearly says previous U.S. elites made “mistaken” assumptions about China such as the famous one that letting China into the WTO would integrate Beijing into the famous rules-based international order. Trump tells us that instead China “got rich and powerful” and used this against us, and goes on to describe the CCP’s well known predatory subsidies, unfair trade, IP theft, industrial espionage, supply-chain leverage, and fentanyl precursor exports as threats the U.S. must “end.” By selling them the most advanced AI chips?

Western governments and investors simultaneously back domestic autonomous-weapons firms—such as Europe-based Helsing, supported by Spotify CEO Daniel Ek—explicitly building AI-enabled munitions for allied defense. That makes exporting equivalent enabling infrastructure to a strategic competitor indefensible.

The AI Moratorium Makes This Worse, Not Better

This contradiction unfolds alongside a proposed federal AI moratorium executive order originating with Mr. Sacks and Adam Thierer of Google’s R Street Institute that would preempt state-level AI protections.
States are told AI is too consequential for local regulation, yet the federal government is prepared to license exports of AI’s core infrastructure abroad.

If AI is too dangerous for states to regulate, it is too dangerous to export. Preemption at home combined with permissiveness abroad is not leadership. It is capture.

This Is What Policy Capture Looks Like

The common thread is not national security. It is Silicon Valley access. David Sacks and others in the AI–VC orbit argue that AI regulation threatens U.S. competitiveness while remaining silent on where the chips go and how they are used.

When DOJ prosecutes smugglers while the White House authorizes exports, the public is entitled to ask whose interests are actually being served. Advisory roles that blur public power and private investment cannot coexist with credible national-security policymaking particularly when the advisor may not even be able to get a US national security clearance unless the President blesses it.

A Line Has to Be Drawn

If a technology is so sensitive that its unauthorized transfer justifies prosecution, its authorized transfer should be prohibited absent extraordinary national interest. AI accelerators meet that test.

Until the administration can articulate a coherent justification for exporting these capabilities to China, the answer should be no. Not licensed. Not delayed. Not cosmetically restricted.

And if that position conflicts with Silicon Valley advisers who view this as a growth opportunity, they should return to where they belong. The fact that the US is getting 25% of the deal (which i bet never finds its way into America’s general account), means nothing except confirming Lenin’s joke about selling the rope to hang ourselves, you know, kind of like TikTok.

David Sacks should go back to Silicon Valley.

This is not venture capital. This is our national security and he’s selling it like rope.

Less Than Zero: The Significance of the Per Stream Rate and Why It Matters

Spotify’s insistence that it’s “misleading” to compare services based on a derived per-stream rate reveals exactly how out of touch the company has become with the very artists whose labor fuels its stock price. Artists experience streaming one play at a time, not as an abstract revenue pool or a complex pro-rata formula. Each stream represents a listener’s decision, a moment of engagement, and a microtransaction of trust. Dismissing the per-stream metric as irrelevant is a rhetorical dodge that shields Spotify from accountability for its own value proposition. (The same applies to all streamers, but Spotify is the only one that denies the reality of the per-stream rate.)

Spotify further claims that users don’t pay per stream but for access as if that negates the artist’s per stream rate payments. It is fallacious to claim that because Spotify users pay a subscription fee for “access,” there is no connection between that payment and any one artist they stream. This argument treats music like a public utility rather than a marketplace of individual works. In reality, users subscribe because of the artists and songs they want to hear; the value of “access” is wholly derived from those choices and the fans that artists drive to the platform. Each stream represents a conscious act of consumption and engagement that justifies compensation.

Economically, the subscription fee is not paid into a vacuum — it forms a revenue pool that Spotify divides among rights holders according to streams. Thus, the distribution of user payments is directly tied to which artists are streamed, even if the payment mechanism is indirect. To say otherwise erases the causal relationship between fan behavior and artist earnings.

The “access” framing serves only to obscure accountability. It allows Spotify to argue that artists are incidental to its product when, in truth, they are the product. Without individual songs, there is nothing to access. The subscription model may bundle listening into a single fee, but it does not sever the fundamental link between listener choice and the artist’s right to be paid fairly for that choice.

Less Than Zero Effect: AI, Infinite Supply and Erasing Artist

In fact, this “access” argument may undermine Spotify’s point entirely. If subscribers pay for access, not individual plays, then there’s an even greater obligation to ensure that subscription revenue is distributed fairly across the artists who generate the listening engagement that keeps fans paying each month. The opacity of this system—where listeners have no idea how their money is allocated—protects Spotify, not artists. If fans understood how little of their monthly fee reached the musicians they actually listen to, they might demand a user-centric payout model or direct licensing alternatives. Or they might be more inclined to use a site like Bandcamp. And Spotify really doesn’t want that.

And to anticipate Spotify’s typical deflection—that low payments are the label’s fault—that’s not correct either. Spotify sets the revenue pool, defines the accounting model, and negotiates the rates. Labels may divide the scraps, but it’s Spotify that decides how small the pie is in the first place either through its distribution deals or exercising pricing power.

Three Proofs of Intention

Daniel Ek, the Spotify CEO and arms dealer, made a Dickensian statement that tells you everything you need to know about how Spotify perceives their role as the Streaming Scrooge—“Today, with the cost of creating content being close to zero, people can share an incredible amount of content”.

That statement perfectly illustrates how detached he has become from the lived reality of the people who actually make the music that powers his platform’s market capitalization (which allows him to invest in autonomous weapons). First, music is not generic “content.” It is art, labor, and identity. Reducing it to “content” flattens the creative act into background noise for an algorithmic feed. That’s not rhetoric; it’s a statement of his values. Of course in his defense, “near zero cost” to a billionaire like Ek is not the same as “near zero cost” to any artist. This disharmonious statement shows that Daniel Ek mistakes the harmony of the people for the noise of the marketplace—arming algorithms instead of artists.

Second, the notion that the cost of creating recordings is “close to zero” is absurd. Real artists pay for instruments, studios, producers, engineers, session musicians, mixing, mastering, artwork, promotion, and often the cost of simply surviving long enough to make the next record or write the next song. Even the so-called “bedroom producer” incurs real expenses—gear, software, electricity, distribution, and years of unpaid labor learning the craft. None of that is zero. As I said in the UK Parliament’s Inquiry into the Economics of Streaming, when the day comes that a soloist aspires to having their music included on a Spotify “sleep” playlist, there’s something really wrong here.

Ek’s comment reveals the Silicon Valley mindset that art is a frictionless input for data platforms, not an enterprise of human skill, sacrifice, and emotion. When the CEO of the world’s dominant streaming company trivializes the cost of creation, he’s not describing an economy—he’s erasing one.

While Spotify tries to distract from the “per-stream rate,” it conveniently ignores the reality that whatever it pays “the music industry” or “rights holders” for all the artists signed to one label still must be broken down into actual payments to the individual artists and songwriters who created the work. Labels divide their share among recording artists; publishers do the same for composers and lyricists. If Spotify refuses to engage on per-stream value, what it’s really saying is that it doesn’t want to address the people behind the music—the very creators whose livelihoods depend on those streams. In pretending the per-stream question doesn’t matter, Spotify admits the artist doesn’t matter either.

Less Than Zero or Zeroing Out: Where Do We Go from Here?

The collapse of artist revenue and the rise of AI aren’t coincidences; they’re two gears in the same machine. Streaming’s economics rewards infinite supply at near-zero unit cost which is really the nugget of truth in Daniel Ek’s statements. This is evidenced by Spotify’s dalliances with Epidemic Sound and the like. But—human-created music is finite and costly; AI music is effectively infinite and cheap. For a platform whose margins improve as payout obligations shrink, the logical endgame is obvious: keep the streams, remove the artists.

  • Two-sided market math. Platforms sell audience attention to advertisers and access to subscribers. Their largest variable cost is royalties. Every substitution of human tracks with synthetic “sound-alikes,” noise, functional audio, or AI mashup reduces royalty liability while keeping listening hours—and revenue—intact. You count the AI streams just long enough to reduce the royalty pool, then you remove them from the system, only to be replace by more AI tracks. Spotify’s security is just good enough to miss the AI tracks for at least one royalty accounting period.
  • Perpetual content glut as cover. Executives say creation costs are “near zero,” justifying lower per-stream value. That narrative licenses a race to the bottom, then invites AI to flood the catalog so the floor can fall further.
  • Training to replace, not to pay. Models ingest human catalogs to learn style and voice, then output “good enough” music that competes with the very works that trained them—without the messy line item called “artist compensation.”
  • Playlist gatekeeping. When discovery is centralized in editorial and algorithmic playlists, platforms can steer demand toward low-or-no-royalty inventory (functional audio, public-domain, in-house/commissioned AI), starving human repertoire while claiming neutrality.
  • Investor alignment. The story that scales is not “fair pay”; it’s “gross margin expansion.” AI is the lever that turns culture into a fixed cost and artists into externalities.

Where does that leave us? Both streaming and AI “work” best for Big Tech, financially, when the artist is cheap enough to ignore or easy enough to replace. AI doesn’t disrupt that model; it completes it. It also gives cover through a tortured misreading through the “national security” lens so natural for a Lord of War investor like Mr. Ek who will no doubt give fellow Swede and one of the great Lords of War, Alfred Nobel, a run for his money. (Perhaps Mr. Ek will reimagine the Peace Prize.) If we don’t hard-wire licensing, provenance, and payout floors, the platform’s optimal future is music without musicians.

Plato conceived justice as each part performing its proper function in harmony with the whole—a balance of reason, spirit, and appetite within the individual and of classes within the city. Applied to AI synthetic works like those generated by Sora 2, injustice arises when this order collapses: when technology imitates creation without acknowledging the creators whose intellect and labor made it possible. Such systems allow the “appetitive” side—profit and scale—to dominate reason and virtue. In Plato’s terms, an AI trained on human art yet denying its debt to artists enacts the very disorder that defines injustice.

Too Dynamic to Question, Too Dangerous to Ignore

When Ed Newton-Rex left Stability AI, he didn’t just make a career move — he issued a warning. His message was simple: we’ve built an industry that moves too fast to be honest.

AI’s defenders insist that regulation can’t keep up, that oversight will “stifle innovation.” But that speed isn’t a by-product; it’s the business model. The system is engineered for planned obsolescence of accountability — every time the public begins to understand one layer of technology, another version ships, invalidating the debate. The goal isn’t progress; it’s perpetual synthetic novelty, where nothing stays still long enough to be measured or governed, and “nothing says freedom like getting away with it.”

We’ve seen this play before. Car makers built expensive sensors we don’t want that fail on schedule; software platforms built policies that expire the moment they bite. In both cases, complexity became a shield and a racket — “too dynamic to question.” And yet, like those unasked-for, but paid for, features in the cars we don’t want, AI’s design choices are too dangerous to ignore. (Like what if your brakes really are going out, not just the sensor is malfunctioning.)

Ed Newton-Rex’s point — echoed in his tweets and testimony — is that the industry has mistaken velocity for virtue. He’s right. The danger is not that these systems evolve too quickly to regulate; it’s that they’re designed that way designed to fail just like that brake sensor. And until lawmakers recognize that speed itself is a form of governance, we’ll keep mistaking momentum for inevitability.

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.

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.

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.

David Sacks Is Learning That the States Still Matter

For a moment, it looked like the tech world’s powerbrokers had pulled it off. Buried deep in a Republican infrastructure and tax package was a sleeper provision — the so-called AI moratorium — that would have blocked states from passing their own AI laws for up to a decade. It was an audacious move: centralize control over one of the most consequential technologies in history, bypass 50 state legislatures, and hand the reins to a small circle of federal agencies and especially to tech industry insiders.

But then it collapsed.

The Senate voted 99–1 to strike the moratorium. Governors rebelled. Attorneys general sounded the alarm. Artists, parents, workers, and privacy advocates from across the political spectrum said “no.” Even hardline conservatives like Ted Cruz eventually reversed course when it came down to the final vote. The message to Big Tech or the famous “Little Tech” was clear: the states still matter — and America’s tech elite ignore that at their peril.  (“Little Tech” is the latest rhetorical deflection promoted by Big Tech aka propaganda.)

The old Google crowd pushed the moratorium–their fingerprints were obvious. Having gotten fabulously rich off of their two favorites: The DMCA farce and the Section 230 shakedown. But there’s increasing speculation that White House AI Czar and Silicon Valley Viceroy David Sacks, PayPal alum and vocal MAGA-world player, was calling the ball. If true, that makes this defeat even more revealing.

Sacks represents something of a new breed of power-hungry tech-right influencer — part of the emerging “Red Tech” movement that claims to reject woke capitalism and coastal elitism but still wants experts to shape national policy from Silicon Valley, a chapter straight out of Philip Dru: Administrator. Sacks is tied to figures like Peter Thiel, Elon Musk, and a growing network of Trump-aligned venture capitalists. But even that alignment couldn’t save the moratorium.

Why? Because the core problem wasn’t left vs. right. It was top vs. bottom.

In 1964, Ronald Reagan’s classic speech called A Time for Choosing warned about “a little intellectual elite in a far-distant capitol” deciding what’s best for everyone else. That warning still rings true — except now the “capitol” might just be a server farm in Menlo Park or a podcast studio in LA.

The AI moratorium was an attempt to govern by preemption and fiat, not by consent. And the backlash wasn’t partisan. It came from red states and blue ones alike — places where elected leaders still think they have the right to protect their citizens from unregulated surveillance, deepfakes, data scraping, and economic disruption.

So yes, the defeat of the moratorium was a blow to Google’s strategy of soft-power dominance. But it was also a shot across the bow for David Sacks and the would-be masters of tech populism. You can’t have populism without the people.

If Sacks and his cohort want to play a long game in AI policy, they’ll have to do more than drop ideas into the policy laundry of think tank white papers and Beltway briefings. They’ll need to win public trust, respect state sovereignty, and remember that governing by sneaky safe harbors is no substitute for legitimacy.  

The moratorium failed because it presumed America could be governed like a tech startup — from the top, at speed, with no dissent. Turns out the country is still under the impression they have something to say about how they are governed, especially by Big Tech.