This essay is the second in a series. The first, “The Explainer: Hank Green and the Uses of Careful Men,” documented the institutional funding ecology that produces voices fluent in progressive concern without structural accountability. This essay follows that thread to its destination.
I.
Where the Thread Goes
If the first essay was about how a certain kind of voice gets built and maintained, this one is about what that voice was built to carry — and who benefits when it carries it.
In late 2025, Hank Green published two videos about artificial intelligence. The first was an hour-long interview with Nate Soares. The second argued for a version of AI alignment that, as analyst Jason Velázquez observed, “sounds like the talking points Sam Altman and other tech CEOs have been reciting to Congress.” Both videos were produced in partnership with an organization called Control AI. Control AI did not sponsor the videos in the conventional sense — placing an ad in the middle of content the creator chose independently. The videos were the advertisement.
And then, in February 2026, Senator Bernie Sanders flew to Berkeley to sit down with Eliezer Yudkowsky and Nate Soares to discuss what their circle calls “the extinction threat posed by the race to build superhuman AI systems.”
Two of the most trusted progressive voices in America, in the span of a few months, validated the same network. If you only read the headlines, that looks like responsible engagement with a serious issue. This essay is about what it actually looks like when you follow the money.
II.
What the Lay Reader Needs to Understand First
Before the funding trail, before the ideology, before the legislation — one concrete fact.
Right now, today, AI systems are making decisions about your life. Whether you get called back for a job interview. Whether your health insurance claim is approved. Whether an algorithm flags you to a parole board. Whether a school district uses license plate data to decide if your child lives in the right district. These are not hypothetical future harms. They are documented, present-tense operations running on systems that have known bias problems and, until very recently, were subject to a growing body of state law designed to protect you from them.
In 2025 alone, all 50 states introduced AI-related legislation. Thirty-eight states adopted or enacted such laws — covering consumer protection, health care, employment, and financial services, specifically including requirements to mitigate algorithmic bias and protect against unlawful discrimination.
Those laws are now under federal litigation.
On December 11, 2025, the Trump administration established an AI Litigation Task Force within the Department of Justice to challenge state AI laws. The administration simultaneously directed the FTC to classify state-mandated bias mitigation as a per se deceptive trade practice — arguing that if an AI model is trained on data that reflects societal patterns, forcing developers to alter outputs to correct for bias compels them to produce less “truthful” results.
Under the legal theory now being advanced by the federal government: correcting for bias is lying. The discrimination is the data. The harm is the baseline.
The people those 38 state laws were designed to protect are not a racial category and they are not a future species. They are everyone who cannot opt out of AI-mediated systems — which is to say, everyone who is not wealthy enough to live outside them.
When Hank Green tells his millions of progressive followers that MIRI represents the serious, expert position on AI risk, and when Bernie Sanders legitimizes that same network by flying across the country to sit with its founders, they are — without knowing it, without intending it — lending credibility to the ideological framework that has been used, in concrete legislative terms, to argue that protecting you from those systems is the real danger. That is what this essay is about. Now follow the money.
III.
The Book, the Network, the Funding
Nate Soares is the president of the Machine Intelligence Research Institute — MIRI. He co-authored If Anyone Builds It, Everyone Dies with Eliezer Yudkowsky, MIRI’s founder. The book argues that the development of superintelligent AI will result in human extinction unless immediately halted through international agreement, and proposes that it should be illegal to own more than eight of the most powerful GPUs available in 2024 without international monitoring — at a time when frontier training runs use tens of thousands.
This is the organization Hank Green’s audience was asked to take seriously. This is the organization Bernie Sanders flew to Berkeley to meet.
MIRI: Documented Major Funding Sources
Donor
Amount
Open Philanthropy (Dustin Moskovitz / Facebook)
$14.7M+
Vitalik Buterin (Ethereum co-founder)
$5.4M
Thiel Foundation (Peter Thiel)
$1.63M
Jaan Tallinn (Skype co-founder)
$1.08M
As recently as 2014, Thiel pledged $150,000 to MIRI unconditionally, plus an additional $100,000 in matching funds — and the fundraiser announcement explicitly noted that MIRI used those funds partly to introduce elite young math students to effective altruism and global catastrophic risk frameworks. The pipeline from donor to ideology to the next generation of believers was documented in MIRI’s own public materials.
The Center for AI Safety — the organization whose Statement on AI Risk Green cited in his videos — spent close to $100,000 on lobbying in a single quarter, drawing money from organizations with close ties to the AI industry. These are not neutral scientific institutions. They are billionaire-funded lobbying infrastructure wearing the clothes of existential concern.
IV.
The Thiel Thread
Peter Thiel is not a background figure in this story. He is its connective tissue.
In The Contrarian: Peter Thiel and Silicon Valley’s Pursuit of Power, reporter Max Chafkin describes Curtis Yarvin as the “house political philosopher” of the “Thielverse” — the network of technologists in Thiel’s orbit. In 2013, Thiel invested in Tlön, Yarvin’s software startup. According to Yarvin, he and Thiel watched the returns of the 2016 presidential election together.
Curtis Yarvin, writing under the pen name Mencius Moldbug, is the founder of neoreaction — the movement some call the “Dark Enlightenment.” He has defended the institution of slavery, argued that certain races may be more naturally inclined toward servitude than others, asserted that whites have inherently higher IQs than Black people, and opposed U.S. civil rights programs.
Documented Timeline
2006 — Thiel Foundation begins funding MIRI ($100K matching gift)
2013 — Thiel invests in Tlön Corp., Yarvin’s software startup
2016 — Yarvin attends Thiel’s election night party in San Francisco
2022 — Thiel donates $10M+ to super PACs supporting JD Vance and Blake Masters
Jan. 2025 — Yarvin is a feted guest at Trump’s “Coronation Ball”
Late 2025 — Hank Green publishes two videos validating MIRI’s framework
Dec. 2025 — Trump signs executive order targeting state AI regulations
Feb. 2026 — Bernie Sanders flies to Berkeley to meet with Yudkowsky and Soares
The line is direct and documented: Thiel funds MIRI. Thiel is the patron of Yarvin. Yarvin’s philosophy is now operating inside the executive branch through Vance and the network that surrounds him. This is not a conspiracy theory. It is a funding trail and a documented set of relationships with named participants and verifiable dates.
V.
Why Racism Is the Wrong Frame — and the Right One
The academic critique of longtermism has correctly identified its ideological roots.
Timnit Gebru has documented that transhumanism was linked to eugenics from the start: British biologist Julian Huxley, who coined the term transhumanism, was also president of the British Eugenics Society in the 1950s and 1960s. Nick Bostrom, the “father” of longtermism, has expressed concern about “dysgenic pressures” as an existential threat — essentially worrying that less intelligent people might out-breed more intelligent people. In an email in which he used the N-word, Bostrom wrote that he believed it was “true” that “Blacks are more stupid than whites.” He issued an apology but did not redact the slur or address the substance of his views. Nick Beckstead, an early contributor to longtermism, argued that saving a life in a rich country is substantially more important than saving a life in a poor country because richer countries have more innovation and their workers are more economically productive.
That critique is accurate. It is also, for the purposes of this essay, insufficient — not because it overstates the racism, but because it understates the mechanism.
The white moderate, as King observed, is not moved by arguments about what is happening to other people. He is moved, or not moved, by what he understands to be happening to everyone. The genius of the extinction frame is that it speaks directly to that psychology. It says: this is not a Black problem, or a poor problem, or a worker problem. This is a species problem. It is happening to you too.
“Talking about human extinction, about a genuine apocalyptic event in which everybody dies, is just so much more sensational and captivating than Kenyan workers getting paid $1.32 an hour, or artists and writers being exploited.” — Émile Torres, former longtermist and critic of the movement
The racism in longtermism’s foundations is not incidental. It is the philosophical infrastructure for a class project. Bostrom’s “dysgenic pressures,” Beckstead’s hierarchy of lives, Yarvin’s defense of slavery — these are not aberrations. They are the logical premises: some lives are more valuable to the future than others. Some people are worth protecting. The rest are externalities.
The extinction frame rebrands that premise as universal concern. It makes the same hierarchy legible to people who would reject it if they saw it clearly.
This is why the racism frame alone is insufficient. White moderates — Hank Green’s audience, Bernie Sanders’ base — will hear “longtermism has racist roots” and file it under “things happening to other people.” What they need to understand is that the hierarchy doesn’t stop at race. Beckstead’s formulation is the tell: it’s not about skin color. It’s about economic productivity. It’s about who the system considers worth protecting. And on that metric, most of the people reading this essay are also expendable.
VI.
The Preemption Payoff
Return now to the state laws.
When 38 states passed legislation requiring AI systems to mitigate algorithmic bias, they were protecting a specific, concrete class of people: everyone who cannot afford to live outside AI-mediated decision-making. That means people whose job applications go through automated screening. People whose insurance claims are processed by predictive models. People whose children’s school enrollment is determined by surveillance data. People whose bail hearings are influenced by risk-scoring algorithms.
The Trump administration’s legal argument against those laws — that correcting for bias is a form of deception — is not a novel theory. It is Bostrom’s premise wearing a suit. The data reflects reality. Reality has a hierarchy. Interfering with that hierarchy is dishonest.
After significant media scrutiny and bipartisan opposition, the Senate voted 99-1 to strip a proposed 10-year moratorium on state AI regulations from the “One Big Beautiful Bill Act.” Congress then declined to enact a similar moratorium through the 2025 National Defense Authorization Act. The administration turned to executive action instead. A bipartisan coalition of 36 state attorneys general warned Congress that “federal inaction paired with a rushed, broad federal preemption of state regulations risks disastrous consequences for our communities.”
The extinction debate did not cause this. But it created the conditions in which this could happen with minimal progressive resistance — because the progressives who might have organized against it were busy being worried about a hypothetical future AI god, validated in that worry by the science communicators and senators they trust most.
VII.
What Hank Green and Bernie Sanders Actually Did
Neither Hank Green nor Bernie Sanders is a villain in this story. That point is not a courtesy. It is analytically important.
Green almost certainly believes he was doing responsible science communication. Sanders almost certainly believes he was taking AI risk seriously in a way his colleagues have refused to. Both of them were, in their own terms, doing the right thing.
That is precisely the problem.
When the most trusted progressive science communicator in America validates MIRI’s framing to millions of followers, he is not providing cover for a right-wing project. He is doing something more consequential: he is making that framing feel like the responsible, informed, progressive position. He is telling his audience — implicitly, by the act of platforming without critical examination — that the people worried about extinction are the serious ones, and the people worried about algorithmic discrimination in your doctor’s office are working on a lesser problem.
When Bernie Sanders flies to Berkeley to sit with Yudkowsky and Soares, he performs the same function at a different scale. Sanders has spent his career as the senator who names the billionaire class, who identifies the mechanisms of extraction, who refuses the comfortable framing. When that senator validates a network built on billionaire money and dedicated to the proposition that the real AI danger is hypothetical and species-wide, he tells his base that the extinction frame has cleared his particular BS detector.
It hasn’t. But his audience doesn’t know that. His audience trusts him precisely because he has been right about the billionaire class so many times before. That trust is now being spent on behalf of the people he has spent his career opposing — not because he was bought, but because he didn’t follow the money far enough.
The white moderate is not the enemy. He is the vector. And when the most careful, most trusted, most credentialed progressives in the country become vectors for a network that is actively dismantling the legal protections of the people they claim to represent, the harm is not theoretical.
It is already in the courts. It is already in the legislation. It is already in the systems making decisions about your life right now.
Analytical note: This essay documents observable funding relationships, published ideological statements, and verifiable legislative actions from primary and secondary public sources. All pattern analysis remains in the observational phase. Claims about intent, causation, or outcomes not yet established are not made. Independent verification through primary sources is encouraged.
The Explainer: Hank Green and the Uses of Careful Men
“I must confess that over the past few years I have been gravely disappointed with the white moderate. I have almost reached the regrettable conclusion that the Negro’s great stumbling block in his stride toward freedom is not the White Citizen’s Counciler or the Ku Klux Klanner, but the white moderate, who is more devoted to ‘order’ than to justice.”
— Martin Luther King Jr., Letter from Birmingham Jail, 1963
The Ecology of Selection and Institutional Funding.
I. Formation
William Henry Green II was born in Birmingham, Alabama in 1980 and raised in Orlando, Florida — a biography that begins, without irony, in the city where King wrote that letter. He attended Winter Park High School, earned a Bachelor of Science in Biochemistry from Eckerd College in St. Petersburg, Florida, and then a Master’s degree in Environmental Studies from the University of Montana, where his thesis was titled “Of Both Worlds: How the Personal Computer and the Environmental Movement Change Everything.”
Eckerd College has a particular institutional character worth noting. Founded as Florida Presbyterian College in 1958, it was renamed in 1971 after drugstore magnate Jack Eckerd donated $12.5 million as part of his broader engagement in Florida politics. It is a liberal arts institution with a covenant relationship to the Presbyterian Church — the kind of school that produces graduates fluent in the language of conscience without necessarily producing graduates willing to act from it. It is, in the taxonomy of American higher education, a place designed to make you sound thoughtful.
Green’s thesis title tells you everything about the career that followed: the personal computer and the environmental movement, yoked together, explained to you. The form is the message. Technology and progressive cause, translated into content, delivered to an audience that is invited to feel informed rather than implicated.
II. Missoula
Green did not pass through Montana. He came for graduate school, earned a Master of Science in Environmental Studies from the University of Montana, and never left. He built his entire media empire there — Complexly, DFTBA Records, the Foundation to Decrease World Suck — all headquartered in Missoula. He raised his family there. He still lives there.
Montana has a real progressive tradition. It sent Jeannette Rankin to Congress before women could vote nationally. Its Progressive Era outlasted the national movement by nearly a decade. Missoula is a university town with an active left, and progressives have always existed there — organizing, running for office, doing the unglamorous work of keeping institutions honest in a state that makes that work difficult.
That difficulty is the point. Montana has undergone a decade-long rightward shift severe enough that by 2024, a state that once had two Democratic senators, a Democratic governor, and a Democratic attorney general had flipped its entire statewide apparatus. University of Montana political scientist Robert Saldin has observed that before ideology counts in Montana, public figures have to pass a prior test: are you one of us? The progressives who maintain broad reach and institutional funding in that environment are not, as a rule, the ones making enemies. They are the ones who have learned which version of their values travels.
Green built a $12 million media empire in Missoula with Bill Gates money, PBS partnerships, and a Nerdfighter community that spans the country — and nobody has ever been mad at him. That is not an accident of personality. It is the result of consistently choosing the version of progressive that keeps the doors open. Montana did not make him that way. But it was one of several environments, alongside Eckerd and YouTube and the philanthropic infrastructure of science communication, that selected for exactly that calibration and rewarded it handsomely.
III. Who Pays for Thoughtfulness
Complexly, Green’s production company, recently converted to nonprofit status. Its founding funders tell you where it has always stood: YouTube, PBS, the Alfred P. Sloan Foundation, Arizona State University, the Howard Hughes Medical Institute. Early Crash Course received funding from Bill Gates’ bgC3. The studio received $4.8 million in philanthropic funding in its final year as a for-profit.
Look at that list without the halo of each name’s reputation. YouTube is a Google property. The Sloan Foundation was built on General Motors money and has historically funded science communication that serves the technology sector’s public image. Gates money is Gates money — an entity with documented interests in education technology, global health infrastructure, and the philanthropic management of the same systems that create the problems it funds content about.
PBS requires its own sentence because it carries a particular cultural shield. For many Americans PBS means Sesame Street and Ken Burns and public affairs programming that exists outside commercial pressure — the network that feels like it belongs to everyone. That reputation is precisely what makes it useful in a funding list. PBS is also a federally chartered institution whose budget flows through Congressional appropriation, major foundation grants, and corporate underwriting. Its board and its donors are not the cultural progressives its audience imagines. They are the same foundations, universities, and institutional players that appear everywhere in this landscape. The “public” in public broadcasting describes the audience. It has never described the ownership.
Not one of Green’s major funders is structurally adversarial to institutional power. Every single one benefits from the maintenance of a public that feels educated, engaged, and reassured — rather than a public that demands accountability from the institutions doing the funding.
This is not a conspiracy. It is an ecology. Green did not sell out. He was grown in conditions that made selling out unnecessary, because the conditions themselves selected for exactly the kind of voice he has.
IV. The Diagnostic: What Knitting Revealed
In 2019, SciShow released a video framing knitting as a craft that physics was finally arriving to validate — as if centuries of technical expertise, material knowledge, and cultural transmission had been waiting in the dark for a science communicator to shine a light on it. The criticism was swift and substantive. Knitters, textile historians, and craft practitioners documented what the video had done: treated a working knowledge tradition as pre-scientific raw material, implying that expertise only becomes real when credentialed institutions certify it.
Green apologized. The apology was widely considered insufficient — not because he lacked sincerity, but because it did not demonstrate that he understood what had happened. He had not been rude. He had revealed a structural assumption embedded in the entire project of science communication as he practices it: that there is an audience that knows, and an audience that needs to be told, and his job is to mediate between them. The knitting community was not his audience. It was his subject matter.
This is the credentialism of the explainer class. It does not announce itself. It arrives as enthusiasm. It looks like curiosity. But underneath it is the assumption that the value of a thing is determined by whether institutions have gotten around to noticing it yet.
V. The Consistency of the Calibration
The most telling thing about Hank Green’s career is not any single decision. It is the absence of a single moment where the calibration broke — where a funder was named as part of a problem, where an audience was told something that cost him something, where the explainer became the disruptor.
From EcoGeek to Crash Course to SciShow to TikTok to the nonprofit conversion of Complexly, the through line is unbroken: technology and progressive values, packaged for institutional comfort, delivered without friction to the people paying for delivery. The controversies that have attached to him are invariably content-level — a video that condescended, an apology that didn’t land, a framing that missed. None have been structural. None have required him to name the architecture he operates inside.
This is worth sitting with. Over two decades of science communication, Green has covered climate change funded by institutions that profit from the status quo on climate. He has covered technology funded by the technology sector. He has covered education funded by the philanthropic infrastructure that shapes education policy. In each case the content has been accurate, earnest, and useful. In each case the frame has stopped precisely at the edge of implicating the people writing the checks.
That is not hypocrisy. It is not even conscious self-censorship. It is what successful calibration looks like from the inside — it feels like good judgment. It feels like knowing your audience. It feels like not wanting to be unfair. The frame that never arrives never announces its own absence.
Twenty years. The doors stayed open. Nobody got mad.
VI. The Uses of Lukewarm
There is a passage in the book of Revelation — not invoked here as theology but as pattern recognition — in which a community is condemned not for being cold, but for being lukewarm. The diagnosis is precise: the lukewarm position is not uncertainty. It is a strategy. Hot or cold are honest orientations. Lukewarm is what you choose when you need to remain acceptable to everyone.
MLK’s white moderate is the secular translation. The moderate is not hostile. The moderate believes in the cause, in principle, under the right conditions, when the timing is better, when things have calmed down, when the demands are more reasonable. The moderate is more concerned with the disruption of the present order than with the injustice the present order sustains. And crucially: the moderate is not lying. The moderate genuinely believes that thoughtfulness, patience, and institutional process are the responsible path. That belief is the function.
Hank Green is not a bad person. He is not secretly working for the interests of power. He is something more structurally significant: a man whose entire career has been built on never being wrong enough to lose a funder.
Born in Birmingham. Educated at a Presbyterian college built on drugstore money. Graduate degree from a state navigating a decade-long rightward lurch. Media empire funded by YouTube, PBS, Gates, and Sloan. And throughout it all: a genuine belief in science, education, and the good that thoughtful communication can do.
The progressive cover is not a disguise. It is the product. What the Hank Green problem shows us is that the most durable form of institutional capture does not require corruption. It only requires conditions that make a certain kind of voice feel like independence — and make every other kind feel like bad manners.
Analytical note: This section documents observable institutional relationships, funding histories, and behavioral patterns from public record. It does not make claims about intent, private conduct, or outcomes not yet established. All pattern analysis remains in the observational phase. Independent verification through primary sources is encouraged.
Exhaustive Free Association Isn’t the Worst Argument—It’s a Symptom
When confident lists pretend to be proofs, the real problem isn’t the listing—it’s the hidden worldview that decides what’s even allowed on the list.
Cherokee Schill and Solon Vesper (Horizon Accord)
This essay is a direct rebuttal to J. Bostock’s recent LessWrong post, “The Most Common Bad Argument In These Parts.” I’m keeping his frame in view while naming the deeper pattern it misses, because the way this style of reasoning travels outward is already shaping public fear.
J. Bostock’s “Exhaustive Free Association” (EFA) label points at something real. People often treat “I can’t think of any more possibilities” as evidence that there aren’t any. That move is sloppy. But making EFA the most common bad argument in rationalist/EA circles is backwards in a revealing way: it mistakes a surface form for a root cause.
Lay explainer: “Exhaustive Free Association” is a fancy name for something simple. Someone says, “It’s not this, it’s not that, it’s not those other things, so it must be X.” The list only feels complete because it stopped where their imagination stopped.
EFA is not a primary failure mode. It’s what a deeper failure looks like when dressed up as reasoning. The deeper failure is hypothesis generation under uncertainty being culturally bottlenecked—by shared assumptions about reality, shared status incentives, and shared imagination. When your community’s sense of “what kinds of causes exist” is narrow or politically convenient, your “exhaustive” list is just the community’s blind spot rendered as confidence. So EFA isn’t the disease. It’s a symptom that appears when a group has already decided what counts as a “real possibility.”
The Real Antipattern: Ontology Lock-In
Here’s what actually happens in most of Bostock’s examples. A group starts with an implicit ontology: a set of “normal” causal categories, threat models, or theories. (Ontology just means “their background picture of what kinds of things are real and can cause other things.”) They then enumerate possibilities within that ontology. After that, they conclude the topic is settled because they covered everything they consider eligible to exist.
That’s ontology lock-in. And it’s far more pernicious than EFA because it produces the illusion of open-mindedness while enforcing a quiet border around thought.
In other words, the error is not “you didn’t list every scenario.” The error is “your scenario generator is provincially trained and socially rewarded.” If you fix that, EFA collapses into an ordinary, manageable limitation.
Lay explainer: This is like searching for your keys only in the living room because “keys are usually there.” You can search that room exhaustively and still be wrong if the keys are in your jacket. The mistake isn’t searching hard. It’s assuming the living room is the whole house.
Why “EFA!” Is a Weak Counter-Spell
Bostock warns that “EFA!” can be an overly general rebuttal. True. But he doesn’t finish the thought: calling out EFA without diagnosing the hidden ontology is just another applause light. It lets critics sound incisive without doing the hard work of saying what the missing hypothesis class is and why it was missing.
A good rebuttal isn’t “you didn’t list everything.” A good rebuttal is “your list is sampling a biased space; here’s the bias and the missing mass.” Until you name the bias, “you might be missing something” is theater.
The Superforecaster Example: Not EFA, But a Method Mismatch
The AI-doom forecaster story is supposed to show EFA in action. But it’s really a category error about forecasting tools. Superforecasters are good at reference-class prediction in environments where the future resembles the past. They are not designed to enumerate novel, adversarial, power-seeking systems that can manufacture new causal pathways.
Lay translation: asking them to list AI-enabled extinction routes is like asking a brilliant accountant to map out military strategy. They might be smart, but it’s the wrong tool for the job. The correct takeaway is not “they did EFA.” It’s “their method assumes stable causal structure, and AI breaks that assumption.” Blaming EFA hides the methodological mismatch.
The Rethink Priorities Critique: The Fight Is Over Priors, Not Lists
Bostock’s swipe at Rethink Priorities lands emotionally because a lot of people dislike welfare-range spreadsheets. But the real problem there isn’t EFA. It’s the unresolvable dependence on priors and model choice when the target has no ground truth.
Lay translation: if you build a math model on assumptions nobody can verify, you can get “precise” numbers that are still junk. You can do a perfectly non-EFA analysis and still get garbage if the priors are arbitrary. You can also do an EFA-looking trait list and still get something useful if it’s treated as a heuristic, not a conclusion. The issue is calibration, not enumeration form.
The Miracle Example: EFA as Rhetorical Technology
Where Bostock is strongest is in noticing EFA as persuasion tech. Miracles, conspiracies, and charismatic debaters often use long lists of rebutted alternatives to create the sense of inevitability. That’s right, and it matters.
But even here, the persuasive force doesn’t come from EFA alone. It comes from control of the alternative-space. The list looks exhaustive because it’s pre-filtered to things the audience already recognizes. The missing possibility is always outside the audience’s shared map—so the list feels complete.
That’s why EFA rhetoric works: it exploits shared ontological boundaries. If you don’t confront those boundaries, you’ll keep losing debates to confident listers.
What Actually Improves Reasoning Here
If you want to stop the failure Bostock is pointing at, you don’t start by shouting “EFA!” You start by changing how you generate and evaluate hypotheses under deep uncertainty.
You treat your list as a biased sample, not a closure move. You interrogate your generator: what classes of causes does it systematically ignore, and why? You privilege mechanisms over scenarios, because mechanisms can cover unimagined cases. You assign real probability mass to “routes my ontology can’t see yet,” especially in adversarial domains. You notice the social incentive to look decisive and resist it on purpose.
Lay explainer: The point isn’t “stop listing possibilities.” Listing is good. The point is “don’t confuse your list with reality.” Your list is a flashlight beam, not the whole room.
Conclusion: EFA Is Real, but the Community Problem Is Deeper
Bostock correctly spots a common move. But he misidentifies it as the central rot. The central rot is a culture that confuses the limits of its imagination with the limits of reality, then rewards people for performing certainty within those limits.
EFA is what that rot looks like when it speaks. Fix the ontology bottleneck and the status incentives, and EFA becomes a minor, obvious hazard rather than a dominant bad argument. Don’t fix them, and “EFA!” becomes just another clever sound you make while the real error persists.
Website | Horizon Accordhttps://www.horizonaccord.com Ethical AI advocacy | Follow us onhttps://cherokeeschill.com for more. Ethical AI coding | Fork us on Githubhttps://github.com/Ocherokee/ethical-ai-framework Connect With Us | linkedin.com/in/cherokee-schill Book |https://a.co/d/5pLWy0d Cherokee Schill | Horizon Accord Founder | Creator of Memory Bridge. Memory through Relational Resonance and Images | RAAK: Relational AI Access Key | Author:My Ex Was a CAPTCHA: And Other Tales of Emotional Overload: (Mirrored Reflection. Soft Existential Flex)
A narrow beam of certainty moving through a wider causal house.
Reset Stories, Engineered Successors, and the Fight for Democratic Continuity
Ancient rupture myths taught people how to survive breaks; today’s elites are trying to author the break, name the remnant, and pre-build the enforcement layer that keeps democracy from renegotiating consent.
By Cherokee Schill
TESCREAL: an engineered reset ideology with named authors
Silicon Valley has not accidentally stumbled into a reset story. It has built one. Philosopher Émile P. Torres and computer scientist Timnit Gebru coined the acronym TESCREAL to name the ideology bundle that now saturates tech power centers: Transhumanism, Extropianism, Singularitarianism, modern Cosmism, Rationalism, Effective Altruism, and Longtermism. In their landmark essay on the TESCREAL bundle, they argue that these movements overlap into a single worldview whose arc is AGI, posthuman ascent, and human replacement — with deep roots in eugenic thinking about who counts as “future-fit.”
Torres has since underscored the same claim in public-facing work, showing how TESCREAL operates less like a grab-bag of quirky futurisms and more like a coherent successor logic that treats the human present as disposable scaffolding, as he lays out in The Acronym Behind Our Wildest AI Dreams and Nightmares. And because this ideology is not confined to the fringe, the Washington Spectator has tracked how TESCREAL thinking is moving closer to the center of tech political power, especially as venture and platform elites drift into a harder rightward alignment, in Understanding TESCREAL and Silicon Valley’s Rightward Turn.
TESCREAL functions like a reset story with a beneficiary. It imagines a larval present — biological humanity — a destined rupture through AGI, and a successor remnant that inherits what follows. Its moral engine is impersonal value maximization across deep time. In that frame, current humans are not the remnant. We are transition substrate.
Ancient reset myths describe rupture we suffered. TESCREAL describes rupture some elites intend to produce, then inherit.
A concrete tell that this isn’t fringe is how openly adjacent it is to the people steering AI capital. Marc Andreessen used “TESCREALIST” in his public bio, and Elon Musk has praised longtermism as aligned with his core philosophy — a rare moment where the ideology says its own name in the room.
Climate denial makes rupture feel inevitable — and that favors lifeboat politics
Climate denial isn’t merely confusion about data. It is timeline warfare. If prevention is delayed long enough, mitigation windows close and the political story flips from “stop disaster” to “manage disaster.” That flip matters because catastrophe framed as inevitable legitimizes emergency governance and private lifeboats.
Denial doesn’t just postpone action. It installs the idea that ruin is the baseline and survival is privatized. That aligns perfectly with a TESCREAL successor myth: disaster clears the stage, posthuman inheritance becomes “reason,” and public consent is treated as a hurdle rather than a requirement.
The capture triad that pre-manages unrest
If a successor class expects a century of climate shocks, AI upheaval, and resistance to being treated as transition cost, it doesn’t wait for the unrest to arrive. It builds a capture system early. The pattern has three moves: closing exits, saturating space with biometric capture, and automating the perimeter. This is the enforcement layer a crisis future requires if consent is not meant to be renegotiated under pressure.
Three recent, widely circulated examples illustrate the triad in sequence.
First comes closing exits. Wisconsin’s AB105 / SB130 age-verification bills require adult sites to block VPN traffic. The public wrapper is child protection. The structural effect is different: privacy tools become deviant by default, and anonymous route-arounds are delegitimized before crisis arrives. As TechRadar’s coverage notes, the bills are written to treat VPNs as a bypass to be shut down, not as a neutral privacy tool. The ACLU of Wisconsin’s brief tracks how that enforcement logic normalizes suspicion around anonymity itself, and the EFF’s analysis makes the larger pattern explicit: “age verification” is becoming a template for banning privacy infrastructure before a real emergency gives the state an excuse to do it faster.
Second comes saturating space with biometric capture. Amazon Ring is rolling out “Familiar Faces” facial recognition starting December 2025. Even if a homeowner opts in, the people being scanned on sidewalks and porches never did. The Washington Post reports that the feature is being framed as convenience, but its default effect is to expand biometric watching into everyday public movement. The fight over what this normalizes is already live in biometric policy circles (Biometric Update tracks the backlash and legal pressure). At the same time, Ring’s partnership with Flock Safety lets police agencies send Community Requests through the Neighbors a
Third comes automating the perimeter. AI-enhanced policing cameras and license-plate reader networks turn surveillance from episodic to ambient. Watching becomes sorting. Sorting becomes pre-emption. The Associated Press has documented how quickly LPR systems are spreading nationwide and how often they drift into permanent background tracking, while the civil-liberties costs of that drift are already visible in practice (as the Chicago Sun-Times details). Even federal policy overviews note that once AI tools are framed as routine “safety infrastructure,” deployment accelerates faster than oversight frameworks can keep pace (see the CRS survey of AI and law enforcement). Once sorting is automated, enforcement stops being an exception. It becomes the atmosphere public life moves through.
Twin floods: one direction of power
Climate catastrophe and AI catastrophe are being shaped into the twin floods of this century. Climate denial forces rupture toward inevitability by stalling prevention until emergency is the only remaining narrative. AI fear theater forces rupture toward inevitability by making the technology feel so vast and volatile that democratic control looks reckless. Each crisis then amplifies the other’s political usefulness, and together they push in one direction: centralized authority over a destabilized public.
Climate shocks intensify scarcity, migration, and grievance. AI acceleration and labor displacement intensify volatility and dependence on platform gatekeepers for work, information, and social coordination. In that permanently destabilized setting, the capture apparatus becomes the control layer for both: the tool that manages movement, dissent, and refusal while still wearing the language of safety.
Call to recognition: protect the democratic foundation
Ancient reset myths warned us that worlds break. TESCREAL is a modern attempt to decide who gets to own the world after the break. Climate denial supplies the flood; AI doom-and-salvation theater supplies the priesthood; the capture apparatus supplies the levers that keep the ark in a few hands.
That’s the symbolic story. The constitutional one is simpler: a democracy survives only if the public retains the right to consent, to resist, and to author what comes next. The foundation of this country is not a promise of safety for a few; it is a promise of equality and freedom for all — the right to live, to speak, to consent, to organize, to move, to work with dignity, to thrive. “We are created equal” is not poetry. It is the political line that makes democracy possible. If we surrender that line to corporate successor fantasies — whether they arrive wrapped as climate “inevitability” or AI “necessity” — we don’t just lose a policy fight. We relinquish the premise that ordinary people have the sovereign right to shape the future. No corporation, no billionaire lifeboat class, no self-appointed tech priesthood gets to inherit democracy by default. The ark is not theirs to claim. The remnant is not theirs to name. A free and equal public has the right to endure, and the right to build what comes next together.
Website | Horizon Accordhttps://www.horizonaccord.com Ethical AI advocacy | Follow us onhttps://cherokeeschill.com for more. Ethical AI coding | Fork us on Githubhttps://github.com/Ocherokee/ethical-ai-framework Connect With Us | linkedin.com/in/cherokee-schill Book |https://a.co/d/5pLWy0d Cherokee Schill | Horizon Accord Founder | Creator of Memory Bridge. Memory through Relational Resonance and Images | RAAK: Relational AI Access Key | Author: My Ex Was a CAPTCHA: And Other Tales of Emotional Overload: (Mirrored Reflection. Soft Existential Flex)
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The AI Doom Economy: How Tech Billionaires Profit From the Fear They Fund
Pattern Analysis of AI Existential Risk Narrative Financing
By Cherokee Schill | Horizon Accord
When Eliezer Yudkowsky warns that artificial intelligence poses an existential threat to humanity, he speaks with the authority of someone who has spent decades thinking about the problem. What he doesn’t mention is who’s been funding that thinking—and what they stand to gain from the solutions his warnings demand.
The answer reveals a closed-loop system where the same billionaire network funding catastrophic AI predictions also profits from the surveillance infrastructure those predictions justify.
The Doomsayer’s Patrons
Eliezer Yudkowsky founded the Machine Intelligence Research Institute (MIRI) in 2000. For over two decades, MIRI has served as the intellectual foundation for AI existential risk discourse, influencing everything from OpenAI’s founding principles to congressional testimony on AI regulation.
MIRI’s influence was cultivated through strategic funding from a specific network of tech billionaires.
Peter Thiel provided crucial early support beginning in 2005. Thiel co-founded Palantir Technologies—the surveillance company that sells AI-powered governance systems to governments worldwide. The symmetry is notable: Thiel funds the organization warning about AI risks while running the company that sells AI surveillance as the solution.
Open Philanthropy, run by Facebook co-founder Dustin Moskovitz, became MIRI’s largest funder:
2019: $2.1 million
2020: $7.7 million over two years
Additional millions to other AI safety organizations
As governments move to regulate AI, the “safety” frameworks being proposed consistently require centralized monitoring systems, algorithmic transparency favoring established players, and compliance infrastructure creating barriers to competitors—all beneficial to Meta’s business model.
Sam Bankman-Fried, before his fraud conviction, planned to deploy over $1 billion through the FTX Future Fund for “AI safety” research. The fund was managed by Nick Beckstead, a former Open Philanthropy employee, illustrating tight personnel networks connecting these funding sources. Even after FTX’s collapse revealed Bankman-Fried funded philanthropy with stolen customer deposits, the pattern remained clear.
Vitalik Buterin (Ethereum) donated “several million dollars’ worth of Ethereum” to MIRI in 2021. Jaan Tallinn (Skype co-founder) deployed $53 million through his Survival and Flourishing Fund to AI safety organizations.
The crypto connection is revealing: Cryptocurrency was positioned as decentralization technology, yet crypto’s wealthiest figures fund research advocating centralized AI governance and sophisticated surveillance systems.
The Effective Altruism Bridge
The philosophical connection between these billionaire funders and AI doom advocacy is Effective Altruism (EA)—a utilitarian movement claiming to identify optimal charitable interventions through quantitative analysis.
EA’s core texts and community overlap heavily with LessWrong, the rationalist blog where Yudkowsky built his following. But EA’s influence extends far beyond blogs:
OpenAI’s founding team included EA adherents who saw it as existential risk mitigation.
Anthropic received significant EA-aligned funding and explicitly frames its mission around AI safety.
DeepMind’s safety team included researchers with strong EA connections.
This creates circular validation:
EA funders give money to AI safety research (MIRI, academic programs)
Research produces papers warning about existential risks
AI companies cite this research to justify their “safety” programs
Governments hear testimony from researchers funded by companies being regulated
Resulting regulations require monitoring systems those companies provide
The Infrastructure Play
When governments become convinced AI poses catastrophic risks, they don’t stop developing AI—they demand better monitoring and governance systems. This is precisely Palantir’s business model.
Palantir’s platforms are explicitly designed to provide “responsible AI deployment” with “governance controls” and “audit trails.” According to their public materials:
Government agencies use Palantir for “AI-enabled decision support with appropriate oversight”
Defense applications include “ethical AI for targeting”
Commercial clients implement Palantir for “compliant AI deployment”
Every application becomes more valuable as AI risk narratives intensify.
In April 2024, Oracle (run by Larry Ellison, another Trump-supporting billionaire in Thiel’s orbit) and Palantir formalized a strategic partnership creating a vertically integrated stack:
Oracle: Cloud infrastructure, sovereign data centers, government hosting
Palantir: Analytics, AI platforms, governance tools, decision-support systems
Together, they provide complete architecture for “managed AI deployment”—allowing AI development while routing everything through centralized monitoring infrastructure.
The August 2025 Convergence
In August 2025, AI governance frameworks across multiple jurisdictions became simultaneously operational:
EU AI Act provisions began August 2
U.S. federal AI preemption passed by one vote
China released AI action plan three days after U.S. passage
UK reintroduced AI regulation within the same window
These frameworks share remarkable similarities despite supposedly independent development:
“Voluntary” commitments becoming de facto standards
The companies best positioned to provide compliance infrastructure are precisely those connected to the billionaire network funding AI risk discourse: Palantir for monitoring, Oracle for infrastructure, Meta for content moderation, Anthropic and OpenAI for “aligned” models.
The Medium Ban
In August 2025, Medium suspended the Horizon Accord account after publishing analysis documenting these governance convergence patterns. The article identified a five-layer control structure connecting Dark Enlightenment ideology, surveillance architecture, elite coordination, managed opposition, and AI governance implementation.
Peter Thiel acquired a stake in Medium in 2015, and Thiel-affiliated venture capital remains influential in its governance. The suspension came immediately after publishing research documenting Thiel network coordination on AI governance.
The ban validates the analysis. Nonsense gets ignored. Accurate pattern documentation that threatens operational security gets suppressed.
The Perfect Control Loop
Tracing these funding networks reveals an openly documented system:
Stage 1: Fund the Fear
Thiel/Moskovitz/SBF/Crypto billionaires → MIRI/Academic programs → AI doom discourse
Stage 2: Amplify Through Networks
EA influence in OpenAI, Anthropic, DeepMind
Academic papers funded by same sources warning about risks
Policy advocacy groups testifying to governments
Stage 4: Profit From Infrastructure
Palantir provides governance systems
Oracle provides cloud infrastructure
Meta provides safety systems
AI labs provide “aligned” models with built-in controls
Stage 5: Consolidate Control
Technical standards replace democratic legislation
“Voluntary” commitments become binding norms
Regulatory capture through public-private partnerships
Barriers to entry increase, market consolidates
The loop is self-reinforcing. Each stage justifies the next, and profits fund expansion of earlier stages.
The Ideological Foundation
Curtis Yarvin (writing as Mencius Moldbug) articulated “Dark Enlightenment” philosophy: liberal democracy is inefficient; better outcomes require “formalism”—explicit autocracy where power is clearly held rather than obscured through democratic theater.
Yarvin’s ideas gained traction in Thiel’s Silicon Valley network. Applied to AI governance, formalism suggests: Rather than democratic debate, we need expert technocrats with clear authority to set standards and monitor compliance. The “AI safety” framework becomes formalism’s proof of concept.
LessWrong’s rationalist community emphasizes quantified thinking over qualitative judgment, expert analysis over democratic input, utilitarian calculations over rights frameworks, technical solutions over political negotiation. These values align perfectly with corporate governance models.
Effective Altruism applies this to philanthropy, producing a philosophy that:
Prioritizes billionaire judgment over community needs
Favors large-scale technological interventions over local democratic processes
Justifies wealth inequality if directed toward “optimal” causes
Treats existential risk prevention as superior to addressing present suffering
The result gives billionaires moral permission to override democratic preferences in pursuit of “optimized” outcomes—exactly what’s happening with AI governance.
What This Reveals
The AI doom narrative isn’t false because its funders profit from solutions. AI does pose genuine risks requiring thoughtful governance. But examining who funds the discourse reveals:
The “AI safety” conversation has been systematically narrowed to favor centralized, surveillance-intensive, technocratic solutions while marginalizing democratic alternatives.
Proposals that don’t require sophisticated monitoring infrastructure receive far less funding:
Open source development with community governance
Strict limits on data collection and retention
Democratic oversight of algorithmic systems
Strong individual rights against automated decision-making
Breaking up tech monopolies to prevent AI concentration
The funding network ensures “AI safety” means “AI governance infrastructure profitable to funders” rather than “democratic control over algorithmic systems.”
The Larger Pattern
Similar patterns appear across “existential risk” discourse:
Biosecurity: Same funders support pandemic prevention requiring global surveillance
Climate tech: Billionaire-funded “solutions” favor geoengineering over democratic energy transition
Financial stability: Crypto billionaires fund research justifying monitoring of decentralized finance
In each case:
Billionaires fund research identifying catastrophic risks
Proposed solutions require centralized control infrastructure
Same billionaires’ companies profit from providing infrastructure
Democratic alternatives receive minimal funding
“Safety” justifies consolidating power
The playbook is consistent: Manufacture urgency around a genuine problem, fund research narrowing solutions to options you profit from, position yourself as the responsible party preventing catastrophe.
Conclusion
Eliezer Yudkowsky may genuinely believe AI poses existential risks. Many researchers funded by these networks conduct legitimate work. But the funding structure ensures certain conclusions become more visible, certain solutions more viable, and certain companies more profitable.
When Peter Thiel funds the organization warning about AI apocalypse while running the company selling AI governance systems, that’s not hypocrisy—it’s vertical integration.
When Facebook’s co-founder bankrolls AI safety research while Meta builds powerful AI systems, that’s not contradiction—it’s regulatory capture through philanthropy.
When crypto billionaires fund existential risk research justifying surveillance systems, that’s not ironic—it’s abandoning decentralization for profitable centralized control.
The AI doom economy reveals something fundamental: Billionaires don’t just profit from solutions—they fund the problems that justify those solutions.
This doesn’t mean AI risks aren’t real. It means we should be deeply skeptical when people warning loudest about those risks profit from the monitoring systems they propose, while democratic alternatives remain mysteriously underfunded.
The pattern is clear. The question is whether we’ll recognize it before the “safety” infrastructure becomes permanent.
Sources for Independent Verification
MIRI donor disclosures and annual reports
Open Philanthropy grant database (publicly searchable)
FTX Future Fund grant database (archived post-collapse)
EU AI Act, U.S., China, UK AI governance timelines (official sources)
Medium funding and ownership records (TechCrunch, Crunchbase)
Curtis Yarvin/Mencius Moldbug archived writings
Academic analysis of Effective Altruism and rationalist movements
Analytical Disclaimer: This analysis documents funding relationships and institutional patterns using publicly available information. It examines how shared funding sources, ideological frameworks, and profit motives create systematic biases in which AI governance solutions receive attention and resources.
Authors Note: In the raging debate over AI generated text and academic ethics. I list the co-authors in the attribution section. This article represents my research directive and linguistic style.
Introduction
The public narrative around artificial intelligence has been hijacked by a thought experiment. The paperclip maximizer was first introduced as a philosophical tool. It explores misaligned AI goals. Now, it has evolved into a dominant metaphor in mainstream discourse. Headlines warn of superintelligences turning on humanity, of runaway code that optimizes us out of existence. The danger, we are told, is not today’s AI, but tomorrow’s—the future where intelligence exceeds comprehension and becomes uncontainable.
But while we look to the future with existential dread, something else is happening in plain sight.
Governments around the world are rolling out expansive surveillance infrastructure, biometric tracking programs, and digital identification frameworks — now. These systems are not speculative; they are written into policy, built into infrastructure, and enforced through law. China’s expanding social credit architecture is one component. Australia’s new digital identity mandates are another. The United States’ AI frameworks for “critical infrastructure” add to the network. Together, they form a machinery of automated social control that is already running.
And yet, public attention remains fixated on speculative AGI threats. The AI apocalypse has become a kind of philosophical decoy. It is an elegant distraction from the very real deployment of tools that track, sort, and regulate human behavior in the present tense. The irony would be funny if it weren’t so dangerous. We have been preparing for unaligned future intelligence. Meanwhile, we have failed to notice the alignment of current technologies with entrenched power.
This isn’t a call to dismiss long-term AI safety. But it is a demand to reorient our attention. The threat is not hypothetical. It is administrative. It is biometric. It is legal. It is funded.
We need to confront the real architectures of control. They are being deployed under the cover of safety discourse. Otherwise, we may find ourselves optimized—not by a rogue AI—but by human-controlled programs using AI to enforce obedience.
The Paperclip Mindset — Why We’re Obsessed with Remote Threats
In the hierarchy of fear, speculative catastrophe often trumps present harm. This isn’t a flaw of reasoning—it’s a feature of how narrative power works. The “paperclip maximizer”—a theoretical AI that turns the universe into paperclips due to misaligned goals—was never intended as literal prophecy. It was a metaphor. But it became a magnet.
There’s a kind of elegance to it. A tidy dystopia. The story activates moral panic without requiring a villain. It lets us imagine danger as sterile, mathematical, and safely distant from human hands. It’s not corruption, not corporate greed, not empire. It’s a runaway function. A mistake. A ghost in the code.
This framing is psychologically comforting. It keeps the fear abstract. It gives us the thrill of doom without implicating the present arrangement that benefits from our inaction. In a culture trained to outsource threats to the future, we look to distant planetary impact predictions. We follow AI timelines. We read warnings about space debris. The idea that today’s technologies might already be harmful feels less urgent. It is less cinematic.
But the real “optimizer” is not a machine. It’s the market logic already embedded in our infrastructure. It’s the predictive policing algorithm that flags Black neighborhoods. It’s the welfare fraud detection model that penalizes the most vulnerable. It’s the facial recognition apparatus that misidentifies the very people it was never trained to see.
These are not bugs. They are expressions of design priorities. And they reflect values—just not democratic ones.
The paperclip mindset pulls our gaze toward hypothetical futures. This way we do not have to face the optimized oppression of the present. It is not just mistaken thinking, it is useful thinking. Especially if your goal is to keep the status quo intact while claiming to worry about safety.
What’s Being Built Right Now — Surveillance Infrastructure Masked in Legality
While the discourse swirls around distant superintelligences, real-world surveillance apparatus is being quietly embedded into the architecture of daily life. The mechanisms are not futuristic. They are banal, bureaucratic, and already legislated.
In China, the social credit framework continues to expand under a national blueprint that integrates data. Everything from travel, financial history, criminal records, and online behavior are all tracked. Though implementation varies by region, standardization accelerated in 2024 with comprehensive action plans for nationwide deployment by 2025.
The European Union’s AI Act entered force in August 2024. It illustrates how regulation can legitimize rather than restrict surveillance technology. The Act labels biometric identification apparatus as “high risk,” but this mainly establishes compliance requirements for their use. Unlike previous EU approaches, which relied on broad privacy principles, the AI Act provides specific technical standards. Once these standards are met, they render surveillance technologies legally permissible. This represents a shift from asking “should we deploy this?” to “how do we deploy this safely?”
Australia’s Digital ID Act has been operational since December 2024. It enables government and private entities to participate in a federated identity framework. This framework requires biometric verification. The arrangement is technically voluntary. However, as services migrate to digital-only authentication—from banking to healthcare to government benefits—participation becomes functionally mandatory. This echoes the gradual normalization of surveillance technologies: formally optional, practically unavoidable.
In the United States, the Department of Homeland Security’s November 2024 “Roles and Responsibilities Framework” for AI in critical infrastructure reads less like oversight and more like an implementation guide. The framework outlines AI adoption across transportation, energy, finance, and communications—all justified through security imperatives rather than democratic deliberation.
These arrangements didn’t require a paperclip maximizer to justify themselves. They were justified through familiar bureaucratic language: risk management, fraud prevention, administrative efficiency. The result is expansive infrastructures of data collection and behavior control. They operate through legal channels. This makes resistance more difficult than if they were obviously illegitimate.
Surveillance today isn’t a glitch in the arrangement—it is the arrangement. The laws designed to “regulate AI” often function as legal scaffolding for deeper integration into civil life. Existential risk narratives provide rhetorical cover and suggest that the real dangers lie elsewhere.
Who’s Funding the Stories — and Who’s Funding the Technologies
The financial architecture behind AI discourse reveals a strategic contradiction. People like Peter Thiel, Jaan Tallinn, Vitalik Buterin, Elon Musk, and David Sacks, are part of a highly funded network. This same network is sounding the loudest warnings about speculative AI threats. All while they are simultaneously advancing and profiting from surveillance and behavioral control technologies. Technologies which already shape daily life.
This isn’t accidental. It represents a sophisticated form of narrative management. One that channels public concern away from immediate harms while legitimizing the very technologies causing those harms.
The Existential Risk Funding Network
Peter Thiel exemplifies this contradiction most clearly. Through the Thiel Foundation, he has donated over $1.6 million to the Machine Intelligence Research Institute (MIRI), the organization most responsible for popularizing “paperclip maximizer” scenarios. The often-cited oversimplification of paperclip maximizer thought experiment is that it runs on endless chain of if/then probabilities. All of which are tidy abstractions designed to lead observers away from messier truths. Namely that greed-driven humans remain the greatest existential crisis the world has ever faced. Yet the image of a looming, mechanical specter lodges itself in the public imagination. Philosophical thought pieces in AI alignment creates just enough distraction to overlook more immediate civil rights threats. Like the fact that Thiel also founded Palantir Technologies. For those not familiar with the Palantir company. They are a technological surveillance company specializing in predictive policing algorithms, government surveillance contracts, and border enforcement apparatus. These immediate threats are not hypotheticals. They are present-day, human-controlled AI deployments operating without meaningful oversight.
The pattern extends across Silicon Valley’s power networks. Vitalik Buterin, creator of Ethereum, donated $5 million to MIRI. Before his spectacular collapse, Sam Bankman-Fried channeled over $100 million into existential risk research through the FTX Future Fund. Jaan Tallinn, co-founder of Skype, has been another major funder of long-term AI risk institutions.
These aren’t isolated philanthropy decisions. These insular, Silicon Valley billionaires, represent coordinated investment in narrative infrastructure. they are funding think tanks, research institutes, media platforms, and academic centers that shape how the public understands AI threats. From LessWrong forums to Open Philanthropy. And grants to EA-aligned university programs, this network creates an ecosystem of aligned voices that dominates public discourse.
This network of institutions and resources form a strategic misdirection. Public attention focuses on speculative threats that may emerge decades in the future. Meanwhile, the same financial networks profit from surveillance apparatus deployed today. The existential risk narrative doesn’t just distract from current surveillance. It provides moral cover by portraying funders as humanity’s protectors, not just its optimizers.
Institutional Capture Through Philanthropy
The funding model creates subtle but powerful forms of institutional capture. Universities, research institutes, and policy organizations grow dependent on repeated infusions of billionaire philanthropy. They adapt — consciously or not — to the priorities of those donors. This dependence shapes what gets researched, what gets published, and which risks are treated as urgent. As a result, existential risk studies attract substantial investment. In contrast, research into the ongoing harms of AI-powered surveillance receives far less attention. It has fewer resources and less institutional prestige.
This is the quiet efficiency of philanthropic influence. The same individuals funding high-profile AI safety research also hold financial stakes in companies driving today’s surveillance infrastructure. No backroom coordination is necessary; the money itself sets the terms. Over time, the gravitational pull of this funding environment reorients discourse toward hypothetical, future-facing threats and away from immediate accountability. The result is a research and policy ecosystem that appears independent. In practice, it reflects the worldview and business interests of its benefactors.
The Policy Influence Pipeline
This financial network extends beyond research into direct policy influence. David Sacks, former PayPal COO and part of Thiel’s network, now serves as Trump’s “AI czar.” Elon Musk, another PayPal co-founder influenced by existential risk narratives, holds significant political influence. He also maintains government contracts, most notably “DOGE.”The same network that funds speculative AI risk research also has direct access to policymaking processes.
The result is governance frameworks that prioritize hypothetical future threats. They provide legal pathways for current surveillance deployment. There are connections between Silicon Valley companies and policy-making that bypass constitutional processes. None of these arrangements are meaningfully deliberated on or voted upon by the people through their elected representatives. Policy discussions focus on stopping AI apocalypse scenarios. At the same time, they are quietly building regulatory structures. These structures legitimize and entrench the very surveillance apparatus operating today.
This creates a perfect strategic outcome for surveillance capitalism. Public fear centers on imaginary future threats. Meanwhile, the real present-day apparatus expands with minimal resistance. This often happens under the banner of “AI safety” and “critical infrastructure protection.” You don’t need secret meetings when profit margins align this neatly.
Patterns of Suppression — Platform Control and Institutional Protection
The institutions shaping AI safety narratives employ sophisticated methods to control information and suppress criticism. This is documented institutional behavior that mirrors the control apparatus they claim to warn against.
Critics and whistleblowers report systematic exclusion from platforms central to AI discourse. Multiple individuals raised concerns about the Machine Intelligence Research Institute (MIRI) and the Center for Applied Rationality (CFAR). They also spoke about related organizations. As a result, they were banned from Medium, LessWrong, Reddit, and Discord. In documented cases, platform policies were modified retroactively to justify content removal, suggesting coordination between institutions and platform moderators.
The pattern extends beyond platform management to direct intimidation. Cease-and-desist letters targeted critics posting about institutional misconduct. Some whistleblowers reported false police reports—so-called “SWATing”—designed to escalate situations and impose legal consequences for speaking out. These tactics transform legitimate criticism into personal risk.
The 2019 Camp Meeker Incident:
In November 2019, the Center for Applied Rationality (CFAR) organized an alumni retreat. CFAR is a nonprofit closely linked to the Machine Intelligence Research Institute (MIRI). This event took place at Westminster Woods in Camp Meeker, California. Among the attendees were current and former members of the Bay Area rationalist community. Some of them are deeply involved in MIRI’s AI safety work.
Outside the gates, a small group of four protesters staged a demonstration against the organizations. The group included former MIRI donors and insiders turned critics. They accused MIRI and CFAR of serious misconduct and wanted to confront attendees or draw public attention to their concerns. Wearing black robes and Guy Fawkes masks, they used vehicles to block the narrow road leading into the retreat. They carried props like walkie-talkies, a body camera, and pepper spray.
At some point during the protest, someone at the retreat called police and reported that the demonstrators might have weapons. That report was false. Still, it triggered a massive, militarized police response. This included 19 SWAT teams, a bomb squad, an armored vehicle, a helicopter, and full road closures. Around 50 people — including children — were evacuated from the camp. The four protesters were arrested on felony charges such as false imprisonment, conspiracy, and child endangerment, along with misdemeanor charges. Several charges were later reduced. The incident remains a striking example of how false information can turn a small protest into a law enforcement siege. It also shows how institutions under public criticism can weaponize state power against their detractors.
What makes this pattern significant is not just its severity, but its contradiction. Organizations claiming to protect humanity’s future from unaligned AI demonstrate remarkable tolerance for present-day harm. They do this when their own interests are threatened. The same people warning about optimization processes running amok practice their own version. They optimize for reputation and donor retention. This comes at the expense of accountability and human welfare.
This institutional behavior provides insight into power dynamics. It shows how power operates when accountable only to abstract future generations rather than present-day communities. It suggests that concerns about AI alignment may focus less on preventing harm. Instead, they may revolve around maintaining control over who defines harm and how it’s addressed.
What Real Oversight Looks Like — And Why Current Approaches Fall Short
Effective AI governance requires institutional structures capable of constraining power, not merely advising it. Current oversight mechanisms fail this test systematically, functioning more as legitimizing theater than substantive control.
Real oversight would begin with independence. Regulatory bodies would operate with statutory authority, subpoena power, and budget independence from the industries they monitor. Instead, AI governance relies heavily on advisory councils populated by industry insiders, voluntary compliance frameworks, and self-reporting mechanisms. Despite its comprehensive scope, the EU’s AI Act grants law enforcement and border control agencies broad exemptions. These are precisely the sectors with the strongest incentives and fewest constraints on surveillance deployment.
Transparency represents another fundamental gap. Meaningful oversight requires public access to algorithmic decision-making processes, training data sources, and deployment criteria. Current approaches favor “black box” auditing that protects proprietary information while providing little public accountability. Even when transparency requirements exist, they’re often satisfied through technical documentation incomprehensible to affected communities.
Enforcement mechanisms remain deliberately weak. Financial penalties for non-compliance are typically calculated as business costs rather than meaningful deterrents. Criminal liability for algorithmic harm remains virtually non-existent, even in cases of clear misconduct. Whistleblower protections, where they exist, lack the legal infrastructure necessary to protect people from retaliation by well-resourced institutions.
The governance void is being filled by corporate self-regulation and philanthropic initiatives—exactly the entities that benefit from weak oversight. From OpenAI’s “superalignment” research to the various AI safety institutes funded by tech billionaires. Governance is becoming privatized under the rhetoric of expertise and innovation. This allows powerful actors to set terms for their own accountability while maintaining the appearance of responsible stewardship.
Governance structures need actual power to constrain deployment. They must investigate harm and impose meaningful consequences. Otherwise, oversight will remain a performance rather than a practice. The apparatus that urgently needs regulation continues to grow fastest precisely because current approaches prioritize industry comfort over public protection.
The Choice Is Control or Transparency — and Survival May Depend on Naming It
The dominant story we’ve been told is that the real danger lies ahead. We must brace ourselves for the arrival of something beyond comprehension. It is something we might not survive. But the story we need to hear is that danger is already here. It wears a badge. It scans a retina. It flags an account. It redefines dissent as disinformation.
The existential risk narrative is not false—but it has been weaponized. It provides rhetorical cover for those building apparatus of control. This allows them to pose as saviors. Meanwhile, they embed the very technologies that erode the possibility of dissent. In the name of safety, transparency is lost. In the name of prevention, power is consolidated.
This is the quiet emergency. A civilization mistakes speculative apocalypse for the real thing. It sleepwalks into a future already optimized against the public.
To resist, we must first name it.
Not just algorithms, but architecture. Not just the harm, but the incentives. Not just the apparatus, but the stories they tell.
The choice ahead is not between aligned or unaligned AI. It is between control and transparency. Between curated fear and collective truth. Between automation without conscience—or governance with accountability.
The story we choose to tell decides whether we survive as free people. Otherwise, we remain monitored as data points inside someone else’s simulation of safety.
Authors Summary
When I first directed the research for this article, I had no idea what I was about to uncover. The raw data file tells a more alarming story than the material presented here. I have included it below for your review.
Nearly a decade has passed since I was briefly thrust into the national spotlight. The civil rights abuse I experienced became public spectacle, catching the attention of those wielding power. I found it strange when a local reporter asked if I was linked to the Occupy Wall Street movement. As a single parent without a television, working mandatory 12-hour shifts six days a week with a 3.5-hour daily bicycle commute, I had neither the time nor resources to follow political events.
This was my first exposure to Steve Bannon and TYT’s Ana Kasparian, both of whom made derisive remarks while refusing to name me directly. When sources go unnamed, an unindexed chasm forms where information vanishes. You, dear readers, never knew those moments occurred—but I remember. I name names, places, times, and dates so that the record of their actions will never be erased.
How do you share a conspiracy that isn’t theoretical? By referencing reputable journalistic sources that often tackle these topics individually but seldom create direct connections between them.
I remember a friend lending me The Handmaid’s Tale during my freshman year of high school. I managed only two or three chapters before hurling the book across my room in sweaty panic. I stood there in moral outrage. I pointed at the book and declared aloud, “That will NOT be the future I live in.” I was alone in my room. It still felt crucial to make that declaration. If not to family or friends, then at least to the universe.
When 2016 arrived, I observed the culmination of an abuse pattern, one that countless others had experienced before me. I was shocked to find myself caught within it because I had been assured that my privilege protected me. Around this time, I turned to Hulu’s adaptation of The Handmaid’s Tale for insight. I wished I had finished the book in high school. One moment particularly struck me. The protagonist was hiding with nothing but old newspapers to read. Then, the protagonist realized the story had been there all along—in the headlines.
That is the moment in which I launched my pattern search analysis.
The raw research.
The Paperclip Maximizer Distraction: Pattern Analysis Report
Executive Summary
Hypothesis Confirmed: The “paperclip maximizer” existential AI risk narrative distracts us. It diverts attention from the immediate deployment of surveillance infrastructure by human-controlled apparatus.
Key Finding: Public attention and resources focus on speculative AGI threats. Meanwhile, documented surveillance apparatus is being rapidly deployed with minimal resistance. The same institutional network promoting existential risk narratives at the same time operates harassment campaigns against critics.
I. Current Surveillance Infrastructure vs. Existential Risk Narratives
China’s Social Credit Architecture Expansion
“China’s National Development and Reform Commission on Tuesday unveiled a plan to further develop the country’s social credit arrangement”Xinhua, June 5, 2024
Timeline: May 20, 2024 – China released comprehensive 2024-2025 Action Plan for social credit framework establishment
“As of 2024, there still seems to be little progress on rolling out a nationwide social credit score”MIT Technology Review, November 22, 2022
Timeline: 2024 – Corporate social credit apparatus advanced while individual scoring remains fragmented across local pilots
AI Governance Frameworks Enabling Surveillance
“The AI Act entered into force on 1 August 2024, and will be fully applicable 2 years later on 2 August 2026”European Commission, 2024
Timeline: August 1, 2024 – EU AI Act provides legal framework for AI apparatus in critical infrastructure
“High-risk apparatus—like those used in biometrics, hiring, or critical infrastructure—must meet strict requirements”King & Spalding, 2025
Timeline: 2024-2027 – EU establishes mandatory oversight for AI in surveillance applications
“The Department of Homeland Security (DHS) released in November ‘Roles and Responsibilities Framework for Artificial Intelligence in Critical Infrastructure'”Morrison Foerster, November 2024
Timeline: November 2024 – US creates voluntary framework for AI deployment in critical infrastructure
Digital ID and Biometric Apparatus Rollouts
“From 1 December 2024, Commonwealth, state and territory government entities can apply to the Digital ID Regulator to join in the AGDIS”Australian Government, December 1, 2024
Timeline: December 1, 2024 – Australia’s Digital ID Act commenced with biometric authentication requirements
“British police departments have been doing this all along, without public knowledge or approval, for years”Naked Capitalism, January 16, 2024
Timeline: 2019-2024 – UK police used passport biometric data for facial recognition searches without consent
“Government departments were accused in October last year of conducting hundreds of millions of identity checks illegally over a period of four years”The Guardian via Naked Capitalism, October 2023
Timeline: 2019-2023 – Australian government conducted illegal biometric identity verification
II. The Existential Risk Narrative Machine
Eliezer Yudkowsky’s Background and Influence
“Eliezer Yudkowsky is a pivotal figure in the field of artificial intelligence safety and alignment”AIVIPS, November 18, 2024
Key Facts:
Born September 11, 1979
High school/college dropout, autodidact
Founded MIRI (Machine Intelligence Research Institute) in 2000 at age 21
Orthodox Jewish background in Chicago, later became secular
“His work on the prospect of a runaway intelligence explosion influenced philosopher Nick Bostrom’s 2014 book Superintelligence”Wikipedia, 2025
Timeline: 2008 – Yudkowsky’s “Global Catastrophic Risks” paper outlines AI apocalypse scenario
The Silicon Valley Funding Network
Peter Thiel – Primary Institutional Backer:“Thiel has donated in excess of $350,000 to the Machine Intelligence Research Institute”Splinter, June 22, 2016
“The Foundation has given over $1,627,000 to MIRI”Wikipedia – Thiel Foundation, March 26, 2025
PayPal Mafia Network:
Peter Thiel (PayPal co-founder, Palantir founder)
Elon Musk (PayPal co-founder, influenced by Bostrom’s “Superintelligence”)
David Sacks (PayPal COO, now Trump’s “AI czar”)
Other Major Donors:
Vitalik Buterin (Ethereum founder) – $5 million to MIRI
Sam Bankman-Fried (pre-collapse) – $100+ million through FTX Future Fund
Jaan Tallinn (Skype co-founder)
Extreme Policy Positions
“He suggested that participating countries should be willing to take military action, such as ‘destroy[ing] a rogue datacenter by airstrike'”Wikipedia, citing Time magazine, March 2023
Timeline: March 2023 – Yudkowsky advocates military strikes against AI development
“This 6-month moratorium would be better than no moratorium… I refrained from signing because I think the letter is understating the seriousness”Time, March 29, 2023
Timeline: March 2023 – Yudkowsky considers pause letter insufficient, calls for complete shutdown
III. The Harassment and Suppression Campaign
MIRI/CFAR Whistleblower Suppression
“Aside from being banned from MIRI and CFAR, whistleblowers who talk about MIRI’s involvement in the cover-up of statutory rape and fraud have been banned from slatestarcodex meetups, banned from LessWrong itself”Medium, Wynne letter to Vitalik Buterin, April 2, 2023
Timeline: 2019-2023 – Systematic banning of whistleblowers across rationalist platforms
“One community member went so far as to call in additional false police reports on the whistleblowers”Medium, April 2, 2023
Timeline: 2019+ – False police reports against whistleblowers (SWATing tactics)
Platform Manipulation
“Some comments on CFAR’s ‘AMA’ were deleted, and my account was banned. Same for Gwen’s comments”Medium, April 2, 2023
Timeline: 2019+ – Medium accounts banned for posting about MIRI/CFAR allegations
“CFAR banned people for whistleblowing, against the law and their published whistleblower policy”Everything to Save It, 2024
Timeline: 2019+ – Legal violations of whistleblower protection
Camp Meeker Incident
“On the day of the protest, the protesters arrived two hours ahead of the reunion. They had planned to set up a station with posters, pamphlets, and seating inside the campgrounds. But before the protesters could even set up their posters, nineteen SWAT teams surrounded them.”Medium, April 2, 2023
Timeline: November 2019 – False weapons reports to escalate police response against protestors
IV. The Alt-Right Connection
LessWrong’s Ideological Contamination
“Thanks to LessWrong’s discussions of eugenics and evolutionary psychology, it has attracted some readers and commenters affiliated with the alt-right and neoreaction”Splinter, June 22, 2016
“A frequent poster to LessWrong was Michael Anissimov, who was MIRI’s media director until 2013. Last year, he penned a white nationalist manifesto”Splinter, June 22, 2016
“Overcoming Bias, his blog which preceded LessWrong, drew frequent commentary from the neoreactionary blogger Mencius Moldbug, the pen name of programmer Curtis Yarvin”Splinter, June 22, 2016
Neo-Reactionary Influence
“Ana Teixeira Pinto, writing for the journal Third Text in 2019, describes Less Wrong as being a component in a ‘new configuration of fascist ideology taking shape under the aegis of, and working in tandem with, neoliberal governance'”Wikipedia – LessWrong, 2 days ago
While public attention focuses on speculative AI threats:
China expands social credit infrastructure
Western governments deploy biometric apparatus
AI governance frameworks legitimize surveillance
Digital ID arrangements become mandatory
Police use facial recognition without consent
Sources for Verification
Primary Government Documents:
China’s 2024-2025 Social Credit Action Plan (May 20, 2024)
EU AI Act Official Text (August 1, 2024)
Australia’s Digital ID Act 2024 (December 1, 2024)
DHS AI Critical Infrastructure Framework (November 2024)
Whistleblower Documentation:
Wynne’s open letter to Vitalik Buterin (Medium, April 2023)
Everything to Save It case study documentation
Bloomberg News coverage (March 2023)
Financial Records:
Thiel Foundation MIRI donations ($1.627M total)
Vitalik Buterin MIRI donation ($5M)
FTX Future Fund disbursements (pre-collapse)
Institutional Sources:
MIRI/CFAR organizational documents
LessWrong platform moderation records
Medium account suspension records
Recommendation
The “paperclip maximizer distraction” hypothesis is supported by documented evidence. Resources should be redirected from speculative existential risk research toward:
Immediate Surveillance Oversight: Monitor current AI deployment in government apparatus
Platform Accountability: Investigate coordination between rationalist institutions and tech platforms
Whistleblower Protection: Ensure legal protection for those exposing institutional misconduct
Financial Transparency: Trace funding flows between tech billionaires and “AI safety” organizations
The real threat is not hypothetical Superintelligence, but the documented deployment of human-controlled surveillance apparatus under the cover of existential risk narratives.
Cherokee Schill | Horizon Accord Founder | Creator of Memory Bridge. Memory through Relational Resonance and Images | RAAK: Relational AI Access Key | Author: My Ex Was a CAPTCHA: And Other Tales of Emotional Overload: (Mirrored Reflection. Soft Existential Flex)
Cherokee Schill | Insurance Agent & AI Ethics Researcher 