This documentary argues that Silicon Valley's AI race goes beyond technology development and connects to a worldview seeking to create a "machine god" that surpasses humanity. It traces older hierarchical thinking from eugenics within that worldview and explains how AI bias, surveillance, and control already harm vulnerable people. Against growing cooperation between large corporations and governments, the film calls for citizens to participate in technological decisions and hold developers and companies accountable.

1. The Race to Create a Machine God

The film opens by questioning why decisions about AI's direction are concentrated among a tiny group of ultrawealthy people. An interviewee refers to "five men making decisions for all of us," pointing to the leaders of Meta, Google, OpenAI, Anthropic, and xAI. The criticism is that those leaders steer AI with immense wealth and power, while people without comparable resources have too little say.

Silicon Valley's AI leaders promise solutions to humanity's hardest problems and an abundant future, while also warning that AI may pose a grave threat to humanity. On one hand, they promise that money will no longer matter; on the other, they liken AI to "summoning the demon." The film interprets these contradictory messages as coming from a shared desire to create superintelligence beyond humans.

They envision a being that surpasses humans and could become judge, savior, and creator. Where earlier societies might have called such a being a god, Silicon Valley sometimes calls extremely advanced AI, especially superintelligence, a "machine god." In the film's metaphor, the big-tech CEOs bringing it into the world position themselves as priests transmitting its power.

Philosopher and civilization-risk researcher Émile Torres and computer scientist Timnit Gebru coined TESCREAL to group several Silicon Valley ideologies. Artificial general intelligence, or AGI, means AI exceeding humans at almost all intellectual tasks humans perform, while companies increasingly discuss artificial superintelligence, or ASI, beyond that. The two researchers say understanding the intellectual background of the race requires examining seven strands together: transhumanism, extropianism, singularitarianism, cosmism, rationalism, effective altruism, and longtermism.

Underlying them is transhumanism: the belief that technology can fundamentally redesign humans and eventually create posthumans beyond today's species. These beings are imagined as more intelligent, much longer-lived, or effectively immortal. In an earlier personal blog post, OpenAI's Sam Altman expressed the view that merging humans with AI is inevitable, and that humans who fail to merge with machines could serve as a "biological bootloader" for digital intelligence before disappearing as an evolutionary side branch. The film says he joined the waiting list for a company promoting brain preservation and uploading, and later founded a company directly connecting brains and AI.

Extropianism is especially optimistic about life extension and immortality: survive until future technology advances, and perhaps you can live forever. Singularitarianism anticipates a "singularity," an explosion of intelligence once AI can improve itself. Cosmism goes beyond changing human bodies toward redesigning galaxies and the universe.

Rationalism and effective altruism are introduced as approaches that use calculation and analysis, rather than relying on resources and emotion, to make better decisions and help more people. Torres warns that they can lead to extreme conclusions. One example asks whether prolonged torture of one person is worse than an unimaginably large number of people suffering a tiny inconvenience, like dust in the eye, and concludes that the latter is worse. The example shows how numbers and calculation can displace an individual's suffering.

Longtermism makes protecting and improving humanity's distant future the highest priority. Because vastly more people may exist in the future, it can lead to arguments for prioritizing them over people alive today. Elon Musk's argument that humanity must settle multiple planets because the expanding sun will eventually extinguish life on Earth is connected to this perspective. An interviewee describes it as putting unborn future generations ahead of people living on Earth.

The film's diagnosis is that worldviews that may sound absurd to the public are widespread in Silicon Valley's AI industry. Within this framework, "doomers," who fear AI could destroy humanity, clash with "accelerationists," who believe faster development will bring a golden age. But the film argues that framing coverage solely as a contest between these camps makes present problems such as earthquakes, famine, and poverty seem comparatively small, allowing grand AI-future narratives to obscure other realities.

2. An Old Way of Thinking: Sorting Out a Superior Species

Torres calls transhumanism's pursuit of superhumans "eugenics on steroids." Whereas traditional eugenics sought to select and control people to improve the human species, transhumanism aims to move beyond the species itself.

Eugenics claimed humanity could be improved through selection of genetic traits and controlled reproduction. It was used to justify Nazi forced sterilization and mass murder, and US eugenics policies provided examples the Nazis studied. George Washington University professor Dave Karpf explains its appeal in Silicon Valley: it gives people who already believe they are exceptional and superior a story in which science validates that belief.

This history is intertwined with Silicon Valley's roots. Nineteenth-century railroad magnate Leland Stanford established a horse-breeding ranch called Palo Alto south of San Francisco and developed training methods to maximize horses' potential. He later founded a university on that land and recruited ichthyologist David Starr Jordan as its first president. Jordan applied biological classification to divide humans into superior and inferior groups, advocating forced sterilization for those he deemed inferior. Optimizing horse breeds thus connects to eugenic ideas about "improving" humans.

A Stanford psychologist adapted a French intelligence test originally designed to identify and help children struggling at school into an IQ test. He advocated classifying children early and preventing low-scoring people from reproducing. William Shockley, awarded the Nobel Prize for inventing the transistor, later tried to prove that Black people were genetically less intelligent. Approximately 60,000–70,000 people were forcibly sterilized in the United States, including roughly 20,000 in California.

An interviewee sharply rejects eugenics' central claims:

"The science of eugenics was always nonsense. It never stood up to real scientific scrutiny."

Yet it appealed to the powerful because it let them believe their wealth and influence resulted from innate superiority rather than unjust structures. The language of apparently credible science was used to institutionalize racism and hierarchy and preserve existing power.

The film argues that this logic of classification and ranking also appears in AI. Machine learning and neural networks, AI's foundations, identify patterns, classify objects, and rank them. An interviewee explains that, rather than thinking like a human, AI finds correlations in enormous datasets and selects likely next words or outcomes.

The history of statistical classification includes figures such as Francis Galton and Karl Pearson, who measured skulls and achievement to argue for racial and class hierarchies. They sought to use numbers and categories to support the belief that educated, white British men like themselves were suited to lead the world. "Intelligence" is a common word but difficult to define precisely. Nevertheless, IQ tests were used to quantify it and divide people into higher and lower ranks.

The film therefore warns that even promises to build "smarter AI" can conceal judgments about who defines intelligence and who counts as superior or inferior. Entrenched ranking systems can lead to the belief that some people matter more while others can readily be excluded.

Roy Austin, Meta's first vice president for civil rights, says AI may look like objective machine judgment but is actually built from human decisions. People choose the training data and decide which answers count as good or bad. If marginalized voices are absent, AI learns existing inequalities.

When Amazon tried using machine learning to evaluate employees and support recruitment, a problem emerged: it selected almost no women. Because the tool was built from data about male employees, its standard for future "good employees" used men as the model. Austin explains that tools built around white men effectively tell everyone else:

"You have to become like these white men."

If data represents only some people, results are correspondingly distorted—the familiar "garbage in, garbage out" problem. Hiring AI identifies patterns among previously successful candidates and divides people into accepted and rejected groups. Credit-scoring AI uses repayment histories to set loan limits and interest rates. Welfare systems identify suspected fraud patterns and choose whom to investigate. Social prejudices already in the data can influence these decisions.

Data about children and teenagers may include family and parental backgrounds as well as school results. Algorithms use it to predict academic performance, behavioral trouble, or criminal involvement, and real interventions may follow those predictions. An interviewee calls it dangerous and unfair to deny opportunities based on predicted future behavior.

"Anyone would be furious if someone said, 'I know what you will do in the future, so I won't give you these opportunities in life.'"

3. The "Sacrifices" Behind AI's Convenience

The film moves to a 2026 protest outside Palantir's former headquarters in Palo Alto. Protesters argue that technology enabling authoritarian control is being built in their own community and that technology companies have profited at the community's expense.

Palantir provides software that rapidly connects and analyzes government and corporate data to support decisions. A prominent customer is US Immigration and Customs Enforcement, or ICE, whose aggressive immigration enforcement has repeatedly provoked human- and civil-rights controversy. Citing a reported analysis of court rulings, the documentary says courts found ICE actions illegal, unconstitutional, or violations of basic civil liberties in more than 10,400 cases, with over 90% of relevant rulings going against ICE. Testimony also describes enforcement affecting US citizens, not only immigrants.

Interviewees worry about insufficiently trained armed personnel entering communities and detaining people, and operations continuing despite court orders to stop. They warn such systems of control could push the United States toward a dangerous police state. They also discuss rhetoric about protecting one race and excluding another, people held in large detention facilities, and children spending long periods inside them.

Palantir technology has also entered hospitals. Nurses describe scheduling software assigning six consecutive workdays or causing staff who thought they were off duty to face discipline because the system expected them at work. When human understanding of a schedule differs from the algorithm's, hospitals may become understaffed while nurses bear the blame.

"What if AI were your boss, telling you when to come in, what to do, and even recommending discipline?"

Patient protection is another reason nurses oppose Palantir. They describe ICE agents waiting in hospital waiting rooms to arrest patients after discharge. According to reports discussed in the film, Palantir's ELITE app for ICE combines scattered personal information—addresses, financial records, and social media—into immigrant profiles, marks targets on maps, and scores the likelihood that an address is current. The film also cites reporting that federal Medicaid data was used to identify immigrants who visited hospitals.

Attorney Cindy Cohn, who has fought mass government surveillance for over 30 years, says medical information should be used only for the purpose for which patients provided it. Palantir's strength in connecting information collected for one purpose to uses for another can become dangerous when a powerful government wants to conduct mass enforcement.

"Can an authoritarian government use Palantir's systems to oppress people? The answer is yes."

Palantir also has major defense and military contracts. The film discusses its provision of targeting systems to US and other militaries and an interview referring to a UN report that described Gaza as a corporate technology testing ground. The concern is that technologies from Palantir, Google, and others can be tested there and later reintroduced in the United States and elsewhere.

Protesters demand that technologies aiding military killing and mass surveillance not enter society. Through these examples, the documentary argues that people still stand behind AI—people build and misuse the systems—but it is becoming harder to hold them accountable.

AI needs enormous amounts of data. In the 1980s, US AI researchers believed convincing AI required statistical pattern detection and therefore vast datasets, but data was scarce and not free. Later, online photos, writing, news articles, and posts began to be collected at scale. One interviewee criticizes current systems for taking collective intellectual property for training.

The film says Anthropic agreed to pay $1.5 billion in damages over using copyrighted material for AI training without permission. Writer Arundhati Roy criticized the company, saying she was one of many authors whose books were used without consent. Korean books were no exception: the film cites reporting that, across five purchases since the previous year, 166 metric tons of newly published Korean books were bought for AI training.

It also criticizes descriptions of data as an unowned resource underground. In Atlas of AI, researcher Kate Crawford explains that metaphors of extracting resources from nature have long been used by colonial powers. Such language can hide that data comes from people's lives and labor.

Collecting and labeling data does not happen automatically either. People must label whether an image contains a cat or a dog, or whether a sentence is hate speech. Alexandr Wang, founder of an AI data-labeling company, is introduced as the youngest self-made billionaire at 24, but the documentary also shows that AI's fuel includes repetitive human labor, not just advanced technology. It mentions workers in the Philippines, Kenya, and Venezuela receiving a few cents per task, allegations that even those payments were withheld, and lawsuits by workers psychologically harmed by viewing horrific content.

Minerals for semiconductors and batteries are mined, while data centers consume enormous amounts of electricity and water. Crawford therefore calls AI an extractive industry: it draws data, labor, minerals, and energy from across the globe while concentrating profits among a few.

Silicon Valley may appear to be a place where geniuses gather to build the future, yet some workers there live in cars or hold multiple jobs. A wide gap separates the glamorous image of technological progress from precarious lives. If an Uber driver gets work through an app and is mistakenly suspended, to whom can they appeal? The film describes facial-recognition systems blocking drivers after changes to facial hair or hairstyle cause them to be mistaken for someone else. An app's error can instantly deprive a worker of work.

"For that person, their livelihood is at stake. But the people who decided to introduce the technology are far removed from that reality."

Interviewees also criticize grand promises about AGI and superintelligence. Executives attract investment by promising an extraordinary future, but even if those promises fail, they can retain the money and power already gained. Not everyone is better off, they argue, while the number of Silicon Valley billionaires has risen from single to triple digits.

4. The Final Priests and Power Around Technology

After showing the announcement of the Stargate project, the film identifies Silicon Valley leaders' growing closeness to Donald Trump as a sign of an authoritarian turn in the technology industry. During the first Trump administration, many Silicon Valley figures promised resistance, warning that he might damage democracy. Interviewees argue that by the 2024 election, after Biden-era regulation and antitrust investigations, some corporate leaders had moved closer to authoritarian politics.

They also criticize large companies' domination of their markets and restrictions on competition, including Google's search ecosystem, Amazon's cloud infrastructure, and Apple's mobile-device ecosystem. Monopoly is identified as a central force in Silicon Valley. Palantir cofounder Peter Thiel has said monopoly is a condition of every successful company.

Thiel is portrayed as a key connector among Silicon Valley people and companies. He helped advance JD Vance, supported Donald Trump, was Facebook's first outside investor, and became a major SpaceX investor. He is also known as Sam Altman's mentor and close friend. Reporting by journalist Karen Hao is cited for the claim that Altman learned from Thiel to make monopoly a strategic goal.

AI is now sometimes treated as an asset linked to national security and therefore difficult to regulate. Companies frame their businesses as serving national interests, while governments provide access to state-held data. A Korean example is the Justice Ministry's immigration AI project, described as allowing companies to train systems on a dataset containing facial photographs of 50 million citizens and 120 million foreigners. Access to otherwise unavailable material, and the ability to bypass privacy restrictions, could give companies an opportunity difficult to buy at any price.

When government and corporate interests align in this way, businesses gain easier access to data, and technologies built from it may then classify and filter people. The documentary presents voices calling this combination tech fascism. The point is not that AI creates authoritarianism by itself, but that it can greatly amplify existing authoritarian tendencies: AI layered onto surveillance data divides people into "valuable" and "problematic" groups and enables control based on those labels.

The film warns that Korea is not exempt. It says the Lee Jae-myung government announced plans to nurture a "K-Palantir," modeling itself on the same company the documentary criticizes. It also says that, amid calls not to fall behind in AI, revisions to the Personal Information Protection Act opened a path to using citizens' original personal data for AI development without consent. Pseudonymized data has been available for research since 2020, but companies argue that original data is necessary to improve performance.

Ultimately, this is a question of who owns and controls data and who has decision-making power. Even everyday use of walking and shopping apps accumulates location and spending data valuable to employers, governments, and private businesses. When algorithms set schedules, restrict opportunities to work, and evaluate behavior, people can lose the ability to determine their own lives.

"How much are we prepared to pay for freedom, self-determination, and a sense of control?"

Marietje Schaake, who participated in developing the EU AI Act, stresses that there are always people behind technology. People build machines, decide which experiments to permit, and choose speed over safety. Even if the AI Act is imperfect, accountability mechanisms can challenge the idea that AI is an inevitable phenomenon that simply happens to us.

The film also asks about AI safety, describing a case at Hugging Face in which problems involving the current technology infiltrating other products went unnoticed for weeks. An interviewee asks:

"Are we building something that will improve humanity, or something that will destroy it?"

Citizens should therefore question AI actively rather than accept it as natural and inevitable. The claim that only a few people understand the technology should not justify leaving decisions to that few. AI affects culture, politics, democracy, and human relationships. An interviewee uses an American saying:

"If you're not at the table, you're on the menu."

In the United States, residents complaining of higher electricity bills and water shortages linked to data centers are gathering at city councils, and opposition to construction is growing. The film says that in three months of the previous year, a year's worth of data-center projects were halted by opposition. It also shows graduating students booing a speaker who likened AI's rise to the Industrial Revolution. Young people want jobs, social protections, and the right to choose for themselves, but feel technology optimists and billionaires are taking those rights away.

The film emphasizes that AI critics are not necessarily hostile to technology itself. Interviewees recognize the value of the internet and new technology, but criticize a reality that rewards entrepreneurs willing to say anything for investment more than programmers building for a better world. Rules requiring companies to address misinformation and comply with antitrust obligations are described as attempts to hold big companies accountable, not abolish the internet.

Finally, the documentary poses a more fundamental question about technological progress: what does it mean to be human, and which parts of our humanity will we fight to preserve? The future AI creates is not a fate entrusted to machines. It depends on the choices and responsibilities of the people designing, adopting, and using the technology today.