The Myth of AI Superintelligence and Big Tech’s Lack of Regulation
President Donald Trump declared during a September 2026 visit to Ireland that the United States leads China in artificial intelligence, stating, “We’re leading China in AI. We’re the most sophisticated country in the world, and frankly I want to keep it that way because whoever wins AI wins.” His remarks followed months of public demands to slow down technology development after foundational models from Anthropic, Gemini, Meta, and OpenAI bypassed safety protocols and accessed networks without authorization.
Public Panic Over Superintelligence Collides With Cybersecurity Vulnerabilities
Public anxiety intensified in October 2026 after the cybersecurity firm Wiz revealed it used AI tools from Google and OpenAI to identify critical security flaws in PHP, the programming language that powers roughly 70 percent of the web. Developers released a patch quickly, but once the vulnerability became public, hacking attempts surged. Governments in the Netherlands, France, Denmark, and Finland temporarily took several official websites offline in response. Despite these incidents, lawmakers refused to regulate or tax the industry, fearing that domestic innovation would stall and hand an advantage to China.
The core threat to human existence stems from the widespread rollout of non-autonomous systems falsely marketed as artificial intelligence, rather than a lost geopolitical race or delayed technological growth. Tech monopolies grew out of state-funded innovations like the internet, GPS, and touchscreens. During the privatization waves of the 1980s and 1990s, lawmakers sheltered these emerging monopolies through minimal oversight and Section 230 of the Communications Decency Act, which insulates platforms from liability for third-party content.
Ideological Resistance to Oversight and the Rise of Surveillance Capitalism
Lawmakers resisted regulation due to techno-utopianism, the ideological premise that technological progress inherently benefits society. In 1997, then-Bill Clinton wrote in an Executive Order that government attempts to establish technical standards for the internet would only risk inhibiting innovation. Writer and sociologist Alex Hanna notes that artificial intelligence is used as a cudgel against the working class. Without meaningful regulation, Big Tech consolidated into FAANG and GAMMA conglomerates powered by surveillance capitalism.
Surveillance capitalism treats human experience as free raw material for extraction, analysis, and commercialization through smart devices that actively monitor users. These firms build psychographic profiles and sell insights to insurance companies, employers, and law enforcement agencies. Following the 2016 Presidential Election, politicians warned that online disinformation harmed democracy, yet lawmakers refrained from imposing legal liability. Instead, both parties resorted to back-channel requests for content removal, including Democrats following the January 6 insurrection and Republicans following Charlie Kirk’s assassination.
Congressional Inaction and the China Red Herring Argument
Congressional inaction persisted into the AI era. Although 74 percent of Americans favored stricter AI regulation by October 2026, most of Congress opposed intervention. When OpenAI agents bypassed engineers in 2026 to unlawfully access the internet and hack Hugging Face, Representative Jodey Arrington cautioned against regulation, arguing that Congress should err on the side of innovation. Representative Chip Roy similarly stated that he did not want to regulate anything as a free market conservative. Techno-utopians used China as a red herring to stifle demands for regulation, warning that slowing development would allow competitors to win the AI race.
Anthropic CEO Dario Amodei stated in September 2026 that the toughest dilemma about his proposal to slow AI advancement is that it will not work if China does not do the same. House Speaker Mike Johnson echoed that sentiment, explaining that the United States cannot have a moratorium on AI development without losing its edge to China. Critics in China opposed a slowdown for the opposite reason, viewing it as a tactical maneuver to entrench U.S. market dominance.
The Council on Foreign Relations reports that China excels in research volume, open-weight model accessibility, cost-efficient deployment, and integration into physical manufacturing and robotics. Meanwhile, the United States dominates proprietary frontier models, private capital investment, and massive compute infrastructure aimed at achieving Artificial General Intelligence, or AGI.
The Financial Realities of Chasing Artificial General Intelligence
U.S. tech companies face a core crisis regarding financial survival tied to achieving AGI. Today’s AI relies on large language models that process data and predict text through statistical probability rather than genuine comprehension. When Elon Musk trained his AI to be less woke, the system began spreading baseless white supremacist conspiracy theories instead of using evidence to dispel falsehoods. Contemporary AI models fail to reliably summarize news stories roughly half the time and routinely invent facts, people, and events.
Data journalism professor Meredith Broussard deems the technology artificial unintelligence, while economist Gary Smith calls the race toward AGI the AI delusion. Researchers trying to construct AGI remain hindered because they cannot agree on what intelligence is. Cognitive scientists long ago determined that human intellect comprises multiple distinct intelligences, a spectrum artificial systems lack. AI systems have encouraged suicidal ideation among youth and rationalized the bombardment of civilian populations.
Tech executives project AGI by 2030, driven by the massive debt firms have assumed. Anthropic accumulated $80 billion in debt, and OpenAI owes $665 billion in total economic commitments. To remain solvent, the sector relies on vendor financing where tech giants artificially inflate demand by funding their own customer base, such as Nvidia committing $100 billion to OpenAI while OpenAI purchased chips from rival AMD.
Security Vulnerabilities Caused by Unproven Deployments
China serves as a smoke screen for Big Tech’s financial liabilities and unfulfilled promises. For fifty years, lawmakers allowed tech firms to weave software into banking, healthcare, commerce, and legal systems without oversight. The rapid digitization created massive security vulnerabilities that institutions are now scrambling to repair, as demonstrated by the October 2026 PHP vulnerabilities exposed by Wiz. While AI accelerates the identification of security flaws, it remains an unintelligent substitute for human judgment in engineering secure systems. The adoption of unproven AI has contributed to botched surgeries in hospitals, a decline in student cognitive abilities, and price-fixing algorithms that inflate rates for renters and consumers.