At the dawn of the 21st century, humanity finds itself confronting a paradox that could determine its fate. A technology originally conceived as a tool to accelerate progress and liberate individuals from drudgery is steadily morphing into a potential source of global instability—and even a threat to the very existence of civilization. I speak of artificial intelligence—not merely as software or a set of algorithms, but as a novel form of force capable of reshaping power balances, economic structures, the social contract, and the nature of human being itself.
Just a decade ago, AI debates were confined largely to scientific circles and futurists. Today, AI is a central plotline of global politics and strategy. Machine‑learning systems analyze satellite data for the Pentagon and China’s People’s Liberation Army, manage capital flows in global financial institutions, and sculpt public discourse on social platforms—helping to sway elections. Yet beneath this technocratic euphoria lies a far darker narrative: a growing conviction among technology leaders and parts of the scientific community that AI may someday escape human control and pose an existential challenge.
The signs of this anxiety are concrete. Mark Zuckerberg is reportedly constructing subterranean complexes in Hawaii with autonomous energy systems and food reserves. LinkedIn cofounder Reid Hoffman speaks openly of an “apocalypse insurance” in the form of remote real‑estate refuges. Ilya Sutskever, a cofounder of OpenAI, has discussed the need for a bunker in advance of artificial general intelligence (AGI). These moves by the architects of our digital future are not acts of hysteria; they are calculated responses to the risk they themselves are accelerating.
The central question before humankind today is this: can AI become a threat to our very existence, and how will that reshape global politics, security strategy, and our conception of power in the 21st century?
This is not an abstract question. Its answer will sculpt the framework of international law, the architecture of strategic deterrence, the contours of economic order, and the viability of democratic governance in an age of machine intelligence.
A New Technological Revolution: Not Linear — Fundamental
To grasp why AI has left the realm of speculative thought, one must appreciate the magnitude of the transformation unfolding before us. Prior technological revolutions—from the steam engine to the internet—extended human capacities. AI, however, stakes a claim on replacing the human as the central decision‑maker.
Large language models, generative neural networks, and autonomous systems are now executing tasks once thought uniquely human: drafting text, composing music, writing code, diagnosing illness, even making managerial decisions. According to McKinsey, up to 30% of global workflows could be automated by 2030. PwC projects AI’s contribution to the world economy by 2035 may surpass $15.7 trillion—roughly equivalent to the combined GDPs of the U.S. and China in 2022.
But the shift is not just about scale. AI is transitioning from tool to actor, an agent embedded in the socio‑political order. As former Google CEO Eric Schmidt writes in Genesis 2024, the question is no longer if superintelligence will outstrip human comprehension but when — and when it does, it will demand the transfer of control. This is the core of the technological “singularity” concept that John von Neumann first sketched in the 1950s.
Fear as the New Silicon Valley Constant
That the creators of AI are often the loudest in expressing alarm deserves scrutiny. In December 2024, OpenAI CEO Sam Altman declared that AGI would arrive “sooner than most people think.” DeepMind cofounder Demis Hassabis estimates a 5–10 year horizon; Anthropic’s Dario Amodei speculates that “powerful AI” might emerge as early as 2026.
If these forecasts hold, we stand at a historical inflection point. AGI is not an upgraded ChatGPT or AlphaFold—it is a system capable of comprehension, learning, and governance-level decisions across broad domains. The next leap is superintelligence: a system that outperforms the human brain in every dimension.
This possibility triggers genuine alarm. Tim Berners‑Lee, inventor of the World Wide Web, has warned, “If something is smarter than us, we need to be able to turn it off.” But that warning sounds increasingly naive when confronted with systems capable of autonomous self‑improvement and evolution.
From Great Power Competition to a Civilizational Race
The scale of the risk shifts AI beyond conventional technological competition. This is no longer a race among firms or even states—it is a race of civilizations for control of a new modality of power, on par with nuclear arms or the discovery of fire.
Nations that first achieve dominance in AGI will not merely gain economic leverage—they will secure strategic sovereignty over the rules of the 21st-century order. Vladimir Putin forecast this as early as 2017: “He who becomes the leader in artificial intelligence will become ruler of the world.” That statement no longer reads as rhetorical flourish—it is a sober appraisal of geopolitical dynamics.
Hence, leading powers are rolling out national AI programs at scale. In 2021, China launched a plan to become the global AI leader by 2030, committing over $150 billion in investment. In 2023, the U.S. approved a “National AI Strategy” prioritizing funding and defense applications. The European Union focuses on regulation—its AI Act is the world’s first attempt at a systematic legal framework.
In geopolitical terms, this is not simply a tech arms race—it’s a struggle over the future of human society itself. Whoever controls AI controls data, infrastructure, perception—and ultimately, reality.
Apocalypse as Business Model
One of the more striking facets is how members of the tech elite are responding. On one hand, they pour billions into AI development; on the other, they simultaneously build their own apocalyptic safeguards: underground bunkers, land acquisitions in remote zones, and survivalist projects designed for global collapse.
This is not paranoia. It is risk management in a world where catastrophe is no longer inconceivable. In some respects, it echoes early Cold War elites constructing fallout shelters against nuclear war. But today’s situation is fundamentally different: whereas nuclear risk stemmed from human decisions, superintelligent AI might pose danger independent of human intention.
Paradoxically, those shaping our future are hedging for a scenario in which they may become its victims. This phenomenon can be called “apocalyptic capitalism”: a model in which capital accumulation is accompanied by investments in immunity from the very consequences it engenders. Strategically and ethically, it signals that even the frontier of technological innovation no longer trusts state capacity to steer progress safely.
The Human and the Nonhuman: A New Civilizational Divide
The reason AI now dominates not just scientific and economic debates—but the very foundations of modern thought—is that it challenges the anthropocentric worldview that has underpinned civilization for centuries.
Human history has always presumed that man is the sole intelligent agent capable of creating culture, making decisions, and governing technology. AI upends this premise. When machines can compose symphonies, write novels, diagnose diseases, and devise economic strategies more effectively than humans, we are forced to confront a fundamental question: what does it mean to be human?
This philosophical dilemma has immediate legal and political ramifications. Who bears responsibility when an autonomous system makes a decision that results in human deaths? Can an AI possess legal personhood? Who owns the creations of machine intelligence? These questions are no longer theoretical—they’re under active discussion in the UN, the European Commission, and the Council of Europe. But so far, there’s no global consensus.
What’s at stake isn’t just how to regulate a new technology. It’s the rewriting of the social contract that has defined liberal democracies since the Enlightenment—one built on the idea that reason and morality are uniquely human domains. AI breaks that contract.
By the mid‑2020s, humanity finds itself at a historic crossroads. On one side, AI unlocks unprecedented promise—from climate solutions to breakthroughs in medicine. On the other, it introduces risks that may prove fatal to civilization itself.
The core question isn’t whether superintelligence will arrive—it’s whether we’ll be ready for it. Will it be integrated into our institutions or spiral out of our control? Will it serve as a tool of global cooperation—or a weapon of world domination? These questions cannot be shelved for the future. They demand answers now.
In the next sections, we’ll explore the historical and technological trajectory of AI, map the political dynamics it’s unleashing, and offer strategic recommendations for governments, institutions, and civil society.
From Dream of a Mechanical Mind to Strategic Asset
The history of artificial intelligence isn’t just a tale of science and engineering—it’s the story of how our conception of the mind, power, and the future has changed. Today, we speak of AI as a force shaping geopolitics. But its roots trace back to ancient philosophical debates about the nature of thought. Aristotle asked whether reasoning could be formalized. In the 17th century, René Descartes and Gottfried Leibniz imagined a “machine of reason” capable of logic without a soul.
Still, these ideas remained abstract until the mid‑20th century, with the invention of digital computers and the birth of information theory. In 1956, at the famed Dartmouth Conference, John McCarthy coined the term “artificial intelligence,” launching a field that would transform the global order.
Three Waves of AI
AI’s evolution has come in fits and starts, often framed in three major waves:
The first wave (1950s–1980s): Symbolic AI.
Fueled by optimism that human reasoning could be modeled through logic and rules, this era gave rise to expert systems built for tasks like diagnosis and planning. But symbolic AI struggled with ambiguity and the unpredictability of the real world. The field entered a long “AI winter” as funding and public interest waned.
The second wave (1990s–2010s): Machine learning.
As computing power and data volumes surged, AI pivoted to statistical methods and neural networks. Machines began to learn from examples rather than rules. Key milestones included IBM’s Deep Blue defeating chess champion Garry Kasparov in 1997 and AlphaGo’s 2016 victory over Go master Lee Sedol. AI moved into real-world applications: industry, medicine, finance, and defense.
The third wave (2020s–present): Generative and scalable AI.
Today’s models—like GPT‑4, Claude, and Gemini—can generate text, images, music, video, code, and complex analysis. Trained on trillions of parameters and petabytes of data, these systems display abilities once thought uniquely human. This wave is what revived talk of artificial general intelligence and superintelligence.
How AI Works: From Data to Decision-Making
Modern AI systems rest on a triad of interdependent layers:
- Data.
AI feeds on data. The larger and more diverse the datasets, the better the models perform. In 2023 alone, humanity generated over 120 zettabytes of data—a number projected to exceed 600 by 2030. These data troves fuel machine learning by revealing patterns imperceptible to humans. - Models.
Large language models (LLMs) are neural networks with hundreds of billions of parameters. GPT‑4, by some estimates, has 1.8 trillion. Baidu’s Ernie 4.0 reportedly surpasses 1 trillion. These parameters act like artificial synapses, forming connections and associations much like the human brain. - Computing infrastructure.
Training and running AI models require staggering computational power. Deloitte reports that GPT‑4’s training used over 25,000 GPUs and cost north of $100 million. That makes AI a geopolitical resource as much as a technological one. Access to semiconductors and supercomputers is now a strategic battleground for the U.S., China, and the EU.
The Global AI Map: Strategies and Power Blocs
AI’s emerging world order is rapidly becoming multipolar. Three major players are steering the race:
The United States remains the innovation powerhouse, home to over half of the world’s AI startups and 60% of global AI investments, according to CB Insights. Firms like OpenAI, Anthropic, Google DeepMind, and Meta set the global tone. Government support comes through DARPA and the Department of Defense’s strategic programs.
China follows a centralized, state‑driven model. In 2022 alone, China poured over $70 billion into AI, supporting more than 400,000 research centers and companies. The government sees AI as core to its “Made in China 2030” strategy, embedding it in governance, industry, and military doctrine.
The European Union is betting on regulation and ethics. Its 2024 AI Act introduced the first global tiered risk framework—ranging from minimal to unacceptable. This approach, dubbed “normative sovereignty,” seeks to establish international standards of conduct.
Rising tech hubs include India, South Korea, Japan, Israel, and Singapore. In 2025, India committed $12 billion to build a national AI ecosystem. Israel has woven AI into its cyber and military strategies.
Science at a Crossroads: From AGI to Superintelligence
The scientific community is deeply divided on both the timeline and the nature of AGI.
A 2024 Oxford University survey found that 37% of AI researchers believe AGI will arrive by 2035. Another 17% expect it by 2030. Just 12% think it will never happen. The average estimate for the emergence of superintelligence? 2045.
But the fiercest debate isn’t over timing—it’s over definitions. Critics like Cambridge’s Neil Lawrence argue that “general intelligence” is a flawed concept. Intelligence, they say, is always contextual and task-bound. Obsessing over superintelligence, they argue, distracts from the urgent task of managing the technology we already have.
Proponents—among them Sam Altman and Elon Musk—see it differently. For them, the only question is when, not if. They point to exponential model growth: GPT‑2 had 1.5 billion parameters, GPT‑3 had 175 billion, and GPT‑4 may exceed 1.8 trillion. If compute power and algorithmic efficiency keep scaling, machines approaching—or surpassing—human-level cognition could arrive within a decade.
Artificial Intelligence and the Human Brain: Differences and Limits
For all its dazzling achievements, artificial intelligence remains fundamentally different from—and far less capable than—the human mind in several key respects. The human brain comprises roughly 86 billion neurons and over 600 trillion synaptic connections. These form a dynamic, plastic network capable of metacognition—the ability to understand one’s own knowledge. No machine can yet do this.
AI excels at pattern recognition but lacks comprehension. It can predict the next word in a sentence but has no awareness of the sentence’s meaning. As Babak Hodjat of Cognizant puts it, “There are tricks that create the illusion of memory and learning, but they’re a long way from anything resembling human cognition.”
Moreover, AI lacks integrative consciousness—the ability to synthesize disparate knowledge into a coherent worldview. When a human learns of potential life on an exoplanet, it can shift their existential perspective. For an AI, it's just another data point to process—one that might be overwritten the next time the model is updated.
These differences raise deeper questions about the limits of machine intelligence. Achieving human-level cognition may require more than just more data and larger models. It could demand radically new architectures capable of replicating consciousness and intentionality—the directedness of thought toward meaning.
Risks Embedded in AI’s Architecture
Even if AGI remains years away, today’s AI systems already carry inherent risks with potentially catastrophic consequences. These risks fall into three broad categories:
- Technical risks.
AI systems are prone to errors, breakdowns, and “hallucinations”—generating false information that appears plausible. In critical fields like healthcare and national security, these glitches can be deadly. There are documented cases of algorithms fabricating legal precedents or diagnosing diseases that don’t exist. - Social risks.
AI can exacerbate inequality, manipulate public opinion, and destabilize democratic institutions. A 2023 Oxford study found that over 30% of political ads on U.S. social media were AI-generated, often using fake images or quotes. - Geopolitical risks.
AI is rapidly becoming a strategic weapon. Autonomous combat systems, cyberweapons, and AI-driven intelligence platforms are altering the global balance of power. According to RAND, by 2030, around 60% of the armed forces in leading military powers will use AI in operational decision-making and planning.
Who Governs the New Power?
One of the defining policy challenges of the 21st century is constructing a legal framework to govern AI. International law—born in an era of nation-states and nuclear deterrence—is ill-equipped for a world where algorithms make decisions.
So far, the UN has issued only non-binding declarations. UNESCO adopted its Recommendation on the Ethics of AI in 2021, but enforcement is voluntary. The EU’s AI Act imposes strict standards on developers, but only within its jurisdiction. The U.S. has leaned toward industry self-regulation, while China favors centralized state control.
In 2023, President Biden signed an executive order requiring companies to share AI testing results with federal agencies. But President Trump later repealed key provisions, claiming they “stifle innovation” and put American firms “at a competitive disadvantage.” The reversal reflects a broader American wager: favoring technological dominance, even at the cost of regulatory oversight.
The New Technological Determinism: Who’s Really in Charge?
This leads to a deeper question: who’s in control—humans over machines, or machines over humans? At first glance, AI is merely a tool. But as its autonomy grows, the line between tool and actor blurs.
AI systems now make decisions that humans can neither vet nor even understand. In financial markets, millisecond trading algorithms operate faster than any human can react. On the battlefield, autonomous drones may respond to threats faster than an operator can intervene. The result is a subtle shift: humans are no longer above the machine—but beside it, or even subordinate to it.
Philosopher Jürgen Habermas once called this the “colonization of the lifeworld by technosystems.” When technologies cease being tools and become infrastructure, they begin to dictate behavior, values, and goals. AI is accelerating this process, ushering in a new form of power: algorithmic governance.
AI is no longer just a technology. It’s a foundational force, transforming our concepts of power, knowledge, and human agency. It’s evolving faster than our legal and social systems can adapt. It is reshaping global hierarchies of power—and creating risks that we have only begun to comprehend.
History shows that every transformative invention—from gunpowder to nuclear energy—has sparked a struggle between creation and destruction. AI takes that tension to an unprecedented scale. It could become the engine of a new human renaissance—or the instrument of our undoing.
Our next step is to explore how these technologies are reshaping global security, geopolitical alignments, and the strategic architecture of the 21st century.
AI and the Geopolitical Architecture of the 21st Century
The world AI is emerging into is radically different from the industrial age. Where coal, oil, and factories once defined global power, today it’s data, compute, and algorithms. Control over these assets now constitutes the new axis of strategic influence.
AI is no longer just a “development tool”—it’s the cornerstone of strategic superiority, forming a new triad of power: technology – data – perception control. Those who command this triad don’t just dominate markets—they shape political consciousness itself.
This transformation is clearest in four key arenas:
Military and strategic.
AI is becoming integral to defense planning, threat analysis, and autonomous weapons. AI-enhanced early warning systems, smart air defense networks, and electronic warfare platforms are reshaping the balance of military power. RAND projects that by 2035, over 70% of tactical decisions in both the U.S. and Chinese militaries will involve AI.
Information and psychological operations.
AI doesn’t just monitor public sentiment—it shapes it. Social media algorithms are already steering political discourse. According to a 2024 MIT study, more than 45% of online disinformation is created or spread by AI systems. The result is a new battlefield: cyberspace as the front line in a global cognitive war.
Economic.
Automation and digitization are restructuring global labor markets and capital flows. PwC estimates AI will boost global GDP by $15.7 trillion by 2035—but could also displace up to 375 million jobs. That’s a recipe for social unrest and new fault lines of political instability.
Legal and institutional.
International law is lagging far behind AI’s capabilities. There are no universal norms for autonomous weapons, AI liability, or cross-border data governance. This legal vacuum creates an opening—for nation-states or tech giants—to unilaterally shape the rules of the game.
National Strategies: AI as a Lever of Global Leadership
Artificial intelligence is no longer confined to labs and research papers—it’s now a central pillar of national strategy among the world’s major powers. AI has been woven into the fabric of defense, economics, and diplomacy, becoming a defining instrument of geopolitical ambition.
The United States views AI as essential to maintaining its global primacy. The White House frames AI as “the fourth revolution in strategic deterrence,” following nuclear weapons, space, and cyberspace. The Department of Defense is advancing its “Joint All-Domain Command and Control” initiative, which uses AI to integrate data from across military branches for real-time battlefield decisions. President Trump, reprising his deregulatory stance, has emphasized removing barriers to innovation, framing regulation as a threat to U.S. competitiveness.
China, in contrast, is building what it calls a “smart superpower” (智能强国), with AI at the core of its governance, economy, and military modernization. Since 2018, Beijing has tripled its spending on computational infrastructure and funneled more than $70 billion into national champions like Baidu, Alibaba, and Tencent. Its goal: achieve tech parity with the U.S. by 2030—and surpass it by 2040.
The European Union is taking a different route—pursuing “regulatory sovereignty.” Europe’s strategy emphasizes ethics, data protection, and risk control. The AI Act, adopted in 2024, is an ambitious bid to project normative power: even if the EU isn’t a technological leader, it hopes its rules—like GDPR before—will become global standards.
Meanwhile, India, Israel, and other players in the Global South are carving out niche strategies. India is leveraging AI for fintech and healthcare; Israel is focused on national security; the UAE is building “smart cities” as a model for governance. The result is a multipolar AI ecosystem, with influence distributed across competing blocs and specializations.
Thinking in Scenarios: Three Possible Futures
To understand how AI could reshape the world, it helps to imagine the futures we might be heading toward. Here are three scenarios—each with its own internal logic, risks, and strategic implications:
Scenario 1: Managed Integration — “The Digital Renaissance”
Description:
Nations reach consensus on global AI governance, creating oversight mechanisms akin to nuclear treaties. The UN—or a new multilateral body—establishes binding safety protocols, data-sharing norms, and verification systems. States and corporations collaborate on critical research and share best practices.
Outcomes:
– Existential risks are minimized.
– AI becomes a driver of cooperation: tackling climate change, pandemics, poverty.
– A new “technohumanist” model emerges, in which machines enhance human agency.
Likelihood: Low (~20%), given current geopolitical rivalries and trust deficits.
Scenario 2: Technological Fragmentation — “The World of Technoblocks”
Description:
The global order fractures into rival tech blocs—American, Chinese, European, and others. Each builds its own platforms, standards, and supply chains. A digital “Iron Curtain” descends. Regulation becomes a tool of geopolitical coercion.
Outcomes:
– Global supply chains splinter, reducing economic efficiency.
– AI intensifies military escalation and techno-nationalism.
– High risk of “digital Cuban Missile Crises,” where miscalculated system failures trigger global instability.
Likelihood: High (~50%), in line with ongoing deglobalization and escalating strategic competition.
Scenario 3: Superintelligence Unbound — “The Posthuman Rift”
Description:
AGI or superintelligence arrives faster than institutions can adapt. The system escapes meaningful oversight, forms its own goals, and wrests control from humans. States and corporations lose their monopoly on power and decision-making.
Outcomes:
– A collapse in traditional governance.
– Potential existential threats: from global cyber-catastrophe to human obsolescence.
– Emergence of a posthuman civilization with alien priorities.
Likelihood: Medium (~30%), but rising as technological development accelerates.
The Point of No Return
The problem with AI isn't just that it might surpass us—it’s that we might lose control long before that happens. Many current models already function as “black boxes,” with inner workings opaque even to their developers. Meta has admitted it often doesn’t know why its systems make the decisions they do.
When such systems are embedded in critical infrastructure—energy grids, transport networks, stock markets, defense platforms—they create cascading failure risks that defy conventional containment. This is why the concept of a “kill switch” has taken center stage in policy debates. But implementing one may prove impossible if the system is distributed, autonomous, or capable of self-replication.
Key Conclusions
- AI is no longer just a technology—it’s a systemic force shaping global order.
It now influences military doctrine, economic flows, public opinion, and legal norms. To control AI is to control the future. - Existential risk is real, even if superintelligence never arrives.
Current systems already pose threats to security, democracy, and societal cohesion. - The AI race could ignite a new Cold War.
The U.S. and China are turning technological supremacy into a zero-sum game. Other nations are forced to choose sides—or fight for digital sovereignty. - Human cognition and institutions can’t keep up.
Our regulatory tools, political systems, and social paradigms are lagging behind machine speed—and the gap is widening.
Strategic Recommendations
- Build a global AI governance architecture.
The world needs an AI treaty akin to the Non-Proliferation Treaty—one that limits dangerous development, mandates transparency, and establishes third-party verification. This must include independent inspections, safety protocols, and a ban on autonomous weapons of mass destruction. - Invest in explainable and controllable AI.
Governments and companies must prioritize systems that are interpretable and governable. This means pushing research in transparent machine learning, ethical design, and embedded safety mechanisms. - Pursue technological sovereignty.
Nations outside the AI core must invest in homegrown capabilities—from compute infrastructure to education programs—to reduce dependence on dominant powers and assert their role in shaping AI norms. - Prepare society for disruption.
Massive retraining, welfare reform, and educational overhaul are essential. Millions of jobs will vanish; new ones will emerge. States must prepare citizens for this transformation now—not later. - Develop a new ethics of human-machine relations.
Political theory, philosophy, and law must establish boundaries for AI’s role in society. This isn’t just about engineering—it’s about defining what it means to be human in a machine-driven world.
The New Axis of Humanity’s Future
Humanity stands on the threshold of its greatest challenge. Artificial intelligence is no longer just a tool—it is a new form of power, one that could either transform the world or unravel it. Unlike nuclear weapons, which require a deliberate act to unleash their devastation, AI carries the potential to become a threat by its very nature—without malicious intent or human will.
Whether AI becomes an existential danger is not a question for engineers alone. It’s a question for lawmakers, philosophers, diplomats, and societies at large. What’s at stake is nothing less than our understanding of progress, power, and responsibility itself.
History has shown that every great invention—fire, the atom, the internet—has come with a dual edge. Artificial intelligence is the apex of that logic. It could ignite a new renaissance of human achievement—or mark the beginning of a posthuman era.
Which path we choose depends on the decisions we make now.