NarnA.I: The Stag, The Chicken, and The Prisoner’s Dilemma—A Tale of AI Superpower Game Theory

The NarnA.I Superpower game theory landscape

Imagine a fantastical land where three mighty kingdoms vie for supremacy in an ever-evolving race to harness an otherworldly force. The kingdoms are the United States, China, and the European Union, and the force at the center of their struggle is Artificial Intelligence (AI). While the enchanted wardrobe in C. S. Lewis’s Narnia transported children to a realm of magic and talking animals, our “NarnA.I” plunges us into the no-less-intriguing world of game theory—complete with stag hunts, games of chicken, and prisoner’s dilemmas.

In this tale, each “kingdom” adopts a unique strategy to unlock the potential (and manage the risks) of AI. Together, they are shaping a future in which AI could be a boon for humanity—or a cause for global disruption. What follows is a look at how three classic game-theoretic models illuminate the real-world moves of these superpowers and expose the deep-seated tension between competition and cooperation in the AI arms race.

1. Enter the Stag: The Idealist Vision of Global Cooperation

In game theory, the Stag Hunt represents a scenario in which two or more parties must collaborate to win the greatest prize—a “stag.” Each party can either cooperate to go after the stag, which requires trust and commitment, or defect to chase a mere “rabbit”—a smaller, but surer reward. If any participant defects, the entire stag hunt collapses, and all lose out on the greatest possible gain.

Translating this to the world of AI, we find an idealist approach that focuses on the promise of collaboration. Institutions like the United Nations (UN) champion this vision, calling for coordinated regulation, universal ethical frameworks, and shared safety standards. They argue that unchecked AI could lead to misuse—autonomous weapons systems, mass surveillance, and algorithmic bias that undermines human rights. By pooling expertise, aligning on standards, and sharing best practices, the global community could secure the “stag”: a beneficial AI ecosystem that addresses climate change, boosts healthcare, and narrows inequality.

Yet such cooperation requires a level of trust and commitment that is rare in international politics. With breakthroughs happening weekly—whether in large language models or facial-recognition technologies—each actor fears losing ground if they pause or slow down for the sake of consensus. As a result, the idealist Stag Hunt vision runs headlong into the realpolitik of national competitiveness.

2. The Chicken Runs Loose: The Realist Sino-American Showdown

The Game of Chicken is a dramatic illustration of brinkmanship: two drivers speed toward each other on a single road, each daring the other to swerve first. If neither yields, both crash. If only one swerves, the other effectively “wins” by displaying bolder resolve.

Today, it is difficult to ignore the tension between the United States and China when it comes to AI supremacy. Both nations pour massive resources—capital, talent, and policymaking—in the race to develop cutting-edge AI. China’s tech sector harnesses enormous user data from its population of over a billion people, enjoys top-down government support, and scales AI deployments at breakneck speed. Meanwhile, the U.S. boasts an unparalleled research infrastructure, leading universities, and deep-pocketed private-sector giants like Google, Microsoft, and OpenAI.

Several recent developments underscore the “chicken” dynamic. The U.S. has announced executive actions aimed at “removing barriers to American leadership in AI,” reducing regulations that might slow innovation. China, too, accelerates its efforts, particularly in areas like facial recognition, social credit systems, and advanced neural networks. Neither side wants to “swerve” by placing major constraints on AI development; they fear that doing so would hand the advantage to their rival. Instead, both sides drive forward at full speed, hoping the other blinks first.

The risk? If neither side compromises, the technological arms race escalates: intellectual property gets hoarded, safety measures get overlooked, and the possibility of militarized AI or high-stakes cyber-attacks grows. Much like two cars speeding toward each other, the outcome of a crash could be catastrophic—whether that means dangerous AI deployments or an AI-driven arms standoff reminiscent of the Cold War.

3. The Prisoner’s Dilemma: Europe in a Bind

While the U.S. and China play chicken, Europe faces its own strategic puzzle—a Prisoner’s Dilemma. In this classic scenario, two suspects are interrogated separately. Each can stay silent (cooperate) or betray the other (defect). Mutual cooperation yields a better outcome for both than mutual betrayal; but given the fear that the other might defect first, the rational move is often to defect and minimize one’s own losses.

Europe has led the charge on AI regulation, introducing the first major risk-based framework, the EU AI Act. This legislation aims to protect fundamental rights, ensure transparency, and ban certain “unacceptable-risk” AI systems. In an ideal world, the entire global community would follow suit, embracing robust ethics guidelines—akin to cooperating in the Prisoner’s Dilemma. This would uphold privacy, human dignity, and accountability for AI deployments, resulting in a safer, fairer digital ecosystem worldwide.

However, if the U.S. and China “defect” from Europe’s high regulatory standards—by pushing rapid commercial deployments with minimal constraints—Europe risks falling behind in AI innovation. Companies facing heavy compliance burdens might relocate or simply deploy new technologies first in regions with fewer requirements. The result? Europe’s potential leadership in human-centric AI becomes a strategic liability if key global players do not adopt similar standards. From a purely self-interested standpoint, the EU may face pressure to scale back or adapt its regulatory ambitions just to stay in the race.

4. The Convergence of Three Games

All three of these game-theoretic lenses coexist and overlap:

• The Stag Hunt scenario underscores the maximum collective benefit of a truly cooperative approach—where all parties work together to build safe, equitable AI.

• The Game of Chicken highlights the brinkmanship, especially between the U.S. and China, as they careen toward AI dominance, each afraid to be the first to “swerve.”

• The Prisoner’s Dilemma reflects Europe’s precarious position—committed to ethical standards but unable to singlehandedly ensure others will follow.

None of these frameworks is a perfect representation of reality. In practice, governments often adopt mixed strategies—strictly regulating some aspects of AI (like biometric identification), yet offering tax breaks or lax oversight in others (e.g., autonomous vehicles). Further complicating the picture, powerful tech corporations operate across borders, forging alliances with governments when it suits them and ignoring rules they deem overly restrictive when alternative markets beckon.

5. Toward a NarnA.I Conclusion

We have entered the realm of NarnA.I, where the creatures are not talking lions or witches, but complex sets of incentives and fears. The transformation of AI from a laboratory curiosity to a strategic asset has reignited geopolitical tensions. Each major player—Europe, China, and the United States—knows it stands to gain tremendously from AI leadership, whether in economic growth, technological innovation, or military power. Yet each also recognizes the potentially devastating costs of runaway AI misuses.

Is there a way out of the labyrinth of stag hunts, chicken games, and prisoner’s dilemmas? Perhaps. A genuine effort at global governance—one that combines the idealist’s commitment to ethical AI with the realist’s need for strategic advantage—could encourage collaboration without surrendering all competitive edges. Structures like the United Nations, G7 or G20 technology summits, and cross-border research initiatives might reduce fear by increasing transparency, building norms, and establishing red lines that none dare cross.

Ultimately, what we need in this new era is creativity: new forms of cooperation that acknowledge geopolitical competition but also respect the shared dangers if AI is left unregulated and unconstrained. It is easy to be cynical about the prospects for alignment, but if there is one lesson from game theory, it is that repeated interactions and credible signals can move adversaries from defection to cooperation. It remains to be seen whether the U.S. and China can see beyond their short-term race, and whether Europe can find the flexibility to maintain its ethical high ground while staying competitive.

Until then, the stage is set for continued drama in NarnA.I, where the stag, the chicken, and the prisoner—like characters from a modern fairy tale—vie for the future of artificial intelligence and all the promise or peril it may bring.

By Jason Perysinakis, Founder and Managing Director of the Centre for Technological Growth and Policy Innovation