Game Theory: Human history viewed as “games” between competing groups

Introduction: Zero-Sum and Non-Zero-Sum Games in History

Game-Theoretic Lens: Human history can be viewed as a series of strategic “games” between groups, where outcomes are shaped by whether actors see the world as zero-sum (one side’s gain is another’s loss) or non-zero-sum (cooperation can produce mutual gains). In a zero-sum game, resources or power are assumed fixed – any advantage for one group means an equivalent loss for others. In a non-zero-sum (positive-sum) game, it’s possible for all sides to benefit, expanding the “pie” through collaboration, trade, or innovation. This framing helps explain why some eras were dominated by intense competition and conflict, while others saw cooperation and shared prosperity. Below, we analyze key historical developments – from empires to the Cold War to globalization – as strategic games, highlighting how zero-sum thinking often fueled war and inequality, whereas non-zero-sum models enabled cooperation, trade, and collective progress.

Zero-Sum Dynamics: When leaders and nations adopt a zero-sum mindset, they treat power and wealth as scarce and winnable only at others’ expense. Historically this mindset drove imperial conquest, colonial exploitation, arms races, and trade wars. For example, mercantilist economists explicitly viewed international trade as a zero-sum contest; they taught that one nation’s gain in wealth must come at a rival’s equal loss (Mercantilism - Wikipedia). This led to policies and conflicts aimed at maximizing one’s own gold, colonies, or markets while denying them to others.
Non-Zero-Sum Dynamics: In contrast, periods of peace and integration often emerged from recognizing common interests. Trade based on comparative advantage, diplomatic alliances, and institutions for collective security reflect non-zero-sum thinking – the idea that cooperation can yield win-win outcomes. For instance, after 1945 the U.S. and allies pursued a liberal international economic order on the premise that open trade and interdependence would benefit all and reduce conflict, a sharp break from the beggar-thy-neighbor policies of the 1930s (TRADE IN A ZERO SUM GRAND STRATEGY - War Room - U.S. Army War College). Indeed, unlike mercantilism (which “inevitably led to conflict”), the post-WWII view was that a rules-based trading system would foster greater cooperation and prosperity for everyone (TRADE IN A ZERO SUM GRAND STRATEGY - War Room - U.S. Army War College).

By examining major historical episodes through this game-theoretic lens, we can see how the oscillation between zero-sum competition and non-zero-sum collaboration has shaped human civilization.

Empire and Conquest: The Zero-Sum Imperative

Formation of Empires: The rise and expansion of empires were often driven by zero-sum logic. Rulers saw land, tribute, and glory as finite resources to seize before rivals did. The success of one empire almost always came via the subjugation and loss of independence of others. History shows that empires with superior military technology (steel weapons, firearms) would conquer those with less advanced arms, asserting dominance through war ( Power Politics and Scarcity in the Modern Age: A Zero Sum Game ). This was a classic zero-sum scenario: one society’s gain in territory and plunder was a direct loss for the defeated. As one analysis put it, human societies have often “capitalize[d] on advantages to maximize their interests, through war … at the expense of the weak” ( Power Politics and Scarcity in the Modern Age: A Zero Sum Game ). In imperial expansion, there was typically no notion of a “win-win” with the conquered – it was win-lose, enforced by violence.

Colonization and the Scramble for Resources: The colonial era (16th–20th centuries) provides stark examples of zero-sum competition between great powers. European colonial powers carved up the Americas, Asia, and Africa in a race to claim territories and resources. Each colonial gain for one empire meant the exclusion of others – the world was literally partitioned. During the Scramble for Africa (1880s–1890s), for instance, European nations believed that territorial expansion was the only way to guarantee global power, creating what “resembled a zero-sum game” played out on African soil (The Ottoman Scramble for Africa: Introduction | Stanford University Press). The logic was that if Britain did not grab a region, France or Germany would – any one country’s increase in colonial holdings inherently reduced the opportunities left for its rivals. This mentality drove frenzied competition and led to the Berlin Conference (1884–85) to formalize who got what. As a historian noted, the new imperialism assumed a zero-sum contest: one empire’s pursuit of colonies could only come at the expense of another’s ambitions (How Imperialism Set the Stage for World War I | HISTORY).

Colonial Mindset: Not only was competition between empires zero-sum, but the colonial relationship itself was exploitative: colonizers enriched themselves by expropriating land, labor, and wealth from indigenous peoples. Colonized populations were treated as losers in the game – sources of profit, not partners. Activists and thinkers have since pointed out that “zero-sum thinking [was] a key marker of the colonial mindset itself”, rooted in domination and exclusion (Democracy Was a Decolonial Project - Boston Review). Decolonization in the 20th century was, in part, an effort to escape this zero-sum framework and envision a more inclusive, mutually beneficial order. (For example, post-colonial leaders sought cooperative development or nonaligned movements rather than simply inverting the oppression.) Nonetheless, the legacy of colonial zero-sum games has been long-lasting: it established patterns of inequality and mistrust that echo in global relations today.

Mercantilism – Economics as Zero-Sum: During the empire-building era, mercantilism became the dominant economic theory among European powers. Mercantilists explicitly saw wealth and trade in zero-sum terms: global wealth was like a fixed treasure to be grabbed. Each nation sought to maximize its gold and exports and minimize imports, assuming any benefit to a trading partner would diminish its own prosperity (Mercantilism - Wikipedia). This led to protectionism, trade monopolies, and even wars (e.g. the Anglo-Dutch wars, fought over trade routes and colonies). Adam Smith famously critiqued this mindset, but it was pervasive until the 18th century: “Mercantilists viewed the economic system as a zero-sum game, in which any gain by one party required a loss by another.”. In practice, mercantilist rivalry fueled military conflict – for example, colonial contests between France and Britain – because economic and geopolitical supremacy were entangled. Only later did economists prove that trade can be positive-sum (both sides can gain via comparative advantage), paving the way for freer trade philosophies. But until that insight took hold, mercantilism entrenched a win-lose attitude among states.

World Wars: Total Conflict in a Zero-Sum World

By the early 20th century, zero-sum thinking among great powers had reached a lethal zenith in the form of two World Wars. These wars can be seen as the catastrophic outcome of nations treating power as an all-or-nothing game.

World War I (1914–1918): WWI was ignited by imperial rivalries and alliance commitments that presumed a zero-sum contest for supremacy. Leading up to 1914, European powers formed opposing blocs and armed themselves, convinced that if they did not check their rivals, they would be dominated. As one historian notes, France and Germany “were conditioned to think of each other as competitors … and to think of the world as [a] zero-sum game in which the French pursuit of empire could only come at the expense of the German pursuit of empire.” (How Imperialism Set the Stage for World War I | HISTORY) Each saw the other’s gains – such as colonizing Morocco – as a direct threat to itself. Britain likewise felt it must maintain naval supremacy at all costs; even a distant challenge from Germany was intolerable. This mentality formed a powder keg: when a regional crisis (the assassination at Sarajevo) occurred, the great powers, seeing the situation in win-lose terms, were quick to resort to force. The war itself was fought as a zero-sum slugfest – victory meant utterly defeating the enemy coalition and seizing its colonies or territory. Indeed, the outcome of WWI did see the losers (Germany, Austro-Hungarian Empire, Ottoman Empire) stripped of land and assets to the benefit of the victors. Hints of non-zero-sum thinking (like proposals for mediated peace) found little traction during the conflict, which was largely viewed by leaders as an existential winner-take-all struggle.
World War II (1939–1945): WWII, even more than WWI, exemplified total zero-sum conflict. The fascist powers explicitly framed their expansionist aims as requiring the subjugation or elimination of other peoples. Hitler’s ideology of Lebensraum (“living space”) held that Germany’s prosperity and survival depended on seizing land from others in Eastern Europe – a stark zero-sum worldview where one nation’s growth necessitated another’s destruction (Lebensraum - Wikipedia). From the very start, Nazi leadership cast the war as a binary outcome: “total victory or absolute defeat” (The Malmedy Massacre | The National WWII Museum | New Orleans) – no compromise was acceptable. As Germany began losing, Hitler doubled down on this view, demanding fanatical resistance and scorched-earth tactics, essentially preferring mutual ruin over conceding anything. By late 1944, the war had truly become “a zero-sum game for Germany” – the only options were winning against the Allies or national annihilation. Japan’s militarist expansion similarly was driven by a zero-sum quest for resources (oil, colonies) and honor, which they pursued until catastrophic defeat. The Allied nations, for their part, also treated the war as a fight to utterly defeat evil regimes – a moral zero-sum framing that justified unconditional surrender terms. In short, WWII’s unprecedented violence (50–80 million dead) underscores how destructive a zero-sum game can become, especially when combined with ideologies that deny the very humanity of the “other.” Even though the Allied coalition cooperated internally (a non-zero-sum alliance wherein the US, UK, USSR, etc. coordinated strategy for mutual survival), their coordination served the larger zero-sum goal of enemy destruction.

The devastating world wars taught a hard lesson: viewing global affairs purely as zero-sum contests leads to negative-sum outcomes – everyone loses in terms of lives and resources. This realization set the stage for a post-war shift toward institutions and norms to avoid such total conflict in the future.

The Cold War: High-Stakes Zero-Sum Standoff (and Cooperation on the Margin)

After WWII, the geopolitical arena transformed into the Cold War (circa 1947–1991) – a decades-long “game” between two superpowers (and their blocs). The Cold War is often described as a classic example of a zero-sum game: the United States and the Soviet Union each perceived any gain by the other as a loss to themselves (The Cold War as Cooperation: A Soviet Perspective | SpringerLink). This zero-sum mentality was ideological (capitalism vs communism), military, and political. However, the presence of nuclear weapons also forced a recognition that some outcomes would be disastrous for both sides, which paradoxically led to elements of cooperation and restraint within the rivalry.

Zero-Sum Mindset: In the early Cold War, both superpowers pursued containment or expansion policies that treated influence as zero-sum. If one country fell into the U.S. camp, that was a setback for Moscow, and vice versa. Conflicts were fought by proxy in the Third World (Korea, Vietnam, Afghanistan, etc.) largely under a zero-sum paradigm – each superpower tried to “win” influence while ensuring the other “lost” ground. Washington and Moscow amassed nuclear arsenals and engaged in an arms race, each striving for superiority or at least parity. In game-theoretic terms, this arms buildup resembled a Prisoner’s Dilemma: both sides would prefer to limit the costly arms race, but neither trusted the other enough to unilaterally stop, so both kept arming (the dominant strategy), resulting in massive expenditures that left the world in peril ( Game Theory Applied to Arms Races : Networks Course blog for INFO 2040/CS 2850/Econ 2040/SOC 2090). The overarching mentality remained hostile: even peaceful overtures were often viewed with suspicion as potential tricks. As one scholar noted, for a long period any cooperative moves in the Cold War were dismissed as anomalies, because the “strong conviction” was that this was a zero-sum struggle where one side’s gain was inevitably the other’s loss (The Cold War as Cooperation: A Soviet Perspective | SpringerLink).
Mutually Assured Destruction (MAD) – A Constraint: The advent of thermonuclear weapons imposed a kind of negative-sum logic on the Cold War – if a direct war erupted, both sides (and indeed the entire world) would lose catastrophically. This grim fact introduced an unusual equilibrium: neither side could “win” a nuclear war, so direct conflict was deterred. In game terms, nuclear brinkmanship was often modeled as Chicken (who will blink first to avoid mutual destruction) rather than prisoner’s dilemma. The result was an unstable but sustained balance. Both powers still behaved zero-sum in political contests, but tacitly cooperated in avoiding direct war. Over time, this led to explicit cooperative agreements such as arms control treaties (e.g. the ABM Treaty, SALT agreements) – limited instances where both recognized a shared interest in reducing the risk of annihilation. These treaties and certain diplomatic settlements (like the Cuban Missile Crisis resolution) were non-zero-sum outcomes within the broader zero-sum rivalry, illustrating that even bitter adversaries can find win-win steps when facing a larger common danger.
Cooperation Amid Conflict: Remarkably, even at the Cold War’s height, there were pockets of cooperation. For example, the U.S. and USSR worked together on eradicating smallpox globally, and later cooperated in space (the 1975 Apollo-Soyuz joint mission) – endeavors that benefited all humanity. Such efforts were exceptions that proved the rule: they required leaders to step out of the prevailing zero-sum mindset. For the most part, however, the Cold War remained a tense strategic deadlock. Each side’s drive to not “lose” led to proxy wars and massive arms spending that drained resources from domestic needs – arguably a lose-lose in economic terms. Indeed, by the 1980s the Soviet Union’s attempt to keep up in the zero-sum arms race contributed to its economic collapse. In sum, the Cold War shows how a zero-sum framing (global chess match for dominance) can persist for decades, but also how rational actors might cooperate to avoid worst-case outcomes. The eventual end of the Cold War – largely peacefully – could be seen as a positive-sum development (both sides and the world benefited from reduced tension), enabled by reformist thinking in the USSR and savvy diplomacy.

Globalization and Neoliberal Order: Positive-Sum Promise, Zero-Sum Pitfalls

With the Cold War over, the late 20th century ushered in an era of neoliberal globalization – a worldwide expansion of trade, finance, and governance structures (IMF, World Bank, WTO) aimed at integrating economies. This era was underpinned by the idea that global interaction is not a zero-sum game but a positive-sum engine of shared prosperity. Indeed, much of the post-1990s rhetoric held that all nations could “win” through free markets, openness, and comparative advantage. To a large extent, globalization did yield broad gains (global GDP surged, hundreds of millions lifted from extreme poverty in Asia, etc.). But it also produced new inequalities and frictions that have revived zero-sum thinking in recent years.

Positive-Sum Foundations: After WWII, and especially after 1990, world leaders embraced non-zero-sum frameworks for economics and security. Institutions like the United Nations, General Agreement on Tariffs and Trade (GATT)/WTO, and the European Union were built on cooperation, with the premise that interdependence would create win-win outcomes. For example, the U.S.-led order reduced tariffs and promoted development aid, believing (correctly, for a time) that this would make everyone richer and more stable. One historian notes that post–World War II, the U.S. explicitly abandoned the zero-sum protectionism of the 1930s and instead championed international institutions and interdependence to “increase the prosperity and stability of the entire world” (TRADE IN A ZERO SUM GRAND STRATEGY - War Room - U.S. Army War College). In essence, the policy shifted from a competitive game to a collaborative one. This bore fruit: global trade became largely a positive-sum game where countries traded goods and each side gained (cheaper products for one, export markets for the other). The “pie” of wealth grew rapidly on a global scale from 1950–2008. Even former adversaries found mutual benefit – e.g. the U.S. helped rebuild Japan and Germany (Marshall Plan), integrating them as allies; this generosity was repaid by those countries becoming economic powerhouses and partners, not threats.

Neoliberal Globalization: In the 1980s–2000s, deregulation and technological advances supercharged globalization. Capital, companies, and ideas flowed across borders faster than ever. This was touted as a “win-win” for all nations. Many developing countries did benefit by industrializing and exporting (e.g. “Asian Tigers,” then China). However, the gains were not evenly distributed. Within countries, inequality often widened – those with skills or capital thrived, while many workers lost jobs to offshoring or automation. Between countries, some felt left behind (parts of Africa, Latin America). As dislocations became apparent, zero-sum narratives resurfaced: people began to argue that globalization was helping certain elites or nations at the expense of others. For instance, in the 2010s, rhetoric of trade as a zero-sum competition re-emerged in Western politics (e.g. claims that China’s export success is America’s loss, etc.). Populist movements blamed global trade for local decline, essentially rejecting the earlier win-win story. Economists largely maintain that trade is positive-sum overall (both sides can gain efficiency), not a zero-sum “us vs. them” scenario (Globalization enabled nearly all countries to grow richer in recent ...). Yet the perception of “winners and losers” from globalization has grown. In reality, both perspectives hold some truth: globalization increased the total pie (positive-sum), but its rules and power imbalances meant many outcomes felt zero-sum. For example, multinational corporations often captured outsized benefits, while poorer communities saw few gains – a dynamic that “accentuated economic inequality” and left some seeing the process as a rigged zero-sum game ([PDF] Globalisation: zero sum game and positive sum game).

Cooperation Under Strain: The late 20th century also saw the creation of global cooperative regimes (arms control, environmental agreements, etc.), extending the idea of non-zero-sum beyond economics. However, as global economic stress and geopolitical shifts occurred in the 21st century, even these cooperative ideals came under strain. The current geopolitical tensions (discussed next) reflect in part a backlash against aspects of neoliberal globalization. Some nations have turned back toward protectionism and great-power rivalry, framing international relations once again as a zero-sum contest (often termed “great power competition”). This raises the risk of undoing the positive-sum achievements of recent decades. A telling indicator is the trend toward “deglobalization” – trade wars, tariffs, and fragmentation which, according to a WTO analysis, reflects a return to zero-sum economic thinking (each country fending for itself) ([PDF] World Trade Report 2023: Re-globalization for a secure, inclusive ...). Still, globalization has not collapsed; interdependence is deep, and many leaders recognize that issues like climate change or pandemics demand more cooperation, not less. The question is whether the world can shore up a non-zero-sum approach in time to tackle these collective challenges.

The Current Global Game: Inequality, Crises, and Coordination Failures

At present, humanity faces intertwined crises – stark economic inequality, ecological breakdown, and systemic instabilities (financial volatility, pandemics, geopolitical conflicts). These can be understood via game-theoretic mechanisms such as coordination failures, the tragedy of the commons, and iterated dilemmas. In many cases, short-term self-interest and zero-sum competition are undermining the collective long-term interest, leaving us “stuck” in suboptimal equilibria. (File:DARK CLOUDS OF FACTORY SMOKE OBSCURE CLARK AVENUE BRIDGE - NARA - 550179.jpg - Wikimedia Commons)

Industrial pollution is a classic tragedy of the commons. Each polluter gains profit by dumping waste, but society collectively pays the cost in health and environmental damage.

Pictured: smog from factories obscuring a bridge in Cleveland, 1973.

Global Inequality: Winners, Losers, and Zero-Sum Perceptions

Global wealth has reached record highs, but it is very unevenly distributed. A small elite has captured enormous gains while billions remain in poverty or precarity. This outcome resembles a zero-sum distribution, even if the economy as a whole grew. Recent reports show that the gap between rich and poor is widening: “60% of people in the world have grown poorer – equating to almost 5 billion people” in recent years (Oxfam: 8 ways to bridge the global inequality gap | World Economic Forum), even as global billionaire wealth soars. Such statistics make many feel that the system is rigged – the gains of growth are flowing to the top at the expense of the rest. In game terms, extreme inequality can result from a competitive “game” where certain players (corporations, wealthy individuals) have strategies or advantages that allow them to accumulate wealth faster than others, eventually dominating resources. Once wealth is highly concentrated, it can turn into a zero-sum struggle for power: the rich may use their position to entrench their gains (through lobbying, monopolies, data control), while the poor have diminishing opportunities. This dynamic has led some scholars to describe modern capitalism – especially in its surveillance capitalism form – as producing a zero-sum clash between corporate power and democracy. For example, Shoshana Zuboff argues that Big Tech’s “antidemocratic economic imperatives produce a zero-sum dynamic in which the deepening order of surveillance capitalism propagates democratic disorder” (Surveillance Capitalism or Democracy? The Death Match of Institutional Orders and the Politics of Knowledge in Our Information Civilization by Shoshana Zuboff :: SSRN). In other words, as tech giants extract personal data and wealth, societal stability and equality suffer – one side’s gain is the other’s loss.

From a broader perspective, high inequality is problematic because it erodes social cohesion and cooperation. When large segments of society feel left behind, they may reject proposals for collective action (suspecting they’ll bear costs while elites benefit). This coordination failure is evident in, say, tax cooperation: wealthy actors move assets offshore (defecting from the shared system), forcing nations into a zero-sum competition for tax base, which undercuts funding for public goods. Trust is a key ingredient for any positive-sum solution; inequality undermines trust, as people believe the “game” is unfair. Thus, perceived zero-sum competition between social classes can lead to polarization and instability (e.g. populist vs establishment conflict, or even scapegoating of migrants and minorities as if one group’s progress hurts another). Overcoming this requires restructuring incentives so that broad-based prosperity (a rising tide lifting all boats) is achieved – essentially reframing the game to be non-zero-sum domestically and globally.

Ecological Crises and the Tragedy of the Commons

Perhaps the clearest example of a deadly game-theoretic trap today is the ecological crisis, especially climate change. Climate change can be modeled as a Tragedy of the Commons, a situation where individually rational actions lead to collective ruin. Each country (or company) has an incentive to emit greenhouse gases to grow its economy, but the atmospheric “commons” has limited capacity to absorb those gases. If everyone over-pollutes, the planet (shared commons) is destabilized – a negative outcome for all. The dilemma is that mitigating climate change requires cooperation: all major emitters must restrain themselves, which is costly in the short run. However, any actor that restrains unilaterally fears being at a competitive disadvantage (a classic coordination problem). As NPR succinctly explained, “the countries that produce the most greenhouse gas all need to take action to fix the problem. That raises a classic economic dilemma called the tragedy of the commons.” (Climate Change Is Victim Of 'Tragedy Of The Commons' : NPR).

In game terms, the climate crisis is often seen as an N-player prisoner’s dilemma or commons dilemma: the “defection” choice (emit carbon freely) yields immediate benefits to each player, whereas the “cooperation” choice (cut emissions) only yields benefit if most players do it. The risk is free-riding – each hopes others will sacrifice to reduce emissions while they themselves continue business-as-usual. The outcome of decades of climate negotiations reflects this trap: despite international agreements, emissions continue to rise because promises are weakly enforced and mistrust abounds. Coordination failures plague the process – e.g. disagreements between developed and developing nations over who should cut more or pay for damages.

Similar commons tragedies play out with deforestation, overfishing, and biodiversity loss. For instance, overfishing occurs because each fisherman thinks catching as much as possible is individually optimal, but if all do so, fish stocks collapse. Everyone would be better off with restraint, but enforcing that requires collective agreements and trust. These scenarios show how zero-sum assumptions (or short-term self-interest) lead to negative-sum outcomes. The challenge is establishing mechanisms to enforce cooperation – essentially turning the game into an iterated one where reputation and long-term incentives convince players to cooperate. Some successes exist (the ozone layer was protected by the Montreal Protocol, an example of solving a commons problem), which gives hope that climate change could still be managed if enough transparency and trust can be built.

Systemic Instability: Iterated Dilemmas and Short-Termism

Our global systems – financial markets, supply chains, even public health – have become highly interconnected and complex. This yields great efficiency (a positive-sum aspect), but also vulnerability to systemic shocks. Many instabilities can be traced to strategic misalignment or iterated prisoner’s dilemmas among key actors:

Financial Crises: The 2008 global financial crisis is an example of individually rational decisions (banks taking on risky loans, investors chasing short-term gains) leading to a collective disaster – essentially a coordination failure in the banking “game.” Banks assumed someone else would bear the risk (or that they could bail out before a crash), analogous to prisoners in a dilemma betraying each other for immediate reward. The result was a meltdown that hurt all, arguably a negative-sum outcome. Moreover, wealth inequality can itself increase systemic financial fragility, creating a scenario where the incentives of rich vs poor in the financial system diverge and coordination (like equitable regulation) fails (Wealth inequality, systemic financial fragility and government ...). Governments often step in as “coordinators” after the fact (bailouts, stimulus) to reset the game.
Pandemics: The COVID-19 pandemic revealed a mix of cooperation and zero-sum behavior. Initially, countries shared data and scientists collaborated (non-zero-sum response to a common threat). But when vaccines arrived, “vaccine nationalism” set in – some nations hoarded doses, viewing health as a zero-sum scramble. This left many poorer regions unvaccinated longer, which prolonged the pandemic for everyone (as new variants emerged). Thus, short-sighted competitive strategies undermined what could have been a faster, more cooperative victory against the virus. A coordinated global vaccination campaign would have been positive-sum (faster end to pandemic and recovery), but it faltered due to lack of trust and solidarity.
Great Power Tensions: We are seeing a resurgence of great-power zero-sum thinking (e.g. U.S. vs China rivalry, Russia vs NATO conflict). This is injecting instability into the international system, as cooperation on issues like trade and climate is hampered by strategic distrust. As one policy analysis observed, “the zero-sum great power competition is eclipsing efforts to meet global challenges.” (Great Powers Have Lost the Plot: The Perils of a Split-Screen World • Stimson Center) Resources are diverted to arms races and geopolitical posturing, while planetary threats (climate change, pandemics) go unaddressed – a folly that could lead to mutual ruin. In effect, we risk repeating the mistakes of the Cold War era but in a more multipolar, complex context. Modern great-power competition is often framed as a multi-player game with both zero-sum and potential positive-sum elements. Some analysts argue it need not be purely zero-sum, and that powers could find areas to cooperate even while competing (a concept of “coopetition”). But such nuance is lost if a Cold War mentality fully takes hold.

Coordination Mechanisms (or Lack Thereof): At the heart of current instability is the difficulty of achieving global governance or binding agreements. Whether it’s climate action, regulating financial markets, or controlling pandemics, nations face an iterated game: they will interact repeatedly over time, which in theory encourages cooperation (to preserve reputation and long-term benefits). However, if the iteration span is uncertain or trust is very low, even repeated games can result in defection (this is sometimes called a “grim trigger” equilibrium – once someone defects, everyone stops cooperating thereafter). The climate saga, for instance, has seen cycles of hope and disappointment that erode trust. Each failure makes the next cooperation attempt harder.

In summary, our current predicament can be seen as humanity failing to effectively transition from zero-sum to non-zero-sum models on a global scale. We have unprecedented interdependence (meaning in reality our fates are shared), but our institutions and mindsets lag behind, often defaulting to competitive or short-term behavior. The result is a series of collective action problems: problems that require a cooperative strategy to solve, yet we remain stuck in competitive equilibria. Breaking out will require changing incentive structures and building enforcement frameworks such that doing the cooperative, long-term right thing is also in each actor’s immediate self-interest. This is where advanced technology – especially AI – could play a transformative role, for better or worse.

The Future: Will AI Intensify the Zero-Sum Game or Foster a Non-Zero-Sum Breakthrough?

Artificial Intelligence is poised to become a game-changer in global dynamics. It can be thought of as a powerful new “player” (or at least a tool wielded by players) that could shift the payoffs and strategies available in human society’s game. The question is: Will AI be a force multiplier for zero-sum competition (dystopian trajectory), or can it help unlock new cooperative equilibria (utopian trajectory)? In exploring this, we consider how AI might alter incentive structures, enable better coordination or surveillance, and influence global governance. The future is not predetermined – it likely depends on choices we make now in shaping AI’s development and use.

Dystopian Trajectory: AI and Amplified Zero-Sum Competition

In a dystopian scenario, AI becomes a tool that entrenches and exacerbates zero-sum dynamics – essentially turbocharging competitive and predatory strategies:

AI Arms Race: Already, nations and tech corporations are engaged in an “AI race” to achieve superiority in algorithms, military AI, and economic AI deployment. If viewed through a narrow nationalistic lens, this race is framed as zero-sum: only one can win, and falling behind means being dominated. There is concern that U.S.-China competition in AI is taking on a Cold War style zero-sum mentality (There can be no winners in a US-China AI arms race : r/Futurology). For example, policies to restrict chip exports and build exclusive AI alliances suggest each side is trying to deny advantages to the other. A pundit noted that “the AI competition is increasingly being framed within narrow national security terms, as a zero-sum game”. Such a framing could lead to dangerous outcomes: like the nuclear arms race, an AI arms race could result in over-investment in lethal autonomous weapons or destabilizing systems. If each side rushes deployment without coordination, the risk of accidents or uncontrolled escalation grows – a negative-sum outcome (no one truly wins if AI weapons proliferate wildly). Additionally, treating AI development as zero-sum might discourage the open sharing of safety research, making catastrophic AI failures more likely. In short, an uncoordinated AI arms race is essentially a multi-player prisoner’s dilemma: all would be safer by agreeing to some limits, but distrust pushes them to race, raising collective risk.
Surveillance Capitalism 2.0: In the private sector, AI could supercharge surveillance capitalism, where a few companies harvest the world’s data for profit. This raises the stakes of zero-sum competition in economics: data-rich firms (often monopolies) gain immense power over markets and consumers, squeezing out competitors and exploiting users. AI algorithms could manipulate human behavior (for advertising or political influence), creating a power imbalance where the “winner” (Big Tech or authoritarian governments) reaps all benefits while citizens’ privacy and agency are lost. This is essentially a zero-sum extraction game: human experience is mined as raw material for AI models, with little return to the people providing the data. Already we see how a handful of firms dominate AI research and reap most rewards, contributing to inequality. Without intervention, AI might widen the gap – e.g. automating jobs and concentrating wealth in the owners of AI capital. The result could be a “digital oligarchy” that treats society instrumentally. As mentioned, Zuboff warns that this trajectory pits democratic values against surveillance imperatives in a zero-sum “death match” (Surveillance Capitalism or Democracy? The Death Match of Institutional Orders and the Politics of Knowledge in Our Information Civilization by Shoshana Zuboff :: SSRN). If AI is used mainly to surveil, predict, and control for profit or power, it could entrench an Orwellian world of “surveillance capitalism wrapped around us”, where those at the top win and individual freedoms lose.
Authoritarian and Military Uses: AI offers potent tools for those inclined toward zero-sum domination – from autonomous weapons to AI-driven propaganda and mass surveillance of populations. A dystopian outlook imagines AI deployed by authoritarian regimes to cement their control (facial recognition to quash dissent, predictive policing, censorship algorithms). This would tilt internal political games towards a permanent win for the regime (citizens effectively always lose, as their ability to coordinate resistance is nullified by omnipresent surveillance). Internationally, military AIs (swarms of drones, cyber weapons guided by AI) could make conflicts faster and potentially more decisive – tempting actors to resolve disputes by force. If, say, an AI gives one state a fleeting strategic advantage, it may launch a zero-sum gambit to capture disputed territory before rivals catch up. The speed and opacity of AI systems also raise the risk of miscalculation – imagine two nations’ AI defense systems misinterpreting moves and initiating war (the “flash war” scenario). In a zero-sum strategic culture, fail-safe and cooperative safeguards might be neglected, increasing systemic instability.

Overall, the dystopian path is one where AI fits neatly into old patterns of competition – but with magnified consequences. It could accelerate arms races, enable more efficient exploitation of people and resources, and empower those with zero-sum ambitions (whether states or corporations) to push further. The result could be a world with even greater inequality, loss of privacy, perpetual conflict, and a surveillance-driven social order. It’s a future where the game stays zero-sum but the “winners” use AI to entrench their wins, and the losers have even fewer chances to catch up or seek redress.

Utopian Trajectory: AI and the Shift to Non-Zero-Sum Cooperation

On the other hand, AI also holds promise to solve collective action problems and enable new forms of coordination that were previously impossible. In a more optimistic trajectory, AI helps humanity reach cooperative equilibria – essentially changing the game to make positive-sum outcomes more attainable. Here’s how AI might contribute to a more utopian, win-win future:

Enhanced Coordination and Global Governance: AI could serve as an impartial assistant in global governance, processing vast amounts of information to help leaders make collectively rational decisions. For example, AI systems might monitor compliance with international agreements (like climate targets) by tracking emissions or environmental data in real-time. By increasing transparency, AI can reduce the incentive to cheat – if every country knows that any violation of an emissions cap will be immediately detected by satellites and AI analysis, the payoff for defection in the climate game drops. This is essentially using AI as a verification tool to enforce cooperation. Similarly, AI could optimize the matching of resources to needs globally – akin to a computerized planner that ensures everyone’s basic needs are met with minimal waste. This harks back to ideas of a “global brain” or highly efficient markets guided by AI, where the efficiency gains create a bigger pie to share. If managed well, AI could help distribute that pie more equitably (for instance, algorithms that design fair tax policies or target social investments where they yield the most long-term benefit). The vision is that AI lessens the zero-sum tension by making it clear that cooperative strategies yield better outcomes. Some even imagine AI mediators that can suggest win-win solutions in negotiations (e.g. trade disputes or territorial conflicts), by analyzing preferences and proposing creative compromises humans missed. In essence, AI could raise the game from a primitive Nash equilibrium (stuck in non-cooperation) to a more enlightened equilibrium by changing payoffs – making cooperation the stable choice.
Solving Tragedy of the Commons: Many commons problems might be mitigated with AI oversight. For example, AI-driven smart grids and IoT sensors can dynamically manage resource use (water, electricity) to prevent overuse while meeting everyone’s needs. In fishing or forestry, AI can help set sustainable quotas and monitor compliance, aligning individual actions with the collective good. For climate change, AI is already crucial in modeling outcomes and optimizing renewable energy deployment. If nations collectively deploy AI for climate mitigation, the cost of green technology could plummet (through optimization), making the cooperative path (decarbonization) economically attractive even without selfless virtue. AI can also forecast environmental risks, giving early warnings that prompt joint action. One could imagine a scenario where AI systems coordinate global responses to crises: for instance, an AI network detects a novel virus outbreak and coordinates production and distribution of medical supplies worldwide, minimizing nationalist hoarding. By acting faster and more coherently than disparate human bureaucracies, such an AI-led response could show how everyone wins when we pool knowledge and resources.
Iterated Prisoner’s Dilemma – Building Trust: In repeated interactions, reputation and trust are key. AI could facilitate trust in several ways. One is by enabling smart contracts and blockchain-type accountability – agreements that are automatically enforced by code. If two parties fear the other will defect, they could let an AI arbiter enforce terms (for example, verifying delivery of goods and release of payment). At a global scale, one could imagine treaties that are monitored by AI “referees,” reducing uncertainty. Another aspect is that AI might help model the likely outcomes of defection vs cooperation more clearly for decision-makers. Often, short-term politics cloud judgment; an AI providing unbiased projections (e.g. “if country X launches a first strike, the probability of catastrophic retaliation is 95% – a lose-lose”) could encourage restraint. AI might also simulate scenarios that highlight the benefits of cooperation (much like how in iterated prisoner’s dilemma tournaments, strategies like Tit-for-Tat show the value of reciprocity). If leaders trust AI analysis, it might temper aggressive impulses and promote strategies of conditional cooperation.
Empowering the Many: On the economic/social front, AI could be used to reduce inequality and create new positive-sum opportunities. For example, AI tutors and education platforms could be made universally accessible, massively raising global human capital (everyone gets smarter, which grows the pie of innovation). AI-driven medical research could discover cures and improve quality of life for all. Crucially, if AI productivity gains (from automating labor) are distributed fairly – say through new economic models like a universal basic income or data dividends – it could free humans from scarcity-driven mindsets. In a world where AI helps produce abundance (in energy through fusion optimization, in food through precision agriculture, etc.), zero-sum fights over basic resources could fade. The incentive for war often ties to resources (oil, water, arable land); if AI helps us transition to sustainable energy and climate resilience, those drivers diminish. Utopian thinkers propose that AI, coupled with enlightened policy, might usher in a “post-scarcity” economy, altering the fundamental payoff matrix of human life. People would no longer see others’ gain as their loss, because core needs are met and there are ample opportunities for self-actualization.

Of course, reaching this optimistic future likely requires deliberate effort to design AI for social benefit rather than raw profit or power. It may entail global cooperation in AI governance from the outset. Encouragingly, there are calls that “AI competition is not a zero-sum game. The world’s superpowers need to work together to make sure AI benefits humanity.” (Opinion: AI competition is not a... - MIT Technology Review - Facebook) Initiatives like the UN’s AI for Good, or partnerships on AI ethics, aim to channel AI development toward common good. If democratic societies collaborate, as one commentator urges – “To harness the power of AI for good, [they] need to work together” – we increase the odds of a non-zero-sum outcome. In a positive scenario, AI could actually act as a catalyst for a more conscious civilization, where decisions are guided by data, long-term thinking, and empathy (perhaps fostered by AI insights into our collective well-being).

Altering Incentive Structures: How AI Changes the Game

Whether dystopian or utopian outcomes prevail comes down to incentive structures – the rules of the game. AI will modify these rules in several ways:

Information Asymmetry vs Transparency: AI can either exacerbate asymmetries (if only a few have powerful AI and data, they hold all the cards) or democratize information (if AI tools are widely available and used to reveal truth). In zero-sum conditions, asymmetric AI is likely – e.g. surveillance tech used by the few on the many. In a cooperative regime, AI would be used to shine light on corruption, track emissions, ensure fair elections (detecting misinformation/deepfakes), and generally level the playing field. Much depends on governance – will AI be open-source and broadly accessible, or proprietary and secretive?
Speed and Complexity: AI will accelerate decision-making and could make the world even more complex. This might overwhelm human coordination ability (a risk for instability). However, AI assistance could help humans manage complexity. For instance, global supply chains are hugely complex; an AI could optimize them such that shocks are mitigated (preventing shortages that lead to zero-sum scrambles). In finance, AI might predict crashes and recommend preventative action, stabilizing the system. Essentially, if we delegate some coordination functions to AI, it might handle the complexity better than squabbling nation-states can.
Global Governance and Enforcement: One radical idea is a form of AI-enabled global governance – not AI replacing human governance, but empowering a world institution to enforce cooperation. For example, imagine an international agreement to have AI surveillance of nuclear arsenals to guarantee no first strike goes undetected, making surprise attack impossible and thus discouraging war. Or AI-run audits of supply chains to ensure labor and environmental standards, creating a fairer global market (companies can’t gain by cheating because AI exposes it). These mechanisms would alter incentives by raising the cost of defection. If cheating or aggression is swiftly identified and countered by a coalition (perhaps guided by AI analysis on how to respond effectively), the Nash equilibrium could shift towards compliance and peace.
Changing Values?: An open-ended consideration is whether AI, especially artificial general intelligence (AGI) if it emerges, could influence human values. Some speculate that a superintelligent AI might persuade us to cooperate by illuminating the futility of zero-sum conflict – essentially like an enlightened advisor. Others fear a powerful AI could also exploit our biases to increase division. In any case, AI’s impact on culture and norms will matter. If social media algorithms (a form of AI) continue to reward outrage and partisan content, they push society toward zero-sum tribalism. But if we redesign such AI to reward consensus-building and fact-based discourse, the social climate could become more cooperative. In short, AI will shape the cultural game as well as the geopolitical one.

Conclusion: Toward a Cooperative Equilibrium or Collapse

Looking at the sweep of history, we see a tension between zero-sum and non-zero-sum forces. Zero-sum competition has spurred conquest, exploitation, and conflict – driving progress for some, but often at terrible cost to others. Non-zero-sum cooperation has enabled periods of peace, trade, and collective flourishing – though often imperfect and exclusionary in practice. Today, humanity’s situation is precariously balanced. Inequality, climate change, and geopolitical rivalries show that zero-sum mindsets still hold sway, threatening to turn what could be positive-sum interactions into dangerous contests. Game theory teaches that without effective coordination, individually rational actions can produce collectively disastrous results. We are living that reality: climate inaction, arms build-ups, and economic polarization are all “bad equilibria” we struggle to escape.

AI enters this picture as a wildcard – an amplifier of human intentions and a tool to rewrite the rules. It could reinforce the old games of power (leading to hyper-surveillance, autonomous warfare, and digital monopolies that widen inequality). Alternatively, if guided by wisdom and foresight, AI could transform the game, enabling unprecedented coordination, problem-solving, and equitable resource allocation. The future likely won’t be purely dystopian or utopian, but will contain elements of both. Our challenge is to tilt the balance toward cooperation: to adopt policies that treat AI and other innovations not as weapons in a zero-sum showdown, but as shared solutions for shared problems.

In practical terms, this might mean pursuing international agreements on AI safety and ethics (preventing an unchecked arms race), investing in AI for public goods (health, education, environment) and not just private profit, and creating inclusive forums where all stakeholders (nations, corporations, civil society) define how AI should be deployed. Just as past generations built the United Nations and Bretton Woods institutions after a period of destructive zero-sum conflict, our generation may need to build new global institutions (perhaps an “International AI Agency”) to ensure this powerful technology benefits all and not a narrow few.

Ultimately, game theory reminds us that the game is not fixed. We can change the payoffs and options to escape traps like the tragedy of the commons or prisoner’s dilemma. AI could be the key to implementing those changes at scale – but only if we cooperate in doing so. The hope for a non-zero-sum civilization lies in recognizing our profound interdependence. Climate stability, peace, and prosperity are public goods we either all enjoy together or all suffer without. As the saying goes, we will either win together or lose together. Our historical journey shows both the perils of zero-sum thinking and the promise of cooperation. With AI’s advent, that journey is accelerating toward a fork in the road. It is our collective move to play – whether we continue the zero-sum competition until systems break, or embrace a new strategy of cooperation, enabled by intelligence (human and artificial) to create a better outcome for everyone.

Sources:

Wright, Robert. Nonzero: The Logic of Human Destiny – argues that increasing non-zero-sum interactions drove social complexity (background philosophy).
Hardin, Garrett. “The Tragedy of the Commons.” Science, 1968 – classic article on collective rationality failure.
History and analysis of zero-sum mindsets in imperialism (How Imperialism Set the Stage for World War I | HISTORY) (The Ottoman Scramble for Africa: Introduction | Stanford University Press), mercantilism (Mercantilism - Wikipedia), and Cold War zero-sum perceptions (The Cold War as Cooperation: A Soviet Perspective | SpringerLink).
Oxfam and WEF reports on current inequality (Oxfam: 8 ways to bridge the global inequality gap | World Economic Forum) and how many feel left behind.
Discussion on great power rivalry hindering global problem-solving (Great Powers Have Lost the Plot: The Perils of a Split-Screen World • Stimson Center).
Zuboff, Shoshana. The Age of Surveillance Capitalism – critique of how data monopolies create zero-sum outcomes for democracy (Surveillance Capitalism or Democracy? The Death Match of Institutional Orders and the Politics of Knowledge in Our Information Civilization by Shoshana Zuboff :: SSRN).
NPR on climate change as a tragedy of the commons (Climate Change Is Victim Of 'Tragedy Of The Commons' : NPR).
Cornell blog on arms races as prisoner’s dilemma ( Game Theory Applied to Arms Races : Networks Course blog for INFO 2040/CS 2850/Econ 2040/SOC 2090).
Statements on AI competition and cooperation needsreddit.comtheatlantic.com.

AI Reasoning

Game Theory and Human History: Zero-Sum Dynamics and the Role of AI

Mapping out game theory's evolution, I’m digging into zero-sum and non-zero-sum models throughout history. Major events like empires, colonization, mercantilism, wars, and globalization are pinpointed as key dynamics.

I'm analyzing key game theory concepts like zero-sum and non-zero-sum within current crises, like climate change. Future implications include AI's role in global governance and equity.

I'm bridging global challenges with AI's transformative influence, balancing dystopian and utopian futures, and highlighting how AI can reshape incentive structures and governance.

Searched for mercantilism and zero-sum game theoryChatGPT

Referencing Wikipedia on Mercantilism reveals that trade is often considered a zero-sum game, where one nation's gains result in another's losses.

Read en.wikipedia.org

ChatGPT

Mercantilists see the economy as a zero-sum game, where one party's gain leads to another's loss. This classic reference is crucial for understanding their doctrine.

Searched for empire formation and game theoryChatGPT

Considering "Power Politics and Scarcity in the Modern Age: A Zero Sum Game" and its potential reflections on historical empires.

Read e-ir.info

ChatGPT

This insight highlights how interstate relations, viewed through a realist lens, become a zero-sum game with one state's gain inevitably resulting in another's loss.

Searched for zero-sum thinking and colonization historyChatGPT

The Boston Review article appears to highlight zero-sum thinking as a core feature of a colonial mindset, suggesting potential advantages.

Read bostonreview.net

ChatGPT

I’m noting how activists identified zero-sum thinking as a colonial mindset and aimed to move beyond it through inclusive decolonization efforts, emphasizing the recognition of zero-sum thinking by anti-colonial actors.

Imagining the scramble for Africa as a zero-sum territorial grab. Think of it as a board game where each move signals a new alotted space under a European country's banner.

Searched for colonial powers and zero-sum competitionChatGPT

Examining how the Ottoman Empire and other European powers sought colonial territories to claim global supremacy.

Read sup.org

ChatGPT

I'm analyzing the connection between New imperialism and the zero-sum game, considering territorial expansion, colonialism, and their impact on global power dynamics in the late 19th century and beyond.

Searched for World War I and zero-sum gameChatGPT

OK, let’s see. I'm pulling together insights on "How Imperialism Set the Stage for WWI" and a trench system by Gwern to understand military tactics and their historical development.

Read history.com

ChatGPT

Thinking about zero-sum game. This involves the idea that one's gain is balanced by another's loss, like in competitive sports.

Read more from commons.wikimedia.org

ChatGPT

Let's think about how to open the image link at snippet 118.

Read more from commons.wikimedia.org

ChatGPT

I'm piecing together that the image might not be shown due to a file page load issue, suggesting a potential link to the "Original file" or "Full resolution" for resolution.

Read more from commons.wikimedia.org

ChatGPT

Verifying the resolution of the original image is 1911x2919 to confirm its accuracy. Right-clicking to retrieve the URL ensures the correct link is obtained.

Read more from commons.wikimedia.org

ChatGPT

OK, I'm gathering the original file.

Read upload.wikimedia.org

ChatGPT

I’m organizing citations, integrating references smoothly, and considering narrative flow. Exploring bullet points for clarity while maintaining a balanced flow.

Game Theory: Human history viewed as “games” between competing groups

Table of Contents

Introduction: Zero-Sum and Non-Zero-Sum Games in History

Empire and Conquest: The Zero-Sum Imperative

World Wars: Total Conflict in a Zero-Sum World

The Cold War: High-Stakes Zero-Sum Standoff (and Cooperation on the Margin)

Globalization and Neoliberal Order: Positive-Sum Promise, Zero-Sum Pitfalls

The Current Global Game: Inequality, Crises, and Coordination Failures

Global Inequality: Winners, Losers, and Zero-Sum Perceptions

Ecological Crises and the Tragedy of the Commons

Systemic Instability: Iterated Dilemmas and Short-Termism

The Future: Will AI Intensify the Zero-Sum Game or Foster a Non-Zero-Sum Breakthrough?

Dystopian Trajectory: AI and Amplified Zero-Sum Competition

Utopian Trajectory: AI and the Shift to Non-Zero-Sum Cooperation

Altering Incentive Structures: How AI Changes the Game

Conclusion: Toward a Cooperative Equilibrium or Collapse

AI Reasoning

Comments

Latest

From the Big Bang, to Atoms, to Galaxies to Humans to AI. Entropy & the Arrow of complexity

Female (Egg) vs Male (Seed). Why has evolution produced such a radically asymmetric sexual system in humans?

Open source isn’t just code. It’s about building something bigger than ourselves.

The Enigma of the Collatz Conjecture

Game Theory: Human history viewed as “games” between competing groups

Table of Contents

Introduction: Zero-Sum and Non-Zero-Sum Games in History

Empire and Conquest: The Zero-Sum Imperative

World Wars: Total Conflict in a Zero-Sum World

The Cold War: High-Stakes Zero-Sum Standoff (and Cooperation on the Margin)

Globalization and Neoliberal Order: Positive-Sum Promise, Zero-Sum Pitfalls

The Current Global Game: Inequality, Crises, and Coordination Failures

Global Inequality: Winners, Losers, and Zero-Sum Perceptions

Ecological Crises and the Tragedy of the Commons

Systemic Instability: Iterated Dilemmas and Short-Termism

The Future: Will AI Intensify the Zero-Sum Game or Foster a Non-Zero-Sum Breakthrough?

Dystopian Trajectory: AI and Amplified Zero-Sum Competition

Utopian Trajectory: AI and the Shift to Non-Zero-Sum Cooperation

Altering Incentive Structures: How AI Changes the Game

Conclusion: Toward a Cooperative Equilibrium or Collapse

AI Reasoning

Comments

Related

Latest