The Algorithmic Non-Aligned: How Latin America Can Forge Sovereignty in the Age of AI Empires

Excerpt

Artificial intelligence is not merely a technology but the new arena of geopolitics, culture, and sovereignty. Latin America risks repeating centuries of extractivism by supplying the raw materials and hidden labor of the AI age. Yet by reframing AI as a natural resource, a cultural engine, and the foundation of a new social contract, the region can chart a non-aligned path, transforming itself from periphery into pole of power in the intelligent century.

Introduction: The Dawn of Algorithmic Geopolitics

Empires have always been built on the mastery of resources and the ability to project meaning. The Spanish crown extracted silver from Potosí to finance its dominion; Britain’s railroads and telegraphs knit together a global empire; the United States fused oil and computation to define the twentieth century. Today, a new empire is emerging, and its foundation is neither mineral nor mechanical but algorithmic. Artificial intelligence, the ability to turn data into decisions and signals into power, is the infrastructure upon which twenty-first-century sovereignty, leadership, and success will rest.

The United States, China, and Europe have already staked their claims. Each has fused AI into the core of its economic, military, and cultural strategies. Yet Latin America, as it often finds itself, stands at a crossroads. Will it be relegated to the role of resource periphery, supplying lithium, data, and ghost labor to fuel foreign empires, or will it seize this moment to declare its independence? The real question is whether Latin America chooses to be a digital colony or an algorithmic sovereign.

This article argues that the region’s path must be one of Algorithmic Non-Alignment: neither subject to Washington, nor to Beijing, nor to Brussels, but sovereign in its own right. To do so, Latin America must treat AI as four things simultaneously: a geopolitical position, a natural resource, a cultural engine, and the architecture of a new social contract. These are not abstractions; they are the building blocks of a distinctly Latin American future in the intelligent century.

Part I: The Algorithmic Cold War and the Non-Aligned Path

The global AI race increasingly mirrors the dynamics of the Cold War. The United States envisions AI as the guarantor of both economic preeminence, cultural command, and military supremacy, pouring billions into private-sector models and defense applications. China fuses state capacity with technological might, embedding AI into governance, surveillance, and industrial expansion. Europe, unable to match either in scale, claims authority through regulation, positioning itself as the moral legislator of the algorithmic age.

These three poles do not merely build technology; they export worldviews. A model trained in Silicon Valley does not simply compute; it projects the American faith in markets, cultural identity, and vision of scale. A model designed in Beijing does not merely optimize, it extends the Chinese logic of centralized control. A framework emerging from Brussels does not merely regulate, it encodes European anxieties about ethics, dignity, and law. As the world over adopts chatbots and AI tools across all elements of their daily existence, we must quickly realize that AI is not neutral; it is civilizational.

Latin America, therefore, faces the same dilemma it confronted during the twentieth century: to align with one bloc or to forge an independent destiny. The Non-Aligned Movement of the 1960s offered a third way for postcolonial states, refusing to be pawns in the bipolar contest between Washington and Moscow. Today, the region can pioneer what I call the Algorithmic Non-Aligned Movement, not passive neutrality, but active sovereignty.

In practice, this means engaging with all three empires for investment, technology, and knowledge transfer, while refusing dependency on any single one. It means using neutrality as leverage, positioning Latin America as a swing bloc in the geopolitics of AI, capable of mediating between North and South, East and West. Non-alignment is not passivity. It is strategy, the art of turning vulnerability into bargaining power, and geography into destiny.

Part II: The Resource Paradox and Algorithmic Natural Resources

For half a millennium, Latin America has been locked in a cycle of extractivism. Silver, sugar, rubber, oil, copper, soy—the region has repeatedly provided the raw inputs of global industry, while rarely capturing the higher rungs of value creation. Each boom has ended in dependency, inequality, and disillusionment. The danger is that artificial intelligence will become the newest iteration of this tragic pattern.

Already, the signs are visible. Latin America holds more than half of the world’s lithium reserves, the “white gold” that powers the batteries essential for GPUs, data centers, and electric infrastructure. Simultaneously, the region provides much of the hidden human labor upon which AI depends: tens of thousands of workers across Venezuela, Brazil, and Colombia annotate datasets, label images, and moderate content for global platforms. These “ghost workers” are the coal miners of the algorithmic era, unseen, underpaid, but indispensable.

This is the AI Resource Paradox: the region is central to the global AI economy, yet peripheral to its rewards. Unless sovereignty is asserted, Latin America will once again become the supplier of “algorithmic ore,” while the wealth and power accrue elsewhere.

The way forward is to recognize that data itself is an algorithmic natural resource. Just as nations treat oil, water, and forests as strategic assets, so too must they treat their data. The health records of Brazilian citizens, the financial behaviors of Mexican consumers, and the linguistic richness of Andean communities are not merely inputs for foreign companies to harvest but national treasures to be stewarded, protected, and leveraged. 

This reframing transforms data into the foundation of sovereignty. It means that Latin America must build its own refineries, not of oil, but of algorithms. It must establish its own compute centers, sovereign clouds, and continental data trusts. For in the twenty-first century, the mines are digital, the ore is data, and the refinery is the algorithm. Those who fail to control them will not be producers; they will be subjects.

Part III: AI as Cultural Engine and the Cultural Sovereignty Dividend

The most profound danger of digital dependency is not economic but cultural. For centuries, colonization operated not only through resource extraction but through the imposition of foreign languages, laws, and worldviews. Today, a subtler colonization occurs through algorithms.

The world’s dominant models are overwhelmingly trained on data from the United States, Europe, and China. They carry within them the values, assumptions, and perspectives of those societies. When applied to Latin America, they distort. They mistranslate indigenous languages, misinterpret cultural idioms, and misframe social behaviors. They universalize the particular, presenting foreign norms as global truths. This is the essence of digital colonization.

To resist, Latin America must treat AI not only as a technical system but as a cultural engine. It must train models in its languages, reflecting its histories, idioms, and values. Doing so is not only a matter of dignity, it is a matter of cohesion, growth, and power. A culturally sovereign AI ensures that the region does not see itself through foreign lenses, but through its own reflection.

The rewards extend beyond identity. A Latin American AI, trained in Spanish, Portuguese, and indigenous languages, could serve not only its own citizens but hundreds of millions across Africa, Asia, and diasporic communities worldwide. This is the Cultural Sovereignty Dividend: the ability to turn cultural specificity into a global export. Just as Hollywood projected American values through film, Latin America can project its diversity through code. In the algorithmic century, soft power will not be movies or music; it will be models.

Part IV: AI as the Architecture of a New Social Contract

But the greatest promise of AI in Latin America is political. For centuries, the region has been plagued by fragile states, cycles of inequality, and crises of legitimacy. Governments too often fail to deliver; citizens too often lose faith. The result is a chronic deficit of trust, the foundation without which democracy cannot endure.

Here lies the revolutionary potential of artificial intelligence: it can serve as the architecture of a new social contract. Properly designed, AI can bring transparency to the flows of money and power, exposing corruption and inefficiency. It can optimize welfare systems, ensuring benefits reach the most vulnerable. It can predict crises, pandemics, floods, and energy shortages before they become disasters. It can strengthen fragile states not through authoritarian control, but through algorithmic accountability.

This is the Algorithmic Social Safety Net: AI as the guarantor of resilience in societies where traditional governance mechanisms have too often failed. Importantly, this must not become a Latin American version of Chinese surveillance or American hyper-commercialization. It must be a democratic AI, rooted in participation, transparency, and citizen empowerment.

The boldest step forward would be what I call the Algorithmic Constitution: embedding algorithmic rights, duties, and principles into the very fabric of national charters. Just as constitutions once enshrined property, speech, and suffrage, so too must they now enshrine data dignity, algorithmic transparency, and cultural sovereignty. Latin America, with its long history of constitutional experimentation, from Mexico’s revolutionary charter of 1917 to Chile’s ongoing constitutional debates, can once again pioneer a global model.

An Algorithmic Constitution would not be an abstract legal gesture; it would be a profound act of sovereignty. It would declare that in the age of AI empires, the rights of citizens and the duties of states are not defined in Silicon Valley boardrooms or Beijing ministries, but in the constitutions of sovereign peoples. Empires write rules; nations write constitutions. Latin America must do the latter, or risk being ruled by the former.

Part V: From Vision to Roadmap, Building an Algorithmic Future for Latin America

A vision without architecture risks dissolving into rhetoric. To transform aspiration into sovereignty, Latin America must move beyond abstract principles and adopt a coherent roadmap: a sequence of tangible, innovative policies that operationalize non-alignment, resource sovereignty, cultural engines, and the algorithmic social contract.

This roadmap was not invented in a vacuum. Latin America has centuries of historical experience in confronting external dependency and internal fragility. It has lived through the successes and failures of resource nationalization, regional integration, and constitutional innovation. And beyond its borders, Africa, the Middle East, and Southeast Asia are already experimenting with their own approaches to AI, offering both inspiration and cautionary tales. By situating Latin America’s strategy in this broader context, we not only chart a path forward but ensure it is one rooted in lessons of history and global relevance.

1. Historical Parallels: From Resource Nationalization to Algorithmic Sovereignty

The story of resource sovereignty in Latin America is both inspiring and sobering. Mexico’s nationalization of oil in 1938 demonstrated the power of reclaiming natural wealth, while Venezuela’s petro-nationalism showed both the promise of independence and the perils of mismanagement. Today’s “lithium nationalism” in Mexico, Bolivia, and Chile is a contemporary echo of this struggle.

The lesson is clear: sovereignty requires more than nationalization; it requires the transformation of raw resources into domestic capability. Just as oil nationalism failed when it remained fixated on barrels rather than petrochemicals, AI sovereignty will fail if it remains fixated on lithium or data without building the compute infrastructure, talent pipelines, and model ecosystems that convert resources into power.

Thus, Latin America must pioneer the doctrine of Algorithmic Sovereignty: treating data, compute, and models as national resources, managed with the same gravity as energy or minerals. This demands new legal frameworks, akin to mining codes or water rights, but for data, where citizens are both contributors and beneficiaries of the resource economy.

2. Policy Recommendations for Latin America

To translate principle into practice, I propose a set of pioneering policies:

• Continental Data Trusts: Establish regional data pools governed by sovereign rules, where health, financial, and educational data are anonymized, aggregated, and shared across Latin America for model training. This mirrors the logic of OPEC, but applied to data as an algorithmic resource.

  
  

• AI Compute Commons: Develop regional high-performance compute hubs, owned by coalitions of states rather than foreign firms, ensuring that the raw power to train models is not outsourced. These hubs could be funded through sovereign wealth funds tied to lithium revenues.

  
  

• Algorithmic Citizenship: Grant citizens explicit rights over their data, modeled on suffrage and property rights, while obligating governments to ensure transparency and accountability in algorithmic use. This would be codified in the emerging Algorithmic Constitution.

  
  

• Cultural AI Institutes: Fund research centers tasked with training models in indigenous languages, Latin American dialects, and cultural datasets. These institutes would transform cultural heritage into living algorithmic infrastructure, generating the Cultural Sovereignty Dividend.

  
  

• Climate AI Infrastructure: Position AI as the infrastructure of resilience against floods, droughts, and energy volatility. Latin America, one of the most climate-vulnerable regions, could set global standards for “green AI” applications.

  
  

Together, these policies would ensure that sovereignty is not symbolic but operational, embedding non-alignment, resource control, cultural dignity, and resilience into the everyday life of nations.

3. Comparative Lessons from Africa, MENA, and Southeast Asia

Latin America is not alone in confronting the dilemmas of AI dependency. Other regions provide instructive examples.

• Africa: The African Union has declared data sovereignty a continental priority, exploring shared data frameworks to avoid extractivism by foreign firms. Yet many African states lack compute infrastructure, forcing reliance on external clouds. The lesson for Latin America: sovereignty requires infrastructure first, not only legal frameworks.

  
  

• MENA: Gulf states, especially the UAE and Saudi Arabia, are aggressively investing in AI as part of their post-oil economic visions. They demonstrate the power of using resource wealth (oil) to fund AI ecosystems. But they also reveal the risks of over-centralization: innovation thrives not only on capital, but on openness and pluralism. Latin America must therefore pair state investment with democratic safeguards.

  
  

• Southeast Asia: Singapore has emerged as a hub by positioning itself as a trusted intermediary, neutral, well-regulated, and globally integrated. Its strategy shows that small states can exert disproportionate influence through credibility. For Latin America, the parallel is clear: neutrality in the AI Cold War is not passivity, but strategic positioning.

  
  

By learning from these regions, Latin America can avoid repeating mistakes while adapting successful strategies. It can be neither the fragmented Africa of compute scarcity, nor the authoritarian MENA of centralization, nor the niche Singapore of scale limitations. Instead, it can be the continental bloc that unites diversity, resources, and democratic innovation.

4. Toward a Latin American Algorithmic Bloc

Ultimately, the roadmap points toward a bold but necessary goal: the creation of a Latin American Algorithmic Bloc. Just as Mercosur once aimed to integrate economies, so too must a new alliance integrate AI resources, infrastructures, and standards. This bloc would:

• Pool compute resources and negotiate with global tech firms from a position of strength.

• Establish shared cultural AI datasets and models, ensuring linguistic and cultural diversity.

• Coordinate regulatory frameworks to avoid “data dumping” by foreign corporations.

• Project Latin America’s collective voice in global AI governance forums.

  
  

If the European Union has become the regulator of the digital world, and China and the U.S. its builders, Latin America can position itself as the third pole: the region that proves democracy, diversity, and sovereignty are not obstacles to AI leadership, but its deepest foundation.

This roadmap is ambitious, but it is not utopian. It draws upon the very history of Latin America: the fight for independence, the experiments with resource nationalism, the innovations in constitutional law, the enduring quest for dignity in the face of empire. It situates the region in the broader struggles of the Global South, while offering a distinctive, actionable vision. History’s lesson is merciless: resources without sovereignty produce dependency, but sovereignty without strategy produces isolation. Latin America must claim both.

Conclusion: From Periphery to Pole of Power & AI in Latin America

Latin America’s history has too often been written as a grand tragedy: the richest continent in natural resources, yet too often denied the fruits of its abundance. The rise of artificial intelligence threatens to repeat this story. But it also offers the chance to rewrite it.

By leading an Algorithmic Non-Aligned Movement, by recognizing data as an algorithmic natural resource, by harvesting the Cultural Sovereignty Dividend, and by constructing an Algorithmic Constitution for the social contract, Latin America can break free of its centuries-long cycle of dependency. It can become not the periphery of someone else’s empire, but a pole of power in its own right, a continent that offers the world not only resources, but ideas, not only labor, but models, not only commodities, but culture.

In the intelligent century, sovereignty is no longer given; it is coded. Those who fail to write their own algorithms will live by the algorithms of others.