The Sociological Imperative of Artificial Intelligence: Geopolitical Alliances, Corporate Dominance, and Environmental Implications

OpenAI’s recent proposal for a “North American Pact for AI” reflects a reconfiguration of technological geopolitics, where territorial borders give way to transnational alliances driven by competitiveness in the race for artificial intelligence (AI). By proposing a strategic collaboration between the United States and its neighbors, such as Canada and Mexico, OpenAI suggests a model of regional interdependence to consolidate hegemony against China. This pact, as a promoter of innovation, articulates power dynamics that transcend technology, being a tool for the dispute over global sovereignty.

The plan also reveals the centrality of control over talent and supply chains as structuring factors for the production of emerging technologies. This scenario reflects one of the central characteristics of late modernity: the fragmentation of traditional borders and the rise of transnational networks that reconfigure state sovereignty.

Even more notable is the expansion of the idea to other regions, such as the Middle East, a strategic move to access essential resources such as chips and data infrastructure. However, this expansion raises questions about the role of technology as a vector of contemporary imperialism, where economic interests mask the imposition of hegemonic values and policies.

Private Capital and Academic Research: The Ambivalence of Amazon’s Trainium Program

Amazon’s announcement of its “Build on Trainium” grant program—a $110 million investment aimed at academic use of its Trainium chip—highlights the growing corporate influence over the field of AI research. Through this funding, the company seeks to instrumentalize academic infrastructure to meet demands that, although covered by scientific objectives, are intrinsically linked to market interests.

By offering significant financial support and access to advanced hardware, Amazon presents itself as a catalyst for academic innovation, especially in contexts where institutions face financial barriers to conducting cutting-edge research. However, the decision of which projects will be funded, which is centralized by company experts, reveals a critical point: the possibility of "corporate colonization" of academic priorities. The selectivity of the "most promising and impactful" projects denotes a structured bias that prioritizes private interests over the impartial advancement of knowledge. This symbiotic relationship between academia and corporate capital reflects neoliberal dynamics that, while expanding access to resources, erode the autonomy of science and reinforce epistemological inequalities.

The Growth of AI and its Socio-Environmental Impacts: Contradictions of Energy Innovation

The exponential increase in energy demands associated with AI highlights a central paradox of contemporary technological advancement: while it promises innovative solutions, it also exacerbates environmental impacts. The initiatives of large technology companies, such as Microsoft and Google, to invest in nuclear energy and liquid cooling, illustrate the search for energy sources that sustain the pace of AI growth. However, such movements reveal the contradictions inherent in the current technological development model.

On the one hand, the use of nuclear energy and quantum computing represents an attempt to transcend energy and computational performance limitations. On the other hand, the long-term environmental consequences, such as nuclear waste management and the impact of cooling systems, still remain insufficiently debated.

At the same time, the rise of quantum computing as a possible sustainable solution reflects the attempt to balance energy efficiency with processing demands, but its large-scale implementation is far from being a reality. This tension points to one of the most pressing issues of our time: how to reconcile economic growth, technological innovation, and environmental responsibility.

Conclusion: Sociology of Technology in the Age of AI

These three cases demonstrate that the evolution of AI is simultaneously a technical, social, and political phenomenon. The pact proposed by OpenAI highlights the reconfiguration of power relations in the international system, while Amazon’s program makes explicit the subordination of academic structures to corporate capital. Finally, initiatives aimed at energy sustainability reveal the tension between innovation and ecological responsibility.

The sociology of technology, therefore, must address how these phenomena interconnect and create new forms of inequality, while redefining the relationship between the human, the technological, and the natural. Artificial intelligence is not just a tool; it is a social force that reconfigures global dynamics and shapes the future of human interactions.