Exploring the Cross-Impacts between AI and International Development Cooperation

By Javier Surasky

This post summarizes the presentation I delivered at the 17th Congress of the Argentine Society of Political Science (SAAP), held at the National University of Rosario (Rosario, Argentina) on July 24, 2025.


Artificial Intelligence (AI) is reshaping global structures, including international development cooperation (IDC), not only as an applied technology but also as a multifaceted phenomenon with political, ethical, and cultural implications. This work examines the two-way relationship between AI and IDC, exploring how AI is transforming international cooperation and how IDC can and must influence the global governance of AI.

1. AI as a Driver of Transformation and Object of Geopolitical Contestation

The AI ecosystem is complex and dominated by a contest among three national models: the U.S. model (market-driven), the Chinese model (state-controlled), and the European model (principle-based regulation). However, other mid-size actors—such as India, Israel, South Korea, Brazil, and South Africa—are also developing specific capabilities that challenge the power concentration in the hands of major powers alone.

This geopolitical landscape is further shaped by the decisive role of private companies such as OpenAI, Nvidia, Baidu, and Meta, whose decisions often exceed the regulatory capacity of states. IDC, still structured around territorial and state-based frameworks, struggles to engage with this decentralized, multi-actor setting, where power is also exercised through control of data, infrastructure, and algorithms.

2. Alienating Duality and the Limits of the Technocratic Paradigm

Drawing on the concept of alienating duality, it becomes clear that AI reinforces the disconnection between human beings and their environments, interposing algorithmic layers of abstraction between people and reality. As a result, AI-based decisions—such as aid allocation, policy design, or beneficiary profiling—are often portrayed as “objective,” concealing the cultural frameworks, values, and biases embedded in their structures.

Furthermore, technocratic logics, with their focus on efficiency and prediction, tend to depoliticize debates in favor of technical considerations, marginalizing the voices of the most vulnerable. Unless intentionally counterbalanced, this dynamic reproduces forms of domination that deepen historical inequalities.

3. Data Colonialism and Algorithmic Justice: Ethical Challenges

AI relies on massive amounts of data, drawing from a process described as data colonialism—the large-scale extraction of information from people and communities in the Global South without providing equitable returns. This appropriation perpetuates colonial logics of dispossession, turning the intimate into commodified capital.

In addition, several studies have shown that AI systems reproduce biases based on ethnicity, gender, and nationality, thereby compromising fairness in critical areas such as hiring, healthcare, and access to credit.

Together, these two dimensions—data colonialism and discriminatory biases—highlight the urgent need to construct algorithmic justice, which must be integrated into IDC’s design framework. If IDC fails to examine its approaches to technological transfer and data cooperation critically, it risks becoming a vector that amplifies these injustices.

4. Sustainability and Cooperation: A New Agenda for AI

AI is highly energy- and resource-intensive. Without an IDC capable of articulating sustainable strategies, the development of AI could contribute to environmental collapse or be monopolized by those who control energy sources. As a space for collective action and preventive diplomacy, IDC must assume a new leadership role in the global management of the resources required by AI.

At the same time, the notion of sovereignty must be rethought: data no longer respects physical borders, and key decisions regarding its use are made in transnational arenas. In this context, IDC must adopt principles of shared digital sovereignty, inclusive algorithmic governance, and binding ethical frameworks.


AI-IDC relations (simplified diagram)

Source: Own


Conclusion: Toward an “IDC 2.0”

The intersection between AI and IDC calls for moving beyond traditional approaches and designing an IDC 2.0 that includes:

  • Inclusion of dedicated chapters on data in cooperation agendas.
  • Promotion of technological transfers grounded in algorithmic justice and digital sovereignty.
  • Active involvement of non-state actors and communities from the Global South.
  • Strengthening of state capacities in AI governance.
  • Building alliances to promote contextualized, sustainable, and pluralistic AI.

The key question is not whether AI will transform IDC, or how IDC might influence AI. Instead, it is about how to guide these transformations in an increasingly unequal and crisis-prone world. If governed through ethical principles and inclusive frameworks, AI can become a cornerstone of sustainable global development cooperation.