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 is transforming international development cooperation not only as a technological tool, but also as a political, ethical, and geopolitical phenomenon. It is reshaping priorities, actors, and cooperation mechanisms, changing how data are produced and used, and forcing a reconsideration of the capacities countries need to participate in the global digital economy.
But the relationship also works in the opposite direction. International development cooperation should not be limited to adopting AI tools designed elsewhere; it should also help shape global AI governance around algorithmic justice, digital sovereignty, sustainability, and the inclusion of the Global South.
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.
This agenda also connects with the debate opened by the World Summit on the Information Society on the need to build a people-centered digital future.
AI-IDC relations (simplified diagram)
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.
This orientation is also reflected in new UN spaces for AI governance, where an agenda of AI for sustainable development is beginning to take shape.
The key question is how to
guide transformations in an increasingly unequal and crisis-prone world.
If governed through ethical principles and inclusive frameworks, AI could become
a cornerstone of sustainable global development cooperation.