By
Tuhu Nugraha
Africa-Press – Mauritius. Artificial Intelligence (AI) today is heralded as a revolutionary force across industries. I was personally shocked when the Indonesian government quietly approved a cross-border data transfer agreement with the United States under proposals initially advocated during the Trump administration. Even more troubling, this move received almost no public scrutiny—drowned out by other domestic political and economic distractions that were deemed more urgent.
This is alarming because such decisions are not minor—they shape the strategic architecture of our digital future, affecting everything from national security to economic sovereignty. But for the Global South, it represents a double-edged sword: promise and peril. As with previous waves of technology, AI is arriving embedded in the legacies of colonialism—centralized control, asymmetric benefits, and erasure of local agency.
The terms “AI colonization” and “digital colonialism” have emerged to describe how wealth, data, and decision-making remain concentrated in established power centers, while many in the Global South shoulder disproportionate burdens.
I care deeply about this issue because history has shown us how exploitation can begin subtly—often without a full grasp of its long-term consequences. The early stages of colonialism, such as European expeditions in search of spices or the establishment of the transatlantic slave trade, may not have imagined the centuries of suffering, extraction, and inequality they would set in motion. In many cases, the true scale of harm was only acknowledged generations later, with regret and corrective actions attempted long after the damage had been entrenched.
Similarly, today’s unchecked digital structures risk repeating those same mistakes in virtual form. By raising this discourse now, we have a chance to intervene before patterns become entrenched. This is not about resisting technology; it is about preventing the past from being digitally replayed. It is about giving future generations a system that reflects dignity, agency, and mutual respect.
AI has become the new territory to be mapped, extracted, and governed. But unlike traditional colonialism, it doesn’t require boots on the ground. Instead, it operates through code, data centers, licensing agreements, and the architecture of the cloud. Artificial Intelligence holds enormous potential to transform healthcare, education, finance, and agriculture.
Yet over 80% of AI research and development remains concentrated in the United States, China, and Western Europe—while most data powering these systems is harvested from populations in the Global South (ROAPE, 2024; Datapop Alliance, 2025). These datasets often lack proper consent, contextual fit, or fair economic return (Project MUSE, 2025). At the same time, critical minerals like cobalt and lithium—essential for AI hardware—are extracted under exploitative conditions in African nations (ICTworks, 2025).
As a result, economic benefits from AI remain heavily concentrated in a few regions, while the Global South continues to serve as a digital raw material provider rather than an empowered co-creator in the AI future. The patterns are global and widespread across the Global South. In Africa, countries like Kenya face exploitative digital labor conditions where low-paid content moderators and data labelers endure psychological harm while sustaining the backend of global AI systems.
Across Asia, from the Philippines to India and Indonesia, linguistic representation remains unequal, regulatory frameworks often lag behind deployment, and the cultural contexts of users are underrepresented in model design. Meanwhile in Latin America and the Middle East, algorithms trained on Western-centric data frequently misclassify or misinterpret local realities, while countries like Peru have turned to generative AI as a means of resisting epistemic erasure by preserving Indigenous languages.
These disparities, if left unaddressed, risk producing deeper social consequences—including the erosion of cultural diversity and the marginalization of minority groups. This invisibility can breed resentment, identity-based backlash, and the rise of radical movements asserting recognition through force. Without structural change, we risk reinforcing historical extractivism under digital guise—a challenge we must address together.
Why Decolonization is Essential for Trustworthy AI
The European Union’s “trustworthy AI” paradigm cannot be transplanted wholesale into the Global South. Trust, in many African or Southeast Asian societies, is not merely a matter of data privacy but a collective and relational value shaped by historical, cultural, and communal norms.
To build AI systems that communities can trust, we must go beyond importing regulations. This is not about being different for the sake of difference; it is about acknowledging that AI systems reflect and reinforce the social orders, value systems, and epistemologies of those who create them.
When AI is built solely within a Western-centric framework, it carries embedded assumptions about autonomy, efficiency, and control that may conflict with the relational, communal, or spiritual values of many societies in the Global South. This divergence of foundational values can, if left unchecked, evolve into more than a technological gap—it risks fueling a deeper ideological rift, a digital-era clash of civilizations. Much like the post–Cold War period has revealed renewed cultural and ideological frictions, we now face the possibility that AI becomes a new battleground of epistemological dominance.
Compounding this risk is the reality that AI can be even more dangerous than nuclear weapons in certain contexts. Open-source AI systems, while democratizing access and fostering innovation, also make it alarmingly easy for malicious actors—including individuals or terrorist groups—to misuse the technology. Unlike nuclear weapons, which require state-level resources, AI tools can be developed, adapted, and deployed with far fewer barriers. This accessibility heightens the difficulty of governance and oversight, enabling the spread of disinformation, the manipulation of democratic processes, and even the disruption of vital infrastructure.
Therefore, we must cultivate locally grounded governance models, community-led design processes, and capacity-building efforts that reflect the social fabric, cultural priorities, and lived experiences of the people affected. Decolonizing AI is not only about fairness in access or representation—it is about preventing digital hegemony and ensuring that technology evolves in ways that honor plural worldviews, promote inclusive coexistence, and sustain human dignity across all contexts.
Two Diverging Futures
A decolonized AI future features regional data sovereignty, ethical design rooted in Indigenous knowledge systems, robust local infrastructure, and fair South-South and global partnerships. In contrast, a digital colonialism scenario perpetuates extractive data practices where communities remain data-rich but power-poor; continued dependency on foreign technology providers who dictate terms and frameworks; and epistemic exclusion—where local knowledge systems, languages, and cultural values are sidelined in favor of dominant Western narratives embedded in algorithms and training data.
These exclusions manifest when AI fails to recognize Indigenous identities, misinterprets non-Western speech patterns, or devalues communal-based ethical frameworks. The result is not only technological marginalization but also the deepening of structural inequalities: where access to quality digital tools, representation in digital labor, and participation in decision-making remain skewed toward a privileged minority. Over time, these gaps can widen into systemic divides, with the Global South reduced to a passive consumer rather than a co-architect of AI’s future.
The direction we take depends on critical variables: political will, investment in AI education and infrastructure, regional regulatory coordination, and the courage to challenge prevailing power dynamics. This is important not simply as a matter of geopolitical rebalancing, but because AI is more than a technical tool; it is an expression of societal logic, a projection of underlying value systems, and an infrastructure of future governance.
The decisions encoded into AI—about what is optimized, who is recognized, and which data matters—can either reinforce historical injustice or open up new possibilities for inclusion and dignity. Ensuring that the Global South actively shapes this process is not a symbolic gesture, but a foundational step toward technological justice and resilient digital sovereignty.
At the same time, we must foster sustained dialogue and mutual understanding between the Global North and Global South. This is not a zero-sum struggle; it is an opportunity for shared resilience. The Global South is home to the fastest-growing populations, the youngest demographics, and some of the most adaptable digital labor forces on the planet.
It offers massive market potential, rapid adoption environments, and cost-effective talent. But if these advantages are exploited without equity, they will exacerbate inequalities and sow the seeds of future conflict.
Yet one of the foundational challenges within the Global South is internal: many key stakeholders, including policymakers and economic elites, still fail to recognize the economic value of data. Their mental models are shaped by decades of extractive economics, where value is associated almost exclusively with tangible resources like mining, oil, or land. As a result, data is not yet seen as a strategic asset—let alone a national or regional priority. This is compounded by political systems that, in many cases, are still in the process of maturing.
Decision-makers often find themselves preoccupied with maintaining domestic stability and social cohesion, leaving little bandwidth for long-term strategic planning, especially in emerging domains like artificial intelligence. This short-termism can lead to populist or reactive policies, further delaying the development of forward-looking frameworks necessary for building digital sovereignty.
This gap in perception leaves the door open for continued exploitation, underinvestment in data infrastructure, and weak bargaining positions in international tech negotiations. Building true sovereignty in the AI age begins with shifting this mindset.
Conclusion: A Matter of Digital Survival
The decolonization of AI is not an ideological luxury. It is a practical and moral necessity. Without it, the Global South risks becoming a passive testing ground and a digital resource mine—not a sovereign participant in shaping the future.
But the importance of decolonizing AI does not end in the Global South. For the Global North, this agenda is equally vital. When digital systems are built on unequal foundations, they fuel instability—political, economic, and social. Unjust technological deployment can aggravate horizontal conflicts, marginalization, and distrust in local institutions across the South. These fractures have spillover effects: forced migration, political radicalization, economic stagnation, and the collapse of markets that Global North actors depend on for labor, data, and investment.
Thus, decolonizing AI is not only a matter of justice, but also of long-term global stability. The risks extend beyond inequality—they also impact global security. If AI is weaponized by identity-based groups, terrorist organizations, or radicalized individuals, its impact could be even more catastrophic than that of nuclear weapons. Unlike nuclear arms, AI is accessible to non-state actors and individuals, making governance and oversight exponentially more difficult. The rise of open-source AI models amplifies this risk: while they make AI development more inclusive, they also lower the barriers for malicious use, enabling even lone actors to deploy advanced capabilities for harm. Such actors can manipulate public opinion through disinformation, disrupt democratic institutions, or even paralyze vital infrastructure—from power grids to financial systems.
These threats are not confined to the Global South; they reverberate globally, contributing to unpredictable instabilities and weakening both local and international trust architectures. A more equitable AI ecosystem minimizes the potential for conflict, builds more inclusive global value chains, and safeguards the very markets into which Northern innovation flows. It is in everyone’s interest to ensure that digital transformation is not extractive, but generative for all.
We must assert that the knowledge systems, ethical principles, and lived experiences of the Global South matter. And they must shape the technologies that will define the 21st century.
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