AI and the Fight Against Poverty: Friend or Foe?

How will the fight against poverty evolve when humans become obsolete? Many experts point to Universal Basic Income (UBI) as the obvious solution. UBI would function as a guaranteed periodic payment to all citizens, regardless of work, offering economic security in the face of the growing replacement of human labor by machines. Poverty, at its core, is the condition of lacking sufficient resources to meet basic needs for survival, dignity, and full participation in society.

UBI addresses the first of these needs, but to what extent does it resolve the second and third? If poorly designed, UBI risks turning citizens into chronic dependents of the state or corporations, weakening their freedom by reducing incentives for personal development and economic autonomy. By eliminating the need to cultivate human capital—skills, knowledge, and resilience—UBI can erode the dignity derived from conscious, active contributions to society. Without human capital, even with guaranteed income, full participation becomes an illusion: there is no voice, relevance, or real power of choice.

A commonly proposed solution to mitigate the effects of automation and AI on employment is massive investment in reskilling. Yet this assumes that the pace of human learning can keep up with the exponential advance of technology—an increasingly untenable assumption. If reskilling programs were already struggling to make an impact before the rise of AI, expecting them to now suffice in both scale and speed ignores the widening imbalance between human and machine capacity.

The belief that “technology has always created more jobs than it destroyed” overlooks the unprecedented asymmetry of the AI era: displacement is exponential, while job creation is slow, elitist, and barely scalable. What was once a painful but compensatory transition could now become a structural and permanent rupture of the traditional labor market. Blindly betting on the repetition of the past is to deny the uniqueness of the present.

The idea that AI will solve poverty through the “democratization of knowledge” is a comforting narrative for tech elites but detached from reality. Poverty is not ignorance—it is systemic failure. Technological education only flourishes when there is a material, institutional, and emotional foundation. Without this, we end up handing out tablets to people who lack sanitation, security, food, and respect. Democratizing knowledge without democratizing dignity simply perpetuates a new form of exclusion, now wrapped in an elegant interface.

The belief that human-centric skills can be the great equalizer in the AI era is well-intentioned but flawed. These skills do not spontaneously emerge in barren ground—they flourish in environments of support, stability, and opportunity. By ignoring how poverty erodes the soil of human dignity, this thesis transforms a potential path of inclusion into yet another polished form of exclusion. If we truly want human skills to be universal, we must first ensure the basic conditions for them to grow.

The idea that progressive public policies will shape the positive impact of AI ignores geopolitical reality. In a world where global powers compete for digital supremacy, ethics and social justice become vulnerable to strategic pragmatism. Without a binding and effective global agreement—which has never been achieved even for climate change—isolated national policies may be not only ineffective but also detrimental to the economic sovereignty of nations attempting to lead responsibly.

The fight against poverty in the age of AI cannot rely on the tools of the past. We must stop treating the symptoms—such as the absence of income—and begin addressing the causes: lack of dignified infrastructure, extreme concentration of value, and institutional obsolescence. AI will only become a friend of social justice if accompanied by a profound reengineering of economic, urban, legal, and political systems. Without this, it will merely be the elegant face of a more efficient exclusion.

“Extreme concentration of value” is the new name for inequality on an algorithmic scale. Whereas capital once resided in banks, factories, or land, today it lies in data, AI models, and the control of the platforms that operate them. Combating poverty and ensuring dignity in the AI era, therefore, requires solutions to this asymmetry that go beyond mere income redistribution.

Institutional obsolescence is the rusted gear at the core of the global public machine. We can have UBI, AI, reskilling, and infrastructure, but if we continue to operationalize the future with the systems of the past, we will fail. Poverty, inequality, and geopolitical instability are visible symptoms of institutions that refuse to reinvent themselves because doing so requires relinquishing power. True disruption is not technological—it is political. Reimagining governance, representation, and public administration is the next inevitable step—or it will be imposed by collapse.

The greatest threat of AI is not human obsolescence—it is the obsolescence of the structures that govern human life. Rather than forcing solutions into outdated systems, we must create space for the controlled emergence of new ones. City 5.0 and AGE-Zones (Autonomous Governance Experimental Zones) are not utopias; they are living laboratories where the future can be tested responsibly. We need a world that allows a thousand models of society to flourish so we can discover which ones truly work. The risk does not lie in the boldness of trying—it lies in the cowardice of preserving what has already failed.

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