Artificial inequalities
After analysing how AI reconfigures power relations within companies and reshapes skill fractures, it is now time to examine the new forms of inequality it generates at the socioeconomic level. These inequalities, which transcend the organisational sphere, are articulated around the concept of artificial inequality developed by Chakravorti. In a 2025 paper, the author warns that AI’s potential to exacerbate existing disparities in contemporary societies lies in its ability to concentrate opportunities in certain socioeconomic groups and exclude others. This dynamic, he points out, limits equitable access to resources and deepens structural gaps. According to Chakravorti, six divisions contribute to the formation of this artificial inequality:
- Data can discriminate, generate biases, and even produce false or incomplete information,
- Income, as the use of AI, can increase the productivity of some workers while replacing others, leading to income and job losses,
- Use, because people with access to education and economic resources are more likely to trust and use AI tools,
- Geography, according to the IMF, the productivity and income gains linked to AI will mainly benefit high-income countries, which risks accentuating inequalities on a global scale,
- Industry, because it is dominated by a small group of companies that limit new entrants to the AI sector, creating an oligopoly,
- Energy, since AI has high energy and water demands, this likely contributes to energy poverty, as energy systems tend to be concentrated in richer socioeconomic spaces, leaving people without access to water or energy behind.
Giving these divisions importance is essential, as Chakravorti suggests; companies must take responsibility for reducing artificial inequality to ensure an ethical use of AI that does not harm vulnerable populations.
Data, uses, geography, industry and energy resources are crossed by other forms of technological, economic, geopolitical and institutional power. AI transforms these relationships by centralising control of knowledge, optimising resource allocation, and redefining the global distribution of power.
Multiple power dynamics thus shape these six axes. Technological power is wielded by those who control digital infrastructures and AI systems, determining how data is collected, processed, and used. Economic power is concentrated in industries capable of integrating AI to optimise their processes and dominate markets. Geopolitical power, in turn, influences the unequal distribution of energy resources, connectivity and talents on a global scale. Finally, institutional power intervenes in the regulation or deregulation of access, sustainability, and equity in these areas (Montes, 2024; UNDP, 2023).
Thus, artificial inequality is not only the result of technology, but of the interaction between AI and pre-existing power structures that are reinforced, reconfigured, or displaced by its adoption. Understanding this interdependence is key to anticipating risks and designing strategies that allow AI to contribute to inclusion, rather than deepen inequalities.
0 Comments