AI as a Common Good: Decolonial Neuroscience, Data, Pachamama, and DREX Citizen

Perhaps the most urgent question for adolescents today is not only: “How do we use artificial intelligence?” The deeper question is: who controls the intelligence that will organize the future?

AI is already entering schools, work, health, security, art, politics, and learning. It corrects texts, suggests paths, organizes data, predicts behaviors, automates decisions, and influences how we see the world. But there is a silent risk: if AI is controlled only by technological, financial, and political elites, it may become another layer of capture over the body, territory, and attention.

In the BrainLatam2026 perspective, AI should not be treated as a neutral machine. It reorganizes perception, time, language, desire, and decision-making. Before asking whether an AI is efficient, we must ask: does it increase Jiwasa or dependency? Does it expand criticality or capture behavior? Does it serve the territory or merely extract data from it?

UNESCO’s 2021 Recommendation on the Ethics of Artificial Intelligence is grounded in human rights, dignity, transparency, fairness, and human oversight. The OECD also updated its AI Principles in 2024, defending trustworthy AI systems that respect human rights and democratic values. These references are important, but Decolonial Neuroscience must go further: it is not enough to speak of abstract ethics; we must ask whether AI strengthens real belonging in territories.

A smart State is not a State that watches everything. It is a State that uses technology to reduce abandonment, improve care, protect data, qualify public policies, and return power to citizens. The OECD shows that smart cities generate large volumes of real-time data and that data governance is decisive for efficient, trustworthy, people-centered public services.

Here enters the idea of AI as a common good. Data from health, education, territory, climate, mobility, and security should not be treated merely as digital oil for companies. They are traces of the social body. They are signals of Jiwasa. When a child drops out of school, when a family cannot access health care, when a woman cannot find protection, when a young person enters Zone 3, those data should not serve only cold statistics. They should activate care, prevention, and shared agency.

The decolonial critique is this: many technologies call themselves “intelligent” but still operate through colonial language. They classify, rank, predict, and control isolated individuals. Few ask about APUS, territory, Jiwasa, brain formation, hunger, sleep, fear, shame, family history, and absence of belonging. AI sees patterns, but it does not always see life.

This is where Pachamama changes the question. If Earth is a living body, data cannot be treated as dead resources. Data emerge from bodies, streets, schools, territories, accents, movements, relationships, memories, clicks, images, and ways of living. When a platform collects attention, language, location, consumption, and behavior from a population, it extracts value from a living territory. In the language of this block, this is mining the digital APUS.

Bribri prosperity helps illuminate this direction. Among the Bribri of Talamanca, Costa Rica, agroforestry practices sustain biodiversity, culture, and community ways of life. The logic is not to prosper by destroying territory, but to maintain life, forest, food, autonomy, and cultural continuity. Prosperity, in this sense, is not infinite accumulation; it is living territory that continues generating future.

That is why AI as a common good must include a question almost nobody asks today: who pays the territory for data mining?

Just as land, water, and forests were exploited without fair return to the peoples who sustained those territories, data can now be extracted without proportional return to the communities that produce them. The difference is that now the mine is not only in the soil. It is in attention, language, and behavior.

A municipal policy for AI as a common good could create a territorial contribution on data mining carried out by large platforms and algorithms that profit from the local population. These resources could form a Municipal Fund for Territorial Prosperity, dedicated to four axes: education, health, citizen defense, and environmental regeneration.

In education, the fund would finance critical training in AI, science, data, body, territory, handwriting, sleep, capoeira, Jiwasa, and Brain Bee. In health, it would support prevention in mental health, sleep, early childhood, pregnancy, postpartum, belonging, and community care. In citizen defense, it would protect children, adolescents, women, older adults, and vulnerable territories. In regeneration, it would finance reforestation, agroforestry, water, adaptation to urban heat, and carbon credits.

Here Pachamama stops being only symbol and becomes a criterion for public policy. If Earth is a living body, and if data are traces of the social body, then the digital economy must return energy to territory. Recent research on Rights of Nature shows that legal personality and guardianship models for ecosystems have gained strength as attempts to protect rivers, forests, mountains, and other nonhuman beings, although debates remain about effectiveness and implementation.

In this model, the city hall would not be merely an administrator of property taxes, traffic, and infrastructure. It would act as a guardian of the physical and digital territory. Just as we discuss environmental impact, land use, and local economic exploitation, we must also discuss algorithmic impact, data extraction, and territorial return.

This does not mean the city hall should own people’s data. On the contrary. The proposal requires data protection, transparency, public auditing, social participation, and the right to contest decisions. The city hall should not capture data; it should prevent the population from being captured by those who mine data without returning prosperity to the territory.

Brazil already shows that this debate is real. In 2024, the National Data Protection Authority suspended Meta’s policy that would allow the use of Brazilian personal data to train generative AI, citing risks to fundamental rights. Later, Meta informed Brazilian users about data use and opt-out mechanisms. This shows that data are not free raw material: they are part of social life and require public governance.

This is where DREX Citizen enters as metabolism. If large platforms extract value from the local digital APUS, part of that value can return to citizens and territory through public funds, municipal policies, and transparent digital mechanisms. DREX Citizen allows us to imagine money being born or returned to citizens not as debt, but as energy of belonging.

AI, in this scenario, could help calibrate public policies with transparency: where health is lacking, where schools need support, where the territory is heating too much, where dropout is growing, where violence prevents belonging, where youth are being captured by algorithms. But this only makes sense if AI is under democratic governance, with human oversight, auditing, territorial participation, and protection of vulnerable populations.

In Jiwasa mode, AI should help teachers, students, families, managers, and communities perceive together where the social body is in Zone 2 or Zone 3. Not to punish, but to care better. A school could use data to identify overload, dropout, sleep difficulties, territorial violence, and lack of belonging. But these data must be protected, auditable, and oriented toward the common good — never used to humiliate, exclude, or sell behavior.

AI cannot become the new owner of the cardboard. In the Island of 1000 blog, we saw that the problem begins when whoever cuts the papers starts controlling the collective. Now the risk is greater: whoever controls data, models, and algorithms may control the pixels of social life. Therefore, the political question is simple: will AI be a tool of Jiwasa or a tool of capture?

For adolescents, this discussion is essential. Youth should not be trained only to “use AI.” They must learn to ask: who trained this model? With which data? Who profits? Who becomes invisible? Which territory was ignored? Which body was reduced to a number? Which decision should remain human? And above all: if a platform profits from the data of our territory, why does the territory not receive part of that value to care for its children, schools, health, security, and environmental regeneration?

AI as a common good must form young people capable of using technology without losing body, territory, and criticality. Before becoming a prompt, the adolescent must remain breathing, hand, sleep, dream, circle, capoeira, writing, friendship, APUS, and Jiwasa.

The future will not be decided only by whoever has the most powerful AI. It will be decided by whoever can prevent AI from separating intelligence from belonging.

In Decolonial Neuroscience, intelligence is not only predicting patterns. It is caring better for life. It is perceiving when the social body is in defense. It is creating conditions for Zone 2. It is preventing data from becoming a commodity against the people who produce them. It is making technology, State, economy, and territory compose as shared agency.

AI as a common good is this: not a machine above us, but a tool inside Jiwasa. An intelligence that does not replace “we,” but helps “we” see more clearly where life needs care.

There is no ethical AI if the territory that produces the data remains poor, sick, and without belonging.

References

UNESCO. Recommendation on the Ethics of Artificial Intelligence, 2021.
OECD. AI Principles, adopted in 2019 and updated in 2024; Smart City Data Governance, 2023.
Banco Central do Brasil. Institutional materials on Drex and the Drex Pilot.
Reuters. Coverage of Brazil’s National Data Protection Authority action regarding Meta’s use of Brazilian data for AI training, 2024.
Mongabay. “For Costa Rica’s Indigenous Bribri women, agroforestry is an act of resistance and resilience,” 2021.
Rodríguez Valencia, M. “The Practice of Co-Production through Biocultural Design,” Sustainability, 2020.
Kahui, V. et al. “Comparative analysis of Rights of Nature case studies,” 2024.
Weis, L. K. “Does Nature Need Rights?”, Oxford Journal of Legal Studies, 2025.
AP News. Coverage of legal personhood recognition for Taranaki Maunga, 2025.
Damasio, Antonio. Feeling & Knowing: Making Minds Conscious, 2021.
Escobar, Arturo. Pluriversal Politics: The Real and the Possible, 2021.
Haesbaert, Rogério. “Do corpo-território ao território-corpo (da Terra),” 2020.
De Felice, Silvia et al. “Relational Neuroscience: Insights from Hyperscanning Research,” 2025.
Grasso-Cladera, Aitana et al. “Embodied Hyperscanning for Studying Social Interaction,” 2024.