Today Darío Gil takes the centre of the radar, but he does not appear alone. His Genesis Mission makes it possible to read artificial intelligence as state infrastructure, while Philippe Descola, Eduardo Viveiros de Castro and Veena Das offer three anthropological keys for thinking about what world that infrastructure makes visible, what universals it reproduces and how it is then inscribed in everyday life.

Darío Gil and AI as national infrastructure

Darío Gil was born in Murcia and grew up in Madrid. He then trained in the United States, first in California, later as an engineer at the Stevens Institute of Technology and finally as a doctor at MIT. That Spanish origin and that transatlantic educational trajectory help us read his figure not only as a success story, but as a symptom of an institutional difference: what happens when a scientific career is inserted into a system capable of articulating universities, national laboratories, companies and public funding on a large scale. The El País profile reconstructs that origin and his early move to the United States, while Stevens recalls his training in electrical engineering and the DOE presents him as Under Secretary for Science. (El País, Stevens Institute of Technology, Department of Energy)

The Genesis Mission does not present artificial intelligence as a simple office tool, nor as just another conversational application. It presents it as national infrastructure. A platform to connect laboratories, universities, companies, supercomputers, scientific data, artificial intelligence and quantum computing.

The Department of Energy has identified 26 major science and technology challenges linked to this mission. Energy, national security, new materials, electricity grids, quantum computing and scientific discovery appear as fields where AI must accelerate processes, coordinate institutions and reorganise research. The DOE has also presented a funding line of 293 million dollars for interdisciplinary teams linked to the mission.

Here the anthropological question begins. It is not only about whether this infrastructure will work. It is about asking what kind of world is fabricated by a science organised around AI, security, energy and geopolitical competition.

Descola and the ways of making a world visible

Philippe Descola helps us look at another dimension of the problem. In his recent conversation in Theory, Culture & Society, “From Image to Structure: A Dialogue with Philippe Descola”, he returns to the ways of making a world visible, to images, figurations and the modes in which different ontologies order the real.

From there, generative AI is not only a machine that produces texts or images. It is a machine that learns to show the world in certain ways. It decides, statistically, which relations become visible, which bodies appear, which landscapes are repeated and which forms of life are left out of frame.

Viveiros de Castro and the critique of modern universals

Eduardo Viveiros de Castro introduces another counterpoint. His interview “Reanimating Animism”, also in Theory, Culture & Society, insists that there is no single modern way of defining intelligence, nature or the relationship between humans and non-humans. Animism appears as a critique of modern universals and as a way of thinking worlds that cannot be reduced to our categories.

That idea is crucial for thinking about AI. Many digital infrastructures are trained as if there were a single world, a single rationality and a single legitimate form of knowledge. Viveiros de Castro allows us to invert the question. Perhaps the problem is not that AI does not yet understand “culture”, but that it is usually built from a tradition that turns its own universals into a technical system.

Veena Das and ordinary life after harm

Veena Das takes the radar to another scale. In the interview “Veena Das interviewed by Paul Standish”, published in the Journal of Philosophy of Education, she returns to one of her great concerns: how violence, the event and harm are inscribed in ordinary life. It is not only the great event that matters, but what happens afterwards, in the gestures, the institutions, the forms of care and the everyday ways of going on living.

Applied to artificial intelligence, this shifts the gaze considerably. AI should not be studied only at the moment of launch, investment or political announcement. We must follow it afterwards, when it enters the school, the hospital, the administration, the laboratory, work and daily life.

Closing

In this radar, Darío Gil represents something more than an institutional figure. He represents the shift from AI as product to AI as political infrastructure.

Genesis Mission does not organise only machines. It organises priorities. It orders problems. It connects data. It selects possible futures.

Anthropology does not have to reject that agenda automatically, but it does have to ask uncomfortable questions. Who defines the great scientific challenges? What forms of knowledge enter the platform? What forms of knowledge are left out? What happens when public science is reorganised around productivity, national security and technological leadership?

Descola reminds us that every system makes a world visible. Viveiros de Castro warns us against universals that present themselves as neutral. Veena Das forces us to look at the ordinary effects after the great announcement. And Darío Gil shows us that AI is already entering a new phase, where technique, state, science and geopolitics become inseparable.

Perhaps that is today’s central question. Not only what artificial intelligence can do, but who organises it, with what institutions, from what idea of the world and with what consequences for life in common.

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