What is the Genesis Mission and why does it worry Europe?

The call Genesis MissionThe project, recently launched by the White House, has become central to the international debate on artificial intelligence, science, and geopolitical power. The project aims to reorganize the way scientific knowledge is generated in the United States, and by extension, to to set the pace for the rest of the world in the race for global technological dominance.

While in Washington there is talk of a an initiative on par with the great milestones of the 20th centuryIn Europe—and especially in Spain—people are observing with a mixture of interest, caution, and some unease how this massive commitment to AI applied to science It can redefine who leads the knowledge economy in the coming decades.

What is the Genesis Mission really?

The Genesis Mission is an executive order signed by US President Donald Trump that proposes a coordinated national effort to apply artificial intelligence to scienceThe administration itself describes it as a project “comparable in urgency and ambition to the Manhattan Project,” the secret program that led to the first atomic bomb, and as “the largest mobilization of federal scientific resources since the Apollo program".

This is not a new laboratory or an isolated research center, but rather a data, computing, and partnership architecture designed to transform the US scientific system.

The underlying idea is to create a kind of national “scientific brain”: to integrate all scientific data generated with public funds into a single platform, connect them with the power of the Department of Energy's federal supercomputers, and add the research capacity of universities, national laboratories, and large technology companies.

The stated objective is accelerate discoveries in fields such as biomedicineenergy, new materials, robotics, or quantum computing, using Advanced AI models that are capable of detecting patterns, proposing hypotheses, and optimizing processes on a scale impossible for human teams. on their own.

In the words of its promoters, the magnitude of the project could trigger a real “knowledge industrial revolution”By unifying decades of scattered data and combining it with supercomputing capabilities and state-of-the-art AI models, the aim is to drastically shorten the timescales of scientific research: what now takes years or decades to discover could be reduced, at least theoretically, to a few months.

A centralized platform at the service of AI

The executive order outlines a federal platform for public-private partnerships which places major technology companies at the heart of the project. Companies like OpenAI, Google, Microsoft, Meta, Anthropic, Nvidia, and SpaceX are among the preferred partners, both to contribute computing infrastructure and AI technology and to co-develop advanced scientific applications based on next-generation agents and assistants.

The plan involves integrate federally funded scientific databases And by centralizing the computing power of the 17 US National Laboratories, plus the data centers operated by major companies in the sector. In practice, this means concentrating a large portion of strategic US data—from health and biotechnology projects to climate simulations, energy research, and high-energy physics experiments—into a single AI architecture.

This new infrastructure will rely on the next generation of AI agents and assistantsThese systems are capable of executing complex task sequences with minimal human intervention. Beyond everyday uses—such as managing reservations or automating consumption processes—they will be deployed in high-impact areas: designing new drugs, discovering industrial catalysts, optimizing energy networks, and advanced natural disaster prediction, among other fields.

The order itself states that it will be the federal government that Select the companies that will participateDetermine access to data and infrastructure and define policies regarding intellectual property, licenses, trade secrets, and commercialization methods for the results. In this way, the Genesis Mission also functions as a powerful industrial policy, wrapped in a national security discourse, which reinforces the position of a few companies and consolidates their influence over the American scientific and technological ecosystem.

Race against China and risk of concentration of power

The Genesis Mission is openly framed within the strategic competition with China for the dominance of artificial intelligence and cutting-edge technologies. The order itself makes this clear: the United States considers itself to be in a race for global leadership in AI and sees the initiative as a response to the rapid advances of the Asian giant, both in scientific output and patents, as well as in robotics, autonomous mobility, and AI systems integrated into industry and infrastructure.

In recent years, China has installed hundreds of thousands of industrial robots equipped with intelligent systems and has developed AI models that, according to some analysts, They have acted as a technological “Sputnik”. by demonstrating that open architectures can outperform closed ones. The restrictions imposed on Chinese scientists and companies have spurred the strengthening of a more self-sufficient ecosystem of their own, which now competes head-to-head with major American and European players.

In that context, the Genesis Mission is interpreted as a form of regroup public and private resources To maintain the US advantage and, incidentally, sustain an economy heavily reliant on speculative investment in AI. Seven major tech companies dominate the national and global market capitalization, with valuations that have skyrocketed precisely because of their bets on artificial intelligence and the gigantic data centers they are building. The problem is that a significant portion of these investments has yet to translate into clear profits, which many experts describe as a new bubble reminiscent of the dot-com bubble.

Beyond the economic dimension, the project opens a delicate front: concentration of scientific and data power in the hands of a very small number of actors. Whoever controls the Genesis Mission platform, some analysts argue, will control what is researched, what is prioritized, and what remains hidden. And in a world where knowledge is the main economic and geopolitical engine, that decision-making power largely equates to controlling key levers of global power.

Warnings about governance, transparency and ethics

Voices from academia and the international scientific community have begun to focus on the risks of a centralized data and AI mega platform that it depends on the political and corporate interests of a single country. The fear is that, under the promise of democratizing access to knowledge, the greatest concentration of scientific power in recent history will end up being consolidated, with the capacity to guide the global research agenda.

Authors who have studied the collective intelligence and distributed systems They point out that when information is concentrated in few hands, deep gaps open up between those who control the data and those who depend on it.Instead of fostering open and collaborative ecosystems, the risk is creating "knowledge deserts" in large regions of the planet, where institutions lack real access to the data and computing power needed to compete on a level playing field.

From the perspective of the scientific method, fundamental questions also arise. Science is not just about finding patterns in enormous databases; it demands detect anomalies, question previous assumptions, choose between rival theories and to convince a community of experts through open discussion and peer review. Transferring too much decision-making power to opaque AI systems, trained on previous research, can reinforce established fields and overshadow emerging ideas, which typically start with less data, fewer citations, and less funding.

Researchers like Akhil Bhardwaj point out that major success stories in scientific AI, such as AlphaFold in structural biology, work because They are integrated into people-led ecosystemswhere human teams supervise, validate, and correct. Their proposal is clear: The Genesis Mission should conceive of AI as a set of powerful tools at the service of the scientific communitynot as an autopilot making decisions about what to investigate, how to interpret the results, or what to translate into public policy.

Similarly, experts in nanotechnology and technology transfer insist that the final decision on what to investigate and how to apply the findings must remain in human hands. Delegating critical tasks to opaque models can encourage subtle errors, scientific “hallucinations,” or biases that, once propagated in the literature, would be very difficult to correct. The rise of the so-called “AI Slop"—low-quality scientific content generated by AI— illustrates the magnitude of the problem."

Faced with this scenario, the solution proposed by many scientists involves strengthening the Open science, traceability, and independent auditing of AI systems used in research. It is demanded that the models, data, and decision-making processes be auditable, with clear rules of public governance and effective mechanisms of democratic control, so that private interests cannot silently impose their agenda over the common good.

The European response: its own model of scientific AI

In Europe, the launch of the Genesis Mission has reignited the debate about the continent's role in the global race for AI. For researchers like Javier García Martínez, director of the Molecular Nanotechnology Laboratory at the University of Alicante and an international authority on technology transfer, “Europe cannot afford to fall behind, because our economic future depends on leadership in AI.The point, he clarifies, is not to copy the American initiative, but design a major European strategy aligned with its values.

The European Commission has begun to make moves with a two-pronged roadmap: on the one hand, Expanding AI in industry and public administration; for another, to make Europe an AI-powered science powerhouseThe core of this scientific component is RAISE, a virtual institute tasked with coordinating data, computing power, and talent so that the European researchers can make the most of artificial intelligence in areas such as health, climate, or energy.

The community plan foresees investments of 58 million euros to attract and retain AI experts, more than 600 million to improve access for researchers and startups to supercomputers and future “AI gigafactories”, and a Doubling of annual AI effort within the Horizon Europe program, that This would exceed 3.000 billion eurosOne of the stated priorities is to identify strategic data gaps and build the high-quality datasets that scientific AI needs to be useful and reliable.

García Martínez, who coordinated the report A roadmap for innovation in complex times (INTEC 2025) For the Rafael del Pino Foundation, it is emphasized that AI has been a cornerstone of many research areas for decades. From large telescopes to particle accelerators, scientific teams They generate unmanageable volumes of data without sophisticated algorithmswhich allow finding patterns, simulating complex scenarios, and accelerating the transition from discoveries to market.

The examples are multiplying: thanks to AI, abaucine has been discovered, one of the few antibiotics capable of fighting one of the superbugs which the WHO considers a critical threat due to its resistance to existing drugs. In the field of materials, companies like Kebotix and the German firm ExoMatter use predictive AI models to identify industrial catalysts, which they then license directly to companies, significantly shortening innovation cycles. These types of cases demonstrate that AI not only accelerates scientific discovery but also strengthens the competitiveness of those who integrate it into their processes.

Spain's role and the need for coordination

In a possible European version of the Genesis Mission, Spain could play a significant roleThe presence of world-class supercomputing infrastructure, such as MareNostrum 5 in Barcelona, ​​puts the country in an advantageous position to become one of the main nodes of a European AI network applied to science. This would give Spanish and European teams access to cutting-edge computing resources, essential for competing with major American and Chinese projects.

However, having supercomputers is not enough. The real challenge, as several experts point out, is effectively coordinate resources, talent and scientific capabilitiesEurope has top-level researchers, leading universities and benchmark technology centers, but it often suffers from fragmentation, excessive bureaucracy and difficulties in transferring discoveries from the laboratory to the productive sector with the speed that global competition demands.

The journalist and AI ethics expert Idoia Salazar, co-founder of the Observatory of the Social and Ethical Impact of Artificial Intelligence (OdiseIA), insists that “it would be unethical not to take full advantage” of AI applied to European data. As she explains, Europe has the technical capacity, the infrastructure, and a valuable ethical heritage which could become a practical framework for promoting more responsible science. But to achieve this, he warns, it is necessary to reduce the obstacles and bureaucracy that still hinder many projects, and to make a clear commitment to AI that strengthens the scientific quality of the continent.

Salazar and other specialists believe that the success of a European strategy depends on agile governance structurescapable of adapting to the speed at which AI evolves. Current models, based on very traditional procedures, risk failing if they are not updated quickly. In a scenario where AI agents will become increasingly autonomous in performing complex tasks, regulatory and supervisory frameworks cannot afford to always be several steps behind.

Towards a global, open and democratically controlled mission

In contrast to the American approach, marked by centralization and the leadership of a few large companies, many European researchers argue that a global knowledge mission based on AI should be open, cooperative, decentralized and interoperableInstead of a single national megaplatform, They are committed to an international network involving laboratories, universities, public centers, and scientific communities share data under common standards and distributed governance systems.

This model would fit better with the European tradition of open science, protection of fundamental rights and democratic controlThe idea is not to abandon ambition or scale, but to build an alternative that combines the power of AI with robust safeguards for transparency, oversight, and equitable distribution of benefits. This means, among other things, that key decisions regarding research priorities, the use of sensitive data, or the commercialization of results should not be left exclusively in the hands of a small group of companies or a single government.

Unlike the American approach, perceived by many as a “anything goes” where The red lines are not always clear.Europe has the opportunity to offer a different path, drawing on its regulatory experience and a culture that values ​​the balance between innovation and rights. To achieve this, future European scientific AI initiatives must require transparent, traceable, and auditable systems, and the rules of the game must prevent private interests from opaquely influencing the global agenda.

In both the US and Europe, the key will be that Let humans provide direction, purpose, and an ethical framework to artificial intelligence. If the Genesis Mission ends up serving as inspiration for the rest of the world to pursue more open, responsible, and cooperative scientific AI projects, humanity could be on the verge of a qualitative leap in its capacity to understand and transform reality. If, on the other hand, it becomes a new symbol of concentrated power and inequality in access to knowledge, the risk is that the next great technological revolution will leave many more behind than we imagine.