A maturing technosphere can achieve balance with the biosphere.

Ibrahim Rayintakath for Noema Magazine

Credits

Nathan Gardels is the editor-in-chief of Noema Magazine. He is also the co-founder of and a senior adviser to the Berggruen Institute.

In the next century, human civilization will likely look back from its singular planetary awareness upon today’s nationalist revivals and Great Power rivalries as the last hurrah of a lingering past still foolishly fragmented by its tribal origins.

Even as so many nations appear to be going their own way, embroiled in historically familiar trade wars and military conflicts, the simultaneous emergence of AI-driven planetary-scale computation is disclosing the imperative of forging a common future.

The material basis of this evolving consciousness is the technological exoskeleton of satellites, sensors and cloud computation, which is expanding the heretofore limited scope of human understanding of the world and repositioning our place in the natural order. The climate crisis this apparatus has unveiled is a window into the realization that we are neither above nor apart from nature, but part and parcel of one interdependent organism comprised of multiple intelligences striving for sustainable equilibrium.

The unprecedented capacity for insight into the interface with Earth systems, made possible by frontier technologies, promises to enable our species and others not only to survive, but also to flourish on the only planet we know of with a livable biosphere. In the near term, it will also empower us to predict threats resulting from Anthropocene overreach and design adaptive responses.

‘Earth AI’ & ‘Aurora’

Two recent developments from Google and Microsoft are embryonic stepping-stones in this direction.

Last month, Google launched its “Earth AI” platform. As described in an explanatory paper, “Geospatial data offers immense potential for understanding our planet. However, the sheer volume and diversity of this data along with its varied resolutions, timescales and sparsity pose significant challenges for thorough analysis and interpretation … Earth AI, a family of geospatial AI models and agentic reasoning, enables significant advances in our ability to unlock novel and profound insights into our planet. This approach is built upon foundation models across three key domains — Planet-scale Imagery, Population, and Environment — and an intelligent Gemini-powered reasoning engine.”

The paper continued: “When used together, they provide complementary value for geospatial inference and their synergies unlock superior predictive capabilities. To handle complex, multi-step queries, we developed a Gemini-powered agent that jointly reasons over our multiple foundation models along with large geospatial data sources and tools. On a new benchmark of real-world crisis scenarios, our agent demonstrates the ability to deliver critical and timely insights, effectively bridging the gap between raw geospatial data and actionable understanding.”

As the Berggruen Institute’s Nils Gilman further explains: “The ultimate goal of Earth AI is to help users answer complex, real-world questions that require multifaceted reasoning across diverse models and data bases. Such queries can be categorized into a hierarchy of increasing complexity:

1. “Descriptive and retrieval queries involving fact-finding (e.g., “What was the highest recorded temperature in New York in August 2020?”).
2. Analytical and relational queries seeking to uncover patterns between different data sources (e.g., “How many hospitals were located in areas experiencing severe storm conditions in the state of Louisiana when Hurricane Katrina came ashore?”).
3. Predictive or inferential queries involving forecasting new information (e.g., “Which Indian cities have the most vulnerable populations at high risk of being impacted by flooding by Nov. 25, 2027?”).”

In May, Microsoft scientists unveiled Aurora, a large-scale foundation model trained on more than one million hours of diverse geophysical data. As described in a paper published in Nature, “Aurora outperforms operational forecasts in predicting air quality, ocean waves, tropical cyclone tracks and high-resolution weather, all at orders of magnitude lower computational cost. With the ability to be fine-tuned for diverse applications at modest expense, Aurora represents a notable step toward democratizing accurate and efficient Earth system predictions. These results highlight the transformative potential of AI in environmental forecasting and pave the way for broader accessibility to high-quality climate and weather information.”

These developments are taking place in tandem with other exciting leaps, most notably Google’s new “Suncatcher” plan for “space-based computing” that will draw the vast energy needs of data centers from low-orbit clusters of solar panels, thus enabling compute to scale without further depleting Earth’s resources.

From Disequilibrium To Planetary Homeostasis

The incipient capacities of Earth AI and Aurora hold out the evolutionary prospect that human, machine and Earth intelligence might one day merge into what Gilman calls “planetary sapience”, wherein a maturing technosphere restores and maintains a homeostatic planetary balance rather than fosters a “disequilibriated or disruptive” relationship with the biosphere.

If we manage to make it through our present Age of Upheaval, what settles on the other side of the Anthropocene will be a sensibility far more in sync with the ecology of existence.

As we have written often in Noema, this conceptual reorientation will, in turn, entail a redefinition of what realism means in geopolitics as we have known it. The new condition calls not for the exhausted “realpolitik” that seeks to secure the interests of nations or blocs against each other, but for a new planetary realism, or “Gaiapolitik,” aimed at securing a livable biosphere for all.

It is a paradox of the long trajectory of human endeavor that technological progress will, in the end, not have distanced us from natural systems but further embedded and entangled us in them.

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