AI Unleashes the Earth's Secrets - Praxis
AI Unleashes the Earth’s Secrets

AI Unleashes the Earth’s Secrets

As the Earth transforms and we navigate the digital age, AI emerges as a powerful tool. Can it unlock the mysteries of climate change, or will private profit eclipse public good?


In the midst of navigating the consequences of the digital revolution and a swiftly evolving natural world, artificial intelligence (AI) emerges as a potential solution to untangle the complexities that have eluded our understanding. However, as research tools increasingly fall into the hands of industry, policymakers must actively ensure that these innovations contribute to public welfare.

A seismic shift in Earth Sciences is underway, highlighted by a groundbreaking study published in Nature in July. The study revealed that a neural network, representing AI, outperformed the European Center for Medium-Range Weather Forecasts, boasting the world’s most advanced forecasting system. Gone are the days of clunky weather models. Deep learning neural networks, like those from Google’s DeepMind and Huawei, are outperforming the world’s best forecasting systems. This AI revolution transcends simple equations, learning directly from massive datasets. The implications reach far beyond predicting rain: agriculture, energy, fire risks, and even global negotiations are poised for disruption.

Golden age of Earth observation

Traditional weather forecasting relies on initial conditions derived from point-in-time observations, employing equations based on physical principles. In contrast, AI processes data collected over extended periods, “learning” the dynamics explicitly described by traditional equations. Both methods employ supercomputers, but AI transcends the need for formally developed theories.

Unlike traditional models, AI embraces the messy complexity of Earth. Our data deluge, fueled by thousands of satellites and sensors, paints a hyper-detailed picture of our planet. From plant growth to infrared radiation, we’re witnessing a boom in Earth observation. This, combined with AI’s analytical prowess, could rewrite our understanding of Earth and our place within it.

The implications extend beyond weather forecasting, influencing areas such as aviation, maritime navigation, and risk management. While AI-driven forecasting may displace skilled labor, it also challenges established notions about the relationship between historical system knowledge and predictive accuracy, as highlighted by Norbert Wiener’s observations in the 1950s.

In recent years, our observational data of Earth has exponentially grown, with the number of Earth-observing satellites soaring from 25 between 1993 and 2003 to 997 between 2014 and 2022. This wealth of data, coupled with new AI models and expanding computational infrastructure, ushers us into a golden age of Earth observation.

Policy challenges

Examining climate change, traditionally addressed by the Intergovernmental Panel on Climate Change (IPCC), is set for disruption through AI. While unlikely to replace traditional climate modeling entirely, AI is already contributing significantly. Its agnostic approach could enhance our understanding of how biomass changes over time, aiding in forest and agriculture management, early-warning systems for natural disasters, and predicting economic and climate negotiation impacts.

However, this transformative shift also poses policy challenges, as private entities increasingly control the infrastructure driving AI innovations. High-tech companies, armed with substantial capital and resources, lead in machine learning advancements. Planet Labs dominates Earth observation satellites, and tech giants like IBM and Nvidia lead the AI charge. These well-resourced companies lack the obligation to serve public good, raising concerns about equitable access and profit-driven research agendas. Policymakers must navigate this landscape, ensuring that AI serves public interests and contributes to equitable access to infrastructure.

In confronting the complexities of the digital revolution and a changing natural environment, AI emerges as a key tool. Yet, with research tools predominantly in private hands, policymakers play a crucial role in ensuring these innovations benefit the public and align with countries’ legitimate policy goals.

The AI revolution in climate science isn’t just about technology; it’s about reshaping our relationship with Earth. Can we steer this powerful tool towards a sustainable future, or will it be lost in the pursuit of private gain? The answer lies in our collective vision and policy choices.


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