he impact, intensity and frequency of climate change risks are becoming more profound and unprecedented than ever before. According to the 2025 Global Risks Report by the World Economic Forum extreme weather events, biodiversity loss and ecosystem collapse, critical change to Earth systems and natural resource shortages will be the highest-ranked global risks within the next ten years in terms of severity. The main cause of this perpetual climate change is the unsustainable anthropogenic and economic systems that embed the extractive principles of industrial modernity.
The recent announcement by Nvidia regarding its new AI–powered generative foundation model cBottle that can enable simulations on Earth’s global climate with an unprecedented level of resolution is a stark reminder of the pivotal role emerging and data–led technologies can play in terms of mitigating climate change and its effects. Nvidia’s Climate in a Bottle model can compress the scale of Earth observation data 3,000 times and transform it into ultra–high–resolution, queryable and interactive climate simulations. Researchers may be able to predict conditions far ahead into the future, leveraging cutting–edge precision and predictive capabilities. At the same time, a philosophical dive into this technological advancement unveils the blurry lines between authoritative outputs and probabilistic reasoning of climate knowledge within the new world of synthetic certainty. Let’s not forget that such projections are still based on uncertain variables (e.g. emissions, climate sensitivity).
The imminent threat of climate change paves the way towards a new epistemic era—epistemology referring to our relationship with knowledge, how it is gathered, what knowledge is valid, and the scope of that knowledge. In this new era, data–led emerging technologies do not just reflect the world; they can help generate plausible futures and develop powerful solutions capable of tackling climate change, at both micro and macro levels. The responsible deployment of emerging technologies could alter the existing systemic foundations of climate change (anthropogenic economic activity) and ease the structural inertia embedded within the prevailing global economic and political systems. Emerging technologies should be contextualized not only as mitigation vehicles but as facilitators of a shift in how we envision the relationship between humanity and the planet Earth.
Climate futures are not anymore abstract warnings. Scientific advancements driven by the powerful nature of data and emerging technologies make alternative climate futures visually immersive and simulated. However, overreliance on technological representations and highly–detailed projections created by computational systems raises ethical and epistemological concerns. Epistemology must remain democratized and foundational climate models must embrace predictive assurance despite the underlying complexity and unpredictability of real-world climate change. This reconfiguration may redefine how we relate to one another and our environment.
a global affairs media network
Tech–driven climate models bring mitigation hopes, ethical dilemmas
Image via Adobe Stock.
September 10, 2025
AI–powered climate models promise unprecedented predictive power and new tools for mitigation. Yet they raise ethical and epistemological dilemmas about certainty, authority, and how humanity envisions its relationship with the planet, writes Dimitrios Salampasis.
T
he impact, intensity and frequency of climate change risks are becoming more profound and unprecedented than ever before. According to the 2025 Global Risks Report by the World Economic Forum extreme weather events, biodiversity loss and ecosystem collapse, critical change to Earth systems and natural resource shortages will be the highest-ranked global risks within the next ten years in terms of severity. The main cause of this perpetual climate change is the unsustainable anthropogenic and economic systems that embed the extractive principles of industrial modernity.
The recent announcement by Nvidia regarding its new AI–powered generative foundation model cBottle that can enable simulations on Earth’s global climate with an unprecedented level of resolution is a stark reminder of the pivotal role emerging and data–led technologies can play in terms of mitigating climate change and its effects. Nvidia’s Climate in a Bottle model can compress the scale of Earth observation data 3,000 times and transform it into ultra–high–resolution, queryable and interactive climate simulations. Researchers may be able to predict conditions far ahead into the future, leveraging cutting–edge precision and predictive capabilities. At the same time, a philosophical dive into this technological advancement unveils the blurry lines between authoritative outputs and probabilistic reasoning of climate knowledge within the new world of synthetic certainty. Let’s not forget that such projections are still based on uncertain variables (e.g. emissions, climate sensitivity).
The imminent threat of climate change paves the way towards a new epistemic era—epistemology referring to our relationship with knowledge, how it is gathered, what knowledge is valid, and the scope of that knowledge. In this new era, data–led emerging technologies do not just reflect the world; they can help generate plausible futures and develop powerful solutions capable of tackling climate change, at both micro and macro levels. The responsible deployment of emerging technologies could alter the existing systemic foundations of climate change (anthropogenic economic activity) and ease the structural inertia embedded within the prevailing global economic and political systems. Emerging technologies should be contextualized not only as mitigation vehicles but as facilitators of a shift in how we envision the relationship between humanity and the planet Earth.
Climate futures are not anymore abstract warnings. Scientific advancements driven by the powerful nature of data and emerging technologies make alternative climate futures visually immersive and simulated. However, overreliance on technological representations and highly–detailed projections created by computational systems raises ethical and epistemological concerns. Epistemology must remain democratized and foundational climate models must embrace predictive assurance despite the underlying complexity and unpredictability of real-world climate change. This reconfiguration may redefine how we relate to one another and our environment.
