Rebecca Brown is president and CEO of the Center for International Environmental Law. Lien Vandamme is its senior campaigner on human rights and climate change.
The world doesn’t just need stronger climate targets. It needs a fairer, faster and more accountable multilateral system to deliver climate action.
This November, with the world gathered in Belém, Brazil, for COP30, the negotiations unfold against a backdrop of a deepening climate crisis and rising frustration with the slow pace of progress.
These talks matter because the UN climate process is the world’s best platform for much-needed global action on the climate crisis. But after three decades, the process must evolve to meet the moment – which means changing the rules that too often delay action, dilute ambition and disconnect decisions from science, equity and the law.
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Powerful countries use procedural deadlock to block ambition. Polluting countries and corporations exert influence to protect their interests and weaken outcomes. And too often, the people most affected by the climate emergency are sidelined or excluded from the decisions that affect them the most.
Given its global nature, effective multilateralism is the only way out of the climate crisis. At COP30, leaders have a choice to continue with the status quo or revise the rules to deliver climate justice.
Reform of UN climate talks
The case for reform is undeniable.A systemic lack of compliance and accountability demands a serious, good-faith effort to reform the system.
For example, this year was supposed to mark a milestone, as all countries were expected to submit their new plans – known as Nationally Determined Contributions (NDCs) – to scale up their ambition, bringing us closer to truly limiting warming to 1.5°C. But around half of the plans have yet to arrive.
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Many of the plans that have been submitted largely missed the mark to keep warming below the legal limit of 1.5C. They avoid the one measure that science demands: an explicit fossil fuel phaseout. And the financing that developing countries need to raise ambition in their climate plans remains scarce.
Reforming the UN climate talks is therefore not procedural housekeeping; it is climate action. Without reform, the best science and strongest legal obligations will continue to collide with an outdated process. With reform, we can accelerate the phase-out of fossil fuels, deliver real finance at scale and protect human rights.
Principles for reform
Efforts are already underway. Calls for reform are coming from inside and outside the process: from civil society and experts to former negotiators and even the UNFCCC executive secretary and the COP30 presidency.
States are also testing the waters, with a recent call from Panama to allow for majority decision-making and Vanuatu naming the need for additional architecture to force states to comply with their obligations. The momentum is real.
But to succeed, this reform must be grounded in a few basic principles.
First, voting needs to be possible when consensus fails. When one or two holdouts block the ambition the world needs, the majority must be allowed to move without them.
Second, fossil fuel interests must not warp climate action priorities. Fossil fuel and other polluting industry lobbyists outnumbered national delegations of almost every country at recent talks. It is time to enforce robust conflict of interest rules to limit the influence of those whose business model depends on delay and denial.
This has been done before. The World Health Organization excluded Big Tobacco from public health conversations. Climate talks should do the same with Big Oil.
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Third, there must be meaningful accountability. Shiny declarations from states and private actors made at COPs need criteria, monitoring, and compliance. States must be held accountable for the commitments they make.
While the Paris Agreement’s compliance mechanisms may be toothless by design, the International Court of Justice recently affirmed that states are responsible for meeting their climate obligations and can be held liable if they don’t.
They have a choice to make: set up legitimate accountability mechanisms under the climate regime or face their responsibilities in courts around the world.
Human rights at its core
Finally, reform also needs to guarantee human rights protections and civic space at every COP, and make negotiations participatory, inclusive and transparent. Civil society and the public have the right to know what is being decided in their name, and to challenge decisions when they fall short.
At its core, this reform is about restoring faith in international cooperation to solve global crises. It is about making the process stronger, fairer and more capable of delivering what science and justice require.
Comment: It’s time for majority voting at UN climate summits
In Belém, governments have the opportunity to begin closing the gap between promises and action, not just through stronger targets and better policies, but by changing the rules of the game.
The science is clear. The law is clear. Now, the process must catch up.
If COP30 is to be remembered as a turning point, it won’t be because the system was perfect, but because governments decided to make it better.
The post Not another COP-out: We must rewrite the rules of the UN climate talks appeared first on Climate Home News.
Not another COP-out: We must rewrite the rules of the UN climate talks
David Sathuluri is a Research Associate and Dr. Marco Tedesco is a Lamont Research Professor at the Lamont-Doherty Earth Observatory of Columbia University.
As climate scientists warn that we are approaching irreversible tipping points in the Earth’s climate system, paradoxically the very technologies being deployed to detect these tipping points – often based on AI – are exacerbating the problem, via acceleration of the associated energy consumption.
The UK’s much-celebrated £81-million ($109-million) Forecasting Tipping Points programme involving 27 teams, led by the Advanced Research + Invention Agency (ARIA), represents a contemporary faith in technological salvation – yet it embodies a profound contradiction. The ARIA programme explicitly aims to “harness the laws of physics and artificial intelligence to pick up subtle early warning signs of tipping” through advanced modelling.
We are deploying massive computational infrastructure to warn us of climate collapse while these same systems consume the energy and water resources needed to prevent or mitigate it. We are simultaneously investing in computationally intensive AI systems to monitor whether we will cross irreversible climate tipping points, even as these same AI systems could fuel that transition.
The computational cost of monitoring
Training a single large language model like GPT-3 consumed approximately 1,287 megawatt-hours of electricity, resulting in 552 metric tons of carbon dioxide – equivalent to driving 123 gasoline-powered cars for a year, according to a recent study.
GPT-4 required roughly 50 times more electricity. As the computational power needed for AI continues to double approximately every 100 days, the energy footprint of these systems is not static but is exponentially accelerating.
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And the environmental consequences of AI models extend far beyond electricity usage. Besides massive amounts of electricity (much of which is still fossil-fuel-based), such systems require advanced cooling that consumes enormous quantities of water, and sophisticated infrastructure that must be manufactured, transported, and deployed globally.
The water-energy nexus in climate-vulnerable regions
A single data center can consume up to 5 million gallons of drinking water per day – sufficient to supply thousands of households or farms. In the Phoenix area of the US alone, more than 58 data centers consume an estimated 170 million gallons of drinking water daily for cooling.
The geographical distribution of this infrastructure matters profoundly as data centers requiring high rates of mechanical cooling are disproportionately located in water-stressed and socioeconomically vulnerable regions, particularly in Asia-Pacific and Africa.
At the same time, we are deploying AI-intensive early warning systems to monitor climate tipping points in regions like Greenland, the Arctic, and the Atlantic circulation system – regions already experiencing catastrophic climate impacts. They represent thresholds that, once crossed, could trigger irreversible changes within decades, scientists have warned.
Yet computational models and AI-driven early warning systems operate according to different temporal logics. They promise to provide warnings that enable future action, but they consume energy – and therefore contribute to emissions – in the present.
This is not merely a technical problem to be solved with renewable energy deployment; it reflects a fundamental misalignment between the urgency of climate tipping points and the gradualist assumptions embedded in technological solutions.
The carbon budget concept reveals that there is a cumulative effect on how emissions impact on temperature rise, with significant lags between atmospheric concentration and temperature impact. Every megawatt-hour consumed by AI systems training on climate models today directly reduces the available carbon budget for tomorrow – including the carbon budget available for the energy transition itself.
The governance void
The deeper issue is that governance frameworks for AI development have completely decoupled from carbon budgets and tipping point timescales. UK AI regulation focuses on how much computing power AI systems use, but it does not require developers to ask: is this AI’s carbon footprint small enough to fit within our carbon budget for preventing climate tipping points?
There is no mechanism requiring that AI infrastructure deployment decisions account for the specific carbon budgets associated with preventing different categories of tipping points.
Meanwhile, the energy transition itself – renewable capacity expansion, grid modernization, electrification of transport – requires computation and data management. If we allow unconstrained AI expansion, we risk the perverse outcome in which computing infrastructure consumes the surplus renewable energy that could otherwise accelerate decarbonization, rather than enabling it.
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What would it mean to resolve the paradox?
Resolving this paradox requires, for example, moving beyond the assumption that technological solutions can be determined in isolation from carbon constraints. It demands several interventions:
First, any AI-driven climate monitoring system must operate within an explicitly defined carbon budget that directly reflects the tipping-point timescale it aims to detect. If we are attempting to provide warnings about tipping points that could be triggered within 10-20 years, the AI system’s carbon footprint must be evaluated against a corresponding carbon budget for that period.
Second, governance frameworks for AI development must explicitly incorporate climate-tipping point science, establishing threshold restrictions on computational intensity in relation to carbon budgets and renewable energy availability. This is not primarily a “sustainability” question; it is a justice and efficacy question.
Third, alternative models must be prioritized over the current trajectory toward ever-larger models. These should include approaches that integrate human expertise with AI in time-sensitive scenarios, carbon-aware model training, and using specialized processors matched to specific computational tasks rather than relying on universal energy-intensive systems.
The deeper critique
The fundamental issue is that the energy-system tipping point paradox reflects a broader crisis in how wealthy nations approach climate governance. We have faith that innovation and science can solve fundamental contradictions, rather than confronting the structural need to constrain certain forms of energy consumption and wealth accumulation. We would rather invest £81 million in computational systems to detect tipping points than make the political decisions required to prevent them.
The positive tipping point for energy transition exists – renewable energy is now cheaper than fossil fuels, and deployment rates are accelerating. What we lack is not technological capacity but political will to rapidly decarbonize, as well as community participation.
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Deploying energy-intensive AI systems to monitor tipping points while simultaneously failing to deploy available renewable energy represents a kind of technological distraction from the actual political choices required.
The paradox is thus also a warning: in the time remaining before irreversible tipping points are triggered, we must choose between building ever-more sophisticated systems to monitor climate collapse or deploying available resources – capital, energy, expertise, political attention – toward allaying the threat.
The post Using energy-hungry AI to detect climate tipping points is a paradox appeared first on Climate Home News.
Using energy-hungry AI to detect climate tipping points is a paradox
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