Florian Géron’s Post

Explosive growth of AI data centers is expected to increase greenhouse gas emissions. An August 2025 analysis from Goldman Sachs Research forecasts that about 60 percent of the increasing electricity demands from data centers will be met by burning fossil fuels, increasing global carbon emissions by about 220 million tons. In comparison, driving a gas-powered car for 5,000 miles produces about 1 ton of carbon dioxide. Researchers are now seeking solutions to reduce these environmental harms. #artificialintelligence #ai #environment #sustainability Campaign for Greener Arbitrations: The Green Pledge North America Committee - CGA #internationalarbitration #esg

OECD.AI published a new commentary by CIL researcher Dr. Jon Truby entitled ‘𝗣𝗲𝗼𝗽𝗹𝗲, 𝗣𝗹𝗮𝗻𝗲𝘁, 𝗣𝗿𝗼𝗴𝗿𝗲𝘀𝘀: 𝗔𝗻 𝗼𝗽𝗽𝗼𝗿𝘁𝘂𝗻𝗶𝘁𝘆 𝗳𝗼𝗿 𝗮𝗻 𝗶𝗻𝘁𝗲𝗿𝗻𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗮𝗴𝗿𝗲𝗲𝗺𝗲𝗻𝘁 𝗼𝗻 𝗔𝗜 𝗰𝗹𝗶𝗺𝗮𝘁𝗲 𝘀𝘂𝘀𝘁𝗮𝗶𝗻𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗮𝘁 𝗜𝗻𝗱𝗶𝗮’𝘀 𝗔𝗜 𝗜𝗺𝗽𝗮𝗰𝘁 𝗦𝘂𝗺𝗺𝗶𝘁 𝟮𝟬𝟮𝟲’ The commentary outlines practical steps for an international agreement on AI climate sustainability at India’s AI Impact Summit 2026, integrating AI compute into the Paris Agreement architecture so countries account for model and data-centre emissions.  He makes the case for mandatory emissions disclosure for AI systems and data centres, alongside shared efficiency and green-procurement standards to drive lower-carbon compute, and for coordinated action via the UNFCCC, UN, OECD and G20 to avoid policy fragmentation.  Dr Truby is an expert member of the OECD.AI Climate & Compute ad hoc body. https://lnkd.in/gtigXjUT #AI #ClimateAction #InternationalLaw #AIGovernance #Sustainability

Regulators are calling for primary data. Practitioners demand standardisation and regulation. But all agree: cooperation and transparency will make the AI ecosystem work sustainably — both environmentally and financially. It was one of the most insightful discussions at the OECD - OCDE Forum on Green Finance and Investment — so difficult to limit it to a short post! Jules Besnainou (Cleantech for Europe) set the tone with numbers. "ChatGPT consumes 10× more energy than a Google search,” “Electricity demand in Europe is projected to rise by 40–50% by 2033,” “France alone has 11 GW of new data centres in the pipeline — equivalent to 6–8 nuclear plants.” The first big risk, he warned, is layering digital growth on top of fossil infrastructure: “You’re going to need a brand new energy system to make it work.” Europe is strong in invention but weak in scaling. Tech investment is about €10 bn a year, and although Europe attracts 23% of global seed capital, it captures only 6–7% of growth equity. Pension funds invest 100× less in innovation here than in the US. 💡 Shifting public support from subsidies to de-risking tools like guarantees, mobilising long-term investors, and front-loading carbon revenues, as Japan does, can accelerate deployment. Claire Dorville phD (Ministères Aménagement du territoire Transition écologique) emphasised that “green AI and AI for green go together.” She stressed four levers: regulation, financing, innovation, and cooperation. France helped launch the International Sustainable AI Coalition (220 members) and published a national framework on frugal AI and eco-design of digital services to help companies measure AI’s footprint, build trust, and steer capital towards the most sustainable solutions. Boris Gamazaychikov (Salesforce) highlighted transparency as a critical bottleneck. A 60K× difference in energy use exists between the least and most intensive models — yet data on environmental impacts is scarce. Although open-source models are growing, “closed models still dominate” the market, and without mandatory disclosure investors and policymakers operate in the dark. Devon Swezey (Google) focused on energy optimisation and clean electricity. Efficiency gains are possible across software, hardware, and infrastructure, but reporting standards must evolve. “Today, a company can claim to be powered by solar at night simply by buying enough certificates over the year,” he noted. “We need to reconnect standards to the reality of power markets — from annual to hourly accounting, and from distant certificates to local generation.” 💡 AI can accelerate the net-zero transition or derail it. Making it part of the solution will require better primary data, harmonised standards, smarter financing, and unprecedented cooperation between regulators, industry, and investors. Deep gratitude to all the panelists for their candid insights and to Audrey Plonk for steering a conversation as honest as it was inspiring. #GreenFinance #AI

Explosive growth of AI data centers is expected to increase greenhouse gas emissions. Researchers are now seeking solutions to reduce these environmental harms. https://lnkd.in/exyNx5hb

Here is the challenge we're up against. AI will unlock a massive amount of 'brown' handprints. AND it could help supercharge a heap of 'green' handprints. Which will it be? Well, according to a wildly out of touch new report by Wood Mackenzie it will be an extra trillions barrels of oil. Yeah, no biggie. That's just roughly the equivalent of all US fossil fuel consumption. Listen to this: - "Using our data on reservoir geology, hydrocarbon quality, in-place resources, operator access to finance and technology, costs and fiscal terms, we estimate upside oil recovery factors for every significant field in the world." - "The results of our new AI-powered analysis, therefore, are encouraging. Better recovery from existing fields could yield an additional 470 billion to over 1,000 billion barrels of oil" We know that if AI is used to support business as usual we will blast through the remaining planetary boundaries and be beyond the help of any positive tipping points. This does NOT mean we should not explore AI. To the contrary. What I'm seeing happening in realtime is positive. - I'm seeing AI speed up research and deployment of new clean technologies, supporting RE uptake and simplifying permits and development. - I'm seeing AI strengthen grid modernization and smart energy solutions. - I'm seeing AI give time back to overworked conservation nonprofits and allow them to be more cost efficient without working more hours. Participants in our AI for Earth trainings are asking for more. They are starting to build their own tools and share what they've learned with their peers. The network effect here is so inspiring. International Energy Agency (IEA) said it best - - "The energy footprint of AI will be determined by its deployment in service of sustainability. Currently, there is no momentum for widespread adoption of AI for emissions reduction”. We are building this movement at Climate Collective. By building responsible and sustianable AI fluency for climate and nature professionals we're building a movement where being AI-informed and empowered allows participants in our cohorts to get ahead. They are supercharging their missions AND impact with green AI. But we can't do this alone. We depend on partners that support our work and fund our programs. Our partners help us unlock more impact across nonprofits, civil society and corporate sustainability teams. They help us drive AI augmented impact IN SERVICE of sustainability. I think WMs numbers are inflated. Nevertheless they should cause you to stop and think. As AI is transforming society - who do we want in the driver seat? Join us, to build agency among climate and nature professionals so that they can influence technology decisions made today - and grow the movement of 'green AI handprints'.

Happy Friday to all of your! Let’s harness Good AI to shape a sustainable tomorrow. As a sustainability expert, I’m captivated by AI’s potential to transform our planet’s future, yet cautious about its risks. It’s a paradox: AI data centers may double energy use by 2030 (IEA), but Good AI (used ethically), can drive climate solutions that outweigh its footprint. This isn’t just tech buzz; it’s a defining moment. Our duty? Guide AI with purpose to amplify its benefits. Here are inspiring examples: - IBM & UNICEF: Satellite AI maps floods instantly, speeding disaster relief. - Google.org & Zindi: AI cameras safeguard endangered species in remote areas. - Microsoft & MIT: Smart systems cut campus CO₂ emissions by 20%. - African NGOs & Data Innovators: AI tools help farmers adapt to climate shifts, boosting yields. - XPRIZE: Solar-powered AI captures CO₂, scaling climate action. These projects, led by diverse teams, show AI’s power when driven by purpose. Scaling them demands bold funding, smart policies, and ethical choices to ensure positive impact. Explore more in the Grand Challenge Initiatives in AI for Climate & Nature report. Let’s make this Friday count for a better planet!

Effective data collection is a critical enabler for advancing Net Positive approaches. AI systems show great promise in areas vital to Net Positive outcomes, such as climate change mitigation. But where do you start? This guide offers a clear path forward, showing how to align your tech investments with long-term value for business and society. Explore this article by @Economist Impact and learn how to build your digital handprint: https://okt.to/jDy2aN #NetPositive #AI #Data #TechForGood #SustainableInnovation #DigitalLeadership #DataStrategy #Oracle #OCI #OracleExperts

Effective data collection is a critical enabler for advancing Net Positive approaches. AI systems show great promise in areas vital to Net Positive outcomes, such as climate change mitigation. But where do you start? This guide offers a clear path forward, showing how to align your tech investments with long-term value for business and society. Explore this article by @Economist Impactand learn how to build your digital handprint: https://okt.to/fMKzDI #NetPositive #AI #Data #TechForGood #SustainableInnovation #DigitalLeadership #DataStrategy

Effective data collection is a critical enabler for advancing Net Positive approaches. AI systems show great promise in areas vital to Net Positive outcomes, such as climate change mitigation. But where do you start? This guide offers a clear path forward, showing how to align your tech investments with long-term value for business and society. Explore this article by @Economist Impactand learn how to build your digital handprint: https://okt.to/imRLP7 #NetPositive #AI #Data #TechForGood #SustainableInnovation #DigitalLeadership #DataStrategy

AI is booming — but so are its carbon emissions. Big Tech companies like Microsoft, Amazon, and Alphabet have set bold net-zero goals, but can they truly balance explosive AI growth with genuine decarbonization? Indeed, we’re seeing progress — AWS achieved an impressive PUE of 1.15, and leaders like TSMC and ASML are tackling supply chain emissions for now. But as AI models get more powerful (and power-hungry), the gap between ambition and reality could widen really fast. Can AI really be part of the climate solution — or is it quietly becoming a bigger part of the problem?