Brief Author Note

Last week was nuts in terms of energy policy! We are fast approaching an age where AI policy is turning into energy policy.

One of the main bottlenecks that we are seeing with the data center rollout is simply energy demand and generation. However, other factors such as compute governance to permitting reforms are also big things to consider moving forward into 2026.

Here’s a couple of cool articles that I wanted to share with all of y’'all:

• U.S. Department of Energy forms $1 billion supercomputer and AI partnership with AMD (10/27/25)

• OpenAI’s 11 pager letter to the White House about AI policy needing to be energy policy (10/27/2025)

• New Trump Administration Energy Rule Would Enable Data Centers with ‘Large Loads’ (10/25/2025)

Watt you later! ⚡️ 

Nate

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Can We Be Optimistic About AI Sustainability? (AI & Policy/ESG): The potential impact of AI on the climate crisis is heating up, literally and figuratively. Guest Iuna Tsyrulneva, a materials scientist at the Earth Observatory of Singapore, offers a grounded yet hopeful perspective on how AI can align with sustainability goals. She highlights emerging research that reframes AI as both a challenge and a catalyst for environmental progress, encouraging a shift in mindset from skepticism to stewardship.

How Much Energy Does Google’s AI Use? (AI & Energy): Host Sanjay Podder sits down with Cooper Elsworth, Google’s lead for AI and cloud emissions insights, to unpack the company’s new data on AI’s true energy, carbon, and water footprint. They discuss how Google’s integrated hardware-software approach and clean-energy procurement have reduced Gemini’s carbon footprint forty-four-fold in one year. The episode also examines trade-offs between energy efficiency and water use and the growing importance of transparent sustainability metrics in AI development.

AI’s Double-Edged Sword: Navigating Environmental Impact and Opportunity (AI & Environment): In the SPRingBoard Environmental Law Podcast, host Ahlia Bethea speaks with Shaolei Ren (UCR) and Will Kletter (ClimateAi) about AI’s environmental costs and potential benefits. They explore the heavy resource demands of large language models alongside the promise of AI-driven climate forecasting and adaptation tools. The discussion underscores that the same technology straining planetary systems could also help protect them, if guided by smart policy and ethical design.

Artificial Intelligence and Automation in Evidence Synthesis: An Investigation of Methods Employed in Cochrane, Campbell Collaboration, and Environmental Evidence Reviews (AI & Environment): A review of 2,271 evidence syntheses from 2017–2024 reveals that machine learning and automation are still rarely used in environmental and public health research, only 5% explicitly applied AI tools, mostly for screening. Despite clear potential to accelerate reviews and improve transparency, adoption remains slow due to unclear reporting, low awareness, and trust barriers. The authors call for stronger methodological standards and user training to unlock AI’s full potential in evidence-based environmental decision-making.

Digital Transformation in the Shared Socioeconomic Pathways (AI & Social/Economic Impacts): This NPJ Climate Action study models the trajectory of digitalization across 62 countries within the Shared Socioeconomic Pathways framework. The findings reveal enduring digital divides between regions and outline six pathways through which digital transformation could influence global energy demand, emissions trajectories, and climate policy. The paper emphasizes that digitalization’s role in sustainability depends on how equitably its benefits and infrastructure are distributed.

Navigating Through Turbulence: Blueprint for the Next Generation of Weather-Climate Scientists (AI & Workforce Development): This arXiv paper examines how rapid advances in AI and high-resolution modeling are reshaping weather and climate science careers. The authors argue that the evolving ecosystem of computational tools offers unprecedented opportunities for innovation but also creates uncertainty for early-career scientists. They propose education and training reforms to help future researchers thrive in a hybrid academic–industry environment increasingly defined by automation and cross-sector collaboration.

Measuring Domestic Public Cloud Compute Availability for AI (AI & Infrastructure): The OECD’s new report benchmarks how much public cloud computing power for AI is available across member countries, offering one of the first comparative datasets of its kind. It highlights stark disparities between advanced and emerging economies, underscoring how access to compute has become a strategic determinant of innovation capacity. The findings call for coordinated policy efforts to ensure equitable access to cloud infrastructure critical for AI research and sustainable development.

Overcharged: The Rules of the Electricity Affordability Crisis (AI & Energy): The Climate & Community Institute and Public Grids release an urgent report diagnosing the structural roots of rising electricity costs. It argues that deregulation, private monopolies, and weak consumer protections have deepened affordability gaps threatening the energy transition’s social license. The authors propose public-interest reforms that would reorient energy systems toward affordability, reliability, and equity at a time when AI-driven electricity demand is soaring.

Blueprint to Action: China’s Path to AI-Powered Industry Transformation (AI & Economic Transformation): The World Economic Forum’s latest blueprint examines how China is leveraging AI to modernize its industrial base while navigating decarbonization and global competition. It details sector-specific pilots in manufacturing, logistics, and energy that demonstrate large-scale deployment of AI for efficiency and emissions reduction. The report positions China as both a leader and a stress test for balancing rapid automation with sustainable industrial policy.

I Built a Scope 3 Emissions Tool in 10 Minutes (No Coding) (AI & ESG)
This tutorial demonstrates how to create an interactive Scope 3 emissions onboarding tool using ChatGPT and Replit, no coding required. In less than ten minutes, viewers learn how to build a branded app to help teams or clients understand and manage their indirect emissions. It’s a practical example of how generative AI can streamline ESG engagement and make sustainability tools more accessible.

The Future of Energy with Lisa Audet: AI Super Cycle and the Grid of Tomorrow (AI & Energy): In this episode of The Money Runner, host David Nelson speaks with Lisa Audet, founder of Tall Trees Capital, about how AI’s explosive growth is reshaping global energy systems. Their conversation explores the return of nuclear energy, surging demand for copper, and the race to modernize aging grids to meet AI-era electricity needs. It’s an essential listen for anyone tracking how innovation, investment, and infrastructure are converging in the next energy super cycle.

Will AI Drain Our Power Grid? The Hidden Energy Cost (AI & Energy): This explainer breaks down the unseen electricity demand behind everyday AI use from powering data centers to handling billions of ChatGPT queries. It asks whether AI’s rapid adoption could strain national grids and drive up energy bills, while examining what solutions exist to mitigate its footprint. The episode offers a clear, accessible overview of the tension between digital convenience and energy sustainability.

Machine Learning and Society at Hugging Face (AI & Environment): Hugging Face’s Machine Learning and Society initiative spotlights open research and collaborative projects at the intersection of AI and social impact. The team focuses on transparency, ethical deployment, and collective stewardship of open models and datasets. Their work exemplifies how open-source innovation can serve environmental and societal goals through shared accountability and interdisciplinary collaboration.

Phaidra (AI & Energy): Phaidra develops AI-driven virtual plant operators designed to improve energy efficiency, stability, and sustainability in mission-critical industrial facilities. Their intelligent control systems continuously learn and adapt, enabling optimized performance with reduced energy waste. The company’s approach demonstrates how applied AI can enhance real-world industrial operations while advancing decarbonization goals.

AZX (AI & Infrastructure): AZX provides AI transformation solutions for critical industries such as energy, infrastructure, and real estate. By combining startup agility with deep industry expertise, the company helps clients navigate rapid technological and environmental shifts. Its mission-driven approach prioritizes implementable AI strategies that enhance resilience, efficiency, and sustainability across large-scale systems.

Community Fish Detector (CFD) (AI & Ocean Conservation): Developed by the WildHackers collective, the Community Fish Detector provides pretrained object-detection models to identify fish species across diverse aquatic environments. Trained on a massive open dataset of more than 1.9 million images and 935,000 annotated fish, the project unifies data from 17 sources spanning marine, freshwater, and lab settings. Its goal is simple yet ambitious: detect any fish, anywhere advancing citizen science and conservation through open, collaborative AI (FREE)

Digital Sustainability Library (AI & Sustainability): Created by LIBER Europe, this digital-scholarship guide curates resources for library professionals seeking to embed sustainability into digital practices. It covers topics from green data infrastructures to ethical AI use in library systems, helping institutions align digital transformation with environmental responsibility. The library stands as a practical model for building sustainable knowledge ecosystems (FREE)

ASG² Intelligence Platform (AI & Policy): The Observatory for AI Assurance, Security, and Global Governance (ASG²) offers an integrated platform tracking the evolving landscape of AI regulation, standards, and policy. It provides a hub for researchers and policymakers to explore frameworks on AI safety, governance, and international cooperation. Positioned at the intersection of technology and diplomacy, ASG² supports evidence-based policymaking for a secure and sustainable AI future (FREE)

IEEE‑USA Government Fellowship Program (USA / Early-Career STEM Professionals in Public Policy): Each year, IEEE-USA invites U.S. citizens who are IEEE members to spend a year (September 1 – August 31) working in Washington, D.C., either with the U.S. Congress or the U.S. Department of State. Fellows bring expertise in science, technology, or engineering to help shape federal policy, while gaining first-hand experience in the policymaking process. Applications are due January 9, 2026 for the 2026–27 cohort.

Foreign Policy for America “NextGen Initiative” (USA / Young Leaders in Foreign Policy & Technology: This program supports U.S.-based emerging leaders (ages ~21–35) interested in foreign policy, technology, and advocacy. Participants join a cohort model featuring mentorship, networking, and working groups (e.g., Cyber & Technology, Defence & Intelligence, Democracy & Human Rights) aimed at elevating their voices in policy-tech ecosystems. The winter 2025 application cycle closes on November 24, 2025 at 11:59 PM PT

Environmental Fellows Program, Yale School of the Environment (USA / Graduate Students in Climate & Conservation Leadership): Hosted by the Yale School of the Environment (YSE), the Environmental Fellows Program (EFP) is a 12-week fully funded summer leadership fellowship designed to advance diversity and inclusion in the environmental sector. It places master’s and doctoral students in meaningful roles within environmental nonprofits, foundations, and government agencies, offering mentorship, professional training, and networking opportunities. Fellows gain hands-on experience in conservation, climate policy, and philanthropy, building skills in sustainability leadership and environmental justice. Applications for the 2026 cohort close November 30, 2025 (priority deadline: December 1, 2025; final deadline: January 4, 2026).

If you have resources that you wish to submit to the AI & Environment Resource Hub, fill out the Google Form! Thank you for suggesting resources to add to the Resource Hub. 🙃 

That’s it for this week.

Thanks for reading the 24th issue of The Climate Code! It means a lot to me and we have more coming in the future, so definitely stick around! 💚 

Nate

P.S.

New here? Check out the AI & Environment Resource Hub if you have no idea what it is. 😆