Brief Author Note

How the heck are we in December already?! I’m literally screaming at my calendar to slow down since it is going way too fast.

If y’all are interested, I’m joining a panel of speakers as part of my Digital Economist Fellowship this week during the “Power, Technology, Humanity: A New Alignment” roundtable series on December 11 and December 12 covering the following:

1. Where power is migrating.
2. How technology can serve collective resilience.
3. What new models must emerge to protect human dignity.
4. How institutions can adapt to a rapidly reorganizing world.

Here’s a hint: I will be on the “Regenerative Digital Infrastructure: Architectures for a Shared Future” panel talking about data centers and sustainability.

Ciao!

Nate

Quick Links!

• Podcast Episodes

• Scientific Papers

• Policy Documents

• Multimedia

• Organizations

• Tools

• Fellowships Corner

• Submit Resources

Dr. Hannah Ritchie: Is AI Bad for the Planet? (AI & Environment): This episode explores the environmental footprint of AI through the lens of Dr. Hannah Ritchie’s new book, examining AI’s energy appetite, household energy trends, and why evidence-driven climate solutions still leave room for optimism. Her answers clarify what’s real vs. hype in debates about AI’s sustainability.

Data Centers Are a Climate Enemy (AI & Data Centers/Hardware): Paris Marx and Ketan Joshi unpack how hyperscale data centers are accelerating oil and gas consumption, undermining climate targets, and deepening ties between Big Tech and fossil fuel companies. The episode highlights the political and infrastructural forces behind data centers’ rising emissions.

AI Shaping the Future with Dominic Vergine (AI & Environment): Dominic Vergine argues that AI can meaningfully advance engineering and energy solutions if guided by thoughtful leadership rather than hype, drawing on his decades of experience scaling sustainability at ARM. The episode emphasizes aligning AI development with real-world purpose and long-term value.

Epistemic and Aleatoric Uncertainty Quantification in Weather and Climate Models (AI & Climate Science): This paper presents a unified Bayesian Neural Network framework that quantifies both aleatoric and epistemic uncertainty in subgrid-scale parameterizations across weather and climate regimes. Using the Lorenz-96 system, the authors show that aleatoric uncertainty dominates short-term forecasts, while long-term climate simulations require both uncertainty types for well-calibrated predictions.

AI-Driven Grid Optimization Can Reduce Emissions (AI & Environment): This paper demonstrates that although training machine-learning models for AC optimal power flow has an upfront carbon cost, the resulting efficiency gains in grid operation offset those emissions within minutes. By reducing unnecessary generation and transmission losses, the models deliver substantial long-term climate benefits.

Federated Carbon Intelligence for Sustainable AI: Real-Time Optimization Across Heterogeneous Hardware Fleets (AI & Data Centers/Hardware/Models): This paper introduces a federated carbon intelligence framework that integrates hardware health telemetry, real-time grid carbon data, and RL-based scheduling to route AI inference workloads across accelerators like A100s, TPUs, and Cerebras chips. Simulations show up to a 45 percent emissions reduction and improved hardware longevity, establishing a pathway for climate-aligned, self-optimizing AI infrastructure.

The Next Great Divergence: Why AI May Widen Inequality Between Countries (AI & Economic Transformation): This UNDP report argues that rapid advances in AI risk deepening global inequality by concentrating economic gains, productivity leaps, and geopolitical influence within a handful of technologically advanced countries. It calls for coordinated international policies to ensure that AI-driven growth is broadly shared rather than reinforcing a new digital divide.

Center for Public Enterprise Bubble or Nothing? (AI & Infrastructure): This Center for Public Enterprise report warns that the explosive growth of AI infrastructure resembles a speculative bubble driven by unchecked hype, rising energy demands, and unsustainable capital expenditures. It outlines structural risks across data centers, utilities, and capital markets that could trigger systemic failures without stronger public oversight.

Data Centers as Enabling Infrastructure (AI & Infrastructure): This Mandala/Data Centers Australia analysis frames data centers as critical national infrastructure supporting economic development, AI growth, and digital services, while also examining the energy, water, and grid constraints shaping future expansion. The report highlights the need for strategic planning, resilient grid integration, and long-term infrastructure coordination.

AI for the Planet: Advancing Environmental Data Standards for Sustainable Artificial Intelligence (AI & Environmental Impact): This UNEA-7 session brings together standards bodies, governments, and scientific data networks to explore how interoperable environmental data and aligned digital standards can support trustworthy, responsible, and sustainable AI systems. The discussion builds on UNEP’s Global Environmental Data Strategy to link digital transformation with climate, nature, and pollution action.

We’re Doing AI All Wrong. Here’s How to Get It Right (AI & Environmental Impact): In this TED talk, Sasha Luccioni critiques the massive energy and resource footprint of today’s large AI models and the opaque corporate practices driving it. She proposes a shift toward smaller, more efficient, and more transparent AI systems that deliver social value without deepening environmental harm.

Cycloid's Green IT on a Cloud Podcast: Talking Sustainability, Seriously! (AI & Multiple Applications): This episode tackles practical steps for reducing the environmental footprint of digital infrastructure—from understanding data center growth impacts and scrutinizing PUE/WUE metrics to cutting AI compute costs responsibly. It also covers how GreenOps and FinOps can work together and offers a 90-day roadmap for immediate sustainability gains.

Proon-Tech (AI & Agriculture): Proon-Tech is a cleantech startup developing precision forestry hardware and software to automate tree management, boost survival rates, reduce inputs, and deliver measurable ecosystem benefits from seed to yield. The company operates out of North America.

Seedling.earth (AI & Environment): Seedling helps organizations measure and reduce their full-scope carbon footprint through data-driven tools and climate-science-aligned methodologies, enabling teams to make accurate and confident sustainability decisions. The company is based in the United Kingdom.

Mittwald (AI & Environment): Mittwald provides high-performance, flexible, and fully climate-neutral web hosting for agencies and freelancers, while sharing updates on sustainable digital operations, CMS tools, and modern web practices. The company is located in Europe.

OlmoEarth (AI & Geospatial Analysis): OlmoEarth is a platform that transforms complex Earth data into timely, actionable insights using state-of-the-art AI, enabling organizations and communities to leverage geospatial intelligence without requiring AI expertise. .

ChatNDC (AI & Policy): ChatNDC is an AI-powered tool that increases accessibility and understanding of climate policy data, helping users navigate Nationally Determined Contributions (NDCs) and related climate commitments with ease.

Chat Net Zero (AI & Sustainability): ChatNetZero combines deep Net Zero expertise with large language models to deliver trustworthy, domain-specific climate and sustainability insights while addressing the accuracy and reliability concerns common in general-purpose LLMs. The project is based in the United Kingdom.

Wilson Center Research Fellowship (Open globally to senior scholars, practitioners, and experienced policy professionals): This twelve-month fellowship supports scholars and practitioners conducting policy-relevant, nonpartisan research aligned with the Wilson Center’s pillars, including strategic competition, economic statecraft, technology and innovation, and regional expertise. Fellows work remotely while engaging Washington policymakers through briefings, workshops, written products, and public events, with travel to DC funded at the start and end of the program. The fellowship runs June 1, 2026–May 30, 2027, provides a $10,000 monthly stipend, and applications close January 16, 2026.

Technology Pioneers 2026 (Open globally to early-stage, high-growth tech startups): The World Economic Forum selects 100 early-stage companies developing breakthrough technologies with the potential for large-scale positive impact on society and the planet. Over a two-year term, selected “Technology Pioneers” engage directly with global political, business, and cultural leaders through WEF meetings, workshops, and Innovator Community events, with CEOs expected to devote at least five hours per quarter and attend one global event per year. Eligible companies must be privately held, under ten years old, have raised at least USD $10 million (Series A or beyond), and demonstrate significant technological innovation. Applications close January 31, 2026.

Oxford Accelerator Fellowship Programme (Open globally to researchers, practitioners, and interdisciplinary innovators): This fellowship from Oxford’s Institute for Ethics in AI supports impact-driven work at the intersection of philosophical inquiry and real-world AI ethics, with projects focused on AI & Creativity, AI in Care and Health, AI & Humanity, or AI, Law & Policy. Fellows receive professional development, strategic networks, and support for practical or policy-based outputs, with options for remote or in-person stays, including structured timelines for visa and travel planning. The program recruits 3–4 fellows per cohort, with the 2025–2026 round accepting applications until January 10, 2026, and the 2026–2027 round closing June 13, 2026.

BONUS: You can check out Alisar Mustafa’s December roundup of AI/Tech Policy fellowships. 😀 

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 29th 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. 😆