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8 resources
BloombergNEF's free executive summary of its 2026 New Energy Outlook, covering how global energy supply, demand and emissions could evolve. Useful context for the energy demands of AI data centers.
Pew Research Center survey of 10,548 U.S. adults finds growing concern about data centers' environmental impact, home energy costs and quality of life, with majorities now saying they are mostly bad for the environment.
Why I recommend it: Pew Research Center short read published 22 September 2026, survey fielded 20 July–9 August 2026. 54% of Americans say data centers are mostly bad for the environment (up from 39% in January), 50% say mostly bad for home energy costs, 49% say mostly bad for nearby quality of life. Views on local tax revenue and jobs are mixed. 12% had not heard of data centers at all.
Company building thermodynamic computing hardware it claims is far more energy efficient than GPUs.
From the site: Building thermodynamic computing hardware that is radically more energy efficient than GPUs.
Why I recommend it: The energy cost of AI is becoming the constraint, and this is one bet on solving it in hardware. The efficiency claims are the company's own and unproven at scale.
Ketan Joshi's free analysis picking apart the claims in an industry report on AI and climate, showing where the energy and emissions figures do not hold up.
From the site: What does the real climate footprint of the biggest company on the planet look like? It's a good question, but here's a better one: why don't we already know the answer?
Why I recommend it: A worked example of how to read an industry report critically — useful skill well beyond this topic.
Reporting on a community campaign against a data center's water and energy use during a drought.
Why I recommend it: The clearest single story on what a data center costs the place it lands in.
The open letter and campaign from employees pressing their employer on climate and data-center energy use.
Why I recommend it: An example of workers using an open letter as leverage — worth reading for the wording alone.
A body of writing and practice on computing that lasts — repairable hardware, small software, low energy use.
Why I recommend it: The counterweight to "more compute solves everything".
A free, continuously updated and sourced record of the physical infrastructure behind AI: data centres, GPU clusters, power, chips, cloud prices, measured performance and company financials.
Why I recommend it: Useful grounding when you want facts rather than headlines about the AI build-out.
