When you type a prompt, you summarize. When you speak one, you explain. Wispr Flow captures your full reasoning — constraints, edge cases, examples, tone — and turns it into clean, structured text you paste into ChatGPT, Claude, or any AI tool. The difference shows up immediately. More context in, fewer follow-ups out.

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The detailed ones. The ones with examples and edge cases. Wispr Flow lets you speak them instead — clean, structured, ready to paste into any AI tool. Free on Mac, Windows, and iPhone.

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Sixty percent. That is the share of AI data center energy still drawn from fossil fuels – coal, gas, and other carbon-heavy sources. Globally, across the infrastructure that runs the tools we are all being told to adopt.

The scale is accelerating. In 2024, data centers consumed 460 TWh of electricity worldwide. By 2030, the IEA projects that figure crosses 1,000 TWh – more than double. By 2035, it reaches 1,300 TWh. For reference, that is larger than the entire current electricity consumption of Japan. Coal alone accounts for roughly 30% of the energy mix powering data centers today. Natural gas adds another 26%. Renewables cover just 27%.

The sustainability gap is wide

Tech companies have published ambitious net-zero pledges. Microsoft committed to carbon negativity by 2030. Google claimed 24/7 carbon-free energy as a goal. Google's emissions grew 48% between 2019 and 2024, driven largely by AI infrastructure. Microsoft's emissions rose 30% over the same period. The pledges and the trajectory are moving in opposite directions.

Energy is not the only cost. Data centers are water-intensive, consuming hundreds of millions of liters for cooling. A single conversation with a large AI model can use the equivalent of a 500ml bottle of water. Multiply that by billions of daily queries.

The race has real costs

There is genuine good here. AI tools are improving how organizations model climate risk, allocate humanitarian resources, and track disease outbreaks. The technology has real applications in impact work.

But the infrastructure underneath is fossil-fueled and the competitive pressure is compounding the problem. Microsoft, Google, and Amazon collectively spent over $200 billion on data center infrastructure in 2024 alone.

What to do with this

For impact professionals, the questions are practical: Does your organization have a policy on AI energy use? Are you tracking it alongside travel and operations emissions? Are you asking vendors for energy transparency?

Some organizations are starting to treat AI carbon footprint the same way they treat supply chain ethics.

Go further

The PCDN AI for Impact Hub is our new beta site doing serious work on exactly this. The costs section covers the real environmental, labor, and social trade-offs in depth – grounded, evidence-based, and built specifically for impact professionals navigating this terrain. It is worth bookmarking and sharing with your team.

The tools are here. The grid they run on is not clean. Both things are true, and navigating that honestly is part of the job now.

🤖 AI for Impact Joke

Why did the AI apply for a nonprofit job?
Because it heard the mission was "to serve humanity" — and it finally found a job description that matched its training data.

Brazil's 2026 Elections Are Its First Real Stress Test for AI Regulation — A synthetic AI influencer named "Dona Maria" is flooding Brazilian social media ahead of October elections, exposing how unprepared regulators are to handle deepfake political personas at scale. (TechPolicy.Press)

90% of U.S. Workers Support Union-Backed AI Protections — A sweeping AFL-CIO poll finds 95% of workers say humans must have final say over employment decisions, and 94% want to be told when AI is monitoring them. Unions are trusted more than employers, Democrats, or Republicans to lead on this. (The Guardian)

Huawei's AI Pivot: How Sanctions Sparked a Chinese Innovation Surge — After the U.S. cut off TSMC chip supplies, Huawei built a sprawling AI research campus from scratch. Observers warn the move may have backfired — pushing China toward homegrown alternatives that could challenge U.S. dominance within a decade. (NPR)

The TAKE IT DOWN Act: Good Intentions, Unproven Execution — President Trump's new law targeting non-consensual intimate deepfakes is on the books, but enforcement mechanisms remain untested and platforms haven't meaningfully changed behavior yet. Victims are still navigating long, painful removal processes. (TechPolicy.Press)

Fast Forward Tech Nonprofit Job Board — The only job board dedicated exclusively to tech nonprofit roles, with 1,600+ active openings globally. Whether you're a mission-driven engineer, product designer, or strategist, Fast Forward connects top talent with organizations using tech for systemic change. Current listings include a Director of Portfolio Services ($140k–$150k) and a Fundraising Operations Manager ($100k–$110k). Visit jobs.ffwd.org.

👤 LinkedIn Profile to Follow

Jas Schembri-Stothart — Co-Founder, luna — Jas co-founded luna, a digital companion helping teenage girls navigate adolescence with confidence, care, and community — now trusted by 160,000 families worldwide. She grew luna's audience from zero to millions through social, content, and community-first strategy. A compelling voice on purpose-driven entrepreneurship, teen wellbeing, and building products that actually serve underrepresented users.

🎧 Today's Podcast Pick

It's Been a Minute — "The Human Labor That Makes AI Work" (NPR) — A grounding look at the invisible global workforce of data labelers and content moderators powering frontier AI — many working under exploitative conditions in the Global South. Essential listening for anyone serious about AI ethics and equity.