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Dale and Nick tackle the AI energy debate head-on, armed with Google's first transparent energy report showing a single AI query uses about 0.24 watt hours — a microwave running for one second. Drawing on Hannah Ritchie's analysis from Our World in Data, the Epoch AI research group, and Stanford's inference cost data, they argue that individual guilt over AI use is not only misplaced but actively useful to the companies making the real infrastructure decisions. The episode covers water usage myths, the BP carbon footprint parallel, Jevons paradox, the case for right-sized models in education, and why the better question isn't "how much does AI cost?" but "what does it enable?"
[00:00] — The energy narrative you've heard
[02:04] — Episode introduction
[03:00] — Google's transparent energy report
[04:12] — Hannah Ritchie's individual footprint math
[05:00] — Kettles, washing machines, and query comparisons
[05:27] — The "please and thank you" cost reframed
[06:14] — Crypto as the real energy vampire
[06:38] — 33x efficiency gain in 12 months
[08:21] — Energy used to block AI adoption
[09:03] — Jevons paradox: individual vs aggregate
[11:11] — Water usage myths debunked
[12:20] — BP's carbon footprint playbook
[13:52] — Not all AI use is worth it
[14:30] — Training costs: $43K vs $500 billion
[16:07] — You don't need an F1 car for groceries
[18:08] — Air conditioning uses 10% of global electricity
[19:14] — What AI enables matters more than what it costs
[21:00] — Why education shouldn't sit this out
🎙️ Adjunct Intelligence is the weekly briefing for higher-ed professionals who want AI as a cheat code—not a headache.
Every episode:
• Real tests of AI tools in education and professional workflows
• Fast, Monday-morning actions you can actually try
• Clear signal through the noise (no hype, no jargon)
👉 Subscribe on [YouTube] | [Apple Podcasts] | [Spotify]
👉 Share this with a colleague who still says “I’ll figure AI out later”
👉 Join the conversation on LinkedIn with #AdjunctIntelligence
Stay curious. Stay intelligent. Stay the human in the loop.
By Adjunct IntelligenceDale and Nick tackle the AI energy debate head-on, armed with Google's first transparent energy report showing a single AI query uses about 0.24 watt hours — a microwave running for one second. Drawing on Hannah Ritchie's analysis from Our World in Data, the Epoch AI research group, and Stanford's inference cost data, they argue that individual guilt over AI use is not only misplaced but actively useful to the companies making the real infrastructure decisions. The episode covers water usage myths, the BP carbon footprint parallel, Jevons paradox, the case for right-sized models in education, and why the better question isn't "how much does AI cost?" but "what does it enable?"
[00:00] — The energy narrative you've heard
[02:04] — Episode introduction
[03:00] — Google's transparent energy report
[04:12] — Hannah Ritchie's individual footprint math
[05:00] — Kettles, washing machines, and query comparisons
[05:27] — The "please and thank you" cost reframed
[06:14] — Crypto as the real energy vampire
[06:38] — 33x efficiency gain in 12 months
[08:21] — Energy used to block AI adoption
[09:03] — Jevons paradox: individual vs aggregate
[11:11] — Water usage myths debunked
[12:20] — BP's carbon footprint playbook
[13:52] — Not all AI use is worth it
[14:30] — Training costs: $43K vs $500 billion
[16:07] — You don't need an F1 car for groceries
[18:08] — Air conditioning uses 10% of global electricity
[19:14] — What AI enables matters more than what it costs
[21:00] — Why education shouldn't sit this out
🎙️ Adjunct Intelligence is the weekly briefing for higher-ed professionals who want AI as a cheat code—not a headache.
Every episode:
• Real tests of AI tools in education and professional workflows
• Fast, Monday-morning actions you can actually try
• Clear signal through the noise (no hype, no jargon)
👉 Subscribe on [YouTube] | [Apple Podcasts] | [Spotify]
👉 Share this with a colleague who still says “I’ll figure AI out later”
👉 Join the conversation on LinkedIn with #AdjunctIntelligence
Stay curious. Stay intelligent. Stay the human in the loop.