The problem
What needs solving
Measure how much electricity and water AI uses and what it emits, per task, per model and in total, with one method outsiders can check. Count training, everyday use, idle machines, cooling and making the chips.
Why it matters
The IEA expects data centres’ electricity use to roughly double by 2030, to about 950 billion kilowatt-hours, with AI-focused sites growing fastest. Yet AI’s share is not officially reported. In the EU’s first reporting round, in 2024, about 36% of the data centres estimated to be covered reported, with no split for AI. Methods differ too: for one typical prompt, Google reported 0.24 watt-hours counting idle machines and overhead, but 0.10 counting active chips alone. Meanwhile requests for new data centres are stretching grid planning, and some communities are pushing back.
What counts as progress
(a) ISO/IEC, the ITU or CEN-CENELEC adopts an open standard for counting AI’s electricity, water and emissions, covering training, use, idle machines, cooling and making the hardware, or the EU makes one binding. (b) At least three of the five largest AI computing operators publish a full year of AI electricity, water and emissions under that standard, split between training and everyday use and checked by an independent auditor. (c) Solved when an independent body publishes AI’s total electricity, water and emissions for a past year, from audited reports, to within 20% either way, and repeats it a year later.
Stater & version history
Stated by UNSOLVED editors
18 Oct 2026 — Stated by the UNSOLVED editors for the founding registry, from the research of October 2026.