Measurable

Those measurements will be ignoring issues like the exponentially increasing training cost - a couple of years ago Anthropic's CEO said it then cost $100M to train a model but would soon reach $10B, and maybe $100B [1]. This year they reportedly expect to spend $7B on inference for paying users (not counting free users) and $12B on training [2], for an overall loss of about $11B. They're expecting costs will keep increasing, and they're just one of several companies developing large models. That's quite a lot of GPUs and electricity.

One report estimated data centers will increase from 4.4% of total US electricity usage in 2023, to 6.7-12% by 2028 [3], which is not an insignificant fraction and is about level with residential plus commercial air conditioning [4].

(I don't think energy usage is the strongest criticism of generative AI, but it's not a trivial issue.)

[1] https://www.businessinsider.com/anthropic-ceo-cost-10-bil...
[2] https://www.theinformation.com/articles/anthropic-hikes-2...
[3] https://www.energy.gov/articles/doe-releases-new-report-e...
[4] https://www.eia.gov/tools/faqs/faq.php?id=1174&t=1