@SashaMTL

"For instance, with ChatGPT, which was queried by tens of millions of users at its peak a month ago, thousands of copies of the model are running in parallel, responding to user queries in real time, all while using megawatt hours of electricity and generating metric tons of carbon emissions. It’s hard to estimate the exact quantity of emissions this results in, given the secrecy and lack of transparency around these big LLMs."

https://arstechnica.com/gadgets/2023/04/generative-ai-is-cool-but-lets-not-forget-its-human-and-environmental-costs/

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@SashaMTL

"it’s difficult to carry out external evaluations and audits of these models since you can’t even be sure that the underlying model is the same every time you query it. It also means that you can’t do scientific research on them, given that studies must be reproducible."

https://arstechnica.com/gadgets/2023/04/generative-ai-is-cool-but-lets-not-forget-its-human-and-environmental-costs/

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@SashaMTL

Unknown environmental costs, non-reproducible science, data theft, and exploitative labor practices. And for what? A shiny toy to play with for the masses + the ability to claim "AGI" (while blocking scrutiny of the claim) for OpenAI and other #TESCREAL adherents.

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@SashaMTL Is the horse out of the barn? Do we just have to stand by and watch this go down?

Indeed not. We've collectively handled other sources of pollution (e.g. lead in gasoline, CFCs harming the ozone layer) before and we can do it again.

Let's heed @SashaMTL 's call to get engaged with the regulatory process!

@SashaMTL

p.s. re "the horse is out of the barn". That metaphor is used to express helplessness, a "there's-nothing-we-can-do-now" attitude. But do people with escaped horses really say "Oh well, was nice knowing ya horsey"?

I'd guess probably not.