Off-topic: I had never seen ethernet cables labelled like that before with colour - number codes like resistors, that's really cool and now I must have it
As I expected, the author made no attempt to calculate the carbon footprint of the human artists and other workers that these AIs can replace, or the carbon savings from productivity gains or other similar efficiencies. If a call center gets closed because the workers were replaced by AI that's a ton of commuting and such that's no longer needed.
They may do something that doesn't involve as much commuting. They'll be doing something that wasn't being done before. Productivity gains means more work gets done, overall.
The point is that the author's analysis is simple-minded to the point of uselessness. If I were to object to building a hospital in a neighborhood because whenever a hospital is added to a neighborhood it results in a sharp increase in the number of people dying there, you'd rightly call me out for looking at just one specific number while ignoring the overall benefits. It's not like these AIs just pop into existence and spew CO2 like some sort of Captain Planet villain's pollution factory, the AIs are doing something and that has value.
Answer: reach for the Gartner Hype Cycle, an ingenious diagram that maps the progress of an emerging technology through five phases: the “technology trigger”, which is followed by a rapid rise to the “peak of inflated expectations”; this is succeeded by a rapid decline into the “trough of disillusionment”, after which begins a gentle climb up the “slope of enlightenment” – before eventually (often years or decades later) reaching the “plateau of productivity”.
This hype has given rise to much anguished fretting about its impact on employment, misinformation, politics etc, and also to a deal of anxious extrapolations about an existential risk to humanity.
Which, in turn, means CO2 emissions on a large scale – about which the industry is extraordinarily coy, while simultaneously boasting about using offsets and other wheezes to mime carbon neutrality.
The implication is stark: the realisation of the industry’s dream of “AI everywhere” (as Google’s boss once put it) would bring about a world dependent on a technology that is not only flaky but also has a formidable – and growing – environmental footprint.
A study in 2019, for example, estimated the carbon footprint of training a single early large language model (LLM) such as GPT-2 at about 300,000kg of CO2 emissions – the equivalent of 125 round-trip flights between New York and Beijing.
Ways of seeingIn an intriguing blogpost, Om Malik describes why Apple’s fancy, soon-to-be-released headset Vision Pro will change photography.
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