Despite its name, the infrastructure used by the “cloud” accounts for more global greenhouse emissions than commercial flights. In 2018, for instance, the 5bn YouTube hits for the viral song Despacito used the same amount of energy it would take to heat 40,000 US homes annually.

Large language models such as ChatGPT are some of the most energy-guzzling technologies of all. Research suggests, for instance, that about 700,000 litres of water could have been used to cool the machines that trained ChatGPT-3 at Microsoft’s data facilities.

Additionally, as these companies aim to reduce their reliance on fossil fuels, they may opt to base their datacentres in regions with cheaper electricity, such as the southern US, potentially exacerbating water consumption issues in drier parts of the world.

Furthermore, while minerals such as lithium and cobalt are most commonly associated with batteries in the motor sector, they are also crucial for the batteries used in datacentres. The extraction process often involves significant water usage and can lead to pollution, undermining water security. The extraction of these minerals are also often linked to human rights violations and poor labour standards. Trying to achieve one climate goal of limiting our dependence on fossil fuels can compromise another goal, of ensuring everyone has a safe and accessible water supply.

Moreover, when significant energy resources are allocated to tech-related endeavours, it can lead to energy shortages for essential needs such as residential power supply. Recent data from the UK shows that the country’s outdated electricity network is holding back affordable housing projects.

In other words, policy needs to be designed not to pick sectors or technologies as “winners”, but to pick the willing by providing support that is conditional on companies moving in the right direction. Making disclosure of environmental practices and impacts a condition for government support could ensure greater transparency and accountability.

  • Balder@lemmy.world
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    5 months ago

    AI evangelists act like it’s already perfect and anybody who dares question the church of LLM is declared a Luddite.

    I don’t think that’s the case, though. The only people I see actively “evangelizing” LLMs are either companies looking for investors or “influencers” looking for attention by tapping on people’s insecurities.

    Most people just either find it useful for some specific use cases or just don’t care. And a large part actually hate on it.

    • FiniteBanjo@lemmy.today
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      5 months ago

      You’re doing it right now. You’re criticizing that user for saying it’s okay to talk about AI’s failures. You’re the example, evangelizing and shilling. My advice: STFU.

      • Balder@lemmy.world
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        5 months ago

        You’re doing it right now. You’re criticizing that user for saying it’s okay to talk about AI’s failures. You’re the example, evangelizing and shilling. My advice: STFU.

        It seems like you missed the memo on reading comprehension. I literally quoted the exact part I’m criticizing, which clearly isn’t what you claimed.

        And being overly emotional and telling people to STFU online? That’s a masterclass in civility right there.

        • FiniteBanjo@lemmy.today
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          5 months ago

          Ohmahgosh you’re so right, I see it now, you telling them they were wrong to criticize AI was in fact the correct take all along. You’ve shown me the way, All Hail AI. ALL HAIL AI.

          What a fucking shill.