I agree with you re water. As long as they’re not permitted to use evaporative cooling, the water use is fairly reasonable, in the long term (though it’s a huge amount when first loading up—which imo they should be forced to pay above-market rates for and to fill extremely gradually).
Electricity though I’m not so sure. There’s one that’s going to be built near me (near in Australian terms—it’s a 3 hour drive, most of the way at a clean 110 km/h). It’s supposedly going to be allowed to plug directly into the nearby existing fossil fuel power station, where it will eat up basically the entire output. But if we set a requirement that they be entirely self-sufficient (or, say, 90% self-sufficient with a significant premium paid for any grid import) using only renewable power, then I agree, the electricity usage problem becomes largely a non-issue.
I’d also extend the environmental concern to add a third category, which is the impact specifically on the local community. The enormous use of what could have been otherwise productive land, the highly disruptive noise given off which disturbs locals, etc.
I also largely agree with you re intellectual property. I actually can’t find a moral difference (and the legal difference is yet to be clearly defined and might end up different across jurisdictions) between an AI training on material and a human learning from it. Training on pirated material is a different matter, but training on material available for free online is difficult to call wrong.
I think your point about the social implications and centralisation of control is spot on, but the nuance that I think is important to get out here is the difference between frontier LLMs and self-hosted models. Some people will object to both, but the social argument you made only really works against the former. Same with the environmental impact.
For me, the most important aspect is the economic impact. The reduction in demand for artists and editors. And the damage done by people relying on bad AI-driven information—or worse, decisions. The output is worse art There are ways AI can be used to remove or at least minimise these concerns, but under a capitalistic system that’s not going to happen.
I agree with you re water. As long as they’re not permitted to use evaporative cooling, the water use is fairly reasonable, in the long term (though it’s a huge amount when first loading up—which imo they should be forced to pay above-market rates for and to fill extremely gradually).
Electricity though I’m not so sure. There’s one that’s going to be built near me (near in Australian terms—it’s a 3 hour drive, most of the way at a clean 110 km/h). It’s supposedly going to be allowed to plug directly into the nearby existing fossil fuel power station, where it will eat up basically the entire output. But if we set a requirement that they be entirely self-sufficient (or, say, 90% self-sufficient with a significant premium paid for any grid import) using only renewable power, then I agree, the electricity usage problem becomes largely a non-issue.
I’d also extend the environmental concern to add a third category, which is the impact specifically on the local community. The enormous use of what could have been otherwise productive land, the highly disruptive noise given off which disturbs locals, etc.
I also largely agree with you re intellectual property. I actually can’t find a moral difference (and the legal difference is yet to be clearly defined and might end up different across jurisdictions) between an AI training on material and a human learning from it. Training on pirated material is a different matter, but training on material available for free online is difficult to call wrong.
I think your point about the social implications and centralisation of control is spot on, but the nuance that I think is important to get out here is the difference between frontier LLMs and self-hosted models. Some people will object to both, but the social argument you made only really works against the former. Same with the environmental impact.
For me, the most important aspect is the economic impact. The reduction in demand for artists and editors. And the damage done by people relying on bad AI-driven information—or worse, decisions. The output is worse art There are ways AI can be used to remove or at least minimise these concerns, but under a capitalistic system that’s not going to happen.