Yes, that is a major worry of mine, too. CCTV evidence is worth nil now (could be generated in whole or part), and even eye-witness testimony can be trusted (sure, a witness may think they saw the alleged perpetrator, but perhaps they just saw an AI-generated video/projection of someone).

MS13 was literally tattooed on his knuckles!

Multiple data sources, considering the trustworthiness of the source of the information, and accountability for lying.

You might generate an AI video of me committing a crime, But the CCTV on the street didn't show it happening and my phone cell tower logs show I was at home. For the legal system I don't think this is going to be the biggest problem. It's going to be social media that is hit hardest when a fake video can go viral far faster than fact checking can keep up.

By having people also testify to authenticity and coming down like the hand of God on fakers, the same way we make sure evidence is real now.

If it means anything, I have a 1990 Almanac from an old encyclopedia that warns the exact same thing about digital photo manipulation. I don't think it really matters at this point

AI is certainly a dual good but I think the project is misguided at best.

I put in one of the driest descriptions of the Holocaust I could find and it got a very high score for bias, calling a factual description of a massacre emotional sensationalism because it inevitably contains a lot of loaded words.

It also doesn't differentiate between reporting, commentary, poetry, or anything else. It takes text and spits out a number, which is a very shallow analysis.

It's more work to fight bullshit than it is to generate it, though. Saying "Use AI to fight it" is inherently a losing strategy when the other side also has an AI that is just as powerful.

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In short, yes.

A modern laptop is running almost fanless, like a 486 from the days of yore.

A single H200 pumps out 700W continuously in a data center, and you run thousands of them.

Also, don't forget the training and fine tuning runs required for the models.

Mass transportation / global logistics can be very efficient and cheap.

Before the pandemic, it was cheaper to import fresh tomatoes from half-world away rather than growing them locally in some cases. A single container of painting supplies is nothing in the grand scheme of things, esp. when compared with what data centers are consuming and emitting.

Cheaper/faster tech increases overall consumption though. Without the friction of commissioning a graphics artist to design something, a user can generate thousands of images (and iterate on those images multiple times to achieve what they want), resulting in way more images overall.

I'm not really well versed on the environmental cost, more just (neutrally) pointing out that comparing a single 10s image to a 5-6 hour commission ignores the fact that the majority of these images probably would never have existed in the first place without AI.

I work with direct liquid cooled systems. If the datacenter is working with open DLC systems (most AI datacenters in the US in fact do), there's a lot of water is being wasted, 7/24/365.

A mid-tier top-500 system (think about #250-#325) consumes about a 0.75MW of energy. AI data centers consume magnitudes more. To cool that behemoth you need to pump tons of water per minute in the inner loop.

Outer loop might be slower, but it's a lot of heated water at the end of the day.

To prevent water wastage, you can go closed loop (for both inner and outer loops), but you can't escape the heat you generate and pump to the atmosphere.

So, the environmental cost is overblown, as in Chernobyl or fallout from a nuclear bomb is overblown.

So, it's not.

If that energy is used for research, maybe. If used to answer customer questions or generate Studio Ghibli knock-offs, it's not worth it, even a bit.