eh, farming still requires humans in the loop, only <1% of the number that it used to

OpenAI/Anthropic have never pitched themselves as a replacement for farmers. They do explicitly say that they're going to cause significant job loss in knowledge work sectors all the time.

Right - I'm saying that you can greatly improve productivity / reduce employment while still having humans in the loop. We've already seen it happen with farming, from 1900 -> present.

Oh thank you, yes that makes way more sense.

I mean, wanting billionaires to not live forever (read: wanting power structures to not become excessively entrenched) is a pretty different thing.

I'd even be fine with people who are billionaires living forever, so long as they don't remain billionaires / don't fuck with politics / etc.

> Fundamentally the problem with living forever goes beyond billionaires. People get stuck in their ways of thinking > Philosophically, living forever may be corrupt by nature

Sure, if people get stuck in their ways forever. But what if they don't?

If we can solve longevity, we might also be able to "solve" brain plasticity, therapy, psychology, sociology, etc., such that people's beliefs will be more flexible and people's minds more open.

I think it is incorrect to assume that we would solve biology while all of the fields researching the health of the mind made little progress.

We shouldn't imagine the future as being like today, only different in a few key ways - this is the trap of sci-fi authors. The future will be different in more ways than we expect. We might well fix 'old people are stuck in their ways' before we fix longevity.

You can "solve" human biology? For what optimal outcome? We can all be Elons running around trying to procreate as much as possible? What is the optimal human model? How is human biology NOT going to become anything except the same distorted race to the bottom that everything else has been? We've not solved the mental model of survival-of-the-fittest.

The best analogy for a positive outcome I can come up with is living within our means as a species. Leverage AI, leverage all the tools we have for production, but we have to find equalibrium with ourselves and the universe we live in.

I'll vote for the terminators and meteors if we insist on living beyond our means.

Nah, even in middle and high school it was plain that people sometimes misunderstood what the teachers meant. It's not like that goes away in adulthood; even when people "care", they still often misunderstand nuance or details, and sometimes even the bigger picture.

Honestly, it's plain weird to say that people never just make mistakes.

PS - worth adding that "I misunderstood" and "I didn't care enough" are not mutually exclusive. You can do both, so saying "they didn't misunderstand, they just didn't care" isn't a reasonable rebuttal. But even setting that aside, there'll be plenty of folks who care but still don't understand.

I'm gonna invoke Hanlon's handgun here: not attributing stupidity to what's adequately explained by systemic incentives promoting malice.

I normally assume people make mistakes. I don't believe this is a good explanation for news publications, university press releases, politicians, etc. because those are organizations with agenda, and commit "misunderstanding" of this type pretty much in every thing they publish. The pattern here is pretty conclusive, IMO.

> I normally assume people make mistakes. I don't believe this is a good explanation for news publications, university press releases, politicians, etc. because those are organizations with agenda, and commit "misunderstanding" of this type pretty much in every thing they publish. The pattern here is pretty conclusive, IMO.

The pattern of personal motives fits misunderstanding. You need to show that there is an organizational pattern of "malice" (your word, not mine), rather than an organizational pattern of "we are trying to publish quickly, and quality accidentally falls to the wayside". I.e., negligence, not malice.

You haven't provided even a shred of evidence suggesting there's malice at the journalist level. Every science journalist I have met genuinely cared about the science (which is why they were writing on it), but they didn't have time to learn enough about the subjects to understand they were oversimplifying things.

Not in science journalism, but I've personally encountered a case in normal journalism that I can only attribute to malice. It was many years ago, but it was so blatant I still remember it.

The 911 call went like this, according to its transcript. Caller: "This guy looks suspicious, like he's on drugs or something. It's raining and he's walking around looking into windows." 911 operator: "Can you describe him? What race is he?" Caller: "He looks black."

How the TV news reported it on the air was: Caller: "This guy looks suspicious ... He looks black."

Omitting excess verbiage is one thing. Omitting words that entirely change the context of the statement, making it look like the caller was racially prejudiced rather than responding to a specific question, is something else entirely. That was the last time I trusted reporting from that particular source (it was NBC, by the way).

My principle is that when someone lies to me, I stop trusting them. By lying I mean not just omitting details, or having an obvious bias, but deliberately telling me A when they clearly know that the truth is not-A. I could not see that report any other way but a deliberate lie, knowing the truth and attempting to make people believe the opposite.

> I didn't want to go too off topic, but since this is such a sticking point I need to make a big note about the US: most of the world is more sedentary than 100 years ago. But the obesity epidemic is mostly US-cerntric.

Note: nearly all of the western hemisphere has obesity rates of >25%. Obesity is also high in the Middle East and Australia/NZ.

The US, with an obesity rate of >40%, is exceptionally obese, but it's not correct to say that obesity is mainly a US problem. It's quickly becoming a worldwide problem.

https://en.wikipedia.org/wiki/Epidemiology_of_obesity#/media...

> We do know that LLMs can cause psychosis, we do know it can cause people to behave in an unhealthy manner, etc. We are seeing more and more evidence that AI usages in education is at least correlated with bad grades. We are seeing people exhibit addictive behavior around AI.

Aren't most of these true of amphetamines/methylphenidate also, though? Except the "bad grades" part. Certainly Adderall is habit-forming for some people and has risks for abuse, just like it can contribute to mental breakdowns and psychosis.

Likewise, the psychosis-LLM link is incredibly rare.

It kinda looks like you're overstating the evidence. This is not a good comparison to 1950s tobacco -- by the 1950s, the scientific evidence for tobacco being unhealthy was already quite substantial. The problem was getting that information to the public in the midst of a disinformation campaign. Here, for contrast, the evidence that moderate LLM use in professional settings has overall negative impacts is still pretty light.

I only use LLMs rarely, and I don't have any kind of emotional ties to the issue. I just think your claims extend decently far beyond the evidence.

Still, (chiming in), your claim that " I am also sure that every single one of them did indeed get addicted to nicotine, and many of them died from cancer" could use some evidence to back it up.

My understanding is that only about 35% of those who ever try nicotine become addicted.

If you are going to instead say that nearly everyone who smokes occasionally will become addicted, you need to back it up with evidence, because it's not apparent.

I am speaking general. I don‘t have historical sources either that people spoke like that in the 1950s, and that is a much more glaring omission of citation. If I am wrong about that my whole argument falls apart. But if say 65% of regular tobacco users who use some strategy or otherwise believe the addictive properties of nicotine won‘t apply to them for some reason, then my argument still stands.

I don‘t know the figure here, but if it is true that 35% of those who try tobacco get addicted, and given that we know nicotine is highly addictive, I would guess that most regular users do indeed get addicted (and so would most people).

> Musicians are paid to record music. If they were not, as is the case for ai data, we would indeed consider it theft.

I remember reading literature from the 1930s, and there were quite a few folks who thought that the musicians-doing-recordings were stealing from the old-timers who played for live audiences.

History does not exactly repeat itself, but it rhymes

I mean.. it feels kinda weird to say that you get to determine how other people use your work? Once you've sold your product, it's out in the open and available for use however the customer wants to use it.

If I bought a cake from your bakery, and then said "I'm going to serve it at my friends' gay wedding!", you couldn't be "hey, no, I don't approve of that". You've already sold me the cake; no take-backsies.

And if I buy a hammer, the hardware store doesn't get to tell me what I'm allowed to build.

If you're arguing for abolishing copyright, I'm all for it.

But as long as copyright exists, AI training should not get any exception to it. That creates an asymmetry, where AI gets to rip off our work and use it to compete with us, while we don't get to do the same with proprietary works (e.g. software).

I don't want a world in which AI can rip off all of my Open Source code and not respect its license, but I can't take macOS and virtualize it and not care what Apple thinks of that.

> If you're arguing for abolishing copyright, I'm all for it. But as long as copyright exists, AI training should not get any exception to it.

AFAICT, the courts currently lean towards allowing AI to be trained even without author permission, and this doesn't violate copyright law.

Copyright law says you can't sell unauthorized copies of copywritten works. Doesn't say you need to get author permission before using their works to train AI.

Yes, the courts are leaning towards creating the exception that I said should not exist, giving an advantage to AI companies over the humans that created the work they've trained on. That is not surprising, but it's still harmful.

So long as the AI company owns a copy of the copywritten work.. does training on it represent an "exception"?

They're not reproducing the work for sale, no? So how does training violate CR law?

Preparing a derivative work, and distributing that.

> It doesn't justify a funding system that didn't exist / didn't fund those researchers. We need to come up with better reasons to fund such a thing.

Do we?

For most of us, it seems like the EV (expected value) from such funding is quite positive. The work pays for itself in the long run. That's justification enough.

What you just did is come up with a better reason.

But I would suggest replacing "seems" with the best numbers available.

> But I would suggest replacing "seems" with the best numbers available.

I know there's research on it for applied and basic science in general, and the rewards were massively EV+. But I can't recall whether similar research covers applied and basic mathematics research.

> There's an obvious bias in focusing on retirees though. I mean, the whole notion of retirement exists for a reason.

I see this also among my early retiree friends. People are quite happy just "playing" - gardening, joining a book club, making art, etc.

And I would be, too! There are times I enjoy doing bigger work, but man, I could build quite a delightful life living like a hobbit.