This was interesting right up until "The fund pays every eligible American the same amount each year. "
I'm in Australia. I've contributed my share of dirt to the delta. Why do I not get a share of this?
I get that the frontier companies are (for the moment) US companies. But that's just corporate ownership, it's not what we're talking about. We're talking about compensating the people who wrote the training data for their contribution. That contribution came from all over the world, so the Corpus Fund needs to be paid all over the world.
Set it up in the UN, get the UN to provide the training data sets as a common good, and have the UN collect the money from all AI companies using the training data sets. And the UN should distribute the money in the most equitable manner globally (so most of it going to alleviate poverty, probably).
I'd happily trade my collected years of shitposts to help folks get out of poverty.
I agree UN sounds like a good organization to help distribute the wealth created by AI to the world. But this idea won't be considered by the current U.S. administration. In that case what other countries can do is probably to tax the AI companies at rates higher than regular companies.
The USA helped form the UN as specifically the organisation to do exactly this kind of thing. It's a shame the current administration can't play nicely with others.
The current administration is also playing strange games about export controls (can we run Fable yet? Kinda. Maybe). I think if they keep this up they'll just be shooting the US AI industry in the foot and the Chinese models will take over as the frontier models.
Maybe the UN can levy the USA for this, and leave the USA to collect that levy from its AI companies.
I have additional essays coming out that will address this exact issue and other issues I know that people will raise.
I’m building the essays series around arguing for practical policy I believe can get implemented and am sequencing it as thoughtfully as I can. I just can’t fit every argument into every essay.
It's a great idea, I hope you get traction with it :)
I am personally coming to the conclusion that having these vast repositories of knowledge that can actually talk to us is actually great. We have some issues to solve, but the end-state of having a global repository of all knowledge that can talk to us and answer questions is actually an amazing outcome.
We just need to solve those problems first; mostly getting past the AI bubble and the massive over-investment, and then solving the hallucination problems. I don't believe either of them are insoluble.
I do worry about how future generations move on from this, though. In the same way that 90's music is still effectively the zeitgeist, and we will never move on from that, because of the way that streaming services work. It's a rare new band that can compete with (e.g.) Nirvana when appealing to that segment of audience, a competition that Nirvana themselves didn't have. So we are effectively locking in Nirvana as The Disaffected Youth Grunge Band for the rest of eternity. So similarly, we are in danger of locking in the current state of the world to the training data, and never being able to move on from that, because any new zeitgeist has to compete with this one on unequal footing.
We cannot always want to capture only the (temporary) winners whenever we see a lucrative business and expect to share a free ride. I'd also assume that most of the revenue these AI labs are making is turned into depreciating fixed capital (hardware) and OPEX at this point.
Why don't we capture Meta and Google as they allegedly take advantage of more publicly available information for profit? Let alone the truly valuable knowledge, like mathematics, has nothing to do with the majority of garbage posts that an average person would "contribute" on social media.
If we really want to tax or nationalize some economic activity, then, in my opinion, the target should be what it takes from society, not what it produces for society. By this logic, we should tax all labs, including those lagging ones, that utilize the public knowledge.
However, if everyone can access the public knowledge without rendering it less useful or reducing its available quantity, there should be no reason to tax it.
I agree we’re in an interesting era where frontier research has shifted from mostly publicly funded to mostly private and it creates challenging incentive structures especially regarding externalized costs of research.
Did you have any thoughts on my argument of how public knowledge does get damaged by the proliferation of AI over time?
It was a brilliant article, and it succinctly captured the offenses to ethics and humanism posed by LLMs.
I'm not sure it'll get a lot of reception in the technocracy here on HN, whether of the AI booster or AI nihilist sort. However, I think it's a very comprehensive digestion of the questions that will swirl around the idea of LLMs as a public good in the near to medium future.
What technocracy lol? people here turn into luddites if there's a positive reception of AI.. I can guarantee that there are at least 40 percent of the top 5 comments of any positive/negative post about AI gonna turn "hackers" to luddites. It was amazing before Covid times and now it's indistinguishable from reddit.
Author here. Really appreciate you taking the time to read and for the kind comment.
I think the tension between these ethical questions and the practical realities (both the good and the bad) of AI is likely the defining issues for technology and perhaps society in this decade.
It’s important we’re thorough and rigorous with how we think and act here so I really appreciate you engaging with the topic.
Thank you in turn, I have circulated your piece to thoughtful friends.
My immediate, from-the-hip thought is that we are slowly lumbering toward the idea that LLMs ("AI") should be a public utility. It may take us quite a while to get there yet, as an unprecedented concentration of wealth and power is arrayed precisely against this outcome, but I think that will be the eventual effect, in that, "in the long run, we're all dead" kind of way.
I’m working through thoughts on this as well and agree with your read on the incentives.
There is an interesting set of conditions that happens if/when models get so competent that they’re effectively indistinguishable from each other and inference becomes a true commodity. IRL impact will lag this ofc but it’s such a wild time to be alive.
There’s a quote about how in some articles a switch is quietly flipped in the middle where the article was talking about what is and suddenly the author has everything to say about what should be.
I googled for the quote but all I got is useless web spam and meme style graphics about quotes from writers. But AI told me it was David Hume and provided the full quote.
The real question is when the day will come that AI become the fertile muck that a new thing grows from and clings to and the legal system needs to adjust to. I hope it’s a good thing.
> In every system of morality which I have hitherto met with [...] the author proceeds for some time in the ordinary way of reasoning [...] when of a sudden I am surprised to find that instead of the usual copulations of propositions is and is not I meet with no proposition that is not connected with an ought or an ought not.
I'm in Australia. I've contributed my share of dirt to the delta. Why do I not get a share of this?
I get that the frontier companies are (for the moment) US companies. But that's just corporate ownership, it's not what we're talking about. We're talking about compensating the people who wrote the training data for their contribution. That contribution came from all over the world, so the Corpus Fund needs to be paid all over the world.
Set it up in the UN, get the UN to provide the training data sets as a common good, and have the UN collect the money from all AI companies using the training data sets. And the UN should distribute the money in the most equitable manner globally (so most of it going to alleviate poverty, probably).
I'd happily trade my collected years of shitposts to help folks get out of poverty.
The current administration is also playing strange games about export controls (can we run Fable yet? Kinda. Maybe). I think if they keep this up they'll just be shooting the US AI industry in the foot and the Chinese models will take over as the frontier models.
Maybe the UN can levy the USA for this, and leave the USA to collect that levy from its AI companies.
I have additional essays coming out that will address this exact issue and other issues I know that people will raise.
I’m building the essays series around arguing for practical policy I believe can get implemented and am sequencing it as thoughtfully as I can. I just can’t fit every argument into every essay.
I am personally coming to the conclusion that having these vast repositories of knowledge that can actually talk to us is actually great. We have some issues to solve, but the end-state of having a global repository of all knowledge that can talk to us and answer questions is actually an amazing outcome.
We just need to solve those problems first; mostly getting past the AI bubble and the massive over-investment, and then solving the hallucination problems. I don't believe either of them are insoluble.
I do worry about how future generations move on from this, though. In the same way that 90's music is still effectively the zeitgeist, and we will never move on from that, because of the way that streaming services work. It's a rare new band that can compete with (e.g.) Nirvana when appealing to that segment of audience, a competition that Nirvana themselves didn't have. So we are effectively locking in Nirvana as The Disaffected Youth Grunge Band for the rest of eternity. So similarly, we are in danger of locking in the current state of the world to the training data, and never being able to move on from that, because any new zeitgeist has to compete with this one on unequal footing.
Why don't we capture Meta and Google as they allegedly take advantage of more publicly available information for profit? Let alone the truly valuable knowledge, like mathematics, has nothing to do with the majority of garbage posts that an average person would "contribute" on social media.
If we really want to tax or nationalize some economic activity, then, in my opinion, the target should be what it takes from society, not what it produces for society. By this logic, we should tax all labs, including those lagging ones, that utilize the public knowledge.
However, if everyone can access the public knowledge without rendering it less useful or reducing its available quantity, there should be no reason to tax it.
I agree we’re in an interesting era where frontier research has shifted from mostly publicly funded to mostly private and it creates challenging incentive structures especially regarding externalized costs of research.
Did you have any thoughts on my argument of how public knowledge does get damaged by the proliferation of AI over time?
I'm not sure it'll get a lot of reception in the technocracy here on HN, whether of the AI booster or AI nihilist sort. However, I think it's a very comprehensive digestion of the questions that will swirl around the idea of LLMs as a public good in the near to medium future.
I think the tension between these ethical questions and the practical realities (both the good and the bad) of AI is likely the defining issues for technology and perhaps society in this decade.
It’s important we’re thorough and rigorous with how we think and act here so I really appreciate you engaging with the topic.
My immediate, from-the-hip thought is that we are slowly lumbering toward the idea that LLMs ("AI") should be a public utility. It may take us quite a while to get there yet, as an unprecedented concentration of wealth and power is arrayed precisely against this outcome, but I think that will be the eventual effect, in that, "in the long run, we're all dead" kind of way.
I’m working through thoughts on this as well and agree with your read on the incentives.
There is an interesting set of conditions that happens if/when models get so competent that they’re effectively indistinguishable from each other and inference becomes a true commodity. IRL impact will lag this ofc but it’s such a wild time to be alive.
I googled for the quote but all I got is useless web spam and meme style graphics about quotes from writers. But AI told me it was David Hume and provided the full quote.
The real question is when the day will come that AI become the fertile muck that a new thing grows from and clings to and the legal system needs to adjust to. I hope it’s a good thing.
> In every system of morality which I have hitherto met with [...] the author proceeds for some time in the ordinary way of reasoning [...] when of a sudden I am surprised to find that instead of the usual copulations of propositions is and is not I meet with no proposition that is not connected with an ought or an ought not.