It's hard to imagine what kind of contortions someone would have to go through to come to this conclusion.
Not one word of copyright length, which is now effectively over a century long. Not one word of some of the most successful AI models being open source.
Commons encirclement, as the author is describing, has been happening since source code was labelled art instead of engineering and since lobbying efforts have been extending copyright terms. My view is that AI technology are trampling over the encirclement, which is why so many people are upset.
" an intangible resource that "no one owns and is shared by everyone."" ... but if you try to share this "un-owned" intangible resource with others you will have police all over the globe harassing and maybe even imprisoning you (see: Anna's Archive).
So ... "no one owns" is doing some pretty heavy lifting there ... and it's kind of the foundation of the entire article.
Say what you will, but a million scientists and a network of sometimes-miscalibrated institutions (publishers, funders, universities, etc)... that feels less owned than maybe 4 companies having the edge on every [scientific?] field in the next few years...
Most published research is controlled by 5 for-profit corporations.
Academic publishing is predominantly controlled by a small
oligopoly of five for-profit corporations that collectively
publish roughly 50% of all scientific articles: Elsevier
(owned by RELX Group), Springer Nature, Wiley (John
Wiley & Sons), Taylor & Francis (owned by Informa PLC),
and SAGE Publications.
It only feels "unowned" to academics because their institutions pay for access, which they can use. The general public mostly cannot.
Going forward, colleges can pay for ChatGPT and things like it, and presumably will. The AI companies will be happy to sell to them. There's really no problems here except for self-created ones (for example, if some researchers don't want to use AI). Of course, they're free to do that, just like they're free to not use computers. But then don't complain that doing stuff takes too long.
US public libraries generally have access for everyone (at least they have everywhere I've lived), and you can walk onto a ton of campuses as a visitor to get their access.
Those 5 corporations have an achilles heel: reviewers. If the AI-driven science future has its way, the reviewers at all the major journals will collapse under the weight of submissions. The effect will be a denial-of-service, not unlike the one experienced by open source projects in the era of AI-driven pull requests.
An alternative to journals would be to switch to the arXiv model everywhere: let anyone publish with a bare minimum of moderation, let peer review happen out in the open, and allow for papers to be versioned to allow for fixing mistakes. The importance of a paper is already mostly determined by citations, not publication in a prestigious journal.
The author is coming from astrophysics where this is not the case. The major publications are operated from learned societies or public entities (RAS in UK, AAS in the US, ESO in Europe etc ...)
Well, they might also like a word with all of the scientists and students who make sure their papers are available online, despite Springer's draconic requirements. But that word is no longer heeded. Well, for the most part.
Don't let whiners pollute your mindset. Not even ones who package their insights in a nice scientific artifice like a white paper.
"all knowledge so far" (ie. the data needed for LLM training) is only a grain of sand on a beach compared to the return on making it all regurgitatable on demand.
We are at the bottom of a science, knowledge & art hockey stick chart, we're staring up at it and the steep bit is labeled "the future".
I agree it is terrifying because it is unknown. It is also true that the frontier AI labs have not worked well with affected communities at all and often downright exploited them.
BUT I also agree that, like any new technology, people will find mind-blowingly creative paths forwards with it, opening up whole new art forms.
> AI labs have not worked well with affected communities at all and often downright exploited them
The first reviews of OAI's dump on math are coming out. Quasi-Riemann Hypothesis Proof looks to be valid. The irony is that is uses and approach that the people who work in that area have disregarded for the most part. As well as mining some other parts of maths corpus. There really isnt "innovation" there.
For as much as OAI is guilty of leveraging work in progress, the complaints about some of the other work(s) are looking spurious (and I'm being very kind using that word).
this approach of calling critics "whiners" then making sweeping, naive statements regarding both capital-S Science and also markets, is shallow.
The West collectively has touched markets with Science using concepts of property rights. All of that is upturned now. I agree that publishing portals like Elsivier have done damage to Science while enriching the company and its allies. However that complaint looks quaint compared to literally four military-industrial groups running all new discoveries and their commercialization.
When you can equally reasonably make the opposite argument - that AI is going to open up scientific exploration and contribution to a wider range of participants than ever before - then I think it’s a sign that nobody has any idea what’s going to happen and spending time making either claim is probably pointless until we have more data.
Not necessarily, not in some of the most useful ways of simply having a significantly more capable way of automating research & experimentation of many sorts. Anyone with a dataset and a laptop with a decent gpu, or pretty reasonably priced API or subscription to access models that don't even need to be frontier level, they can setup a loop for intelligent iteration through countless analytical methods, subset analysis, enriching the data with other sources, search and retrieval of research literature to cross reference results of analysis with other findings and write a basic summary for the person to review, look for alternative methods for analysis.
Yes, not everyone will be able to launch a swarm of agents and a few billion tokens, but scientific research has always had areas where the most advanced tools were beyond the reach of every scientist who might like to have access.
Only for about five more years. In 7-10 years the price of memory and compute should drop by 80-90%. In ten years the bleeding edge 14,000 token/s machines and 4TB memory is going to look quaint, "that stuff can't even bootstrap a kernel and entire (usable) posix-compliant OS in less than a week" vs the future of "the computer updates it's firmware in real time to meet the needs of the current task"
The margins on GPUs are estimated at 80% right now. So the price would most likely drop by 70% just by building the additional manufacturing capacity. Assume some modest reductions in cost and the price should drop by 80-90%.
The only reason computers are so expensive is that demand is so out of control.
Not only resources being controlled by a few organizations, but the noise of all of the people who have used AI to “discover” something novel, when they don’t understand the domain in the first place. When everyone is discovering something, but what they are publishing is either incorrect or already known, how do you wade through the slop to find the gems (maybe academic publishing was already filled with human slop, though).
All journals will be brute-forced to death. Not the greatest time to be Phd student. And many people have no shame. They just use agents to make whole papers. Those who don’t, will double-guess their life choices.
> When you can equally reasonably make the opposite argument - that AI is going to open up scientific exploration and contribution to a wider range of participants than ever before
Is typing a prompt into ChatGPT "science"? It's an experiment, I guess, to find out whether you get a useful response out of it, and your hypothesis is that the model is able to answer your question correctly? How do you falsify that if you don't have the academic foundations to verify its answer?
We need to create a new scientific regime in the spirit of open source where scientific papers are not permitted to be used to train closed models. If you want to use the output of human ingenuity, you need to give something back.
One simple way to understand how this is currently manifesting is the administration's severe, and really unprecedented, defunding of basic science at NSF (likely in unconstitutional defiance of Congress' appropriations to specific NSF directorates). Instead the way the funding has been redirected (by the White House OSTP) is based on the assumption that future knowledge will be exclusively AI (sorry SI) generated, so humans not needed.
China, on the other hand, seems to be doubling down on fundamental research, including announcing these changes:
> Instead the way the funding has been redirected (by the White House OSTP) is based on the assumption that future knowledge will be exclusively AI (sorry SI) generated, so humans not needed.
Can you go into more detail about that? My impression is the real reason the Trump administration has defunded basic science (and so much else) is an unholy combination of "government bad" libertarianism and the belief the funding was going to their ideological opponents.
I feel that and use of AI to justify the redirection is most likely post-hoc.
Echoing what the other reply to your question said, I don't disagree that much of this post-hoc, but I think the thinking has evolved such that this post-hoc reasoning is now truly believed. I'm primarily speaking of it as an observer of how and where funds are being directed and to what ends: often big, non-university-centered programs to build labs or generate datasets for AI discovery. While some of the ideas may have merit, there is no free lunch unfortunately, as that was money that would have supported individual PIs and their trainees.
Going by the public announcements, the original plan was to cut science funding but once Congress said "no," the backup plan became directing it towards non - human - scientist items like facilities operations and the Genesis program.
This administration thinks science is 'woke' because it says things that disagree with him. Many of these funding cuts were explicitly politically motivated, e.g. they specifically targeted research about diversity, gender, or vaccines.
It's not about AI, it's about removing funding from liberal causes and giving it to conservative causes.
Unfortunately it is entirely related. The initial wave of cancelations were about those topics, but the more structural thing they are attempting now is to focus funds on tool development for AI models as opposed to human capital development as NSF does.
No it is about AI too. Trump et al want there to be no dispensing of federal grants to academics in the future. They want the government to instead cut checks directly to xAI et al who will do all our research for us in the future and will for certain represent our best interests and not those of shareholders exclusively.
If AI didn't exist, he'd find some other excuse to do the exact same thing.
The real reason for this is that Elon Musk is a conservative megadonor, while academics are vocally opposed to Trump. He takes from his enemies and gives to his friends; that's how he operates.
I don't really understand the rationale behind accepting change and knowing change is inevitable, but wanting any such change to be fully controlled every step of the way?
This is not that difficult. It's just like what happened to physical fitness/obesity after the invention of the car. Go look at countries that do it reasonably well (ie not the US). Copy exactly what they do, wholesale.
Not one word of copyright length, which is now effectively over a century long. Not one word of some of the most successful AI models being open source.
Commons encirclement, as the author is describing, has been happening since source code was labelled art instead of engineering and since lobbying efforts have been extending copyright terms. My view is that AI technology are trampling over the encirclement, which is why so many people are upset.
So ... "no one owns" is doing some pretty heavy lifting there ... and it's kind of the foundation of the entire article.
Going forward, colleges can pay for ChatGPT and things like it, and presumably will. The AI companies will be happy to sell to them. There's really no problems here except for self-created ones (for example, if some researchers don't want to use AI). Of course, they're free to do that, just like they're free to not use computers. But then don't complain that doing stuff takes too long.
Springer would like a word
"all knowledge so far" (ie. the data needed for LLM training) is only a grain of sand on a beach compared to the return on making it all regurgitatable on demand.
We are at the bottom of a science, knowledge & art hockey stick chart, we're staring up at it and the steep bit is labeled "the future".
BUT I also agree that, like any new technology, people will find mind-blowingly creative paths forwards with it, opening up whole new art forms.
The first reviews of OAI's dump on math are coming out. Quasi-Riemann Hypothesis Proof looks to be valid. The irony is that is uses and approach that the people who work in that area have disregarded for the most part. As well as mining some other parts of maths corpus. There really isnt "innovation" there.
For as much as OAI is guilty of leveraging work in progress, the complaints about some of the other work(s) are looking spurious (and I'm being very kind using that word).
The West collectively has touched markets with Science using concepts of property rights. All of that is upturned now. I agree that publishing portals like Elsivier have done damage to Science while enriching the company and its allies. However that complaint looks quaint compared to literally four military-industrial groups running all new discoveries and their commercialization.
This is not resolved at all...
I'm just advocating mindfully managing your own influences.
Yes, not everyone will be able to launch a swarm of agents and a few billion tokens, but scientific research has always had areas where the most advanced tools were beyond the reach of every scientist who might like to have access.
What's different this time is that this situation is expanding to just about every field.
The mechanism through which this occurs being..?
The only reason computers are so expensive is that demand is so out of control.
Is typing a prompt into ChatGPT "science"? It's an experiment, I guess, to find out whether you get a useful response out of it, and your hypothesis is that the model is able to answer your question correctly? How do you falsify that if you don't have the academic foundations to verify its answer?
China, on the other hand, seems to be doubling down on fundamental research, including announcing these changes:
https://www.globaltimes.cn/page/202609/1371583.shtml
and this: https://www.scmp.com/news/china/science/article/3368750/chin...
Can you go into more detail about that? My impression is the real reason the Trump administration has defunded basic science (and so much else) is an unholy combination of "government bad" libertarianism and the belief the funding was going to their ideological opponents.
I feel that and use of AI to justify the redirection is most likely post-hoc.
This administration thinks science is 'woke' because it says things that disagree with him. Many of these funding cuts were explicitly politically motivated, e.g. they specifically targeted research about diversity, gender, or vaccines.
It's not about AI, it's about removing funding from liberal causes and giving it to conservative causes.
The real reason for this is that Elon Musk is a conservative megadonor, while academics are vocally opposed to Trump. He takes from his enemies and gives to his friends; that's how he operates.
UK has strong inheritance tax, so common angricultural land is very strong and doing quite well!
Also shit tons of stuff you can not do on your "private" agricultural land, like producing too many cow farts!
https://www.youtube.com/watch?v=KPUlgSRn6e0 [Not Just Bikes]