AI and the Enclosure of the Scientific Commons

bennettnate5

> The scientific literature can be viewed as an "information commons:" an intangible resource that "no one owns Springer would like a word

contemporary343

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: https://www.globaltimes.cn/page/202609/1371583.shtml and this: https://www.scmp.com/news/china/science/article/3368750/chin...

Herring

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. https://www.youtube.com/watch?v=KPUlgSRn6e0 [Not Just Bikes]

Glyptodon

Admin, maybe merge with submission: https://news.ycombinator.com/item?id=50187248

daishi55

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.

cadamsdotcom

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".

hungryhobbit

" 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.

throw93939e8

> the English agricultural commons no longer meaningfully exist. 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!

anonymousDan

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.

6879346626

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?

abetusk

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.

stellar678

The discussion of open source was pretty anemic. The author seems to think open source is only GPL copyleft. In reality the vast majority of open source is permissively licensed, and the development was funded by for-profit companies. That seems like a crucial thing to consider when discussing how our information commons has come to be. Near the end they include a paragraph claiming we should interpret this piece as being about more than self-interest and resistance to change, but it doesn't really feel like the piece offered a taste of what that "more" is. The most thought-provoking part for me was considering that AI companies have used pretty much all available data for training while "they spend more and more money to create proprietary training data". That seems to break a sort of intuitive social contract - like, well you all used everyone's knowledge. Send yours back out too. Grant from 3brown1blue released a video exploring the economics and mechanics that enable careers in math, in light of the AI company releases over the last couple weeks. Overall it was a lot more hopeful, and it didn't need to strain awkwardly like this piece to apply an ill-fitting historical framework like enclosure. Worth checking out: https://www.youtube.com/watch?v=LKrwhjOI8Nc

hello_hnews

I got mine so FUCK all of you. I’m off to meet with the pope. - Dario

jerf

I have read more paper in the last year than the last ten years. Across a wide variety of subjects. While the AIs still need open access to science in order to function, they have make that open access something I can actually use like no other technology before it. Nothing has opened the scientific commons to me like AI. There may be a concern going forward with locking things down. One can lament that AIs need to be prompted to "hit the literature" directly or they don't really think about it, prefering random web pages most of the time. But at least at the moment science is more open and accessible than ever before.

Alex_Notchenko

Keep in mind if Alexandra Elbakyan shares the knowledge she is a criminal who needs to be extradited to face consequences. When you are a Californian AI lab that needs to train a model to give back all this static information to users, you are alright, actually you are the only thing keeping US economy going. Never be in out group its hard out there.

Merrill

The academic literature has a problem in that it is relatively incoherent. Each new paper provides some small advance, with only a meager indication of how it fits into the known science in the area, its importance, and its consistency with previous results. It also remains in the corpus if later publications disprove its results or fail to replicate them. Only slowly do the aggregate of published results find their way into more systematic and complete authoritative texts. AI promises to solve this problem by absorbing the entire corpus quickly and making a coherent whole available for further research and progress. It will be particularly useful if it can immediately flag any conflicts and inconsistencies, as well as any new relationships with other results not indicated in citations.