I Used AI to Fake a Scientific Paper. Here's What Happened
spectrum.ieee.org
spectrum.ieee.org
There will have to be institutional adaptation to this, but it will be painful and I think the end-result will be worse that what we had pre-LLM. Things will be much more closed, inaccessible, and based on who you know. The openness of the last ~30 years will end.
Where is the profitability of truth in politics? In government? In media? Truth has fallen by the wayside.
The courts only care about the law, not truth or justice. Those are literally words that came out of a sitting federal circuit court judge.
People are being shown every day that truth can be whatever you want it to be. Until there are actual consequences for telling lies, nothing will change, and truth will continue to be increasingly irrelevant.
If LMMs fully flood the journal space with crap, then maybe journal publications can, finally, be de-coupled as a metric from performance assessments. The gate and all its perverse incentives then vanish. If anything LLMs might be the very thing that breaks the system and at least allow the possibility of something better to emerge from the ashes.
Now of course, to each its definition and metaphors are useful tools.
But when one starts a discussion on truth, trust or reality as core topic, it's better to start with what is meant with these words and in which context to which scoped boundaries.
Because of course, science can back a contemporary etnologic account that asserts there is no (longer) different races in homo sapiens, just as much as it can serve as frame for phrenology and whatever supremacism claim.
So no, we didn't build trust in science over centuries, and not even in any scientific person because we don't have that much humans to hold the role of such a trustable entity over such a long period of time.
Social institutions can carry unchanged names over centuries, but that tells nothing about how trustable are the people that inhabit them over time.
LLMs certainly come with their own challenges, but the erosion or scientific institutions with its bizarre scheme of publication process have been there basically as far as I can remember.
I wonder If the hypothetically criterion gives the models carte blanche to make up references.
Agentic models now, however, can correctly search pubmed or OpenAlex and obtain valid refs, so that tell is mostly gone.
Wait until we get the first retractions of papers with AI generated micrographs or blots, and synthetic data plots. That's the bit that really scares me.
Mathematics and science represent two systems for sorting truth from BS. An exponentially increasing supply of BS makes that even more necessary.
If you don’t rigorously verify everything by hand before then, you are telling the world that they must do what you should have done for you. Or more likely, you are telling the world that that you expect free intellectual labor and will be ignored and chastised- and cause more scrutiny to fall upon others who did the work properly.
Except in recent months, I've seen modern agents verify things more rigorously than I do now.
Could be a me thing ofc, but I've found that a human's eyes tend to glaze over while the agent just keeps on checking in more and more detail.
Most importantly, it’s bad at catching things that are not normally part of documented processes or openly reasoned about. I think that this specific weakness is extremely important and exactly how you end up letting something go by that would be trivial to catch for a human reviewer.
Also, kinda scary to think about how many scientific papers are probably written using AI these days. The system might have to change.
Journals now routinely ask you to declare any use of AI in writing. Better authors are up front about its use, so peer review can take this into account.
https://www.reddit.com/r/OpenAI/comments/1xgqv27/two_physici...