In recent years I’ve been struggling with depressive thoughts whenever I think about what’s been going on in the field of fundamental theoretical physics research. As an example of what I find depressing, today I learned that the Harvard Physics department has not only a Harvard Swampland Initiative, but also a Gravity, Space-Time, and Particle Physics (GRASP) Initiative, which this week is hosting a conference celebrating 25 years of Randall-Sundrum. Things at my alma mater are very different than during my student years, which lacked “Initiatives”, but featured Glashow, Weinberg, Coleman, Witten and many others doing amazing things.
For those too young to remember, Randall-Sundrum refers to large extra dimension models that were heavily overhyped around the end of the last millennium. These led to ridiculous things like NYT stories about how Physicists Finally Find a Way To Test Superstring Theory, as well as concerns that the LHC was going to destroy the universe by producing black holes. At the time 25 years ago, hearing this nonsense was really annoying. I had assumed that it was long dead, but no, zombie theoretical physics ideas it seems are all the rage, at Harvard and elsewhere.
One consolation of recent years has been that I figured things really couldn’t get much worse. Today though, I realized that such thoughts were highly naive. A few days ago Steve Hsu announced that Physics Letters B has published an article based on original work by GPT5 (arXiv version here). Jonathan Oppenheim has taken a look and after a while realized the paper was nonsense (explained here). He writes:
The rate of progress is astounding. About a year ago, AI couldn’t count how many R’s in strawberry, and now it’s contributing incorrect ideas to published physics papers. It is actually incredibly exciting, to see the pace of development. But for now the uptick in the volume of papers is noticeable, and getting louder, and we’re going to be wading through a lot of slop in the near term. Papers that pass peer review because they look technically correct. Results that look impressive because the formalism is sophisticated. The signal-to-noise ratio in science is going to get a lot worse before it gets better.
The history of the internet is worth remembering : we were promised wisdom and universal access to knowledge, and we got some of that, but we also got conspiracy theories and misinformation at unprecedented scale.
AI will surely do exactly this to science. It will accelerate the best researchers but also amplify the worst tendencies. It will generate insight and bullshit in roughly equal measure.
Welcome to the era of science slop!
Given the sad state of affairs in this field before automated science slop generation came along, I think Oppenheim is being far too optimistic. There currently is no mechanism to recognize and suppress bullshit in this area, together with strong pressures to produce more bullshit. I hope that I’m wrong, but I fear we’re about to be inundated with a tsunami of slop which will bury the field completely.
I haven’t had time to read the Steve’s paper in detail (or Jonathan’s response) but I think calling it nonsense is somewhat harsh and it’s not what Jon meant to say. I’ve spent a lot of time with GPT Pro in the past months and it has indeed gotten quite good at physics, though it still lacks originality (and has a bad habit of guessing maths rather than actually doing calculations). But either way you look at it, the progress in the past year has been dramatic. It’s gone from basically completely useless, unable to even correctly parse latex, to being mostly correct.
It is foreseeable that we will go through an AI slop period in the foundations in the coming year or two, but personally I think it’s a good thing because it’s basically a reductio ad absurdum for the idiotic theory-production machine that has been going on for the past decades. We’re so-so close now to automating the “invention” of dark sectors or modified gravities and cranking out the maths in a ready-to-submit format, and that stuff is going to flood the arXiv and journals in the years to come before, hopefully, we will finally see journals put an end to this and refuse to publish the stuff (which should have happened 20 years ago).
Regardless of the veracity of the core idea, Hsu doesn’t acknowledge the role of the AI LLM assistance in the main paper in its generation of the research direction. I found it surprising that he then explains that role in a separate paper, but apparently carefully avoids it in the main paper, mentioning only peripheral uses of AI assistance in the acknowledgments section. I’d have thought would be a violation of the journal’s rules around acknowledgment.
Sabine,
I just don’t see how this is going to lead to journal reviewers or the field in general changing and, finally after all these years, turning around and starting to be able to distinguish between what’s worthless and what’s worthwhile. It seems more likely that it’s just going to finish off the field for good.
Gary Ruben,
Some people have argued that Hsu should have listed the LLM as a co-author.
Hsu is now an AI entrepreneur and motivated to sell the story of “AI can now do theoretical physics”. Others out there are motivated to get lots of papers in their name written, so will do the same thing as him, but not acknowledge the LLM role.
Peter,
Another development is much worse. I can testify that at least one journal has started using AI to generate “referee” reports, so that it needs to find fewer real referees. This has happened to me a few months ago. And it was a large publisher.
This development – maybe we should call it “referee slop” – explains the high article processing charges that at least this publisher demands. But this is not what an author wants. And this is not good for theoretical physics.
Calling the GPT5 paper “nonsense” is accurate, not harsh.
A paper that purports to show one thing but uses criteria for showing something else is nothing if not nonsense. It demonstrates lack of understanding (by both the bot and the human author) of what was written.
That it might have accurately reproduced some other physics in the process is irrelevant.