MIT says it no longer stands behind a widely circulated research paper by its student that claimed an AI tool boosted discoveries in a materials science lab

The university says it has no confidence in a widely circulated paper by an economics graduate student

Wall Street Journal 2025-05-17 Justin Lahart

Context & Ripple Effects

MIT’s repudiation of a student-authored paper puts a high-profile claim about AI-assisted scientific discovery under institutional doubt. It echoes a prior high-profile research retraction in which a quantum-computing team said evidence had been selectively presented after a widely read quantum-computing claim was retracted.

The story also fits mounting scrutiny of AI-shaped research output: analysis in the related coverage found that scientists appearing to use LLMs posted more papers on arXiv as LLM-linked authors increased their arXiv output, while arXiv later tightened its screening rules by requiring venue vetting for computer-science submissions.

First-order effects

MIT’s loss of confidence strips the paper of its institutional backing, forcing readers to reassess its claimed evidence that an AI tool improved materials-science discoveries.
The student author and any researchers relying on the paper’s findings face immediate credibility and verification pressure, particularly around the reported discovery process.

Second-order effects

Materials-science labs and AI-tool developers promoting discovery workflows will face stronger demands for reproducible evidence rather than headline results from a single study.
Publishers, repositories and institutions have added incentive to scrutinize AI-related research claims before circulation, a direction reflected in arXiv’s subsequent one-year ban for papers with incontrovertible AI-generated work.

Third-order effects

If similar disputes persist, AI-for-science will be judged less by claimed acceleration and more by auditable experimental validation, tightening the path from model output to accepted scientific knowledge.
Research institutions may increasingly treat provenance, supervision and reproducibility as governance requirements for AI-assisted work—not merely as conventional peer-review concerns.

The trend: AI’s growing role in research is shifting scientific competition toward stronger verification and institutional accountability for AI-assisted claims.

Discussion

@phdhurtbrain Tobias Wilson-Bates on bluesky
The issue with deception is that none of us understand *everything* and therefore there is always some edge to our understanding that can be deceived, and this is true of researchers, and journals, and whole fields of study thebsdetector.substack.com/p/ai- materia...
@kevinjkircher.com Kevin J. Kircher on bluesky
The top economics journal in the world nearly published an article that, to all appearances, is 100% bullshit. It claimed that AI accelerates scientific discovery. An MIT PhD student appears to have used generative AI to fabricate the whole thing, data and all.
@mims Christopher Mims on bluesky
Famous paper saying AI boosts scientific productivity appears to have been completely faked in every aspect, may even have included the researcher faking a web domain to use as a source for the faked data (!) — via @kevinjkircher.com — thebsdetector.substack.com/p/ai- materia…
@sivav Siva on bluesky
Journalists seem ready to believe and promote any AI BS claim — the more implausible the more likely to be hyped. Meanwhile, LLMs threaten to undermine the integrity of the scholarly process. — thebsdetector.substack.com/p/ai- materia...
@oddletters M. R. Sauter on bluesky
my contribution to this discourse is that newspapers and magazines should not cover preprints or working papers. its like giving the front page of the new york times book review section to a draft fished out of slush pile thebsdetector.substack.com/p/ai- materia...
@jdportes Jonathan Portes on bluesky
Fascinating deep dive into the MIT economics/AI paper scandal/clusterf***. — thebsdetector.substack.com/p/ai- materia...
@maurogilli Mauro Gilli on bluesky
This is tragicomic story. It's tragic because the MIT PhD student managed to get kicked out of MIT, might never get a PhD, and might have to change his name to start a new life (not as bad as LaCour, as this was stopped way earlier, but still quite big). — thebsdetector.substa…
@himself Henry Farrell on bluesky
thebsdetector.substack.com/p/ai- materia... If this critique is roughly on the mark, it would suggest that QJE fell victim to a version of the Sokal Hoax problem - accepting at face value claims about a different field that econ editors/reviewers are not, actually, qualified to p…
@prietschka Paul Rietschka on bluesky
Arxiv is pox in every possible way. — Burn it to the ground and salt the earth after.
@skynetandchill.com @skynetandchill.com on bluesky
There was a paper that said a materials science lab was successful with AI, MIT now says “has no confidence in the provenance, reliability or validity of the data and has no confidence in the veracity of the research contained in the paper.” Student is no longer at MIT.
@jakejares Jake Jares on x
Utterly wild fraud case. Econ finally has its LaCour / Gino / Ariely / Stapel moment . I can almost understand why one could expect to get away w/ this in 2012, before replication was in vogue. But it's 2025! How was this going to come out in the QJE without ppl catching on?
@johnruf6 John Ruf on x
At this point what does peer review even accomplish? It doesn't claim to check the data. It doesn't claim to check the code. It just has a few people with clear horses in the race do a “vibes check”, delay it for 5 years, and then someone else has to come along to debunk it?
@emollick Ethan Mollick on x
With the retraction of the MIT paper, we now have no clear experimental evidence that LLMs act as a multiplier for high performers (even though that would still seem to make sense). Lots of evidence that low performers get a big performance boost, though, across many studies.
@emollick Ethan Mollick on x
This paper was apparently fraudulent. From MIT. https://economics.mit.edu/... Thanks to @Robert_Palgrave for following up on his suspicions.
@jon_hartley_ Jon Hartley on x
The crazy part of the story is if he hadn't been caught, there's no doubt he would be a star professor
@cremieuxrecueil @cremieuxrecueil on x
A paper that I previously cited here for it's cool results (described below) was just retracted for fraud. It was entirely made up and the experiment never happened. The author has been kicked out of MIT. [image]
@calebwatney Caleb Watney on x
Woof. Very sad to see. The MIT econ department has recommended that this paper be withdrawn... [image]
@_alialkhatib Ali Alkhatib on x
you should skim the quotes on this tweet, bearing in mind that MIT investigated and recently asked that the paper be retracted because they had “no confidence in the provenance, reliability, or validity of the data [or] ... in the veracity of the research contained in the paper”.
@maiamindel Maia on x
Bro imagine the top economist in the field, who got a Nobel Prize *last year* showing up and going “grok is this true” at your paper and it turning out so badly for you that it gets publicly rolled back and also you get expelled from MIT (clocked the “former student")
@florianederer Florian Ederer on x
It is deeply ironic that the first AI paper to have hallucinations was not even written by an AI.
@captgouda24 @captgouda24 on x
It's funny that when I saw this paper, I saw that he was in his second year, and basically went “gosh, the MIT students really are just better than me”. I'm not saying they're not better than me, just that this gives me a lot more self-confidence!
@arthur_spirling Arthur Spirling on x
I'm curious to see the post-mortem here; I worry it's basically LLM-generated data all the way down. Maybe not much we can do can do about that, but —and I know I'm boring on this—we will need to get a firm hold of what “replication” looks like in the AI-era.
@robert_palgrave Robert Palgrave on x
An addendum to the suspicious AI discovery paper, here is a recording of a seminar given by the author on Jan 15 where he presents and answers questions on his work. Interesting watch given what we now know... https://cassyni.com/...
@rlacombe Romain Lacombe on x
MIT retracted the Toner-Rodgers paper on AI's impact on materials discovery due to fabricated data. Reminder to be skeptical of strong claims about early impacts from rapidly advancing technologies. If it sounds too good to be true, it probably is. We should be more paranoid. [im…
@florianederer Florian Ederer on x
We do not yet know the details of the research misconduct that led to MIT retracting the AI paper and the student leaving the PhD program. But it certainly seems in stark contrast to how other institutions responded to research misconduct of their tenured faculty members.
@heydarisys Babak Heydari on x
Amazing how one (now-retracted) MIT PhD paper wrote the whole “AI makes professionals superhuman” script. A few months ago all researchers wanted its secret sauce; now we're back to Grandma's rule: if it's too good to be true, it probably isn't.
@bradchattergoon Brad Chattergoon on x
Very sad to see that this paper was in fact fraudulent as pointed out by EM in a recent follow up tweet. The disclosure from MIT states the paper is by a “former second-year PhD student in the Department of Economics at MIT” so the author is no longer at MIT. 1/
@vshih2 Victor Shih on x
MIT said it can no longer stand behind a widely circulated paper on artificial intelligence written by a doctoral student in econ/ wow but the pressure is so great that un-established scholars would be tempted but making up data from a large lab? https://www.wsj.com/...
@stuartbuck1 Stuart Buck on x
@BrianCAlbrecht ... I was skeptical of the paper a while back: https://x.com/...
@jerusalemdemsas @jerusalemdemsas on x
Woof. A very interesting paper I covered on Good on Paper about AI's impact on a materials science company is being accused of fraud. [image]
@arnauddyevre Arnaud Dyevre on x
MIT has requested that this paper—which I found impressive—be withdrawn from arXiv and the journal where it was under review. Due to “provenance, reliability or validity of the data”. Full statement here: https://economics.mit.edu/...
@robert_palgrave Robert Palgrave on x
Update on this paper from last year on AI in scientific discovery. MIT put out a press release: “no confidence in the provenance, reliability or validity of the data...[or] veracity of the research.” “The author is no longer at MIT.”
@asymmetricinfo Megan McArdle on x
Every time one of these stories drops, I am once again enraptured by the question of why the hell people fake the kind of ground-breaking research that will definitely get them caught when their fellow scientists scramble to replicate it.
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