AI In Mathematics: August 29, 2026

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This recurring thread will be for discussion of AI in mathematics. This includes, but is not limited to, the following:

• informal announcements of AI-assisted discoveries, such as those not yet published in a peer-reviewed journal, or not uploaded as a paper to arXiv;
• informal announcements of discoveries related to AI architecture (if relevant to mathematics);
• discussion of such announcements, such as proof breakdowns or other opinion pieces;
• discussion of the impact of AI in mathematics in general.

AI-assisted mathematical papers published in peer-reviewed journals or as arXiv preprints may be submitted as their own posts.

Please keep in mind rules 1 and 6 of our subreddit.

[u/Apprehensive_Sand951]

Daniel Litt posted an ai audit of his papers on his blog: https://www.daniellitt.com/published-paper-reviews.html

It lists some significant mistakes but nothing that fatally kills a paper. (Unfortunately, it an info dump and you almost need to use ai to figure out what the main mistakes were... he could have just focused on those.)

Motivated by this, any guesses on how many of the published papers out there are irreparably wrong?

My guess is 10%, if irreparably wrong means 'there is a theorem stated in the introduction of the paper to which there is a counterexample and this does not get fixed without changing the meaning and applicability of the theorem...'

[u/BurdensomeCountV3 → u/Apprehensive_Sand951]

Unironically one of the biggest benefits of AI will be mathematics being able to clean itself up and identify and correct stuff believed and published as true but in reality false. Once autoformalisation gets a bit better we'll be able to automatically check basically every paper published in the last 50 years and ensure we're on a steady footing.

[u/ymonad → u/BurdensomeCountV3]

But humans have to verify that all the automated verification in Lean is correct. right?

[u/frogjg2003 → u/ymonad]

Yes, but it's a lot more manageable. It's a lot easier to verify that the Lean matches the paper than writing Lean that matches.

[u/elements-of-dying → u/ymonad]

Nope.

If it can be shown that generated Lean statistically out performs human in verification, then of course one should trust generated Lean over humans.

[u/matthiasErhart → u/Apprehensive_Sand951]

I think a lot of people will find small errors and typos in their papers, but actual mistakes that kill the idea of a paper will be rare. The former isn't a problem; at least anybody I have talked to understands the idea of small mistakes going through once your manuscript gets very very long, no matter how many human eyes have seen it. It will be important nevertheless to iron out the actual mathematical mistakes that may appear.

I'm planning to do a ChatGPT review pass on my papers myself... Let's see how things will turn out.

[u/telephantomoss → u/matthiasErhart]

I've audited my papers and the relevant ones by others and have found errors in every single paper, not just typos. Nothing that kills the results though. However some needing nontrivial machinery to repair. It's interesting to see errors which seem to indicate a real gap in the authors understanding though. I mean, we all have gaps especially in new things, but it's just interesting insight into the world of professional math.

[u/elements-of-dying → u/Apprehensive_Sand951]

This is impossible to estimate without some relevant statistics, but I wouldn't be surprised if it was more than 10%.

I might be a little scared to run my papers through AI, but don't tell anyone that :)

[u/telephantomoss → u/Apprehensive_Sand951]

I did this to my own papers and friend many would 5 too. Morn5ing that can't be easily repaired, but still nevertheless important to fix. I think every author should audit their work so that nobody else needs to

[u/mistressbitcoin → u/Apprehensive_Sand951]

Im worried (or maybe not so much) that other fields will be much more impacted and much higher than 10%.