The Medium comments on this post are also on point. Running the same experiment with accepted papers is a good control. Running a similar experiment with reviewers would be interesting, but more obnoxious because they are not being paid.
I would keep a private blacklist (shadow ban) the authors who wasted several hours of a reviewer's time to prove they were not legitimate. The existence of such a list would be problematic, though.
Could the same system we use here be applied? Accepted authors could "vouch" for "dead" papers in case they were "auto-killed"?
This system is broken and providing more evidence that it is broken isn't much of a step towards fixing it.
It strikes me as akin to plagiarism. If the purported author can’t even answer basic questions about the paper, how can they plausibly claim to have written it?
In the case where someone uses AI to write the paper and then deeply familiarizes themself with it, it may go undetected, but then it’s also presumably less of an issue since they have actually read it carefully and closely. If it’s still bad or wrong after that, then it’s not that different from a human writing a bad or wrong paper on their own and should be treated similarly.
> It strikes me as akin to plagiarism. If the purported author can’t even answer basic questions about the paper, how can they plausibly claim to have written it?
Authorship standards differ by field. In biology, for example, it would be common to list someone as an author if they assisted in one experiment. They might be at a different institution and may be unaware of all but the vaguest outline of the paper as a whole—they just got brought onboard because they are an expert in one particular task that needed to be done. In exchange they get to be a middle author (not worth much) and develop a relationship with someone whose expertise they may need on one of their own papers in the future (the primary benefit).
That is not the case here, of course—I just wanted to provide some context for your position not being universally applicable.
Only in small papers. Once the project is big or multi-disciplinary enough that co-first and co-last authorship become a thing, it's quite common that no single person fully understands the paper.
Ideally, but often not true of large complex studies. Typical example is that only a middle author statistician understands the details of data analysis. Also commonly true in quantitative genetics.
Yes. The cognitive process performed by a person using an LLM is often no different from that performed by a person using a ghost author, which is a form of plagiarism covered by 42 CFR § 93.234 - Research misconduct.
Plagiarism, at its most fundamental level, is a lie. It is the taking of works or ideas of others and passing them off as your own, either directly or indirectly. The misdeed itself is in the lie, the “I created this” when it is known to be untrue.
However, that lie isn’t being told to the original victim. It’s a lie about the victim, claiming that they didn’t create it or their contributions didn’t matter, but it’s not a lie to them. Instead, it’s a lie to the audience, which is the second victim and the actual target of the con.
This is a very good definition, but today people will just claim the AI is not a victim, and pass this argument off to the legal cases the labs are already having in court wrt fair use. It's sad, but this is the argument people have made to themselves.
In academic settings, it’s also plagiarism to copy your own previous work. Given that, I’m not sure academia gets to take the high ground on what constitutes misconduct or not wrt to plagiarism, at least in the edge cases.
It's often denoted plagiarism or self plagiarism as a short cut. While it's probably better denoted duplicate publication (or similar) it still constitutes a similar academic misconduct, because you're pretending something is novel without it being novel
As a side note quite often it can actually be literal plagiarism as well, many journals require you to assign copyright, so using that work without attribution is plagiarism.
The status of the true author is kind of irrelevant to whether it’s plagiarism or not. The true author may even be an active participant in the conspiracy.
The right response then perhaps would be to correctly assign AI the authorship it deserves instead of the human "operator/patron" who did not understand what the AI wrought, but merely acted as benefactor to provide the token fee.
A paper should stand and fall on its merits; does it build constructively on our collective understanding? Does it advance the state of the art in its field? Does it shed new light on a prior mystery?
So it seems there ought to be a path whereby a quality non-human paper ought to be considered for submission, provided it is adequately and correctly attributed.
fn-mote · · focus · HN ↗
I would keep a private blacklist (shadow ban) the authors who wasted several hours of a reviewer's time to prove they were not legitimate. The existence of such a list would be problematic, though.
Could the same system we use here be applied? Accepted authors could "vouch" for "dead" papers in case they were "auto-killed"?
This system is broken and providing more evidence that it is broken isn't much of a step towards fixing it.
nkrisc · · focus · HN ↗
In the case where someone uses AI to write the paper and then deeply familiarizes themself with it, it may go undetected, but then it’s also presumably less of an issue since they have actually read it carefully and closely. If it’s still bad or wrong after that, then it’s not that different from a human writing a bad or wrong paper on their own and should be treated similarly.
CrazyStat · · focus · HN ↗
Authorship standards differ by field. In biology, for example, it would be common to list someone as an author if they assisted in one experiment. They might be at a different institution and may be unaware of all but the vaguest outline of the paper as a whole—they just got brought onboard because they are an expert in one particular task that needed to be done. In exchange they get to be a middle author (not worth much) and develop a relationship with someone whose expertise they may need on one of their own papers in the future (the primary benefit).
That is not the case here, of course—I just wanted to provide some context for your position not being universally applicable.
nkrisc · · focus · HN ↗
kamma4434 · · focus · HN ↗
CrazyStat · · focus · HN ↗
jltsiren · · focus · HN ↗
robwwilliams · · focus · HN ↗
jedbrown · · focus · HN ↗
Plagiarism, at its most fundamental level, is a lie. It is the taking of works or ideas of others and passing them off as your own, either directly or indirectly. The misdeed itself is in the lie, the “I created this” when it is known to be untrue.
However, that lie isn’t being told to the original victim. It’s a lie about the victim, claiming that they didn’t create it or their contributions didn’t matter, but it’s not a lie to them. Instead, it’s a lie to the audience, which is the second victim and the actual target of the con.
<a href="https://www.plagiarismtoday.com/2019/08/01/the-two-victims-of-plagiarism/" rel="nofollow">https://www.plagiarismtoday.com/2019/08/01/the-two-victims-o...
figassis · · focus · HN ↗
michaelt · · focus · HN ↗
Copying from a book with a long dead author, or paying a willing confederate to write your thesis for you, is still plagiarism.
LadyCailin · · focus · HN ↗
cycomanic · · focus · HN ↗
As a side note quite often it can actually be literal plagiarism as well, many journals require you to assign copyright, so using that work without attribution is plagiarism.
nkrisc · · focus · HN ↗
tmoertel · · focus · HN ↗
dweekly · · focus · HN ↗
A paper should stand and fall on its merits; does it build constructively on our collective understanding? Does it advance the state of the art in its field? Does it shed new light on a prior mystery?
So it seems there ought to be a path whereby a quality non-human paper ought to be considered for submission, provided it is adequately and correctly attributed.
phyzome · · focus · HN ↗