Is it just me, or are the top 0.001% becoming increasingly annoying and dangerous? Given the effectiveness of today's family trusts in preserving wealth from taxes, stupidity, and fraud, this problem may only get worse. The risk free returns on billions is tens to hundreds of millions per year, mostly in tax free shelters. They can't buy yachts and tropical islands fast enough, and Congressmen are surprisingly affordable. Nor will their heirs.
What is equally disturbing is that Ackman and others are using hostile tender offer techniques to acquire non-profit institutions. Specifically, they are using their donation history to threaten the institution...when, in fact, their donation does not come close to the accumulated donations of others in the past, or to all alumni donations now or in the future.
Perhaps alumni associations or informal alumni groups need to stand up and say: Stop the Steal.
Harvard should decide if its mission is to sell prestige to the privileged, or to provide the best education. If it is the latter, here are some ideas:
1) All admissions are through a 'veil of ignorance' on student identifiers and connections.
2) A large percentage of all donations must be directed to scholarships, stipends, books, etc.
3) The number of students increases with donations.
4) Admission essays and English proficiency are accepted in a controlled environment to reduce cheating.
Ivy League schools don't give athletic scholarships. I think educational endowments fall into a special category and they are not required to spend down 5%/year as other endowments are. I'm on a educational non-profit and we don't call it an endowment; it is an investment fund, thus no yearly spend down. The Ivies certainly could provide free tuition to all under grads without doing much to impact their endowment.
Perhaps the Ivies could but considering the demographic from which they pull I really do not care if those students' parent get a good deal. Harvard, with a $50.9b endowment and a $581m total undergraduate tuition charge, certainly could provide a 100% subsidy assuming a 5% spending rate--That would still leave Harvard with $2b per/year endowment support.
That said, considering the tuition discount rate at the Ivies (that is, net tuition after college administered financial aid), they are already subsidizing tuition. I have seen a publication listing Harvard, Yale, Princeton, Columbia, etc., with tuition discount rates of 68% to 64%. And NACUBO reports that last year the nationwide tuition discount rate was 56.2%. Of course, that's an average; your results may vary.
It is most certainly very clear that Ackman has scarcely any grasp of what present neural network AI is truly all about and just how fundamental its limitations really are. It is possible that our "AI" friends will someday manage to find a way to truly intelligent AI but right now it is far from clear how, and Ackman is one of the last people whose advice on such matters should be heeded. Unfortunately, he and the thundering hordes of those of like mind suck a great deal of energy and resources out of serious research.
Another moron who thinks the fact he can play the market means he's smart. Time to start eating the rich. I hear they're tasty, lightly sauteed with a nice Chianti.
What I find insidious about this entire plagiarism situation is that it feels to me like we're defining downward the meaning of texts in favor of their form. Is the measure of ideas Check Undergrad Papers Dot Com? Is this the standard we're reaching for, here? If there's unquoted citations in a paper, if we're dealing with one another in good faith, you know that and I know that.
In effect, once the tables are turned, Ackman is joining the "no big deal" defenders of Claudine Gay, with whom I have some sympathy. He assumes that, with a careful check, everyone in academia will be found to have omitted quotation marks, or quoted Wikipedia improperly. He might be right.
If it's also true that students are being punished severely for small-scale errors of this kind (as Gay's critics have claimed), then maybe we should relax our standards a bit. But Turnitin usually picks up such things - the real issue with students involves essay writers for hire, reuse of essays from students who have taken the course previously and so on.
Speaking as somebody that used to actually do computational lingustics for a living: If you were only worried about a strict string-matching algorithm, the tiniest paraphrase would let you hide. There are various word-substitution and syntactic-analysis things you could do with a rules-based model that would let you identify, say, a string of 50 words that matches source other than the occasional swap. A "fuzzy" string-level match.
But I think it is almost certainly correct that the current generation of LLMs either can, or at least could, do a better job than this, at identifying strings of 50+ words that are likely to be "the same". You might need to train it on a few thousand examples first of not-identical texts that were, in the past, identified as significantly plagiaristic, and then after that, it can compare each paragraph of a paper, to its entire corpus, and spit out instances where it sees a likelihood of plagiarism.
The question would be, as you say, how many false positives it turns up, and how good it can get if you give it feedback when some calls are wrong. My _suspicion_ is that while it would make a lot of false-positives at first, it would get better after a few hundred of those were pointed out to it. And ultimately the goal with it would be that you don't bother to move on to the next level of human review unless it's found _multilple_ examples in a given person's body of work.
Fundamentally I think it is correct that the current-gen LLMs will be possible to train to be _much_ better at this kind of work than a mere fuzzy string match algorithm.
Of course, this all is an enormous and absurd waste of resources, but, well, Bill Ackman is an absurd man.
A slander of Nikolai Ivanovich Lobachevsky, even if Tom Lehrer made a very funny song of it. Really, has the consensus of historians of mathematics done an about-face in the last 50 years or so? Because Lehrer, IIRC, actually recanted his Lobachevsky remarks as an outdated idea -- that is, as a mathematician; naturally as an artist he didn't mess with the song.
I was assuming that was Judd's joke -- Ackman will go hunting for plagiarism and make a lot of wild, unfounded accusations, just as people (wrongly) accused Lobochevsky.
The strange part to me is that of course no one can survive AI interrogating their work, when LLM AI will simply say, "Yes, of course" until you say "No, you're wrong" in which case it will volte-face immediately into "Yes, of course I'm wrong".
I need to have ChatGpt rewrite every quote I failed to put quote marks around the sentence or paragraph I lifted without a footnote.
This is such a joke.
Particularly when they use AI to detect these failures to attribute or cite a source. ChatGpt does this all the time, using its training set.
In reality, what a researcher does is read a whole lot of stuff, and gets trained on it, as does CjatGpt. One get's outed for doing the work of understanding what was read, and the other does not.
The real question is innovation: will we be tied to the learning of the past, which serves as the training set of ChatGpt, and will we give recognition, or be able to recognize, innovation in a paper, even if there are places where someone didn't give a citation or place a quote mark.
This is an innovative comment which has not been generated by ChatGpt, although I am working on a literature review which certainly will be generated by ChatGpt.
And actually, a plain, efficient non-AI test scan could be made to recognize paragraphs and even distinguish between long ones, assumed to have real substance and therefore under grievous suspicion of plagiarism, and single sentences, which are likely, as in large part among the claimed plagiarisms, just cases of the use of the same few words in stating an obvious conclusion, which is what writers do when they want to be clear rather than follow the bad advice of so many language teachers to avoid ever using the same word, or words, twice.
NB: anybody using the above passage without proper attribution is being unscholarly, not that it matters much.
I view Ackerman's tweet as a continuing deflection of the attention on his wife. Ackerman was the "bully" who forced hay's resignation by demanding her palgiarism was a firing offence. Then his wife was outed but he, reasonably, defended her. What he should have done is acknowledged her plagiarism and retracted his deman gay be fired. But no, he has deflected by trying to show everyone in academia has plagiarized work to some extent. But while academices shouldn't plagiarize, why not extend this analysis to everyone in power to extract their plagiarisms? If "everyone does it", why demand such a universal trait be be focused on an academic institutional leader?
If one wants to use an LLM at all, use it to detect outright lies? Then target it at politicians, institutional leaders, religious leaders, pundits etc. That would be far more important than plagiarism.
Is it just me, or are the top 0.001% becoming increasingly annoying and dangerous? Given the effectiveness of today's family trusts in preserving wealth from taxes, stupidity, and fraud, this problem may only get worse. The risk free returns on billions is tens to hundreds of millions per year, mostly in tax free shelters. They can't buy yachts and tropical islands fast enough, and Congressmen are surprisingly affordable. Nor will their heirs.
What is equally disturbing is that Ackman and others are using hostile tender offer techniques to acquire non-profit institutions. Specifically, they are using their donation history to threaten the institution...when, in fact, their donation does not come close to the accumulated donations of others in the past, or to all alumni donations now or in the future.
Perhaps alumni associations or informal alumni groups need to stand up and say: Stop the Steal.
Harvard should decide if its mission is to sell prestige to the privileged, or to provide the best education. If it is the latter, here are some ideas:
1) All admissions are through a 'veil of ignorance' on student identifiers and connections.
2) A large percentage of all donations must be directed to scholarships, stipends, books, etc.
3) The number of students increases with donations.
4) Admission essays and English proficiency are accepted in a controlled environment to reduce cheating.
5) End athletic scholarships.
Ivy League schools don't give athletic scholarships. I think educational endowments fall into a special category and they are not required to spend down 5%/year as other endowments are. I'm on a educational non-profit and we don't call it an endowment; it is an investment fund, thus no yearly spend down. The Ivies certainly could provide free tuition to all under grads without doing much to impact their endowment.
Perhaps the Ivies could but considering the demographic from which they pull I really do not care if those students' parent get a good deal. Harvard, with a $50.9b endowment and a $581m total undergraduate tuition charge, certainly could provide a 100% subsidy assuming a 5% spending rate--That would still leave Harvard with $2b per/year endowment support.
That said, considering the tuition discount rate at the Ivies (that is, net tuition after college administered financial aid), they are already subsidizing tuition. I have seen a publication listing Harvard, Yale, Princeton, Columbia, etc., with tuition discount rates of 68% to 64%. And NACUBO reports that last year the nationwide tuition discount rate was 56.2%. Of course, that's an average; your results may vary.
It is most certainly very clear that Ackman has scarcely any grasp of what present neural network AI is truly all about and just how fundamental its limitations really are. It is possible that our "AI" friends will someday manage to find a way to truly intelligent AI but right now it is far from clear how, and Ackman is one of the last people whose advice on such matters should be heeded. Unfortunately, he and the thundering hordes of those of like mind suck a great deal of energy and resources out of serious research.
Another moron who thinks the fact he can play the market means he's smart. Time to start eating the rich. I hear they're tasty, lightly sauteed with a nice Chianti.
https://yastreblyansky.substack.com/p/of-the-faking-of-brooks?utm_source=profile&utm_medium=reader2
What I find insidious about this entire plagiarism situation is that it feels to me like we're defining downward the meaning of texts in favor of their form. Is the measure of ideas Check Undergrad Papers Dot Com? Is this the standard we're reaching for, here? If there's unquoted citations in a paper, if we're dealing with one another in good faith, you know that and I know that.
In effect, once the tables are turned, Ackman is joining the "no big deal" defenders of Claudine Gay, with whom I have some sympathy. He assumes that, with a careful check, everyone in academia will be found to have omitted quotation marks, or quoted Wikipedia improperly. He might be right.
If it's also true that students are being punished severely for small-scale errors of this kind (as Gay's critics have claimed), then maybe we should relax our standards a bit. But Turnitin usually picks up such things - the real issue with students involves essay writers for hire, reuse of essays from students who have taken the course previously and so on.
Speaking as somebody that used to actually do computational lingustics for a living: If you were only worried about a strict string-matching algorithm, the tiniest paraphrase would let you hide. There are various word-substitution and syntactic-analysis things you could do with a rules-based model that would let you identify, say, a string of 50 words that matches source other than the occasional swap. A "fuzzy" string-level match.
But I think it is almost certainly correct that the current generation of LLMs either can, or at least could, do a better job than this, at identifying strings of 50+ words that are likely to be "the same". You might need to train it on a few thousand examples first of not-identical texts that were, in the past, identified as significantly plagiaristic, and then after that, it can compare each paragraph of a paper, to its entire corpus, and spit out instances where it sees a likelihood of plagiarism.
The question would be, as you say, how many false positives it turns up, and how good it can get if you give it feedback when some calls are wrong. My _suspicion_ is that while it would make a lot of false-positives at first, it would get better after a few hundred of those were pointed out to it. And ultimately the goal with it would be that you don't bother to move on to the next level of human review unless it's found _multilple_ examples in a given person's body of work.
Fundamentally I think it is correct that the current-gen LLMs will be possible to train to be _much_ better at this kind of work than a mere fuzzy string match algorithm.
Of course, this all is an enormous and absurd waste of resources, but, well, Bill Ackman is an absurd man.
Wouldn't it be great if George Soros funded thesis and article research to identify "plagiarism" in conservative academics or spokespersons work?
Of course, if we take this too far we will discover that Shakespeare plagiarized extensively, if Shakespeare even wrote those plays.
If you think about the acquisition of knowledge...based on your own extensive reading...we are all LLM's that spit out what we learned.
Or maybe in the earlier work by Supreme Court justices....
He should call it The Lobochevsky Project.
A slander of Nikolai Ivanovich Lobachevsky, even if Tom Lehrer made a very funny song of it. Really, has the consensus of historians of mathematics done an about-face in the last 50 years or so? Because Lehrer, IIRC, actually recanted his Lobachevsky remarks as an outdated idea -- that is, as a mathematician; naturally as an artist he didn't mess with the song.
I was assuming that was Judd's joke -- Ackman will go hunting for plagiarism and make a lot of wild, unfounded accusations, just as people (wrongly) accused Lobochevsky.
Further proof that Hedge Fund managers are not smarter than the rest of us.
The strange part to me is that of course no one can survive AI interrogating their work, when LLM AI will simply say, "Yes, of course" until you say "No, you're wrong" in which case it will volte-face immediately into "Yes, of course I'm wrong".
I need to have ChatGpt rewrite every quote I failed to put quote marks around the sentence or paragraph I lifted without a footnote.
This is such a joke.
Particularly when they use AI to detect these failures to attribute or cite a source. ChatGpt does this all the time, using its training set.
In reality, what a researcher does is read a whole lot of stuff, and gets trained on it, as does CjatGpt. One get's outed for doing the work of understanding what was read, and the other does not.
The real question is innovation: will we be tied to the learning of the past, which serves as the training set of ChatGpt, and will we give recognition, or be able to recognize, innovation in a paper, even if there are places where someone didn't give a citation or place a quote mark.
This is an innovative comment which has not been generated by ChatGpt, although I am working on a literature review which certainly will be generated by ChatGpt.
And actually, a plain, efficient non-AI test scan could be made to recognize paragraphs and even distinguish between long ones, assumed to have real substance and therefore under grievous suspicion of plagiarism, and single sentences, which are likely, as in large part among the claimed plagiarisms, just cases of the use of the same few words in stating an obvious conclusion, which is what writers do when they want to be clear rather than follow the bad advice of so many language teachers to avoid ever using the same word, or words, twice.
NB: anybody using the above passage without proper attribution is being unscholarly, not that it matters much.
Wow.
My guess is that the repeated plagiarism of Caudine Gay and Neri Oxam is rare. Let's see what Bill finds. He is short academic integrity.
I view Ackerman's tweet as a continuing deflection of the attention on his wife. Ackerman was the "bully" who forced hay's resignation by demanding her palgiarism was a firing offence. Then his wife was outed but he, reasonably, defended her. What he should have done is acknowledged her plagiarism and retracted his deman gay be fired. But no, he has deflected by trying to show everyone in academia has plagiarized work to some extent. But while academices shouldn't plagiarize, why not extend this analysis to everyone in power to extract their plagiarisms? If "everyone does it", why demand such a universal trait be be focused on an academic institutional leader?
If one wants to use an LLM at all, use it to detect outright lies? Then target it at politicians, institutional leaders, religious leaders, pundits etc. That would be far more important than plagiarism.
Bard will plagiarize ChatGpt.
He was quoting a well-known dictum without explicit citation (ref: Robert Merton).
Bravo!