The research paper itself has a problem: It sets out to prove a hypothesis which is obvious and self-evident, and doesn't need empirical proof. (See e.g. "Politics and the English Language", by George Orwell). This seems to be a common problem with psychological research.
But the "Corporate Bullshit Receptivity Scale" is kind of neat. I could imagine a version of the scale being useful for screening job applicants, or as a section of the GMAT.
About 36% of eligible US voters didn't even care enough about the outcome of the last presidential election to bother to cast a vote one way or the other.
I agree with most of your post, but this sentence contains a rather large assumption which is almost certainly false: you are saying that the 36% didn't vote because they "don't care about the outcome".
There are a number of possible reasons for not voting, but I think "it's all the same to me who wins" probably ranks rather low among those reasons. One of the most common reasons (and this is backed up by surveys) is the perception that your vote doesn't affect the outcome. If you don't live in a swing state, that is a perfectly rational reason not to vote. Unfortunately, we can't fix this problem without making major changes to the electoral system.
Then there are all the *other* reasons people don't vote-- they didn't register to vote in time, they don't have the right ID, they lack transportation, they were busy working (that's a common one since US elections are held on Tuesdays), and so forth and so on.
If you want to start fixing the problem of non-participation, you have to know the underlying reasons.
Yes, I've considered that angle. But I think the best approach is a simple one: NONE of the language in the final product, not even a sentence or a half-sentence, should be AI-generated. AI sources should be treated the same way as any other written source: If you quote it without attribution, it's plagiarism.
Under these hypothetical rules, a writer could still use AI for preliminary research, in the same way that they might use wikipedia (and with the same caveats).
The idea of "just using a little AI help" for the actual writing is too much of a slippery slope. (I've talked to professional writers who have used that phrase, so I know). How much is "a little help"? If it's only a little bit of help, you haven't saved much time. If it's more than a little, we're back to square one.
There are plenty of talented writers out there who need jobs, and are willing to do the work, and won't complain if you forbid them from using AI "helpers".
"At least they owned their mistake?" When you've been caught red-handed violating your own policy, you don't have a lot of options besides "owning" it.
It may indeed be true that this unfairly penalizes the ethical writers who work for ArsTechnica. Unfortunately, that's kind of how publishing works; when a publication violates standards of integrity or of quality, it hurts the career of everyone who works at that publication.
Regarding the whole topic of "backlash": Even if you, me, and everyone else on this thread stops reading ArsTechnica (which I haven't read in a while anyway), that's not going to affect their bottom line. It won't even be noticed. That's why journalists need to set up a regulatory body, as I suggested in my earlier post. There are tens of millions of people who will deliberately avoid AI-generated news and deliberately seek out news sources with the "no-AI" seal of approval. *That* will damn sure be noticed.
The unfortunate part of the story is that before this story came out, we readers had no way to know ArsTechnica was publishing AI-generated stories. (In fact, their stated policy was that they did *not* use AI).
What working writers should do is to form a nonprofit organization, create a simple but distinctive banner that declares "This news source is free of AI-generated content", and then *trademark* the banner so that it can only be used with permission. Sites that commit to a "no AI" policy get to use the banner free of charge. Sites that don't have such a policy don't get to use it, and sites that are caught lying (like ArsTechnica) get their right to use the banner revoked.
Chess has become more popular in the West, in part, because they've found a way to make it accessible and appealing to beginner and intermediate players.
When I was a kid in the 80s, it seems like most of the major newspapers had a "chess column"... but these were devoted to coverage of games between grandmasters. If you weren't already a dedicated player, you wouldn't have a good time reading the chess column. It was like reading about quantum physics. But even I can follow a GothamChess video about two 400-ELO players.
A non-trivial percentage of Apple users are choosing the platform because it's good for music production. Cloud-based computing won't work for that, because of latency.
Not really. Salt has zero links to high blood pressure. Your body is really good at regulating salt. Saturated fats are also an overrated health risks. Fats are way less efficient and burn though a lot quicker. Sugar turns into a shit ton of fat.
There's strong evidence that too much sodium can increase blood pressure, at least in a subset of the population. Like everything else in medicine, this is an observation based on the available data, and it may change in the future if new data contradicts it. But it's flatly wrong to state that "salt has zero links to high blood pressure".
There's strong evidence that you can improve your lipid profile, and your risk of cardiovascular disease, by limiting saturated fat. Cardiovascular disease is the leading cause of death in the US. Nothing "overrated" about the risk of saturated fat.
But the era of the horse probably wasn't so bad if you lived in Oxford, or in "a rural village around the time of Queen Victoria's Diamond Jubilee" (like the one Tolkien grew up in).
USA has students finger anesthetized patients without their knowledge for training
Citation needed. Offhand, I can't think of anything that a medical school would be less likely to do. Even if they didn't care about the potential eight-figure lawsuits (and believe me, they *do* care very much about that)... what possible "training" purpose would "fingering an anesthetized patient" serve?
I'm not so sure about law. I've met a number of attorneys who, shockingly, *couldn't* get a job anywhere, or at least not a job that paid much more than minimum wage. And this was before LLMs even were a thing. The explanation I've heard is that it's become much easier to get a law degree (some law schools essentially are open admission), so the market got saturated.
Also, if you *do* want to gun for that senior partner job at Dewey, Cheatham & Howe, you'll have to work 90-hour weeks for a lot of years first. I've met attorneys who were on that career path, and they were truly unhappy souls.
For all intensive porpoises, 40 light years or 40,000,000 light years, it's all the same. It is unreachable.
40 light years is perfectly "reachable" by a civilization that wants to get there. You just have to give up on the idea that it's reachable by you or me personally.
At a speed of
the very reason L-glucose passes through us untouched is the same reason a mirror bacterium would likely starve in a right-handed biosphere. Leave the biology to the scientists, and the click-bait distortions to the mainstream press, okay?
As multiple posters have pointed out... there are many varieties of bacteria that can grow using exclusively non-chiral molecules (and/or photosynthesis) as a food source. They don't need to eat amino acids, they can synthesize their own.
You're correct, of course, in saying that there is a big difference between making L-glucose and making an entire mirror organism. But there is a real, end-of-the-world danger here if they were to succeed.
Impact factor generally is a credibility factor or at least I do not know of any journal in my field where there is a low-credibility journal with a high impact factor, although there are some specialist journals - e.g. instrumentation - which are highly credible but with a low impact factor. Generally speaking though anyone in the field worth their salt will know which the good journals are and where a paper is published generally does have a large impact on how we regard its quality.
Impact factor seems like more of a measure of "this is important and consequential", rather than "this is free of fraud". Anyway, there have been multiple instances of fraudulent papers coming out in high-prestige journals with extremely high impact factors (Nature, for one).
I do not see a good way for a "credibility factor" to be calculated in an objective manner that would not have significant negative repurcussions e.g. counting the number of retractions would be bad since it would encourage journals never to retract papers.
Right, that's why retractions shouldn't count against you. If anything they should boost your score (if done in a timely/responsible fashion).
I don't know exactly how to "measure" fraudulent research or what criteria should be used-- but obviously the PNAS authors figured out a way, or they wouldn't have been able to do a "statistical analysis" of the problem.
Similarly even the best intitutes can hire rogue researchers - or more commonly have bad grad students or postdocs - and enouraging journals to accept anything from any researcher in a "respected" instistute to boost their credibility would be bad too. Also papers in many fields cannot and do not have a single "primary" author.
The credibility score of the institute would be calculated separately from the credibility score of the journal and of the researcher. That's why I suggested multiple scores. In other word, it wouldn't automatically boost the journal's score to publish results from a high-credibility institution-- except indirectly, by reducing the probability that they are publishing a fraudulent paper.
Look, there are all sorts of fine points to debate over, when it comes to exactly how to calculate scores. But that doesn't mean it's a bad idea.
No. The *correct* way to fix this is to resolve the root cause: How funding is awarded.
This is a big problem and it's going to take a multi-pronged approach to fix it. Your suggestion is good, but the OP's suggestion of an "accrediting agency" is also quite good (and somewhat easier to implement than yours).
Journals are already "ranked" according to their "impact factor", which is a number calculated based on how often their articles are cited by other articles; it would make sense to also calculate a "credibility factor", based on the number of (known or suspected) instances of fraud. Ideally, you would want to calculate three different credibility factors for each article: one based on the journal, one based on the institution they're from, and one based on the primary author. (Maybe add a fourth based on the secondary authors).
The beauty of that suggestion is that it wouldn't cost a fortune to implement-- you could set up a nonprofit agency to do it with only modest funding. Scientists would be falling all over themselves to work for that agency. Some of them would probably volunteer their time for free.
Of course, it would be nice to fix scientific funding as well, but that's going to take much more money and time (it ain't happening under #47).
A *third* potential strategy would be to start imposing criminal penalties-- both on the individual scientists and on their institutions-- for instances of outright fraud.
Kill Ugly Processor Architectures - Karl Lehenbauer
