Charles Piller
speaker
984 appearances
4 recordings
4 series
first heard Mar 2025
last heard 17 Apr
Charles Piller’s voice in public audio — every appearance, attributed to the second.
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Journals do not want replicated studies, especially if they're equivocal or if they disprove something, particularly if the original experiment showing something ostensibly important was done by a well-known or famous or perhaps just esteemed experimenter.
I can imagine if you're trying to grow your career and you're looking to have more citations, it's not helpful to do a replication study because odds are that it's not going to have a lot of citations. The original work might, but yours probably won't. Odds are you're not even going to get it published. Yeah.
Do you think that creates a crisis for us where we're putting out new research that is hellbent on creating a new discovery, but it's based on shaky science as we currently have it?
Well, let me say that I think that the vast majority of scientists are honest. They're trying their best to do something useful. They may feel the pressure of the field they're in and the competition and the incentive structures that may be misguided, but they're not dishonest. They're not cheating. They're not falsifying information. That said, there are many who are.
Just like in every walk of life, you have people who are cutting corners or doing something illegal or dishonest. And so I would say that people can trust the vast majority of experimentation.
I think what's not as well understood is that a few experiments, or a relative few of experiments, that are done improperly, that are based on false ideas, or are deliberately doctored, deliberately changed in inappropriate ways to, say, support a hypothesis that can't be supported by the actual data in the experiment, When those things happen, they can skew thinking in the field.
They can have subtle or sometimes very obvious effects in steering other scientists in certain directions, particularly if they're done by important people who have a lot of influence in the field, including some that I've written about.
How does that factor in when we look at our hierarchy of evidence and expert opinion being low on that pyramid, and as you go higher to the meta-analyses, the systemic reviews, how does it factor in that there are perhaps studies that were done with poor data, falsified data? How does that impact our ability to do those high-quality reviews?
Well, I think the reviews are only as good as the stuff that they're built on, so it's garbage in, garbage out, I'm afraid. And if studies are unreliable, they can have that ripple effect. Also, you see in many of the metadata studies and the reviews that you're referring to, even by some of the best review organizations like the Cochrane folks over in the UK,
Those are done with extremely high standards, and they try to throw out data often that isn't really that reliable. The problem is, if data is falsified, it can be very difficult to know how reliable it is. And so therefore, you see over and over again that a lot of these review studies are equivocal in their conclusions. They don't come down firmly on one side or another.
Is this treatment valuable or is it worthless? They often say, well, we can't really quite tell. And the forest plots all over the place. There we go. It's partly because you have not enough data. It's partly because sometimes you have poorly done studies or even falsified data that skews the overall thinking in the field and the ability to combine it just for a concrete solution. Hmm.
Where do paper mills fall into this equation?
Well, this is a phenomenon that is a pernicious effect on scientific research. So I mentioned before the publisher-parish ethos within scientific careers. And because of the pressure that scientists feel and the competitive nature of the field—the too few jobs for too many PhDs, for example—
What you have is a situation where clever entrepreneurs, if you want to call them that, have developed these companies where they generate fake papers. In other words, kind of interesting sounding papers. kind of plausible sounding scientific papers. And then they sell authorships to the papers. Sometimes these are generated even by AI programs.
And they sell these authorships to people who are desperate enough or simply confused enough to pay a little money to get in on the game and be able to enhance their resume to get jobs or to increase their ability perhaps to have publications in legitimate journals.
So how do we fight back against this potential fraud that seems to be growing?
Yeah, so it's a great question, Mike, for a few reasons. And let me answer it in a couple different ways. So We are very privileged in this country to have excellent institutions that regulate, monitor science. The funders, the journals, the regulatory agencies like the Food and Drug Administration, these are agencies and groups that have
for many, many years served the public well with advancing scientific ideas, but I think have fallen behind in critical ways, in ways that we need to press them to improve for the sake of the scientific record and also for the advancement of medicine in general.
Let me give you the example of, this is something that to me was a pretty stunning example from research that I did for the book that also appeared in Science Magazine recently about the guy who used to be the chief neuroscientist in the head of the division of neuroscience at the National Institute on Aging.
That is a very important agency that funds research into Alzheimer's and other neurological disorders. And what this guy was, I found in my reporting, had been apparently falsifying images and other data in his studies going back a quarter century. This is Dr. Maslia? That's right. Very important guy in the business, very highly regarded.
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