The Jordan Harbinger Show - 436: Stuart Ritchie | The Science Fictions Undermining Facts

Episode Date: November 24, 2020

Stuart Ritchie (@StuartJRitchie) is a lecturer in the Social, Genetic and Developmental Psychiatry Centre at King’s College London and author of Intelligence: All That Matters and Science Fictions: How Fraud, Bias, Negligence, and Hype Undermine the Search for Truth. What We Discuss with Stuart Ritchie: Why good, meaningful science too often gets pushed aside by the hype around bad science that makes for sensational headlines. How and why incentives in research are often skewed and lead to bad science — and even outright fraud. What happens when good scientists are hoodwinked by bad science and vouch for it as gospel because its pedigree seems legit. How can you spot bad science before you adapt your lifestyle to correspond to its dodgy, worthless, or perhaps even dangerous advice? What is the Open Science movement, and how might it help us reform these problems in research going forward? And much more… Full show notes and resources can be found here: jordanharbinger.com/436 Sign up for Six-Minute Networking — our free networking and relationship development mini course — at jordanharbinger.com/course! Like this show? Please leave us a review here — even one sentence helps! Consider including your Twitter handle so we can thank you personally!See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

This episode is sponsored in part by Conspiruality Podcast. You know how I'm always talking about critical thinking and spotting manipulation? Well, there's a podcast that's all about dismantling new age cults, wellness grifters, and conspiracy mad yogis, basically the wild overlap of spirituality and misinformation. It's called the Conspiruality Podcast. The hosts, a journalist, cult researcher, and a philosophical skeptic, dive deep into how this stuff spreads, from Project 2025 and the Heritage Foundation's dystopian vision of the future to how former leftists get pulled into far-right conspiracies.

An interesting episode to checkout is called Speaking Truth to Goop, where Jen Gunter breaks down the pseudoscience behind the wellness industry in a way that is super entertaining and eye-opening. It's sharp, funny, and makes you a lot harder to fool, which, if you listen to this show, you know I'm all about that. From exploring cults to analyzing our cultural and political landscape, the Conspiratuality Podcast will help you stay informed against misinformation and resist fear tactics.

Find Conspirality on Apple Podcasts, Spotify, and wherever you get your podcasts. Coming up on the Jordan Harbinger show. The journal itself, the Lancet, one of the world's top medical journals, ran a crowing editorial that said, Paolo MacUrini is not guilty of misconduct. Just a few weeks later when all the stuff about the Pope and all that came out, and also there was this documentary where they actually went and met some of the patients

and saw the terrible condition they were in. After that came out, they had to all, they humiliatingly climbed down and say, okay, we were wrong, actually this guy has been fraudulent all along. So in this case, you had, like, big medical institutions covering up, and, like, they were on his side. They were on the side of a psychopathic fraudster that was leading to the deaths of his patients. Welcome to the show. I'm Jordan Harbinger. On the Jordan Harbinger show, we decode the stories, secrets, and skills of the world's most fascinating people. If you're new to the show, we have in-depth conversations with people at the top of their game.

That means astronauts, entrepreneurs, spies, psychologists, even the occasional undercover of FBI agent. Now, each show turns our guest's wisdom into practical advice you can use to build a deeper understanding of how the world works and become a better critical thinker. If you listen to this show, chances are you're a big believer in science and you put a lot of trust into it. I do as well. But what happens when we lose some of the transparency that is the cornerstone of the scientific process?

Well, today, we'll discuss why hype in science can be bad for society, bad for medicine, and bad for those of us that rely on it, which is everyone. We'll also learn how and why incentives in science are often skewed and lead to bad science and even outright fraud. If you're wondering how I managed to book all the great guests from my show, these authors, these thinkers, even celebrities, every single week, it's because of my network. I'm teaching you how to build your network for free over at Jordan Harbinger.com slash course. And by the way, most of the guests on our show, they're in the course, they contribute to the course. Come join us. You'll be in smart company. Now, here's Stuart Ritchie.

The book starts with a professor from the look of it, kind of trying to prove that we're all psychic when it comes to porn. Is that? Did I understand that correctly? Okay. So basically that is, yeah, what that paper? And that was published in a, you know, a mainstream psychology journal. So what happens there? First of all, are we psychic when it comes to porn? And if not, how did we get that? How did that happen? How did that get published? It is a kind of absurd thing. And that's, you know, the absurdity is part of the story. This was a paper published by Darrell Bamm, who's at Cornell University, who is like a top-rated social psychologist. well-known, well-respected, published this paper that he got Cornell undergraduates to come in to sit in a computer cubicle. Actually, people in the US only say cubicle. No, you know, it's us in the UK. Sorry, in the UK, we say cubicle for offices and toilets. Oh, yeah, no, we only use it for offices. Yeah. Although I strongly recommend that we start using it for toilets because, coincidentally, there's a lot of overlap in those two activities. Yeah, I think so. I think so. Anyway, so they're looking at computer screen and they're told, there's two pictures of curtains on the screen behind one, there is a picture, behind one there's nothing. So you just have to click the one

there's a picture behind. And they say, well, I don't know what one. Then they just say, well, you know, just whatever one you feel. The experiment claimed to show that if you put a picture of just something really boring like a tree or a chair or something behind one of the curtains, people get it 50-50, right? Just what you would expect. They get the picture, they click the one that there's a picture behind 50% of the time, right about that. But if you put porn behind one of the curtains, so he claimed in this experiment, and then they get it like slightly above chance. So they get it like 51.3% in the time or 53.1% of it like slightly above 50%. So, and that was a statistically significant difference. And it apparently showed that the undergraduates could sense that

there was porn in the future going to be shown to them. And there was like an opposite way around where they put like a violent, unpleasant picture behind one of them. And they tended to avoid that one, like just by chance. And they couldn't possibly have known that that was the one that was going to come up except by psychic intuition. Okay. Except for since we know that that's not real or so far has yet to be proven, what happened here? Well, yeah. I mean, people would be like breaking casinos, I think, if they could like really sense a future in this way. But right. There are several things that occurred here. I mean, this was a paper which was used all the standard ways that psychologists used to analyze their experiments, right? It was a standard experimental set up. They used standard

statistical analyses. They used published it in a mainstream psychology journal and so on. And yeah, it got these completely absurd results. And so what a lot of people concluded from this was that there must be some kind of problem with the standard way that psychologists analyze their data and do their research, which, you know, is part of what this book is about. But what also happened, what also was kind of revealing about this was that we ran the same experiment again, and we found no such results. Like we found no psychic results in our replication study. Surprise. Yeah, yeah, yeah, exactly. And we sent our replication study off to the same journal that had published the original.

And they said, sorry, we're not interested in publishing replications. So they were interested in publishing the, like, super flashy psychic result? Fake psychic results, fake psychic porn results, yes. And not the one that said, you know what, actually probably people don't have a psychic ability to detect the future. I'm not claiming that this is a fraudulent result, right? It's not a case where someone has just made up the data, but it's a case where the standard methods that we use in our studies have led us to results that we kind of all know are not true, right? We kind of know that that's. Okay, so the guy who ran this, right?

And I assume it was a guy, because let's be honest, who does a psychic porn study? It was indeed a guy. He also knows, and his team is like, this is bull crap, but we're going to get it published, right? It's kind of like that, right? They're not like, wow, we've discovered this groundbreaking psychic pornography effect. I actually think in the world of parapsychology, which is what he was, you know, the research that he was doing. I think there are true believers. I think people believe that this stuff is real.

I think people believe that we have like a tiny, tiny tendency. It's not like you can go to the medium and get them to read your tea leaves or whatever it is, but it's that we have this kind of tiny little thing that evolution, is built into us to kind of search for erotic stimuli in the future and avoid violent stimuli in the future. And also, like, just to generally sense stuff that's coming up in the future. I mean, the part of the experiment that we specifically replicated was just about word lists. Like, we didn't do the exciting porn part. Sure you didn't.

Well, I wouldn't even know where to look for porn. Oh, yeah, of course. Yeah, yeah. And so, yeah, I think we can safely assume that he believes that this is true. There is a kind of tradition in psychology of parapsychology research. But it's been described as like the jester in the court of science because it's like a really absurd thing which looks really ridiculous and is kind of totally like it doesn't fit with physics. In physics there's causes and then effects not the other way around. And yet it kind of illustrates that there's something maybe a bit funny with the way we do science.

And so if you dig into the statistics of the paper, there are lots of reasons where he might have been able to find what looked like a real result but actually there wasn't. And you can kind of, and this is again what I go into in the book when I'm talking about like the bias that scientists have. You can convince yourself that you've found something real when actually you haven't, and it's just noise, it's just statistical fluctuations in your data that you've collected. You know, if you really believe something and you really want something to happen, if you really want something to come out of your data, which a lot of scientists do. They want to find the next cure. They want to find the next big, exciting result. They want to find the next thing that'll change the world. Then you can run the statistics in such a way that it comes out with really whatever you're looking for. Right. That makes sense. If you're a psychologist who studies the paranormal and there's not a whole lot to work with because we've found that there just isn't really that so far.

at least no proof of that, and you're looking for that, and you're looking for that. And it just so happens that if you find something, you'll be world famous overnight and at the top of that field forever, there's a strong incentive to just maybe slide something to the left when maybe it shouldn't have been slid to the left. Absolutely, absolutely. Thereby getting some imaginary results. Yeah, exactly. And it's not even just a matter of like doing the statistics. It's a matter of like the way people write up their papers. You know, even if they haven't really found much in their paper, they can write the paper as if this is like the most exciting result ever. And, you know, the nice thing about this story, and the reason that this story is so good, I had the experience of, like, the failed replication and trying to get that published. I think that illustrates a lot about the way science works, the kind of journals, and we can talk about that. But I think the paper itself illustrates so much about how, if we just let people just carry on with the standard way they're doing science, they will find, like, on their face, patently observed results like the porn sensing, that remote sensing of porn. And so I think, I think this is like, it's for good reason that this was one of the first studies that kicked off what's being described as, like,

the replication crisis in psychology. Right. And we'll talk about that, right? Because look, why the hell was that published? That's what everyone's thinking. How is it that that got into a journal? It's not one of those... Well, let me back up.

Do most scientific studies just get published? Well, most scientific studies that get published, and this is the vast majority of them, have positive results, right? And that implies that not all scientific studies are getting published. When you're running a scientific study, you're looking for...

You're interested in testing a hypothesis, usually. And then obviously, once you've tested that with statistics, you're sending that off to a journal, you're getting that published. That's what you really want. It gets peer reviewed. The peer reviewers check that you haven't screwed anything up in the analysis. They check that you've written up in a fair way and whatever, and then it gets published. But there are lots of ways that that can go wrong along the way. You yourself. Let me pause this here, though. If I'm looking to test a hypothesis,

shouldn't like half or more than half of my tests of hypotheses just not yield anything? Like, I guess I was wrong. I mean, shouldn't that happen more than being right? I think we could debate about like how many hypotheses would expect to go wrong. Like scientists can make an educated guess. A hypothesis is usually an educated guess. So you might not expect it to be just 50-50. You might expect to be slightly higher than that because they're like testing the next thing that comes from their theory and so on. Right.

It's not just like whole cloth. Like I'm not just pulling something and flipping a coin and being like new hypothesis. Yeah, I think it will do this. Correlated with this or this experiment will work on this. Like, yeah, people are like following a line of research. So you'd expect it to be maybe higher than 50%. But you wouldn't expect it to be like over 90%, which is what it is in some fields.

Right. In psychology and psychiatry, it's been shown that over 90% of studies find positive evidence for the hypothesis that they're testing. And that implies either that the guy at Cornell was right and psychologists are actually psychic, or it implies that something has gone really wrong with the way that we publish science. And as we're saying, there are all these biases that push us towards only seeing these positive results. So, like, this isn't how things have actually happened. The scientific literature, which is supposed to be a really nice reflection, like a clear, accurate reflection of what scientists have been doing, does not accurately reflect what scientists have been doing. In fact, it just shows this kind of rose-tinted view where all the results are positive because, first of all, scientists don't publish the studies that they do that don't support their hypothesis.

You tried that, right? And they were like, yeah. Yeah, exactly, precisely. So that's a clear example of where they said, hey, we'll publish the really exciting initial result. The one that shows that, you know, that psychic powers are real, but we're not interested in showing the one that they're going. That's too boring. Is this why we see all this crap, like, in CNBC, and it's like, eating red peppers can cut cancer. It's like, scientist, colon.

Eating red peppers can cut cancer risk by half. And you're like, what? Oh, probably not, though, right? I think, you know, there's a bit in the book where I specifically take, like, nutrition research to task because I think it's exactly that. I think you have these huge data sets where people collect the data on, like, people's dietary habits, and they fill in every food they've eaten for the last two,

weeks or what they can remember, you know, they ate for the last two weeks, and then, you know, their health outcomes and all sorts of different, you know, mental health, physical health, whatever. If you dig around in that data for long enough, you'll find something and you can find red peppers and cancer if you want. You can find eating milk and, sorry, eating eggs and drinking milk and heart disease. You can find drinking red wine and heart disease, all sorts of stuff, and you can publish it. And that's why the literature or nutrition is so confusing. You know, a huge amount of the findings are likely to be just statistical noise rather than like real signal, which is what we really want. And people want to know. Like, this is a real

failure of science because people want to know what they should and shouldn't eat. You can see from the amount of books on this that gets sold and the amount of interest in this that there is, people want to know. And scientists should at this point have been able to provide reliable evidence on that. But we're still really not at the point where we can reliably tell people that. Well, you must be popular among your fellow scientists for blowing up all their studies and results and making it harder for people to claim street cred by writing their bullcrapy, you know, science articles. It's this movement, this kind of, you know, since 2011 or so when that psychic paper got published, the kind of movement of the people talking about the replication crisis have

certainly caused a lot of upset. Like, people are very upset about that. People are saying, like, but I've made my whole career on publishing positive results, basically, and doing the statistics this way. And that's why you're part of the problem. And why, yeah, exactly, exactly. But, you know, it must also be said that lots of scientists are like, oh, God, yeah, right enough. We have a serious problem here. And there have been some positive kind of, you know, steps in the right direction in terms of changing the way we publish stuff. So social science is something you spoke about a lot in the book. So priming was one of these. Can you sort of briefly explain priming? Is that I'm going to do a bad job. So just go ahead and do it. Well, this is a, it was a particular, like almost like a fad in social psychology for maybe, you know, a decade or more where there were loads of these experiments about unconscious cues in the environment and how they can affect our behavior and our feelings or beliefs. I mean, like my favorite example of this, which I think actually might only be in a footnote in the book because it has never actually been directly replicated.

but I would put money on how that replication would go if someone else came along tried to do the study. But this is one where they got people to come into a room students again and they were doing a creativity test and so it's like how many uses can you come up with for a brick. So that's, I mean, psychology is not a very high level of assessing people's creativity if that's what they could do, but that is probably the best we can do in the lab

for a creativity test. They had the people either sitting, like they had a big cardboard box in the middle of the room and they had people either sitting in the cardboard box while they were doing this test, this creativity test, or sitting outside the box when they were doing the creativity test. And what they found was that the people

who were sitting outside the box and thus thinking outside the box higher scores on the creativity test than those who were sitting in the box. And so the idea here was, like, this sounds completely absurd to me, but the idea was that priming the concept or priming that idiom,

that idiom of thinking outside the box, had actually translated directly to people's creativity and made them and given them a boost in how creative they were. And there's a whole host of studies that are like this. It wasn't just a tiny effect. This was like a huge boost to their creativity because they were sitting outside the box versus inside the box. Like that type of research, that general type of research where, you know, things in the world influence your behavior, even though you're completely unconscious of them. Holding a cup full of warm coffee makes you feel warmer to your friends compared to holding a cup

of cold water because warmth is activated in your mind and so you feel warmer in a metaphorical sense to your friends when you fill in the questionnaire about like how much do you feel like your friends and family. All that kind of stuff has not done well when people have tried to replicate it. It's not done well when people have looked into the stats, but it was a big thing in psychology and, you know, it has made its way into loads of really popular books, including by really reliable and respected people like Daniel Canaman. There's loads of stuff in thinking fast and slow. It's like ultra popular and really good, overall really good book. I'm not, you know, criticising the book. I think it's a great book, but, you know, he says in that book,

there are these studies on priming, unconscious influences can have, you know, big effects on our behavior. And, you know, these are published in scientific journals. This is a direct quote. He says, you have no choice but to believe that these are true about you, about your behavior. Yeah. So that's scary, right? Because this is a brilliant scientist who wrote us, I guess, could you call that a seminal work? Because everyone reads it and everyone talks about it. I don't know if that's... It's like, I mean, he's one of the, the, the only person to have won a Nobel Prize, technically in economics, but he's a psychologist. So like, he shared the Nobel Prize for that. So he's like, as big is it gets in psychology. And here's this guy saying, well, you know, even if I think that sounds fantastical,

it was published and it's settled science, therefore it settled science or whatever. So it almost sounds like he's talking to himself like, geez, that doesn't sound right. But you know what? Who am I to say that this person who did all this research is wrong? And it's like you're a Nobel prize winning multi-million copy bestselling author. But we can't expect him to go, you know, that doesn't sound right to me. Let me just do a brief three to five-year study that's double-blinded and funded by some organization just to make sure this isn't bull crap. Right. And he totally would get the funding to do such a study.

Sure. And to be fair to him, he has after, you know, several years of like these results being criticized and failing to replicate when other people tried to do them and, you know, to the replication studies, he has come back and said, look, I was wrong about this. I shouldn't have been so certain. But, you know, if he, and by the way, you know, his specialist subject is how we're irrational and how we make incorrect conclusions about stuff and how we're kind of drawn into thinking in irrational ways, if even he can make the mistake, like, what hope is there for

anyone else? What hope is there for the rest of us? When we're assessing science and understanding science, all these priming studies have become kind of, I think they've become sort of less popular now in social psychology and, you know, people are kind of moving on to kind of different stuff. I have to realize that it was kind of fun to come up with all these ideas, like warmth.

The concept of warmth. Yeah, what did I do? Oh, let's do that. There was one where it was like being higher up on an escalator made you feel more high and mighty so you would like rate yourself more arrogantly compared to your friends and stuff. I think that actually, that study was actually fraudulent that was made up. But there was a whole spate of these studies and it might kind of fun to come up with,

but actually quite scientifically flimsy, you know, when you look into them. One of the biggest ones that, and this happened on our show, and I had to sort of eat a little bit of crow on this, is I had a guest on named Amy Cuddy and she had that power posing thing. I know you're well aware of that. But for people that don't know, this was the idea that you could, it's so Tony Robbins when you think about it. Like you stand up and you raise your arms in the air and you can either scream or stand up in this very dominant body language. And it's like, look at what we found and she did its head talk and it got like, I don't know, 80 million views or 28 million or whatever, umpteen million views. Okay. It's the second most watched head talk of all time, I think.

Right. And it turned out to just be just not real. Well, it was based on one study of 42 people, right? And it turned out that that study, the lead author of that study, who was not Amy Cuddy and she was like one of the three, I think, authors on the study. But the lead author of the study who's Dana Carney, who's at Berkeley, I think. She came out and said, I don't believe this anymore. If you look back at the way we did the statistics in the original study. We kind of like drop the odd participant out here and there and did it kind of inconsistently. We ran the statistics in such a way that we kind of pick the results that were positive and kind of just kind of hushed up the ones that were negative. And, you know,

again, it's not like accusing anyone of fraud. It's bias, right? It's bias towards finding exciting results, just like, you know, the psychic study that we talked about and in the the nutritional studies. Only in rare cases is this like deliberate fraud, but it's like the whole way that the incentives are set up. And think about the incentive of you will have a New York Times bestselling book. You'll be able to. to go and have the second most watched TED talk of all time if you publish this study and if you do the statistics in a certain way. So you can see how these like incentives are pushing people towards getting the result

rather than pushing them towards finding true things about the world, finding true facts about the world. That, you know, power posing study has been various attempts to replicate it. And I know Amy Cuddy is still quite pro at being true the power posing effect. And there's huge debate over that. Although the debate tends to be Amy Cuddy versus basically everybody else who's kind of saying, look, this is not reliable. Yeah.

Especially the claims in the study about your testosterone rising when you do the power pose and the hormonal stuff really hasn't held up at all. The subjective feeling of power possibly is true. But it might also be in the experiment, the comparison is between people like slumped over versus people doing the power pose. And it might be more a negative effect of slumping rather than a positive effect of doing the power pose. So it's like the whole thing might be a bad interpretation of the data in the first place. So it kind of has crumbled, yeah. Yeah. I mean, I understand.

I don't know her well. so I can't be like, oh, it's all a bunch of crap so she can get speaking gigs. Like, I can't say that. But also, it would be hard for me, I'll speak for myself. If I had a TED talk and it had however many million views, and I became famous for that, and I was getting speaking gigs all over the world about that. And someone said, hey, you know, there's a problem with our data. I probably wouldn't be like, we got to tell everyone about this. I'd probably be like, that's really inconvenient for me, economically, professionally. I'm not sure I really want to dive into that rabbit hole right now because I am about to retire in five years off this. Well, this is why I suggest in the book that scientists should consider more widely what

counts as a conflict of interest, right? So at the moment, scientists, if they're getting paid by, you know, a pharmaceutical company or if they've consulted for a pharmaceutical company or, you know, and they're doing a drug trial, say, it's like totally required. You must say that, you know, in the paper, you must write in the conflict of interest section, I've received money from AstraZeneca or Pfizer or whatever the company is. But they don't have to say, I have a conflict of interest in that I published a really popular book and did a really popular TED talk on this topic and it would be really, as you say, you know, it would really inconvenient for me if the results went a different way or, you know, went one particular way. So I just

want to declare that as a conflict of interest. Like, no one does that. And in fact, like most scientists would think that was really weird if you said that. But, you know, I think people should reconsider. I mean, nutritional research is another one, being suggested that nutritional researchers who are on a particular diet themselves, who are like following one particular diet and then they do a study on that diet, they should declare that in the paper because they have a clear interest in proving themselves right. Like, I haven't been wasting the last five years of my life. Yeah, right. Turns out all this stuff I've been doing that definitely has sunk cost valesemic into it. Turns out I was right the whole time. I just want everyone to know. Yeah. Yeah. That's a problem

for, I think, medicine too, right? Because if doctors have to rely on what is low quality science or low quality evidence because the alternative is no science or no evidence, then bad science, which is what we're talking about, makes this problem a lot worse, right? Precisely, you've got to make a decision. As a doctor, you've got to say to a patient, like, we will treat you with this, or I think this is the best thing to do. And if you look through the scientific literature, often the only data is low quality stuff from small studies, studies that might be statistically dodgy in the way that we've described. You might be missing because of this publication bias idea where people only publish the positive results.

You might be missing studies that were genuinely done, but that just have never been published, that just haven't made it into the journals because the journals weren't interested because they're negative results. Scientists have really failed doctors in this case and, you know, by extension, they've failed patients because they haven't provided an actual proper, reliable, accurate summary of what has been done scientifically on all of these drugs and treatments. And so, yeah, that's why you often see this phenomenon that's been described as a medical reversal where, like, a much bigger, higher quality study comes along and totally flips the understanding, totally flips the evidence around on some medical treatment.

I mentioned a few in the book, like peanut allergy, for instance. For a long time, people were encouraged to keep their kids away from peanuts when their babies because that would be helpful in terms of stopping them from developing a peanut allergy. Then a really big, I think 2015 or so, like a really big high-quality, long-term, randomized controlled trial came along that actually properly tested this, and it turned out it was the absolute opposite. The best evidence was that if you expose young kids to eating peanuts, they will be less likely to develop an allergy in later life.

And there's loads of treatments that have had that. There's a book called Ending Medical Reversal by Avinae Prasad and Adam Sifu, which is well worth reading a reference in the book, about medical treatments that have just gone completely opposite because the evidence was never really there in the first place. And yet, that was all doctors had to use. So as I say, scientists have really failed doctors in this respect. Yeah, that's a huge problem because that affects all of us.

It's not just like, oh, it turns out this thing is wrong. It's like, no, when you go to the doctor, and we see this problem now with people, taking drugs that aren't really adequately studied because they're afraid of getting coronavirus or something like that. I mean, I'm literally getting emails from people that are like, trust me, the gargling with bleach works. I haven't gotten it yet. I'm like, oh my God, you're literally ingesting poison. I get the occasional nasty letter from a crazy person that will say something like, you're doing, and I feel bad in a way because these people are genuinely worried that I'm spreading disinformation. And I'm like, no, you don't realize that what you saw in the pandemic movie was fake.

and fraudulent. And we'll get into fraud in a second. That's a different thing. But can you tell are there any sort of basic guidelines where if we're reading a science book or we're making a change in our life, say a diet or based on some scientific finding we've read about on CNBC or whatever, have we picked on earlier? How do we evaluate how strong the evidence is? How do we say, is this bull crap or not? It's really tricky because, you know, different studies will have, you know, some of them will, for instance, be really new. And so it's really hard to tell if that's been properly evaluated. I have a little kind of checklist in the book in the appendix of what you should do in any study. So you can look at like how big the sample was. You can look at generally whether

you feel like the authors might have a bias in one direction or another. You know, whether there's a reason for them to be saying what they're saying, whether it's like political or we've just talked about, you know, other conflicts of interest. One of the useful thing I think is to look for news stories that talk to other scientists that weren't involved. So the whole thing about the psychic study was that me and my colleagues, you know, as independent researchers, came along and try to replicate this, right? So what do independent researchers think? It's all very well getting quotes from the scientists that did the study in the first place, but what do other people think? Because of course, science is all about that is all about reviewing each other's work and this kind of

social process of building up knowledge. So I think you can look for if any independent scientists have commented on it. There are specific ways to do that. In news stories, there are also places like in the UK, we have the Science Media Centre where they actually, whenever any finding that comes out that looks like it might be kind of controversial, they ask a whole bunch of other scientists what they think and they write a little review of the paper. They say, well, this one had a kind of tiny sample or this doesn't make sense or they didn't control for this or whatever it is. You can get independent views. And the thing is just actually, like if you've got the URL of the paper, just put it into Twitter and see what people are saying about it. Like scientists often spend a lot

of their time, like critiquing other people's work on social media. Reddit will shred science. Even good science is not safe. Amazing threads on Reddit on some scientific papers. PubPier is another website where if there's anything like dodgy about a paper in terms of, you know, fraud or anything untoward, other scientists can anonymously comment on the paper there so they can say, we'll go into discuss it, we can say that data doesn't look quite right, there's something a bit funny about this. Can anyone dig into this in a little bit more detail? Of course, you know, when you look at social media and look at Reddit and Twitter and so on, you will get the like less educated comments and the less high quality comments too, so you have to bear that in mind.

But I think that's what my one, you know, one of my main piece of advice is just look at, you know, especially if you can't access the paper itself, just look at what other. the people are saying about it and see if there's a general consensus of this looks really good and really solid or as has been the case for many of the coronavirus papers, you know, there's a massive flurry of all this research appearing on coronavirus, you know, there's a lot of people discussing it. And so you get these threads saying, here's why this paper is wrong, you know, one, two, three, or five, you know, so I think just checking what other people are saying, rather than just relying on the results of that one paper and the way it's written, it's probably

a good idea. I always look on Reddit. There's actually a subreddit called Is It Bullshit? And And then there's also rational skeptics, skeptic, debunk this. And you can post things in there and say, hey, this paper says this. Right. But what's up here? And you'll find, like, the top 20 posters in there will absolutely annihilate pretty much anything you dump in there. Yeah.

Yeah, I know I think that's extremely useful. I mean, that's basically what you're asking there is for post-publication peer review, right? So peer review tends to be done pre-publication, but we know it's inadequate. We know that all the papers that I discuss in the book that are fraudulent, that are biased, that are, like, have mistakes in them. that are hyped up, have all, almost all anyway, all the ones I'm talking about in the book, and there's dozens and dozens of them, have all passed peer review. They've all got through the system that's supposed to be like the ultimate quality check. And so we need to be much

more open to, you know, as you're talking about there, just asking other people, other experts, or people who just know the field to dig into a paper and say, look, what are the pros and cons of of this, even though it's been through the peer review process. I think we make a huge mistake by saying, this is peer reviewed, therefore it's reliable and trustworthy in some way. That's just shown to be totally inadequate. You're listening to the Jordan Harbinger show with our guest, Stuart Ritchie. We'll be right back. And now back to Stuart Ritchie on the Jordan Harbinger show.

Let's get into fraud because this is where, like, you think that's scary that you can just start a diet that doesn't work or do something else and it's peer reviewed and it turns out to be BS. That can happen by mistake. That can happen via bias. And that's what we see in a lot of the social psychology that we've had on the show. I mean, I've been doing the show for almost 14 years. There are people that come on and then years later people are like, remember this person? Yeah, I lost their license or, you know, this study turned out to just be completely made up. And I'm like, oh, oops, you know, and like the power posing thing.

Like, I don't think if Amy Cuddy were here, I wouldn't say, you're a charlatan, you know, how dare you? I don't ask her what she thinks. And I'm sure that when she explains it, it sounds perfectly rational, especially to her about why the results are still legit, you know? Yeah, yeah. But fraud is much more terrifying and often lethal. The study that you talk about in the book, or the example you give in the book, there's this doctor that just, did he invent trachea replacement? And then that just turned out to be a bad idea and just kills a bunch of people by this.

Take us through this. This was nightmare fuel. Yeah, yeah. I start the frog chapter with this because it's such an amazing story. So Paolo Macchiurene is his name. He was a surgeon at the Karolinska Institute. And the Karolinska Institute is like the top university in Sweden or one of the top universities in Sweden.

And it's where you win the Nobel Prize for medicine and physiology. Like it's where they call you up and say, Stockholm calling. you've won a Nobel Prize. It's a seriously respected august institution. It's a really great place with a great medical school, the Carolin's Got Medical School.

He was recruited there and he, yeah, as you say, he was replacing people's windpipe, tracheas. Well, it had been tried a lot. There's a really difficult problem in science. You said trachea. Have I been saying trachea wrong my whole life by saying trachea?

When I recorded the audiobook, the audiobook producer said to me, I said trachea and the audio book producer said, to me, isn't it Trachea? And I said, no, no, I'm pretty certain it's Trachea. And then we looked it up and it's Trachea. Wow. I'm pretty sure that pretty much all of North America says this wrong. I've never heard anyone say that. It's possible that it's a UK-US thing, actually, yeah. Wow. My UK producer and, you know, for the UK, when we're recording this in the audio book, said Trachea. Shall we just say windpipe? I mean, I'm happy to... No, I'm happy for you to

say it weird the rest of the show. I'm cool with that. I think you already have this bizarre sort of amazing unusual accent that a lot of people are going to write to me and say, I sounded interesting, just didn't understand any of it. I like it, so go for it. This is just a, you know, a standard Scottish accent that I've got. But, yeah, so he... You want me to get you back on track? Yeah. Okay.

He came with this idea of taking stem cells from someone who'd had like an injury. Okay. Maybe cancer or for some reason their windpipe was blocked or damaged. And he had the idea of taking stem cells from them and then taking this artificial windpipe and it's kind of seeding it with the stem cells from the transplant recipient so that it kind of it wouldn't be rejected. That's the big thing in transplants is that, you know, you transplant a skin graft to someone, it gets rejected because it doesn't work with their immune system. Right, the immune system attacks the new tissue and tries to kill it.

And that's like the ultimate problem in any kind of transplantation. And it looked like in this case that he had solved that or he was at least one of the first people to have successful operations where you replaced a big section of someone's windpipe with this special stem cell seeded, electro-spun, you know, it was made of artificial materials, and it wasn't like from a donor, it was completely artificial. But it had the stem cells then. And he published papers in some of the world's top medical journals. The Lancet, for instance, is, you know, one of the most respected medical journals in the world. And he published a couple of papers there. Several other journals accepted his papers saying, we've made a successful operation on a patient, on their

windpipe. We've made this massive breakthrough. It turned out that even though it was being reported as a major success in the papers that he published, and again, this is peer-reviewed publications in the scientific literature. It turned out that he was just lying about that. He had fabricated the details of the patients, and in fact, several of them had died. One of them had died before the paper even went to press, like they had died, and they didn't stop to say, maybe we shouldn't publish this paper that says it was a really successful operation. He had a kind of second base of operations in Russia where he was doing more of these transplants, which were failing really badly. There's a horrible story that I counted in the book of one of the patients talking and saying, like, I

have like pus coming out of my neck constantly. There's a big hole in my neck and it's just failed terribly. There was a little kid that he did this operation on in the US that died very rapidly after it happened. And there was never any evidence that this worked because he fabricated all. And he also fabricated data on

like rats that he had, you know, kind of a preliminary part of the experiment. Wow. This is just malignant narcissism, right? He just wanted a scientific cred and he's like, if you have to die for me to get some pads on the back, so be it. Right. And the fascinating thing about it was that he was a con man in other areas of his life too. It was an amazing story in... Surprise, surprise, right?

Right, exactly. So there was an amazing story in Vanity Fair where he was like having this affair with a, I think like an NBC news producer. And he said, oh, by the way, we're going to get married. The Pope is going to officiate our wedding because I'm, by the way, I'm the personal doctor to the Pope. First red flag right there. But he said, like, I am the Pope's personal doctor and also the Obamas are coming to our wedding and Elton John's going to be, you know, doing the music at our wedding and, you know, all this kind of stuff. It turned out he was married to. someone else. He had kids the whole time. Vanity Fair contacted the Vatican and they said, we've never heard of a doctor with this name. Like, the Pope clearly has not got a doctor who has

the name Macarini. He'd just been making all this up. So he was a total like conman, just a classic conman. Yeah, sociopathic con man. But isn't it amazing that a con man like that had managed to con, like one of the world's top medical institutions and the world's top medical journals and all the peer reviewers that reviewed his work? There were people, some of whom are on the, like, the Nobel Prize committee who were lobbying the university. We've got to get this guy employed. We've got to bring him here. He's great. He's a really amazing surgeon. He's going to change the world. And it looked like he was changing, if you just read the papers and took those scientific papers at their word, he was absolutely revolutionary. It's like some Epstein stuff, right? Where you're just like,

everyone's vouching and you're just like, what happened? And is some of this just because normal people don't automatically assume that somebody making an extraordinary claim is a psychopath that murders children? Because I don't know if I would jump to that either, right? That's one of the best explanations for it, I think, is that scientists basically don't want to believe that other scientists are just making stuff up. And in some cases, that's because they themselves have co-authored a paper with that scientist. That's one of the saddest things about fraud

is that you can have like five authors on a paper, say, and one of them is fraudulent, has made up the data. And none of the other ones have any idea about it, but it taints all their careers because this one person has committed fraud. It happens all the time. It's a really sad thing that happens to people's careers is that they have this thing,

and then the investigations that go on for years, and it really ruins your life for a long time because someone has committed fraud. But yeah, I think it was scientists just trust each other. The whole system is based on trust. When you do a peer review of a paper, you're very rarely sent the raw data that goes along with that paper. In this case, it's not like the peer reviewers were sent the medical records of the patients,

like the raw medical records as they were written about the patients. You know, they weren't like involved. They didn't visit the patients and check how they were doing. They took the claims that were written down in the papers at face value, and it turned out that they were fraudulent. So you're already getting, even if you're checking someone's work, you're already getting a version that has been manipulated, has a shalacking over it, has been possibly cherry picks.

It's already been pre-selected. I mean, I guess it makes sense because otherwise you'd have to do the whole study again, kind of, but it also means that you just can't catch. Yeah. That explains why some of this fraud just seems so lazy. Right, because they assume that no one is really going to go in and really check because it's extremely rare that anyone actually sends out their raw data. I think in the last few years it's been increasing a little bit more that people have put

their data online and said, like, and you can go and download that. and just do some checks and just make sure it looks okay and just double check that what they're reporting in the paper is not like completely divorced from what's in the data. You can argue about how to analyze the data. I mean, obviously that's a big part of science is saying, well, no, I think you should use this model. That's all fine. That's all like totally legit. But it's whether the data actually exists in the first place or whether when you look at those numbers, when you see those raw numbers, which often people do for the first time in fraud cases and they say, oh, God, these raw numbers are just impossible. There's no way that this could have happened in reality. This is not what a dataset looks like. One of the tells you, about in the book was that numbers are noisy. So when the data is really clean, like all the numbers are even, or they're all within like X of each other. It just doesn't make any sense because real numbers are just so, you say noisy, it's just like dirty data. It's like, oh, there's one person that has a value that's way over there. Well, okay, they did the thing wrong. This other person didn't fill out the questionnaire. This other person lied. And that's all in a real raw data set where you just have people that are way off base. But if everybody sort of fits neatly into the area

that you needed to reach the conclusion, you end up with all these different fallacies, one of which I think is called the Texas sharpshooter fallacy, where you just take all the data that shows what you kind of wanted, and then you draw a circle around that and get rid of everything else. Or there's like cherry picking and things like that that goes on, where you just pick the samples of people that support what you want and everybody else just gets tossed out. And you're like, look, it works. It's really difficult, actually, to draw a line from between fraud, on one hand, where people are like just, in some extreme cases, like opening up an Excel spreadsheet and typing in the numbers that they want.

There's a blurry line, where does that become analytic decisions? And what I call in the book P hacking, because you're trying to get your P value, which is this really important statistic. You're trying to get it below a certain level, and that's where the cherry picking and all that you just described comes in. So, like, the line between fraud and doing stuff with the statistics that you kind of know is going to give you the result that you want

or you kind of know it's going to push your data in the right direction is really hard to draw. But, you know, in some of the cases, in some of the really extreme cases like I talk about in the chapter in the book on fraud, This is obviously made up. This is like, you look at the data, and one of the worst fraudsters, the guy who has had more papers retracted than any other human being in history.

So obviously... What an accolade, right? I am the most discredited scientist that's still breathing. It's like the anti-Nobal Prize. It's like the worst possible thing you can get in science. I think he's had 182 papers retracted. So he's a Japanese immunologist called Yoshitaka Fuji. There was an analysis done of his trials.

These were all trials of like new... Sorry, not immunologist. He was an anesthesiologist. They're all trials of new, like, anesthesiology treatments. The group, you know, the experimental group and the control group had, like, basically identical variation around their means. So they were almost like it was a made-up bit of data where he, like, added one to every score or something, you know, to make it look different.

So it was, like, really obvious when you look at it. These trials never actually happened. These trials could not have been real. No real trial would have been so regimented and perfect looking, like pristine looking like that. And yet, this guy had, as I think, 100. I think people, they looked at his publication record, 182 trials were fake and I think three, they said, three of his publications were maybe based on actual real stuff that he'd done. But, you know, the first flags of this happened about a decade before he got like fully busted for fraud.

Like someone published a paper. The title of the paper was something like, the statistics reported by Fuji are really nice. And what they meant was that they didn't mean that as a compliment. They meant that as like, they look too good to be true. They're far too perfect. You know, that was kind of discussed at the time. and then about a decade went by where he was still publishing fake studies

before someone else came along and said, I have now found definitive evidence that this guy is making up the studies that these can't possibly be true. And that was the case, by the way, with Paolo Macarini, the windpipe surgeon, because he was basically, you know, there was an investigation done.

These allegations came out like whistleblowers from his, there were other doctors who were looking after the same patients. They said, well, these patients are doing terribly, and this just doesn't fit with what he's written in these scientific papers that are being spread to the world, old and whatever. They went to the university and said, like, we think something really bad is

happening here. They got someone independent to do an investigation. And then the university said, actually, do you know what? We've done our own investigation. This independent investigation, which, by the way, said that there was scientific fraud happening here. We've completely discredited that and we totally believe that this guy is truthful. The journal itself, the Lancet, one of the world's top medical journals, ran a crowing editorial that said, Paolo Macquarie is not guilty of misconduct. Just a few weeks later, when all the stuff about the Pope and all that came out. And also there was this documentary where they actually went and met some of the patients

and saw the terrible condition they were in. After that came out, they had to all humiliatingly climbed down and say, OK, we were wrong. Actually, this guy has been fraudulent all along. So in this case, you had, like, big medical institutions covering up. And, like, they were on his side. They were on the side of a psychopathic fraudster that was leading to the deaths of his patients. There are examples in the book where people were, like, photoshopping the images of their

data set, right? Like, they'll take one picture and they're like, look and then they do a mirror image of the same thing and they're like, here's another sample. It's crazy to me some of the stuff you listed in here. It's like in microscope, microscope pictures of cells or whatever. The peer reviewers are obviously just not looking at every single one and paying enough attention. And so, as you say, people can duplicate. They can like Photoshop things, touch things up, flip things around, recolor things. To make it look more like their result that they want is true. And it happens all the time. It's really, really common biology research.

There are researchers out there who specialize in trying to detect this, and they're like trying to make AI algorithms that go through papers and say, wait a minute, this picture looks identical to this picture. So there's something wrong here. And it's the same principle as the data thing. Like, this looks too good. This looks too perfect. There's no way that in reality this cell would look absolutely identical in every way to this cell. There's no way that that would be the case. So someone must have touched this up. Imagine what's going to happen when we have AI that can go over all the past scientific data sets and go like, hey, there's a problem here. We're going to end up. being like, so it turns out that 30% of all the stuff we thought was human knowledge. It was just complete bull crap made up by somebody who wanted to get tenure at a university. Genuinely chilling thought. And, you know, the only reason that that won't happen for a lot of, like, data sets is because scientists have hidden their data sets and they've got them in a drawer. They've got them in a drawer somewhere.

Yeah, exactly. Freaking infuriating. So if top journals have fraud, then less prestigious journals, probably, would you say they have even more fraud, most likely? It's hard to know. It's like this question of, like, all the frauds I talk about in the book are frauds. frauds who have been caught, right? So they've screwed up in some way. They've made their data look too pristine, or sometimes they've admitted it or whatever. Also, another reason that the fraudsters that

publish papers in the very top journals might get caught more often is because of the attention that that draws. It seems like a really dumb strategy to publish your fraudulent data in a really top journal because everyone's looking at it. The world is looking at it. There's news stories about it. Huge breakthrough has happened in whatever feels. Someone's going to look at it. And eventually, if enough people look at it, someone will say, just a second, that doesn't make sense and then start digging into your fraud. As you suggested, maybe the best thing to do is to kind of hide your paper, you're a fraudulent paper in a journal that's less prestigious, that's less well read, that's less well-known. And undoubtedly, that must happen a great deal. It's just that the scrutiny

isn't there, so you just don't pick up on it. So there's this weird problem of, like, selection bias, where it looks like we've got all these, you know, fraud might even be worse in the top journals, but it's probably just not getting noticed as much in the less prestigious ones. I looked at retraction data, and it looks like 40% of papers that are retouching. It's, and these are rounded numbers, of course. Speaking of perfect data, 40% or so, it's because of a mistake, which happens and is forgivable and is something that just happens. It's actually good if you've made a mistake and you say, hands up, I made a mistake. Please retract my paper.

That's actually really respectable. Like, there shouldn't be like a stigma against, if you put something out there that's objectively wrong, you know, I have huge respect for scientists that say, oh my God, I made a mistake. I'm so sorry, please retract this and we'll do better next time. That's great. And then 20% looks like outright fraud, which was a much higher number than I really wanted to see, honestly. Yeah. That was a bit much. Yeah, it's really, really worrying.

The fraud as well as like plagiarism and other kind of problems, like actual bad behavior on the part of scientists. We want to get to the point where there's not a big stigma and retractions are cool. You can retract things when you make mistakes. That's fine. And only a minority of those retractions are for like the real bad characters, the people who are actually like making up the data. What scares me is something like four in 10,000 stuff. are retracted, which to me doesn't mean that there's not that much bad science. It just means that most people are not getting caught doing this. Yeah, absolutely. There are undoubtedly fraudsters who

are really clever about the way they fabricate their data, who make data sets that look convincing and look normal and look not too pristine. They look like a real data set that was generated by actual data in the real world rather than a human brain. And so they're never going to get caught. And there may even be more dangerous to our scientific knowledge than the ones who have been caught. And we'll never know. From your book, I saw that the biggest defenders of fraud are repeat offenders that make up a large amount of retractions. You mentioned that Japanese anesthesiologist that has, I don't know, how many? It's only like 18, something like that, ridiculous number.

That's a hell of a lot. I was going to say 18, but then I was like, am I off by an odor of magnitude. How are guys like this still able to publish and work? How are scientists like this able to get funding, work in a lab, and put a paper out there? How is it not just, oh, more of this nonsense from this guy? Like, I don't even want to open this email, delete. That's often what happens after the fraud allegation is made. But the problem is that the fraud allegations get made,

and then sometimes years pass before any actual decisions are made by the universities. And, you know, you can understand why that is because universities... Yeah, that's embarrassing. Right. They're embarrassed. They're on the side of their academics, usually, against some random person from the internet who's emailing in. And also, you know, innocent until proven guilty,

they do actually want to check. Like, it does happen sometimes that people point out of fraudulent. fraudulent study and it turns out, or what they think is a fraudulent study, and it turns out that it wasn't fraudulent, they've just misunderstood. That does happen. So you can see why universities, I wouldn't want my university to, if someone accuses me of scientific misconduct, to just say, you're fired. I want them to do a proper investigation. I think once you're on your 117, fraudulently retracted paper, they might be like, you know, we've given you a few strikes here, buddy. The problem is that it often is all retrospective. So, you know, one is discovered, one

fraudulent papers discovered, and then people look through all the old publications, and they go, oh my God, this is really, really bad. It's like plagiarism. You find this with not just scientists, but like other authors who plagiarized, like bloggers who plagiarized stuff, journalists who plagiarize stuff. If you find one instance of plagiarism, you look back through the person's work and you'll probably find more because this is like a personality trait. It's like something people can't help but do. It's just the way they are. And it's the case with fraudsters too. You know, you find the first instance or the first discovery of fraud in someone's publication record, and then you look back all the stuff they've been publishing, and often they're quite prolific, you'll often find

a lot more. All I'm doing there really is saying that, like, personality traits exist. Like, some people are, like, antisocial in their personalities. Yeah. And that feeds into the way they do science, too. I mean, that totally makes sense. If you take a thousand scientists, you're going to find, I would assume, a roughly equal percentage of people who are delusional narcissists, just like you would if you took a big group of lawyers or anybody. Absolutely. Possibly more in the lawyer group, but that's just, I'm saying this is a, as an attorney, I'm, I, maybe just ran across a few more due to exposure. We'll see. That could be my own bias. I don't want to make any assumptions there. Who's committing this fraud, though? I do see that there's more in India and China,

and I thought that was interesting. Why? Why do we think there's more fraud happening in India and China as opposed to, I mean, there's plenty happening in the West as well. I just want to be clear, but why is more happening from that area of the world? It's hard to know. I mean, in the case of China, so I have a quote from the doctor and writer Stephen Novella. And he suggests that the totalitarian regime in China is not really conducive to doing science properly. Like living under a totalitarian regime is not like the best atmosphere for free exchange of ideas and, you know, criticism of people's ideas and so on. And so, you know, he particularly points to this study of acupuncture trials where 100% of those trials showed that acupuncture worked. Even if acupuncture really does work, you're going to find the odd

trial that shows it doesn't because of, as we've talked about, numbers are noisy, statistics are messy, you know, sometimes you're going to undershoot the real effect of a treatment. So it's really unlikely that 100% of trials that have ever been done in China on acupuncture did actually show a positive result. So something is going on there. And what he suggests is

that, you know, acupuncture is part of traditional Chinese medicine, which is favored by the Chinese Communist Party because it was kind of codified by Chairman Mao. And so this might be something that they want to support, that they particularly are, you know, like they reward scientists who come up with support for, you know, this kind of traditional Chinese medicine idea, and that gives a huge

incentive for people to make up their data. This is the Jordan Harbinger show with our guest, Stuart Ritchie. We'll be right back. Before we get back to it, I wanted to thank you for listening to and supporting the show. It means the world to me. Supporting the advertisers, by the way, that's what keeps the lights on around here. So go check out the deals. We put them all on one page. Go to Jordan Harbinger.com slash deals, everything's there with the codes and all that. Also, we have worksheets for every episode of the show in case you didn't know that. The link to those is in the show notes at Jordan Harbinger.com slash podcast, and the sponsors are in there too. Now, for the conclusion of our episode with Stuart Ritchie.

This reminds me in a way of all fascist and totalitarian regimes sort of find their way into science. And it reminds me of, this is obviously more sinister, but the Nazis and eugenics, where they were like, hey look, here's this scientific basis for why we hate people that aren't, quote, unquote, Aryan race people. And the acupuncture thing is a little more benign, I would think, because it didn't result in a holocaust or mass genocide. But it's not that different in that the messaging is, hey, we're the government and we control everything, including who pays you and if you can have a job. So you better find that this thing that was invented in China and contributes to our national identity is real and not a bunch of fake stuff. That's a bunch of kind of old white.

lives tales and traditional garbage that we just still happen to be doing in the country. Precisely. I mean, the other historical example that this, as you say, it happens in totalitarian regimes, fascist regimes. The other, like, classic historical example is Lysenkoism in Soviet Russia. What's this? Trophim Lysenko, who was like a Soviet biologist, who basically didn't believe in the effects of genetics as we normally know it, and was a big fan of Lamarckian inheritance, that is, that you can acquire a trait, and then you will pass that trait on to your kids if you've acquired it. Like if I'm reaching up for something and I get taller, then my kids are tall? That sort of thing, exactly. It's like that giraffe neck story. You get yourself really

huge muscles from like working out, weightlifting and stuff, and then that will somehow pass on to some degree to your kids. And so the standard rules of genetic inheritance were really strongly denied, and this kind of Lamarckian or lysenkoist view of inheritance was pushed. And scientists who pushed back against that were basically purged. You know, many historians think that this contributed really substantially to the famines that struck both in Soviet Russia and also in Mao's China because they basically denied biology about how to breed crops. And so this had massive effects. The evil of eugenics and the evil mirror image of Lysenkoism have killed an awful lot of people over the years. And this is because totalitarian regimes have come in and like trampled all

over science and told people what to do. So it always freaks me out when I see politicians of any respect trampling over science or like making a really strong scientific claim that doesn't seem to be alongside the evidence. And when you've seen all the stuff about hydroxychloroquine, and there's been all sorts of, you know, claims made about COVID-related stuff. But also when you see scientists who seem to have really strong political opinions about something or another, that freaks me out a little bit as well. So I kind of, it's naive to say that scientists shouldn't have political opinions and so on.

But I wonder if they should, like, declare them sometimes as well. And we've talked about, you know, declaring your interests. And I think there's a discussion to be had about whether scientists should say, like, I am a member of the Communist Party. and this might have influenced my view. I'm a member of the Republican Party, and I'm doing this trial on hydroxychloroquine, and maybe this is going to influence my view because I kind of want to show that Donald Trump is right when he says that hydroxychloroquine is a good treatment for COVID-19.

I actually think that one of the recent examples of a retraction due to COVID-19, which is, again, the Lancet and also the New England Journal of Medicine, which is meant to be the top medical journal in the world, they had to retract this paper on hydroxychloroquine. They said hydroxychloroquine was bad. I kind of have like a suspicion that those scientists overlooked what turned out to be massive problems with their data. They may even have been made up by one of the co-authors. It's unclear. They overlooked those massive problems because basically they wanted to get one over on Donald Trump. They wanted to say. I think so. Yeah. I was going to say scientists are usually more liberal versus conservative. So the odds of them being like, I want to prove Donald Trump. Right. Actually, it's going to probably be the other way around where they're like, you know what? We're going to embarrass this guy. I don't even want to look at this. I'm going to have a bias that I don't necessarily see. They're not necessarily.

deciding to do this, but they're like, I want this to be wrong. Right. And there's evidence, you know, from some of the other stuff I talk about the paper and when I talk about negligence, when scientists have made a mistake, and there's these algorithms that are trawling through scientific papers to find errors, like in the statistics. And it turns out that errors are more likely to be in favor of the scientist's hypothesis, right? Yeah, go figure. It implies that. If you find a result that goes against your hypothesis, you're more likely to check it. Oh, it turns out to be an error. Fair enough. But if you find a result that supports your view and is

really great for your hypothesis, you're like, oh, too good to check. I'll just move on to the next thing. So it's like this bias towards finding results in a particular direction stops us from being skeptical about our own research, which is the whole point of science, right? It's being skeptical about stuff, it's being skeptical about our own research, other people's research, and it really stops this process of skepticism in its tracks. How does fraud or just bad science and those consequences, how does that bleed out into industry and into things like drug research and medical treatment. I mean, we've seen some of this anti-vax bull crap from fake doctor or discredited Dr. Andrew Wakefield. Like, this is now in the zeitgeist, if you will. And people are like,

ah, there's science that says this and it's being hidden by the mainstream media or whatever boogeyman, you know, people are looking for. Does this actually affect drug research and medical treatment? Or is it kind of like, do we catch it before that happens? Sadly, it really does affect medical research. For instance, loads of medical trials. Medical trials are required by law, to be registered now. So since about early the 21st century, you have to, if you're doing a medical trial on human subjects, you have to register that. By which I mean you have to go on to clinical trials.gov if you're in the US and you have to say, we're going to do a trial of hydroxychloroquine for COVID-19.

The outcome that we're checking is COVID-19 symptoms. If you then find that the drug doesn't affect COVID-19 symptoms but does reduce people's headaches, say you managed to, you know, just happen to find that it reduced people's headaches, it's really, really common for the process of what's called outcome switching to occur, which is where you say, well, we were never really interested in COVID-19 symptoms to begin with. What we really wanted to look at was headache. And so you then write up the paper as if it was always about headache, a new drug to test headache. And oh, yeah, we probably, you know, on page 55 of the paper, you can say, like, oh, we also looked at COVID-19 symptoms.

But I'm using that as like an example. I'm not sure there's a study that has actually done that. This happens a lot, this outcome switching thing where, and it's just like the cherry-picking stuff that we talked about before, where, you know, medical trials often run by pharmaceutical companies, you know, this does happen when, you know, government-funded trials happen too. If you don't get the result you want, you just pretend you were looking for something else all along. Texas sharpshooter fallacy. That was, I explained it badly before.

No, you explained it very well, which is you basically, you find a result because of the randomness of where numbers are. And this is the Texas sharpshooter who goes up to a barn and, like, randomly shoots all over the side of the barn, and then he goes over and finds where there's a little cluster of bullet holes, and he draws the target around that. So you're drawing the target after you've made the shots,

and that's what scientists are doing a lot of the time with this outcome switching thing. And it's really quite blatant, right, because there's a record of what they have registered that. They've written down their original prediction, their original hypothesis, and then they're just like, you know, let's do something different.

Let's just write the study up as if it was something else. And so there's been analyses of this that really show, you know, I don't have the numbers right to hand, but large proportions of medical trials have changed somewhere along the way and aren't looking at the outcome that they originally planned to. And this is a recipe for finding false results, for finding false positive results, where you think you've found something and there isn't actually anything there.

It's just statistical noise. And this happens in industry. And as you say, this is the incentives of academia and where they meet the incentives of industry, which is we want to find results. We want to find exciting things that we can then market. This is the most important part of the show here. I want to talk about bad results doesn't mean we can just decide not to believe in science anymore

or choose what to believe without any evidence. Because I see this. I did a pandemic debunking video and the YouTube comments are terrifying because it's like nobody addresses the content of the video. It's just like, you're a big pharma shill or like, no, look at this YouTuber who's like a guy in a garage. He's got all the real evidence. And I'm like, no, I'm disagreeing with them.

So I'm wrong because now you're just going to hurl and so. Like it's crazy the lack of critical thinking, but people will hear something like this and go, see, science is also bad and has just as many errors as the guy who made some crap up and is living room this morning and put it on a blog. Yeah, yeah, there's a few responses to that. I mean, the first one is that all of the stuff that I described in the book, the fraud and the bias and all that stuff was discovered by other scientists, right? It was eventually, even though it took longer than it should, and I think there's real problems with the way that science is set up, all of that is, and you know, by the way, that is set up to. find positive results and so on. It's not a big conspiracy to keep down the population by giving them vaccines and like inserting microchips in them, as I believe one of the vaccine conspiracies is currently saying. What I mean by like perverse incentives and the way that the system is set up is

that we're incentivizing scientists to find exciting research results rather than find true stuff, right? So that's the situation we're in. All of that stuff is discovered by other scientists, has been pointed out by other scientists. The process of science has eventually worked here, even if it took a longer time than should have really been the case. The other response is that what my book is arguing for is for us all to raise our standards for what we count as scientific evidence. At the moment, we've got this not very clear process of peer review. Sometimes it works.

Sometimes it doesn't. You find a peer-reviewed study and you don't really know whether it's reliable or not. When you should know, like, that should be the kind of quality seal where you're like, yeah, I can kind of trust this. We've clearly shown that that's not the case. What I'm asking for is for people to raise their standards, for people to be more skeptical of data, be more skeptical of results, be more skeptical of interpretations. And I think if you applied that sort of reasoning, really serious statistical analyses, pre-registering your

analyses before you look at the results, all that sort of stuff, I think if you applied that to the average claim by a vaccine denier or the average claim by a creationist or any of these kind of conspiracy theorists or anti-science science denier type people, their claims would crumble apart in a second, right? They're even worse. Like, for instance, when was the last time you saw an anti-vaccinator retract a paper or retract a paper in one of their phony journals that they've got or criticize another anti-vaccinator. These people are clearly biased in one direction. They are not applying the principles of science that I advocate in this book, which is like constant skepticism, sharing results with each other and sharing results with the world and so on. And I think the fact

that there are people who deny science and who deny the science that we can rely on and vaccines they've been studied within an inch of their lives and they're safe in many cases and scientists should be open in the cases where they've been found not to be safe and things like the MMR, which is the Andrew Wakefield stuff that you mentioned. That really doesn't cause autism. The evidence is very strongly against

that causing autism, which is what the original claim in the Wakefield paper was. If you look at that data, it's really clear. But the fact that there are people who say that MMR might cause autism or worry about MMR means that we in science need to raise our standards even more. We need to say, look, we're nothing like what you claim.

we're not hiding anything. We're being open with our research. We're being transparent. We're not doing what you're claiming we're doing, which is making a kind of tacit agreement not to discuss the flaws. In fact, I had an email from a prominent chemistry professor from one of the University of California system universities

just the other day who said, you're doing damage to science by writing this book because... I could see why they think that. Right, right. People are going to read your book or read your op-eds that you've written or whatever and say, well, I deny science. And basically, the implication of his email

was. And he said, I agree with you about the problems. I agree with you about the empirical stuff that you talk about. So what he's claiming there, what he's saying is that scientists should have all these discussions in the ivory tower and not mention them to the public and not talk about anything at all. And I think that's a recipe for disaster. And I think that's actually a recipe

for feeding the conspiracy theories because it is actually making a conspiracy. It's a conspiracy of silence. It's saying let's not let the man in the street, the hoi-polloy, let's not tell them about any of these problems. Let's just work it all out ourselves, you know? And I don't think that's adequate. I don't think that will work. I think only sunlight and transparency is the only thing that we'll work here. I think that's part of this whole open science thing that I advocate in the book, which is people should be able to read the papers. Anyone should be able to look at your data in pretty much all cases. And anyone should be able to see the flaws in it. So transparency is what we're after here. Yeah. I mean, that's what's beautiful about science, right? We can crack this open, shine a light everywhere in every corner of every element of science, show the problems with it and then get better. And other.

disciplines or fake disciplines or fake science, they can't and won't do that because they can't stand up to any scrutiny. So they just go to their convention and sell their self-published books and that's the end of it. You know, I talk about these norms of science, like one of which is organized skepticism and there are universalism and communality and all these kind of really important disinterestedness is one of the most important aspects of science, which is that we shouldn't come into science with an ideology or with interest in one particular finding or another or any kind of political or any other kind of, you know, set of beliefs that could push us in one direction or other. Charles Darwin described it as scientists should have nothing but a heart of stone when it

comes to the result. So if they do an experiment and it turns out that their theory is completely wrong, they should write up that paper and publish it in the same way that they would if, you know, a similar experiment had shown them to be right. So it's something which, you know, I used to spend a lot of time back in like 2005, 6, when this felt like it was a real problem, before we had real problems and even bigger problems. I used to spend a lot of time reading creationist forums and creationist stuff because I found it really fascinating that there was this

as good as evidence gets for any theory, the theory of evolution, and yet there were still these people denying it. And you could see that they came in, they often explicitly came in and said, if it goes against the Bible, I'm not going to believe it, and now I'm going to do a scientific paper about evolution. It's like, that's completely the opposite of what science should be about.

And that's really what's happening in these cases. They don't have like a Bible maybe, but the, you know, the anti-vaccinators are very strongly taken with, you know, the latest Wakefield book or the latest stuff that's been written on, you know, some of the anti-vaccine sites. And this is clearly their ideology that their preconception that they're bringing to it. That's anti-science. And it's not just anti-science as in the results that are published in scientific journals, but it's anti the whole scientific process and the whole way that science should work. In closing here, how do we

incentivize properly? Because to hype up some fake results or some exaggerated result, that's how a lot of scientists get funding. That's how they get speaking gigs. It's how they end up getting tenure because they got a lot of social media followers and a lot of people want to take their classes. How do we set up the incentives properly because they clearly are not proper right now? Yeah. Universities are kind of aware that the way they hire scientists and the way they promote scientists and get them tenure and stuff are clearly not working. And a lot of universities now are changing the way that they run their tenure committees and they say not just like, how many papers does this scientist have on their CV? We'll hire the one with more papers, because that

encourages scientists to just endlessly publish low-quality research. Journals are now actually changing the way they work, so it doesn't just say, we want your most exciting results, but it says we'll publish replication studies. So they can change the way they work. Funders can also, you know, they don't want to have egg on their face when they've just poured thousands, millions of dollars into a study that turns out not to replicate. So they can require that scientists will not just publish a paper in the most flashy journal, but we'll share their data with the world. They'll incentivise scientists to do stuff like be good scientific citizens and create new software that checks for errors, create new ways to be transparent and share data, create new methods that really

rigorously analyse data. And I think also just talking about this stuff, so just you and I talking about this stuff now is part of how we change the incentive system because I think we've good reason as scientists to look back at some of these real failures, the frauds, the biases, and feel shame about them. And I think just talking about it, having this discussion about the replication crisis and the way that the incentives in science are so badly wrong, I think is half the battle, really, of moving those incentives to a better place. And that's really why I wrote this book. Stuart, Richard, thank you so much for coming on the show today. This is really interesting. I mean, it's a little niche, you know, like I was a little skeptical, oh, my God, you're going to

talk about the problems in science. Whatever, how am I going to make this mainstream? But you did a great job of making this palatable for an audience of geeks, but maybe not scientists. Yeah. Thank you so much. Great to be on. Thanks. I've got some thoughts on this episode, as usual, but before I get into that, here's a preview of my conversation with Austin Meyer. He's a software developer who exposes patent trolls and how they shake down innocent victims using legal loopholes and abuse of this system. I was working at a trade show in Oshkosh, Wisconsin, where I was sitting there in a sweltering hot aircraft hangar, showing X-plane, my flight simulator, to a steady parade of sweaty pilots wandering through the hangar to look at my various wear. and all of us from the phone rings. Hello, I noticed you've been sued for patent infringement.

I'd be happy to represent you for a price. And I said, no, I'm not going to settle with somebody I've never even heard of before for infringing on a supposed patent I've never heard of before. And he said, okay, just remember your defense cost is going to run around $3 million. Wow. The patent claims to own the idea of one computer, checking another computer, to see if a computer program is allowed to run. The patent we were sued on had, as I recall, 113 claims.

And every claim was almost the same. In other words, one claim would say, a computer accessing another computer to unlock software. And the next thing would be software unlocked by one computer accessing another computer. Now, it was just the same thing over and over 113 times phrased a little bit differently each time. Because since it took us four years and two million dollars to overturn one of those sentences, they had the same thing written down 112 more times. so they could put us through this for the rest of our lives. For more with Austin Meyer, including the details of his own investigation into patent trolls

and why none of us are safe, check out episode 326 of the Jordan Harbinger Show. I know I'm a geek, but this topic was really interesting for me. There is a lot to be said about small-scale studies and exaggerated results. A lot of this genetic research, it's just so tempting to read big results into a small amount of data. And especially when you're a new scientist, you can't afford. large studies. If you're small, you're new, you're trying to make a name for yourself. So I get it. This hype, though, in science is dangerous. It makes a dent in the public trust for science. Hyped science flies, and then refutations and corrections just come limping after it, and it makes

people think that you just can't believe anything these days. Fraud likewise wastes a ton of money, as grants are wasted, tax dollars are wasted, and others waste their own funding, trying to replicate results that were fraudulent in the first place. And I wondered when I was doing this. Why is it that whenever we hear of new scientific research, it's always an amazing discovery. I think it's just the news cycle, but it seems like the majority, or at least a huge amount of research and studies, should actually conclude, well, there was nothing there. Our hypothesis was wrong. Nothing was going on. The data was bad. There's just no meat in that burger. And maybe we're just not hearing about this because the failures aren't published, but that's part of the problem, right?

And if you want to see some of the very worst, most outrageous scientific frauds, take a look at the website Retraction Watch. We'll have that linked in the website. There's a leaderboard there. The scientists who have the highest number of retracted papers in history, usually because they made up their results. I mean, these are triple-digit BS, often produlent studies. It's just horrifying. Science is biased sometimes because scientists are human. We all have our own biases. What's the scientific finding that would most upset you if it turned out to be false? Think about that. Your favorite diet doesn't actually work? The studies in your favorite self-help book might not stand up to scrutiny. If you look at these questions and you think about this, this way you can put yourself in the shoes of the scientists who might find that one of their own results is less than solid, and you might understand why some of them might resort to massaging the data a little bit. This is especially prevalent in nutrition. This gut biome bull crap is kind of the new trend.

There are other ways to manipulate data as well. You can fluff the resume. You can do what's called salami slicing, where you just take. little bits, it's like cherry picking, but you just take little tiny bits that lead to something and show a finding and you ignore all of the other results. And you can, of course, cherry pick which results go in which papers. It this wastes the time of pure reviewers and it misleads the public. The good news is, even with all these problems in science today, and there were plenty more in the book, even when people have incentive to hide their failings, the pursuit of truth

is still paramount for most scientists. And that's why we can and should still rely on science. Big thank you to Stuart Ritchie. The book title is Science Fictions. Great title. Links to that stuff will be on the show notes on our website. Please do use the website link if you buy the book. That helps support the show. Worksheets for this episode in the show notes. Transcripts for this episode in the show notes. A video of this interview on our YouTube at Jordan Harbinger.com slash YouTube. And I'm at Jordan Harbinger on both Twitter and Instagram. You can also hit me on LinkedIn. I'm teaching you how to connect with great people and manage relationships using systems and tiny habits over at our six-minute networking course, which is free over at Jordan Harbinger.com

slash course. Dig that well before you get Thursday. A lot of the guests on the show are in the course. They help contribute to the course. So come join us. You'll be in smart company where you belong. This show is created in association with Podcast One. Also, of course, my amazing team, which includes Jen Harbinger, Jace Sanderson, Robert Fogart,

Ian Baird, Millie Ocampo, Josh Ballard, and Gabriel Mizrahi. Remember, we rise by lifting others. The fee for this show is that you share it with friends when you find something useful or interesting. You know somebody who's interested in science or is a scientist? Please share this episode with him. I do hope you find something great in every episode, so please do share the show with those you care about. In the meantime, do your best to apply what you hear on the show so you can live what you listen. And we'll see you next time.

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