1608: The Truth Experts part 1

Speaker: Previously on Pretend, we jumped head first into the world of academic fraud. Celebrity behavioral scientist Dan Ariely from Duke University, Francesca Gino from Harvard, and other behavioral scientists from prestigious universities conducted several experiments aimed at making people more honest. The study tested whether less people would lie if they signed an honesty pledge at the top rather than at the bottom of a form. Except two out of the three experiments in the study, I interviewed Dan Ariely about these allegations, except we ran out of time. I thought that that would be the last time I would ever hear from Dan Ariely. He responded and he said, quote, if you intend to add these false accusations to the podcast, Maybe it's best to have another session and get my answers on the record. But I will ask you to promise me not to edit these and to give my answers exactly as I present them. If you're up for this, let's schedule something. And so I agreed. You're about to listen to my second interview with Dan Ariely. I will play the interview in its entirety. I will, however, cut out the dead air, the ums, the uhs, and I will interject every now and then during the interview just to add a little bit of context. But you will listen to every second of our 43 minute conversation. I will also post a raw, uncut interview of both of my conversations for free on Patreon and Pretend Plus. You don't have to be a subscriber to listen. I'm Javier Leyva and this is Pretend. Stories about real people pretending to be someone else. So let's just jump in because I think last time we talked, I caught you off guard a little bit when I asked you about the car insurance study. And of course, you know, we were talking about misbelief, which is something I'm interested in. You did not catch me off guard. It was just not the right time to ask these questions. So it's not that I wasn't happy to talk about it, but I wanted the Duke investigation to finish before I can talk about it. This is why we're here. I mean, I think that I almost want you to just clarify the situation regarding the insurance company's data. And from your point of view, I think you gave me an answer, but just a second shot. So look, so clearly something very bad went wrong. In the chain of custody, this happened in 2007, 2008, and something very bad happened. And this was under my watch and, uh, I have some responsibility because it was under my watch. But if you ask the question of, did I ever manipulate or change data? And the answer is no. And kind of interesting how people jumped at me. Think about it. I had many years after that, all the data sets are now online. It's a little easier to come up with an accusation of something that happened 15 years ago, because it's very hard. to prove something. If somebody made an accusation of anything that happened in the last five years, it will be incredibly easy to show that it's not happening. Like so many things have improved. You know, the choice to accuse something that happened a long time ago is, is of course, much harder to prove. There's a lot of people that touch this project. So that is true, but continue your thoughts. Lots of people, lots of people, lots of people touch every product, every project. But the other thing to realize is that I'm disabled. And I, everybody who works with me knows that I don't touch data. Uh, in about 2002, 2003, there was a period that I, I had a lot of pain and I decided to, how do somebody like me reduces the amount of activity I have to do? I decided to take a whole category and take it out. So if you talk to anybody who worked with me, they would tell you that from 2002 or 2003, I've not opened a data file. Other people do it. I look at what they do. I give them feedback and so on. So what does that have to do with the disability though? I just want to connect those dots. It's very hard for me to move my hand. What are the things that are difficult for me? Anything that has to do with the mouse, anything that has to do with typing, all of those things are, are difficult for me. So I, I have about. a page and a half of typing and using a mouse in me a day. That's about the amount I have. After that, I have a lot of pain, and if I do more than that, I can't sleep at night from too much pain. So I need to very much regulate what they do. So I find lots of ways to, to go around that. And the world, by the way, has not been kind to people with my type of disability, because think about how much correspondents have moved to text compared to 25 years ago, right? There's almost no phone calls, a lot, a lot more text. So I, I limit myself. So between the fact that I don't do, I don't do data, the Duke investigation found that there's zero evidence to think that I've. messed up with any file. And the fact that if you look at this, there's like the things that you, that are more current and you can look carefully at, there's just no shred of anything that is, that looks like. So, you know, you look at somebody's history and you say, uh, there's been 15 years and we find this blemish. What are the odds? But it happened on one paper that I was the fourth author on and was a very, like, the speed of accusation has been kind of interesting. Yeah, it is true that there's sometimes in the cancel culture, people just ride this wave and it's like a flame, right? I don't want to call it the cancel culture. I think it's a, you know, I had, I had these two experiences of one being disliked by the people who thought COVID was. an invention and one where people thought I was involved in some academic misconduct and they were both related but very different. One of them was complete strangers and included death threats and so on. One of them was people I knew. It wasn't as extreme in terms of the language and But it is interesting to think what, what is social media? And what is identity politics and where do we get this waves of for and against that are so dramatic. Think about what's happening with anti Semitism now. We see students on campuses, kind, wonderful people who are all of a sudden, um, like, you know, there's a war between Israel and Hamas. And the Palestinians are, the war is basically between Israel and Hamas. How do Jewish kids on campus X in Cambridge, Massachusetts connected to this, right? They're not the party to it, but there's something. But people pick a side. People pick a side with rage. It's an important phenomenon to understand. I think this, look at politics in the U. S. Something is incredibly worrisome in this. Yes. In this regard. Okay. Let me pause the tape for a second. I'm about to ask Dan Ariely about Duke University's investigation and the fraud allegations. As you remember, in our last episode, Harvard put Professor Francesca Gino on administrative leave. After they discovered several studies with fabricated data, unlike Gino, Ariely still has a job, while Duke University concludes their ethics investigation. So, can you confirm that Duke has reached their final decision? I know last time we spoke you said to keep that under wraps, but they have finally? And have they released it or will they release it? I don't know, it's up to them. I'm trying to see what they will do, I will hopefully know soon. The next thing you should know, in order for this next part to make sense, is the conditions. Let me explain. The New Yorker magazine was able to obtain the original file of the insurance company data. The spreadsheet contained odometer readings for roughly 6, 000 cars, and about half of the drivers were given the original form with no honesty pledge at all. This was the control condition. Now, let's talk about the second condition. A quarter of the drivers received the honesty pledge at the top of the form, and the third condition were the remaining drivers who got the honesty pledge at the bottom of the form. Capisce? But somehow, by the time Dan Ariely and his co author Nina Mazar Started working with the file? The file went from having three conditions to two conditions. Not only that, but the sample size increased from 6, 000 drivers to now 20, 000 drivers. The Data Collada team believes that 14, 000 of those odometer readings were simply made up. If you're asking yourself, how did no one notice this? Well, Nina Mazar, his co author, figured out that the data wasn't adding up. When Nina Mazar asked Dan Ariely about this, he replied to her in an email. He said he must have relabeled the conditions and, quote, made the data nicer for her. Making the data nicer? How should we interpret that? So, you're right about there is no smoking gun, right? There's no smoking gun and there's a lot of people that were involved in this study. And put that aside, I think I want to talk about the inconsistencies. Last time we spoke, I mentioned that there were three different conditions in the insurance study and then you stopped me and you said, no, there wasn't. But then we never elaborated. So what did you mean by that? Because before you answer. The three different conditions, as I understand it, were half of the people were given the original form, a quarter of those people were given the pledge at the end, and then the other remaining people were given the pledge at the beginning. So there were three conditions according to the New Yorker article, but you disagreed with that. No, there were no three conditions. And I can show you the same email I showed the them that showed me sharing the data and the forms with the people from the insurance company. It includes only two forms and only two conditions. It's one of those accusations. I don't know what to say about this. And there's just no, there were just no three conditions. I don't even know why would I do three conditions. If you look at all the other experiments, none of them had this structure. So somebody look at, look, I don't think people make up stuff, but I think somebody looked at something. It looked like it supported three conditions for them and they went ahead with that study, but I don't know, I don't know what to tell you about this. None of my other experiments on this had three, there's no logic for three conditions. If you look at all my other experiments, look at my research approach, like how I design experiments, nothing. would suggest that there were three conditions and then I can show you the email to the insurance people that basically had, like, at some point I consulted with them. I sent them back the data file with all my co authors. Everybody was CC'd on the email and I say, help me understand a few questions. And the two forms were there. If there were three conditions, They would have said, Hey, something is missing here. No, there are only two. And the insurance people would have known if there were three conditions. So anyway, look, I don't want to speculate about made up nonsense. You know, I know how fake news works. Like you, you create the fake news about something. And then I say, Oh, this didn't happen. And then people remember. So anyway, complete that claim should make you worried about where you get your information. I would love to see that email if you don't mind, because I would like to wrap my head around it because there's definitely a discrepancy there. From your recollection, how many people participated in this study? 15 years ago, I remember that we talked initially about trying to get about 20, 000, but I don't remember the exact number. And now we know that it was dramatically less, right? Look, the term, now we know, is very confusing to me. There are clearly, different statements. But if you ask me what's correct, I don't know. Like, you know, the statement about three conditions, I can prove to you, I can prove to you that it wasn't. I can show here's an email that shows only two. The other ones, I don't know. I don't know how to prove or disprove. Wouldn't the Excel spreadsheet that, that's floating around the internet be the proof? There's so many, there's so many ways to think about other things. Like I think that you have a narrative. And you look at evidence and you try to build that case. But there's lots of other possible narratives too. Did you ever reach out back to the insurance company asking for more data, more participants? Look, don't ask me about what correspondence I had with anybody 15 years ago. Let me ask you, how old are you? I'm 43. And now, yeah, I would struggle to remember any details. When you were 28, when you were 28, how many emails did you write your mother? It's ridiculous. It's ridiculous. That is, that's fair. That's fair. Because 15 years is a long time to remember specific details. But we do know that we have the data is out there and it's, let's say we know that there's a data file out there, but we don't know it's the data file. So that's where we're trying to untangle this mess. And I'm happy to participate in this exercise, but look, as you can imagine, this has been Important for me and I spend huge amounts of time in the last two and a half years trying to figure this out trying to talk to anybody who would talk to me and trying to understand and trying to reason And at the end of the day, I don't have a smoking gun at the end of the day I don't have a smoking gun something very bad happened. I take some responsibility not for doing anything but for Under my watch, I could have been more careful. In retrospect, I could see all kinds of things I could have done. But after two and a half years of engaging in continuous search, I engage, you can engage, all kinds of people engaged. I can't find an answer. And at some point I need to say, I need to move on with my life. Like, imagine it was you. Imagine it was you and something bad happened in your past, let's say the same timeframe, 15 years ago, how many years would you dedicate to look at it? And at what point would you say the diminishing returns of looking more is gone. I need to move on with my life. Like, how much time would you look at it? Absolutely. I, I definitely, and that's one thing that I commend about you because, you know, Francesca, Gina is going about it one way, and you're going about it another way, right? I, I also don't want to talk about her. Everybody's a unique case. Everybody has their own approach. But I looked far and wide. Duke looked far and wide. You have to realize that, actually, you tell me. People who act unethically, how many do you find that act unethically and then stop? Because if you look at my data for the last, you know, things have gotten so much better in terms of data management and online and so on, and systems that track who opens the file and single login and all kinds of things like that. In your experience, and you're an expert on it, how common is a pattern for people to do something unethical and then stop? It's very rare for anybody in the criminal world or just in an ethical setting that you have a first time and only offender. Like usually there is a, you start pulling on a thread and then you find some more things. But hey, I also want to move people. Past this section, but I do have some yes or no questions that just to get through it. Right. Because I don't want to harp on it. Right. Just like you don't want to harp on it. You mentioned there's ways to track data files now, but according to some of the reporting, they're saying that some of the conditions were relabeled. Did you relabel any of these conditions? Yes or no? I know this is not, I don't know exactly what you're talking about, but look, the files. And this is, I'm drawing from memory, okay? But my vague memory is the file had a heading. And the heading was the name of the form. Form 17 15 16 A. B. And I don't know if I mailed, again, I don't use my hands that much. If I mailed or, Usually ask my assistant, like she used to sit next to me and you will do it, or one of the research assistant depends. And I asked them to, let's say I asked them, I'm not sure exactly if I did or they did, but let's say I asked, I asked them to change the heading, the files to say sign before sign after. and mail it to Nina. And in the email, apparently it says, I made a data file nicer for you. Some people are looking at it as if I said, I'm cheating. Think about what it would take from somebody to say, Oh, I'm cheating on the data set. And I'm sending it to you. I'm telling you that I'm doing that. I'm giving you proof, uh, electronic proof. And then she responded and she said, look, the results look the opposite. So then we looked at the file, probably a previous version or something and said, Oh no, we missed. We missed the labels, right? Instead of saying this is before and this is after, we did the opposite. So we fixed the labels, but it was a, like a typo, right? Where you basically get the condition you type in. I don't know if I did it or research assistant did it, but that was what happened. But this is the level of craziness. If I, okay, I hope you agree that I'm not one of the dumbest people on earth. I'm not saying very intelligent, but not somebody would have to be, I don't know what. To write an email to a collaborator about something that they did wrong, to say, I made the data nice for you. No, I changed the labels to make it more English and not, you don't have to go back to the labels. So anyway, so the answer is me or somebody that worked with me or under my instruction and change the heading names. to more meaningful terms, did it in a mistake in the beginning and then fixed it. Fair enough. Thank you for answering that very directly, by the way. I appreciate it. So now I want to move past this a little bit because like you said, uh, some of this stuff is like beating a dead horse, right? But you have been very, uh, forthcoming and I appreciate it. In the previous episode, I mentioned that Dan Ariely's latest book is called Misbelief and focuses on an online backlash that he received for his work during the pandemic. However, after hours of searching, I couldn't produce a single post bad mouthing him about COVID. In the book, Dan Ariely talks about a man named Richard. According to the book, Richard wanted Ariely dead and he said he would personally be his executioner. According to Ariely, this Richard fellow had a podcast and invited Ariely to be his guest. But Dan Ariely never mentioned the name of the podcast. Now let's switch to Misbelief, because there was a couple loose ends that we didn't tie there, but you mentioned that there were some screenshots, these COVID posts, I struggled finding these screenshots. If, and I'll send you a reminder, but I would love to see some of these. Because I just couldn't find it. There was also a video that connected me to October 7th. Oh, more recently since the book came out. Yeah. Yeah. Let me see if I have it. And I would like the podcast that with the Richard, I don't know who it was, Richard, that was yelling at you the whole time. What was the name of that podcast? Do you remember? No, I'll find out. I don't have the video here, but I'll send you, so you want to see some screenshots and so on, I'll send you some. Yeah, because I think that it's so interesting that. In your book, it's very central. It's a central theme of your book, Misbelief, that you've been the target of this crazy anti vaxxer movement where people have been attacking you online, but there's such a parallel, right? Because in the real world, in the physical world, where you work amongst your peers, just like you described, the people that have been attacking you as well. So the parallels of that is, is very fascinating. Yeah. I can also connect you with the guy who was sitting next to me when the first time I was attacked. And in person. Mm-Hmm? . He was still shot. Oh, in person? Yeah, yeah, yeah. Oh, wow. The in, in the first in-person attack was very troubling. Somebody just couldn't stop pointing at me and shouting, psychopath murder. Psychopath murder. It was, um, and this was because of the October 7th? No, no, no. This was, this was, this was before that. Yeah. Yeah. And this was way before that. So anyway, I'll send you some stuff. All right. All right. Now I want to talk about just general academia, the field in general. So one of the questions that I start thinking about when it comes to this topic, and you know, uh, Freakonomics just came up with a piece on it too. I think the saddest thing about this, and not just your case, I'm just talking about this topic, is that I think of like the news media, you can't trust it anymore. Like people don't trust the news media. You see polls and, and like the trust in the media is going down. But I always thought academia, we could always trust academia. And so like, what are ways that we could do to make Such as yours, but like anybody's studies more trustworthy, like should we share the data with every study? So first of all, the answer is that things have gotten much better, right? So you think so? Yeah. With academia or with the media? With academia. I think the media is going the wrong direction. Okay. So, so academia, I think we've done a couple of things. is a discipline that are really good. So first of all, there's something called the open science framework. So every time we are about to run a study, we write, we describe the study, we describe the data, and we describe the analysis. that we want to run, right? So that's very important. We don't do the analysis and see what works and what doesn't work. We protect us against ourselves, right? It's a good thought exercise and we put it in a, in a public place so everybody can see. And then our data goes into that place. So everybody can see that and re examine this. And the data, of course, helps because people make mistakes. And sometimes, I think mostly it's, if you look at all the people that touch it, I think most of the mistakes are not with intention, but sometimes they are. intentions, but I think that most are without intention, but having things in the repository gets people to be more careful and more thoughtful. And saying in advance what we're going to look for is also very interesting. And there are journals now that would accept your paper before you have the result. Like you say, here's what I'm going to do is here's, I'm going to collect the data and here's how the data would look like. And some journals say, you know what, this is sufficiently interesting. If it comes as Positive, it's interesting and in common negative, I'll accept both of them. And that's also very important because we used to have this draw problem. I ran maybe a thousand studies in my life, maybe more, and I ran many of them that don't work out. Until about eight years ago, I didn't have anything to do with the ones that didn't work out. Now, by the way, I publish in my labs, we have an annual report. I publish all the studies that didn't work out. as well, right? So I published the things that worked out and I started things that don't work out. But the things that don't work out very hard to publish in academia. So if you think about mistakes, I think there's a mistakes of, let's say I run a study with seven things. I look at the results in many different ways. I find a way that looks significant. The other ones don't look significant. And I convince myself that that's really the right way, but I do it all after the fact, like not cheating on purpose, but justifying, Oh yes, this is the right way to look at this data. So we, we now set the analysis before we get the data. Posting the data is good. The fact that there are some journals who accept It's not very common, but it's, it's a bit, it's a bit more common and that's great because it solves some of the draw problems. And then in my lab specifically, we publish the results that don't work as well. So all of these are good ways to move, to move forward. Is there a lot of pressure in the industry to get it right and to withhold the data? What do you mean to withhold the data? Maybe because for proprietary reasons, or you can't publish it for X or Y reason, Like, what kind of pressure are academics like yourself facing to, to get one, knock one out of the park? So, you know, academics, academics get promoted, right? We start as PhD students, then we get associate professor, then assistant professor, then professor. Then, you know, there's a promotion level. By the way, by, by 2008, by 2007, I've, 2008, I already finished all my possible promotions. Like, there was like, if you think about, was I interested in like, no, there was just zero promotion ahead of me. So yes, people have incentive problems like everywhere. The incentives are to get promoted, but also the incentives are for grants. Grants have their own, their own logic of what is happening. But this question about, can you trust science? I think that you can, but it's not. about any specific paper. If you look last year, this, lots of people get retracted. If you look at like, for example, nutrition, I think about nutrition, like how many conflicting evidence there are on nutrition. Oh, one day chocolate's good for you. One day it's bad for you. One day wine is good for you. It's not, it's not because it's not because people are dishonest. It's because life is actually very complex. Life is actually very complex, and there are all kinds of intervening variables that we might not think make a difference, but do make a difference. So, let's say you study something in Italy, and then you study something in South Carolina, and the results could look differently because maybe olive oil is different in these two places, or maybe their physical activity is different. Like, doing science is very tough. It's very tough to get things right, and when we think about doing replication. It's almost never the same thing. Just imagine young people today in terms of their attention to when you were 15, you know, that these are different people and different people because they have phones all the time and they have notifications all the time. And they're used to a very different school and very different friends and all kinds of things have changed. So I think of science as the corrective process across studies. But I think that you can study, you can trust. any academic study quite a lot. But, uh, before you go ahead and make a life decision, wait for accumulating, wait for accumulating evidence. So, for example, if you look at the results that, you know, we have the sign on the top, sign on the bottom, since then we've replicated these results. I was going to ask you about that. That was one of my questions that I forgot. I skipped over by mistake. Last time we spoke, you said that it is being replicated currently or recently. We finished. So first of all, the U. S. government used these studies in a very successful way. Was that the Obama administration? Yeah, exactly. The British government used it in a nice way, there's some other academic studies, but we also ran replications. And the replications were do you sign, do you type, what matters? And it turns out it's correct. It does work. As we said, I can send you the, the paper if you want. It's, it's very important. Yeah. Can you tell me, so is it done like solely by you? No, no. Like give me a little bit more information about it. Like it hasn't been published yet or? No, no, no. It's under review. Okay. I hope it will be accepted soon, but I'm happy to send you, I can't share the publicly until it's accepted, but I can send you the current draft. That'd be great. Yeah. But you know, all of these, all of these things are important, right? So things change and nuances are important. So for example, think about like typing your name, the same as writing it is initials. The same as the full name is repeating the statement. You know, all of these things ends up being a nuance. Now, when we talk about things replicating and not replicating, sometimes what we are learning is that the nuances are very important. I think that we too often judge, judge things harshly. Again, let's go to nutrition because it's far away from our field. You look at the study that showed that the Middle Eastern diet is healthy. And then you look at another study that shows that it makes no difference. Now, what should you think? Should you say somebody there is cheating? No, I don't think so. I think you should say there must be some real interesting differences between the two, the two experiments. What could they possibly be? When is one working? When is another one? Is it the duration of the study? Is it the kind of measurement? Is it the kind of people? Is it what they did outside of that? Think about how difficult physics is. And atoms can't think and can't behave and they can't do other things. So I think that in general, the right way to do it is that when science comes up with the finding, you can trust that finding in that domain. But when you ask the question of, can we speculate to, to other domains and to other places, Now you need to basically say, let me wait for more results. It could be very confusing for your average Joe to take in all this information because a lot of these studies are like clickbait where they're almost designed to get a headline, right? Like we said, like, wine is good for you. The Mediterranean diet is good for you. Yeah, it's the kind of, uh, thing that the media will run with it, right? That's right. There's a type of, uh, statistical reasoning called Bayesian statistics. And, um, the, the usual kind of statistics we use is, is this significant or not? But Bayesian statistics is about having multiple hypotheses. And every new piece of information updates your belief in one or another. So let's just take, uh, an example. Should you give your kids an allowance or not? I imagine, or, you know, let's say yes allowance, no allowance, or pay them for chores. Let's say we have these three approaches. You could say that a study could compare and say, oh, this is what we should do. Give them allowance and not pay for chores, whatever. You could say that's the winner. Or you could say, I have these three hypotheses, And every time I learn something, I update my belief. Instead of saying that's the winner, the right way to think about it is to say, I didn't know which to think. Right now, I think there's a 10 percent chance more than giving allowance is good, but giving allowance for sure is not a good idea. And we get another data and we update. So science is not fixed, is what you're saying, it, we're constantly correcting it and improving and refining. That's right. That's right. And that's what is so wonderful about the process is that it's built fact that people replicate and the fact that people build on and so on, that's what we want to do. So if you go back and you look at like introduction to psychology textbook, you'll find things that have been, you know, replicated and vetted and nuances have been found and so on. And that's how we build data. That's how we build our knowledge. So, to your question, can we trust academia? I think, as a whole, absolutely, but we should not be too quick to judge, to make conclusions about single experiments. That's fair. That's fair. By the way, after my call with Dan Ariely, he sent me a PDF of the new Honesty Pledge study. The new research finds that pledges requiring somebody to actually actively do something, like, let's say, copying the text of the pledge, are generally more effective. This time, all of the data is available on the Open Science Framework for anyone to scrutinize. And like Dan Ariely mentioned, it's awaiting to be peer reviewed before getting published in a scientific journal. After the break, we'll continue our conversation with Professor Dan Ariely. It's important to note that the car insurance study wasn't the only time someone had questioned the validity of Dan Ariely's work. Here's a clip from NPR. Dan Ariely conducts experiments too. He's a professor of psychology and behavioral economics at Duke, where he does research into our predictably irrational behavior. And he comes on the program from time to time to share his research. So, you know, you go to a dentist and the dentist x ray your teeth and they try to find cavities. And one of the questions you can ask is, how good are dentists in that, right? So imagine you came to a dentist, you got your x ray, and then we took your x ray and we also gave it to another dentist. And we asked both dentists to find cavities. And the question is, what will be the match? How many cavities will they find that both people would find in the same teeth? And I'd really hope it would be somewhere up around 95 plus percent. That's right. Turns out what Delta Dental tells us is that the probability of this happening is about 50 percent, 50 percent. But the problem with this claim is that Delta Dentist, the insurance company Ariely cites, says that there's no data to lead to that conclusion. Then there's the paper shredder study. In a study, Dan Ariely claims that he had modified a paper shredder so that he could see when participants cheated. One researcher tried to replicate this and couldn't figure out how to modify a shredder as described in the experiment. In another of his most famous experiments, he asked students to score their own math test. Half of the students were asked to list the Ten Commandments, although only a few could actually recall. Ariely found that in that group, quote, nobody cheated. Researchers have tried to replicate this study and have found the opposite results. Ariely says that the study was conducted at UCLA, but the university denies any involvement. Let's get back to my conversation with Dan Ariely. Hey, I thought about, uh, when you were saying replication, I was talking to a friend of mine and, and he was really curious about the shredder, you know, the, the shredder experiment. I know that I've watched the video. You have a video, right? On your YouTube channel where the shredder experiment, and then somebody online, I can't remember who was saying that's impossible. A shredder can't do that. If you take out the teeth, then there's nothing to feed it down. Can you tell me about that? It's again, one of those things I don't even know what to say. It's like, somebody said that you can't make a shredder. And luckily we did a documentary on dishonesty and the shredder was in that documentary. And the person who was the director and the producer remembered. that it worked exactly as we said. How did you get the shredder to work without any teeth? No, it has teeth on the side, just not in the middle. So we shred the sides of the page. But anyway, it's the kind of world where people like, okay, like, you know, if somebody says this, okay, I can go ahead and I can buy a shredder and I can take it back to the machine shop and I can ask them to, To do it for me and prove to the world, Oh, look, I made a shredder. Luckily I had it, but part of my experience with the people who don't believe that the people who believe that COVID was a pandemic is to just realize that some people are going to say negative things and I can't convince them. Like just imagine that I go back to one of these people and I show them that I was able to make the shredder. Do you think that person would apologize? You think that person would say, I'm really sorry, . I thought it was impossible. Clearly I was wrong. No, there would be even. The better question is do you think that if you were to show 'em the shredder. Would they still believe you? You know what I mean? Like they most likely, most likely they would come up with the reason and they would say, Oh, you know, the shredder that existed 10 years ago, they were the ones who couldn't do this new technology. Obviously you can play with it. What about the 10 commandments study? Because there was that lady that I think it was Amy Rossi or whatever, that she says that she has never participated in that study. What can you tell me about that? So look, it's again, it's very hard to go back to 2004. almost 20 years ago and to say what was right. Because these accusations were made, I tried to defend myself. I found the research assistant that remembered photocopying and mailing the forms to UCLA. And he talked to the reporters. I don't know if they, I never read anything that was written about me. So I don't read any. That's probably a good thing because I don't my reviews. But I found the research assistant that remembers. And mailing those things. I found the original file that one of my collaborators did in 2004 with the conditions. Now, just think again. Why would I make up a study that was run in a different university? If I wanted to make up a study, wouldn't I make it in my own university? And not only that, I thanked her on the paper. I thanked her in the paper. So now you have to say, okay, somebody is making up a study at a different university and they thank that person in the article. Now, here's another interesting thing. We misspelled her name in the thank yous. And she called me and was furious that I misspelled her name. spelled her name. Now, if the study was not like, it's proved that she read the paper. If it was not done, wouldn't you have said then all of this thing is just so strange, but look, I think I'm really lucky that I thanked her on the paper. And I'm really lucky that we misspelled her name. And I'm really lucky that she called angry because now we know she read the paper and she was upset with it and she didn't say anything. Anyway, I can go on and on. This is some of those cases where people make up stuff and they, like even you, right? Like before I told you all of this stuff, what was your assumption? That I was wrong or that the accuser was wrong? Answer honestly. Yeah. No, I'm glad you asked me that. I mean, look, I'm going to give you the journalist's answer. The journalist's answer is I try to go unbiased to every story. You know, honestly, I could see a lot of holes in the claims that they're making because there is no smoking gun. So I'm not convinced one way or the other, right? I got to tell you something. I was more put off, honestly, by your book, Misbelief, than I was any of the car insurance companies, because I just thought it was interesting. The angle that you took with the book about making it so personal, right? Like, you could have totally done that book. Without making it about you. Right. But I found that the parallels between the, what's happening with you in your professional life and what's happening with you in misbelief was very interesting. It was almost like an analogy to what was happening. And that, that is my honest answer. I thought about adding something about the academic adventures, but eventually, because I try to describe misbelief and I try to describe, I don't think it's the same. There's something on, on the personal experience of being attacked that is similar in both cases, but the psychology of the people who accuse me of academic things is very different than the psychology of the misbelievers, right? And we were trying, I was trying to go deep into the psychology of misbeliever, but just to finalize about the 10 commandments, another thing you said academics is about replications. So we just finished replicating the 10 commandment experiment. Oh, really? Just recently too? Yeah. Yeah. Yeah. I mean, recently, you know, it takes years, but we're, it's also a paper under review and he chose that the results works and it shows that it is mediated by a belief that the Ten Commandments represents some moral context. So the people who don't believe, it's not about being more or less religious, but it's about having some belief that the Ten Commandments capture something about this. So anyway, so this is all the right, the right, I mean, not the accusation of not doing the experiment, but look, I am delighted when people try to replicate. My study is in a good spirit of trying to find out what's going on. And I am delighted when things work out and I'm delighted when we find differences and figure out more nuances. I think that social science is becoming more and more important as we move forward in society. So that was the end of my call with Dan Ariely. And I thought the interview had humanized him in a way that the previous articles did not. But that same day, Ariely sent me a voice memo. Hello, hello. So I had a little bit of a sense in our last talk that what you're trying to do is to try and do an episode that is kind of going after me in an unfair way. Um, you know, it just, it just felt like you were, um, already have determined things and you were, uh, biased and, um, it didn't, it didn't feel like you even gave me a fair chance. It felt you were. Uh, after a sleazy story as inaccurate as it, as it might be, uh, can we, can we jump on the phone to understand a bit more about what it is that you're trying to do? I have to say that you left me with a very. I felt I've been honest and straightforward and direct and gave you my time and it felt like you're abusing, abusing this and trying to, uh, to do something that like, you know, sometimes the media is, is the judge and executionary and it felt like you're going into that direction. Can we, can we find a time to talk for me to understand better what you have in mind? Were you taking this episode? Um, Thanks. I called Dan Ariely that night to talk to him about his concerns. I didn't record that conversation, by the way. I told him that I understand talking about the controversy is uncomfortable, I mean especially when his career and credibility is on the line. However, I felt that I gave him a fair shake, and I reminded him that I won't be the last reporter to ask him about the fraudulent data. In fact, journalists have a responsibility to question his study. After all, whether or not he's responsible for the fraud, he's the one. He's the one that put this study out into the world in the first place. I reminded him that I still need to see evidence of the online attacks referenced in the book Misbelief. He told me that he would search for it and get back to me. Here's a message he sent me. Hello. Hello. So, I had the research assistant in Israel who downloaded the book. things for me, but I guess because she was in Israel, she downloaded most of the stuff she downloaded. You know, I, I don't use, as you know, because of my disability, I don't use my computer much for, for anything aside from voice responses. So, um, she mostly downloaded stuff from Israel. So I have, I have all kinds of screenshots and things and some even videos from Israel. Uh, but I don't have, uh, ones from the, from the U. S. I can start searching, but again, I don't, uh, like to use my hands much so. He finally sent me a video of his computer screen with multiple screenshots, all in Hebrew. He read a handful to me. Professor Dan Ariely is giving suggestions for research to vaccinate people and how to help us live shorter. See this is not, not funny. Uh, we know you're advising the INSS. Yes. Professor Dan Ariely planted all kinds of messages to the public. Professor Dan Ariely is an advisor to the change of the consciousness of the Ministry of Health and the main advisor for Gallant, the head of the, this, he's recommending to decrease the life expectancy and help people die faster. The height of it's. So far, nothing alarming. I mean, come on, man, it's the internet. People say all kinds of stupid things. Just read my reviews. But there was one alarming screenshot Ariely sent me. It was a post on social media from an anti vaxxer comparing Dan Ariely's work to that of the Nazis during the Holocaust. And at the end of the post, the man suggested Ariely be tried and sent to life in prison. Or even worse, get a death sentence. But that was it. A few bad reviews and some crazy people saying crazy things. It seems to me that everything surrounding Ariely's work is grounded in truth except some of the details get a little mucky. By now you should get the sense that this isn't your typical academic type. You'll never find Dan Ariely wearing a tweed blazer with elbow patches, a dress shirt and slacks. He's more of the un groomed t shirt rolled out of bed into the lab kind of look. He's a big picture guy, a storyteller. He's a star. And only time will tell whether his future work will eclipse all the controversy he's found himself in. I'm rooting for Ariely, and I'm rooting for the integrity of the academic world. We have unfinished business, because I asked Dan Ariely to send me the name of the podcast with the man named Richard. Remember Richard, the man who called for his death? Hello. Hello. I never checked actually, if it was a public podcast or not. Um, so I don't, uh, I don't know. Um, but I will say the following I am, uh, you know, the way people are. Um, trying to push me and blame me and all of these things is causing me to be a little paranoid. A private podcast? What the heck is a private podcast? I hammered Ariely about this over and over again, asking for more clarification. He said that he checked with the Institutional Review Board, and they said that he was not allowed to reveal the name of the person he mentioned in the book, who he refers to as Richard. I'm supposed to keep their privacy. Like, there's lots of rules about, uh, what I need to do to keep their privacy. Next week, I will check with the people who are in charge about, uh, Uh, ethics for, for how to conduct research, I would ask them about, uh, what are the rules and what I can say and what I can't say and can I give, uh, anybody's, anybody's name and so on. I struggled with how to tell this story. After all, no crime was committed and there is no smoking gun. I'm not here to tarnish anyone's reputation. And like I said earlier, Dan Ariely and Francesca Gino put something out into the world and it is up to journalists to scrutinize their findings. And that's all this is. But there's definitely a different way of looking at this. We hyper focus only on a few of his studies, but Ariely has conducted hundreds if not thousands of experiments that haven't raised any eyebrows. He deserves his spot as one of the most intriguing behavioral scientists. There's no doubt that Dan Ariely is perfectly qualified in this space. But sometimes his observations bleed into the world of philosophy. While behavioral science focuses on empirical and often quantitative analysis of human behavior, philosophy deals with more abstract, often normative, questions about the world and our place within it. Both field, although very distinct, Contribute significantly to our understanding of human nature and the world. I'll let Dan Ariely have the last word. We all want to look at ourselves in the mirror and feel that we're good people. At the same time, we want to benefit from cheating. And maybe what we're doing is we're balancing these two goals. We cheat up to the level we would have to update our image of ourselves. So we cheat up to the level that we can still look at ourselves in the mirror and feel good about it. Again, you can find the uncut interviews of both of my calls with Dan Ariely on Pretend Plus, on Apple Podcasts, or on Patreon. I'd love to know what you think about this story, so leave a comment in Spotify, write me an email, put something on social media, or leave me a review. This episode was written by me, Javier Leyva, and edited by Poonance Chenoy with the Podcast Pundits. All right, that's it for this week. I'll talk to you very soon.