The Winner’s Curse: Why Smart People Lose Their Way | Alex Imas – EP 716

Coming up next on Passionstruck. Don't succumb to the sunk cost fallacy. So the sunk cost fallacy is this idea that I've already done something, I've already gone down this path. I might as well keep going even though it's looking like a bad decision. Don't succumb to that sunk cost fallacy. Always take a moment, think, is the next step, if I hadn't gone into this decision to begin with, if I hadn't paid money to invest in the stock, if I hadn't taken that one class on that topic, would I still do that next thing? If the answer is no, stop, do something else. Just this is one of the most important things that behavioral science has taught us. Welcome to Passionstruck. I'm your host, John Miles. This is the show where we explore the art of human flourishing and what it truly means to live like it matters. Each week, I sit down with change makers, craters, scientists, and everyday heroes to decode the human experience and uncover the tools that help us lead with meaning, heal what hurts, and pursue the fullest expression of who we're capable of becoming. Whether you're designing your future, developing as a leader, or seeking deeper alignment in your life, this show is your invitation to grow with purpose and act with intention. Because the secret to a life of deep purpose connection and impact is choosing to live like you matter. Hey friends, and welcome back to episode 716 of Passionstruck. We're continuing our series, The Meaningmakers, where we're examining how meaning is formed, protected, and sometimes distorted in modern life. In our last episode on Tuesday with Dr. Steven Slumman, we explored how beliefs form and how certainty, when left unexamined, can quietly narrow our thinking and distort our sense of meaning. Today, we take the next step, because even when our beliefs feel solid, the real test of meaning shows up in the choices we make under pressure. My guest today is Alex Emus. Alex is a behavioral scientist and professor whose work examines how people make decisions in competitive high stakes environments. Especially when the desire to win quietly distorts judgment and obscures cost. He is the author of The Winner's Curse, written with Nobel laureate Richard Thaler. Our conversation centers on a powerful idea known as The Winner's Curse, a phenomenon where people win by overpaying, over committing, or overreaching, only to discover later that the victory itself carried structural costs that they never intended to accept. What makes this so relevant to meaning is this. Many lives aren't misaligned because of failure. They're misaligned because of success achieved inside distorted environments. In this episode, we explore why capable people make systematically costly decisions, how our environment shape choices more than intentions, why competition amplifies overconfidence and risk, and how recognizing the winner's curse can help us build success that actually holds. Before we dive in, a quick note on a project that mirrors these themes of inherent worth. My new children's book, You Matter Luma, is a bridge to that truth, a reminder that your significance isn't earned by your performance. It's a fact of your existence. You can pre-order it now at Barnes & Noble or YouMatterLuma.com. If this episode resonates, please share it with someone navigating a similar season. And if you haven't yet a five-star rating review on Apple Podcast or Spotify, helps these conversations reach the people who need them most. You can catch the full visual experience on our YouTube channels, Passionstruck Clips and John R. Miles. Now let's continue the meaning makers with Alex Emus. Thank you for choosing Passionstruck and choosing me to be your hosting guide on your journey to creating an intentional life. Now, let that journey begin. I am absolutely thrilled today to welcome Alex Emus to Passionstruck. Welcome, Alex, how are you today? I'm doing great, John. Thank you. I'm so excited to have you on the show. For the listeners, if you don't know who Alex is, he's earned the Sloan Research Fellowship, multiple rising scholar awards, and is widely published. Alex, what first drew you to studying decision making? Was there a formative moment that made you question why people act so differently from what theory predicts? I was drawn to decision making very early on in college. Actually, the first time I was drawn to it was from the perspective of abnormal psychology. So I was drawn to decision making, like thinking about cases when things really go wrong. So schizophrenia, bipolar disorder. And I've always just been fascinated by the different ways that people make decisions. You get into your own head assuming that everybody acts the way that you do. And as I met more people, made more friends, I realized, wow, people, so many people think so differently than I do. And I was just fascinated by that. All of these different perspectives, all of these different minds going out there and making decisions. While I was taking abnormal psychology and psychiatry courses, I was also taking economics courses. And I was an economics major in a pre-med program. And in economics, I was struck by the assumptions in economics were basically the opposite of that, was that everybody thinks exactly the same. And everybody might have different preferences, but the basic idea that everybody has correct beliefs, everybody maximizes a utility function, you might care more about risk than I do, or you might like apples or oranges more than I do. But for the most part, people are very similar. And when you get to the macro models, people are like literally the same. These are like representative agent models. So I was just struck by the fact that, wow, my classes about real human people are very different than the economic classes that I'm taking at the same time. And I was just very fascinated by that fact and wanted to figure out how I can bridge those two things together. And that's how I found behavioral economics and dove right in once I discovered it. Well, a lot of what I talked to people about on the show is the power of our choices. And I remember doing an interview a number of years ago with Michelle Seeger from Michigan, and we were talking about the power of micro choices. And I understand you study how people mentally represent choices. What does it actually mean to represent a decision in the mind? A mental representation is essentially what you think you're facing. So let's say you decide to open up a bank account. So what does that mean? You look at the amount of money that your deposit will grow by you look at the minimum deposit, you look at fees, all of these sorts of things. And then you make a decision whether to go with that bank or a different bank. A mental representation is basically how do I take all of those different features and how do I represent them in my mind? So some people, for example, completely ignore overdraft fees, like they don't even consider them. That's not in their representation of the decision that they're facing. And so when you're choosing to buy a stock or not buying a stock, when you're forming a portfolio, when you're thinking about a job to get. So one classic kind of example is like people from Michigan versus people from California were asked people about to go to college, where do you think they'll be happier? And their mental representation was all about the weather. The majority of their decision was where's the weather better? And when California was a lot better in Michigan, people thought, wow, people in California must be so much happier. And turns out if you actually measure people's happiness, it's not there's not much of a difference between the two places. What were people missing? Well, when you move to California, there's something called traffic. There's something called all of the inconveniences that come from living in Los Angeles. And that's just not in people's representations of that decision. And when it's not in the representation, you don't take it into account and make wrong forecasts, you make the wrong decision and potentially make some mistakes if you're missing something in your representation. Thank you for sharing that. Such a fascinating body of work and something I'm extremely interested in. As is the topic of risk. And I understand that you've researched and written a lot about dynamic inconsistency, which is really gets into the handling of how risk diverges from actions in real time. And I understand there's a gap that can emerge. How does that gap relate to this dynamic inconsistency? Dynamic inconsistency is a very general property that basically means, look, I plan to do one thing and I don't do it. It's the idea that I have a goal. I want to work out. I want to lose weight. I want to get healthy. And then you say, all right, in order to do that, I need to go to the gym. I need to have a good diet. And these are the types of things I need to do. And then you make a plan, you write it down, you do whatever you need to do. You buy a gym membership. You make a nice little plan for yourself to meet the goal. And then when the time arrives to actually do that thing, you don't do it. You do something else. In the case of risk, what my research has shown is that when people start taking on risk, they essentially really like these kind of low probability, high win gambles. So like when I'm thinking about forming a portfolio or buying some stocks, I have a plan for how I'm going to hold those stocks. Essentially, what my plan is, look, if the price goes up, I'm going to hold on to it. If it goes down, I'm going to sell it right away. That plan generates risk that kind of looks like a lottery because the downside's eliminated. But the upside is like essentially infinity or not infinity, but a very large number. So that's what people plan to do. What do they actually do? Turns out they do the exact opposite of that. When the stock goes up or their portfolio goes up, they're like, oh man, I just made some money. Let me cash that in and buy something or buy something else. Whereas when they start losing, what do they do? They think, oh man, I'm in the hole. I got to get out of it. I better hold on to it. I better put even more money into it. They double down. They chase their losses. So basically, what does their portfolio look like? What does their ownership look like? The opposite of what they intended to do. Well, one of the things that really interests me is taking this whole idea of decision making and looking at it now in the world that we live in where digital technology and AI has become so pervasive. What new behavioral patterns or biases are you seeing as humans are adapting to machines? Or it could be our algorithms are adapting to our irrationalities depending on how you look at it. I don't think there's any new psychology out there. The past 10 years, 15 years has not been long enough for us to develop any new biases or psychology. What we're seeing is a lot of the biases erupt on steroids. So we're seeing people double down and risk a lot of money on the fact that now the casino, they don't need to drive to it. It's on their phone. So we're seeing a huge explosion of bankruptcy cases all over the states, all over the world. Like online sports gambling has been legalized all over the America. It's also been legalized in places like Brazil. Brazil, the government is now dealing with the fact that something like 25 or 30% of people's welfare assistance is being spent on sports gambling and things like that and getting people into debt and getting them into bankruptcy. And basically, people are losing all of their money. So that's just one example where access to digital technology where firms are very well aware of the biases that people have because they have full control over the information and the environment that people are in when they're making decisions. They could construct these algorithms in a way that really exploits these biases on a scale we haven't seen before. What do you think the next evolution of that is going to be? We've already seen it being used to disrupt political races. We're seeing used warfare tactics. We're seeing it used by influencers. Where do you see this going? We're at a crossroads where there's one path where artificial intelligence can really be a force for good. This is a similar crossroads we had with information technology in the late 90s where you had access to the library of Alexandria times 100. All of the information in the world at your fingertips. Theoretically, we could be in a utopia right now where everybody knows their biases and heuristics and they have all of the information in the world to solve them. They have governments and firms that create apps for them to make better decisions. They're saving money for retirement, all of these sorts of things. We could have been, that is a world. That's not the world we ended up with. The reason we didn't end up in that world is because there's a lot more money to be made by exploiting biases than to solving them. We're at a similar crossroads right now with AI. We have a situation where you can have artificial intelligence basically act as an agent for you, act as a decision aid for you on a scale that we've never been able to reach before because these are completely personalized. Things that know your biases, know your heuristics and can really help you make better decisions. On the other hand, we could have AI just basically allow firms to engage in first degree price discrimination, which is basically all of the consumer surplus we get, we learn that we get in econ 101 because firms can't engage in first price in discrimination. Now firms can be as they, through these AI machine learning algorithms, they have all of the data on every single individual to allow them to target them with specific prices. We can get into that world too. We can see the emergence of first degree price discrimination that on a scale we've never seen before. We can have an emergence of misinformation, of people not really knowing what's real out there, or we can have something quite different where AI actually helps solve all of these problems. So obviously with all the changes that are hitting us, this is a completely different world in behavioral economics just as it is in every other dimension of our lives. So I thought it was pretty interesting that a winner's curse came about. I understand it over 30 years ago, but you have co-authored a new update to it with Nobel laureate Richard Thaler. How did that collaboration come about? And what did you learn stepping into the world of a foundational thinker as both colleague and co-author? So I've known Richard for a while when I was a graduate school. My office ended up being right next to his because he did his winters in San Diego, and that's where I got my PhD. And we started talking pretty early. And then my first job was a Carnegie Mellon. We kept talking throughout that process. And at some point, he called me up and said, why don't you come out and give a talk at University of Chicago? I ended up with a job at University of Chicago. Sometime in the first year at University of Chicago, he called me and said, hey, I got a project. Would you be interested in thinking about it? And it was basically the original winner's curse, which was basically the anomalies columns that he had been writing about each individual behavioral economics phenomenon, basically taking all of those columns that he had written up to 92, stapling them together and giving them, making them into a book. And it happened to have gone out of print and the publisher asked him if he wanted to do an update. I jumped at the opportunity. It's not every day you get to work with a Nobel laureate. He's a Bikero of mine and we're friends. So I thought it was going to be a lot of fun. It ended up not being an update as those things traditionally are done. About two thirds of the book is brand new. Essentially, what we ended up deciding to do was to take those original anomalies columns and use them as like a foundation for each chapter and then rewriting them to some extent for the modern audience. And then for each chapter that covers a specific topic in behavioral economics, there's an update that looks at all of the research that's happened in over 30 years in that space. So that those updates essentially catch the reader up to what's been happening in behavioral economics since 1992, which includes new topics and kind of new areas that behavioral economics has gone into. And it is interesting over that 30-year period how many of these theories used to be questioned at first and now you can spout them off and they're widely accepted, although I still don't see a lot of them being placed in modern textbooks, which is something that we need to fix. But I'm interested. I've heard a lot about Richard Taylor, haven't had a chance to meet him. Here, he's very humorous, but I'm wondering, what's the most powerful piece of wisdom or advice he's given you? Probably the most powerful piece of advice is in terms of my day-to-day life that I use is to not worry or argue, particularly argue, about things that probably aren't going to happen. So he calls that don't argue over off-equilibrium paths, which is an econ way of saying, look, if you and your wife are arguing about something, what kind of house you're going to get when you move to Stanford, California, think about, are you going to move to Stanford, California, to begin with? And the chances of that are fairly low. So just don't have that argument, say, let's table that. It turns out like a lot of the kind of conflicts and anxiety that I particularly have and many others do too, are about things that counterfactuals, low probability events, things that are probably not going to happen. And thinking through, am I worried about something? What is it? What is the probability of that thing actually happening? And if it's really low, just think about something else, argue about some, well, try not to argue about, but if you have to argue about something that's probably going to happen. And that piece of advice, I actually reference it all the time, particularly in my interpersonal life and how I go about my day. I understand behavior economics began as a rebel field, as I alluded to earlier. But I understand when the book was first written, a lot of the experiments that were done at that point in time were in the classroom or in the lab. And I know one of the big evolutions, especially now through the work that Katie Milfin and Angela Duckworth are doing with behavior change for good, is we're now able to start doing a lot more field research and with their evolution, a lot more mega studies around this. How has that shaped where the field is going? Do you feel? That's mostly what the updates are focused on is the fact that precisely, as you said, the original behavioral economics studies, and that was the pushback, was that they were done with college students at low stakes, sometimes hypothetical, not even like really consequential decisions. And economists were basically like, hey, that's cool, fun study, but we don't really care about college students who don't know what they're doing. We care about stock market professionals. We care about professional athletes. We care about CEOs of companies. And we just don't think they're going to make these mistakes. Nice study, but we don't care. And for the last 30 years, the field has moved into, as you said, the field. It's real, it's studies with real professionals, large studies, field experiments, observational data sets, showing that the types of things that we studied with these college students, they show up with CEOs of major Fortune 500 companies with people with real money on the line making decision after decision. Before we continue, I want to pause on something important. Listening to a conversation about decision making under pressure is one thing. Noticing how those forces shape your own choices is quite another. That tension between momentum and discernment is exactly what this conversation with Alexemus is about. Meaning isn't shaped only by what we choose, it's shaped by what we continue. That's why each episode in this series is paired with reflection tools inside my substack, the ignited life, not to tell you what to do, but to help you see structure more clearly. Asking questions like, where might I be honoring momentum without reassessing cost? What environments are shaping my choices more than my values? And what would it look like to choose sustainability over escalation? You can join us at theignitedlife.net. Now a quick break from our sponsors. Thank you for supporting those who support the show. You're listening to Passionstruck on the Passionstruck Network. Now back to my conversation with Alexemus. It's really interesting. I first started to get immersed in this in the mid-2000s and I was working as an executive at Lowe's at the time and I was in charge of all the data across the company and we spent a lot of time looking at the supply chain, obviously, but even more time looking at customer patterns and interactions. And so we were hiring a team of data scientists and behavioral scientists to help us understand how do we modernize the supply chain ecosystem and get people to work more efficiently. But more importantly, we were looking at how do you engage with the consumer in what we were trying to do as a total closed loop? So as they were using different channels to interact with Lowe's, whether it be online, the call center, in the store, etc. How do you make it feel to them like it's one channel and not separate distinct channels? And that's evolved today for them into my Lowe's and other things. But it's really fascinating to me how much it is now powering so much of commerce that's done around the world. Can you talk about that a little bit more? I think with behavioral economics and behavioral science, I think what many people's perceptions are missing is the amount of behavioral economics and science that's been going on in the private sector. A lot of the focus has been on governments, it's been on public sector initiatives, but the private sector has really been doing behavioral economics before behavioral economics was even a field. Companies like Lowe's, as you mentioned, are doing a lot of behavioral economics in terms of thinking about improving the customer experience. I had worked with PNC briefly at some point, thinking about designing my wallet, which is like their platform for getting people to have all of the information that they would want about their bank account in one spot, eliminating these sorts of barriers for the consumer experience. Again, when you're thinking about kind of the standard model of economics, these things shouldn't really matter. The fact that you have to click a couple of times to get information about the amount that you have on loan versus the amount that you have in your cash or savings account, these sorts of things are so cheap that people should be able to do it and you don't need to create a separate platform for it. But the fact of the matter is because people have bounded rationality, it really matters that they have everything in front of them in an easily digestible way. This goes back into the idea of mental representation. If I have my loan in one spot of the website or the platform, if I have my savings account in a different platform, all of these things are earning different interest rates. I have a credit card open. So what a lot of people do, for example, when they don't have these things at the same time, they have a high interest rate balance on their credit card while at the same time holding enough money in their bank to pay off the credit card. So essentially, they're losing money on the interest rate, paying these high interest rates, well, where they could just completely pay off their credit card and not have to deal with that at all. But the fact is because they don't have all of that information given to them at the same time on some platforms, many people are doing that. And I think a lot of companies are really trying to incorporate behavioral economics to make these sorts of consumer experiences a lot better. Alex, thanks for going into that. I wanted to go back to the book and I wanted to start with the basic idea itself. What is the winner's curse and how does it show up in our daily lives? The winner's curse is best demonstrated in a little experiment that you can do yourself. If you want to make some easy money and you have a free evening, get a jar, fill it with some coins and go to the pub or something like that and say, look, everybody in the room bid on this jar of coins and the winner gets the money. You don't have to take the coins, I'll then mow you the money. And what you're going to see time after time, and I know this because we've run these experiments in class all the time, the person who actually ends up winning will pay more for the jar that's in the jar. So you're going to be able to earn some money from this. So why does that happen? Essentially, when you look at the jar, everybody looks at the jar, people get a different estimate of how much is in the jar. So some people think, let's say there's 15 bucks, some people say it's 18 bucks, sometimes we'll say 12, 9, 8, people are all over the place, they don't know how much money is in there. But who's going to end up winning? The person who wins the jar is going to be the person who's most optimistic, who's most wrong in the positive direction. And that's the winner's curse. It's the idea that the person who's winning is actually going to be losing money because they're wrong in the positive direction. And that's the demonstration of the winner's curse. And that's partly why it happens. But the first time that when it was documented in the 70s, it wasn't with a jar of coins, it was oil executives scratching their head about the fact that, look, we got these expensive engineers looking at oil wells thinking how much oil is going to be in these wells. And every time we actually win a bid at an oil well, we end up having less oil in there than we thought we did. And we keep losing money, what's going on. And they publish these papers in trade journals, calling it the winner's curse by basically saying, look, something is wrong every single time we end up winning, we end up actually losing what's going on. And folks like Richard Thaler, Max Bazerman, and other people delved into it and started to understand the psychology behind the phenomenon. Yeah, man, it's so interesting. I spent the early part of my career working as a practice leader at Arthur Anderson. I was in the Houston market. And I still remember sitting in this room at Exxon Mobile with hundreds of executives across the industry hearing an economist come and talk to us saying that we had reached the peak of big oil. And from this point in history going forward, there was going to be a demise every single year. Boy, was he wrong with the evolution of how we do fracking and other things. But science finds a way. Yes, exactly. But it reminds me of markets and how modern markets change, which is something that you guys covered in the book. And you did it through social contagion and the persistence of overconfidence in modern markets by examining Reddit and Robin Hood. And I was hoping you could give the audience a little bit bigger take of what I'm talking about here. With Robin Hood and the proliferation of these online communities, essentially, so this has a bit more to do with the stock market and these like meme stock phenomenon. There's obviously many more implications, but the meme stock phenomenon is a great example. We've had bubbles in the past. And in the past, then going back to the 1600s, we've had bubbles. And it's this idea that people over, there's this herd mentality where people think like, maybe this is overvalued, but everybody else is bidding on it. If I don't bid in on it, I'm going to miss out on all this money to be made. So I'm going to bid on it too. And the price goes through the roof. And then one day somebody wakes up and says, hey, this is a bubble, I'm getting out. And this starts that whole downstream cycle where everybody ends up losing money, except for that one person who got out in time. And this idea behind bubbles is now, again, super charged when you have these digital spaces, like the combination between Reddit, for example, and Robin Hood. What does that combination look like in practice? The GameStop situation is a very nice example, because it allows people to coordinate their decisions very in a fundamentally different way. They can say in the wall, there's a sub Reddit called Wall Street Bets. What Wall Street Bets allows you people to do is to say, look, we're going to all hold on to this. And actually, they have this their own language to talk about the fact that everybody is going to be holding on to these sorts of stocks. So they buy the stocks. And without Reddit, you don't really know who else is going to sell because nobody's coordinating, everybody's sitting independently in their house. With Reddit, you have the ability for people to coordinate to say like diamond hands. What that means is that everybody's committing on holding. And what that means is that bubble can go on for a much longer time than what we've seen before. Because what we've seen before is these things like are bubbling up and they explode, bubbling up and explode. With GameStop, you look at the price now and it's actually it hasn't crashed. It went down certainly from the peak, but it's still up there because people are coordinating to hold their shares saying, look, we're going to keep this going. And the ability for people to coordinate on buying these things very easily through Robinhood and the combination of being able to publicly coordinate and communicate on these forums has led to a very different financial market for retail traders than say what we had even 10 years ago. Yeah, that was just shocking when that happened a few years ago to see how a community platform like that drove such a huge market change. It was fascinating and scary at the same time. I'm not sure your thoughts about it, but I still remember that and just being in complete awe about what happened. There's two different models of financial markets out there. There's a model of kind of efficient markets where the price of a stock is the discounted future cash flow of that company. That's the standard rational model. The people are saying like, look, this is the price that this stock is worth because that's how much it's going to be paying out through dividends and all sorts of other things to me. And that's how much I'm willing to pay for. This is the fully rational model. The other one is by John Maynard Keynes, who was this giant economist in the 20s and 30s, and he called the stock market a beauty contest. What does he mean by that? Back in the day, you had these newspaper contests where there was a whole page of different faces, let's say usually was women's faces. And the winner of the contest was the one who picked the face that everybody else picked. So not the one he preferred, the one that everybody else picked. So this gets into this idea of theory of mind, where my decisions are based on what I think everybody else is thinking. And that's a fundamentally different model of the stock market where now I don't care how much cash flow GameStop has. I don't care how much cash flow AMC has. I am buying GameStop because I think other people are going to buy GameStop, and that's it. And therefore, because of that, these online forums have this huge power of coordinating this behavior, because now I can say, look, I know that GameStop is going to pop because a lot of people are saying GameStop is going to pop. And now you have AMC and Coles and all of these other different completely random companies popping just because of this phenomenon. Yeah, man, it is so interesting. Yeah, well, I wanted to ask you about some of the classics, and I thought we could start with loss aversion. We've long believed loss has heard about twice as much as equivalent gains please us. Does this still hold true in the hyperstimulated digital environment, or our attention to motion? Do you find changing that ratio? That's a great question. We don't have a lot of data on this, first of all. So you're thinking like, what is the loss aversion crypto or something like that? Right, exactly. Or like just a completely digital asset. I don't think anybody I know has collected data on this, but this is quite an interesting question. What are the implications for all behavioral economics when you have physical goods such as a house, a mug, other sorts of products? What are the implications of those of behavioral economics in that space for a world where a lot of stuff is just going to be digital completely, isn't going to have a physical presence in the world? If I was to hypothesize and based on some of my own data, where I've run endowment effect experiments with digital art. And essentially, I found that things are largely unchanged. If I tell you that you are the owner of an art piece versus I ask you, how much are you willing to pay for that art piece? Your valuations change just from me telling you you own it. The minimum that you now be willing to accept a part with it increases by two and a half times relative to five seconds ago before I told you that. And this is like the end for your audience. This is the NFTs, non fungible tokens, which are now used to allow digital creators to have some ownership over their art. So the endowment effect doesn't seem to really weaken when you go into the digital space, at least in that sense. Okay, well, another one I wanted to go into was the fairness anchoring effect. And so I guess the way I want to frame this is fairness and norms. So there are a lot of modern pricing debates that people get into about rejecting deals that we see online and feeling that they're unfair, even when they cost us money, etc. What does this say about the role of fairness and sustaining social trust? In my view, fairness and norms are key for sustaining cooperation. Again, many experiments is the fact that if you have a game, so it helps to go through an example of this sort of game. So the public goods game is a really nice way of studying these things. What it means is that let's say me and you and maybe two or three other people are playing this game. And the game is fairly simple. Me and you have an amount that we're given. So like that's an earned down and let's say it's two bucks, each of us has two bucks. And then we decide how much of the two bucks to contribute to the quote unquote public good. Whatever we contribute gets added up, multiplied by some amount, and then divided evenly between all of us. What that means is that even those who didn't contribute anything would still get a piece of the public good. What does that mean for economic? What does economic theory say about this? Well, if I get something without contributing anything, guess what I'm going to do? I'm going to contribute nothing. And then guess what happens? Nobody contributes anything. So the economic theory is a very strict prediction of what happens in public goods games. What actually happens in reality? Well, people contribute something. They contribute 20, 30, 40 percent of their endowment, especially in the first period. They contribute something gets divided. Everybody gets something. But as the game continues, especially in the very final round, those contributions go to zero. In the final round, people think, well, everybody else is contributing something. You know what? What if I just don't contribute anything and I'll still get paid? Guess what? Everybody else is thinking the same thing and then nobody contributes and nobody gets anything other than their endowment. So basically the overall pie shrinks as the game progresses. So the real innovation happened in 1999, 2000 with Ernst Faire and Simon Gochter ran a game of the public goods game, but they introduced one little extra thing, which has to do with fairness and norms. What they did is that after every single round of the public goods game, everybody has the opportunity to spend a little bit of their own money to take away a larger amount from somebody else. What does this actually mean in practice? It allows people to punish those who don't contribute. If people feel like, whoa, this was unfair, I contributed something, but you didn't. I can now punish you, hurt you, add a cost to myself. Again, economic theory, very simple prediction. Why the HELL would I spend money to punish somebody else? I wouldn't. So the economic theory predicts no contributions, no punishment. What ended up happening in this game? People felt like non-contributors were acting unfairly and they were more than willing to punish them. And what did that do to the game? It meant that people who were thinking maybe I won't contribute, now they got worried about getting punished. So they contributed. So contributions went up almost all the way. And not only did they go up in the beginning, they stayed high through the entire game, even in the last round, because even in the last round, if I don't contribute, I'm still going to get punished. So I'm going to contribute. So adding this element of fairness, of punishing norms, allowed cooperation to flourish in this setting without the ability to punish people who violate norms. Cooperation just completely went to crap and by the final round, there was none of it left. Well, and now I wanted to talk about one of the things that Richard Thaler is most famous for, which is his work on nudges, which he did with Cass Sunstein, who's been on this program. And what I wanted to revisit this in its ethical dimension, and you've been discussing a little bit about this in the past couple of answers, but we started this episode talking about choice and the research that you've done around how to make better choices. But there's this tension between helping people to make better choices versus manipulating their autonomy. And so you've explored this dual use quality of throughout the book. And what did you find that's most meaningful about the research? So the whole nudge program was started by a paper called Libertarian Perturnalism. And the idea there was to say, look, standard economics defines a choice set in a particular way. And behavioral economics says that we can choices can change without affecting people's ability to make decisions. So what does that mean? So let's go to the 401k example. So the 401k example, the classic opt in opt out study. So before Bridget, Madrian and Sheppard, had this landmark study in the late 1990s. Essentially, what did that look like? People chose to opt in into a retirement plan, and most people didn't. What they did instead is to say, hey, instead of people choosing to opt in, let's make the default that they are in the plan. And if they want to, they can opt out. So all it is that instead of checking the top thing, the bottom thing is checked. Standard economists doesn't matter, right? It's the choice that is exactly the same. I'm deciding whether opt in or opt out. Turned out this raised opt in rates through the roof, many more people ended up being enrolled. Right. So this is the behavioral economics part. This is a classic nudge. You don't change the actual choice environment. People are free to make the same decisions as before, but they're making different decisions because you're introducing this seemingly irrelevant factor, which is what Richard calls it into the mix, what people are defaulted in. The ethicality behind it depends on who you ask, frankly. When you're getting into ethics, this is a normative field, so different people have different opinions. Now you're in the world. You're not in the data world. You're in the opinion world. Right. And there is a group of people who view nudges as perfectly ethical. Other people disagree with that statement. They think that your behavioral economics should be part of the coercion. People can have disagreements about this. I think with something as important as an retirement savings, you have to start thinking about the costs and benefits to people when they're reaching retirement, then they're thinking, wow, I forgot to opt in into my 401K plan. I really wish I did. If only somebody had nudged me to contribute to my 401K, I would have ended up with more money for my retirement. In other cases, in the case of organ donations or something like that, Richard and Cass have work in this space saying, look, we should give people full autonomy and nudges don't really belong in that space. So it really depends on the context and it depends on the argument. Yeah. I also wanted, since we're on this topic, to explore Amazon and Amazon crime sales, because I understand Amazon uses nudges as well as anyone does. How should a listener think about this when it comes to the psychological triggers that happen when Amazon is doing like a prime day? Yeah. So I think we talked about this in the beginning of the conversation. Companies have been doing these behavioral science, behavioral economic experiments since they started. So Amazon is literally doing thousands of VB tests on how a prime day advertisement, how it should look, where it should look, to who would, and then you have different versions and those two different versions are given to different people depending on their buying habits. The optimization of behavioral science in order to get people to purchase is just, it's done to a very, very huge extent by these companies. Now, I haven't looked at specific things that particularly Amazon has done, but certainly there's research in behavioral science showing that something like making shipping free, for example, or doing expedited shipping for a lower amount on a specific day really gets people to purchase because they're thinking, wow, their loss of versions is getting activated there that they feel like they're going to be losing less money. This is something that they really want. They want this thing faster. This is the whole self-control, myopia thing being taken advantage of. Now I get to have this thing, which maybe I don't need at all, but hey, I get it faster. I'm going to buy it. That's to say that they're doing a lot of different things all at the same time and they're making these cocktails of behavioral science in order to get people to purchase. The firms have been doing this since the beginning of capitalism. It's just now it's on a completely different scale. We've talked about the digital world a few times now. I want to think about digital biases. Specifically, digital biases is the standpoint of authoring and I think of substack. I think in general, I'm finding that people are underreporting their use of AI tools because of something you explore in the book, which is social desirability bias. But to me, if someone asks you if you're using AI to help with your writing and someone answers, no, it's almost unbelievable to me because if you're using a Google search or literally any technology that's out there, all of it is underpinned by different AI frameworks. So arbitrarily, you are using it in almost any research that you're doing. But what do you think it reveals about how humans perceive technology's role in their competence or their creativity? I think so. I have a paper about this on AI and social desirability bias. So we run a study in at the large university asking students about their AI use. And when you ask them, how much do you use AI ever? The answer is like 63%. And you might think, wow, that's low. Most students, I think, are using AI. And it turns out if you ask a slightly different question, and this is using techniques from psychology in order to overcome social desirability bias, you ask not whether you use AI, you ask whether your friends use AI. Now social desirability bias isn't really affected because it's not me, you're asking about my friends and guess that number is 95%. So that gap between 95% and 60 something percent, that is the gap that people are misreporting their AI use. Essentially, and we've collected other data to confirm that the gap that it's under reporting versus over reporting in one condition versus the other. So this is something that that's going to be a challenge for companies for policymakers, especially for educators. So this is a space that I'm very interested in from both a personal perspective, I'm a teacher, but also from a policy perspective in terms of like, how do we think about university or higher ed in the age of AI? Obviously, we can't say never use AI become a ludite. But also we want people to use AI in a way that helps them to learn something. So they retain some information, but they also learn how to use these tools in an effective way that's going to help them when they exit the university. And that kind of cause benefit is something that's that conversation is happening right now, but it needs to happen faster. Yeah, I can't remember if I was talking to Bobby Parmar or Judd Kessler, but one of them was telling me in their class that I've understood that the papers that they're getting back are progressively getting better and better because it's obvious students are using AI to help them write them. But what I wish I remembered which one told me this, but what they were doing in their class was taking it to another level. So they were making them come in front of the class to show the application of what they researched to make sure that they were retaining what they were writing about. And they were telling me that it really showed a huge difference between who was actually retaining and using the information versus who was just using the AI tools because I know I find myself when I'm using them a lot. I'm not retaining as much about the work that I'm doing as compared to when I'm doing a whole bunch of research and then having to write it on my own. There's great research about this. Sherri Malamud, who's Judd's colleague at Warton shows that if you do research through AI versus just Googling it, so you have access to Google, which also uses AI, but in a different way versus LLMs, to help you research a topic, you just simply retain more information. Even though you're reading the same information, when you search for it yourself and parse through it, the way that our brain works is to retain the information between the pauses. So like when you're reading a book versus you get the spark notes from a book, right? Why did we discourage spark notes? Like in 30 years ago, 20 years ago when I was in school, the information is the same, but the process of reading the book, the text and pausing, flipping back and forth, all of that is part of learning, but it's discounted because it doesn't seem like that's not where the information is. And that process is really, there's, we need to be very explicit about what actual learning looks like in order for the broader population to understand that AI is an incredible technology. But reading Winner's Curse by saying what is in the Winner's Curse, give me a two paragraph summary versus actually reading the book, you're going to retain something very different. Yeah, absolutely. Well, Alex, if listeners could take two or three practical tools from this conversation to improve their own decision making, where would you tell them to start? Don't succumb to the sunk cost fallacy. So the sunk cost fallacy is this idea that I've already done something, I've already gone down this path. I might as well keep going, even though it's looking like a bad decision. Don't succumb to that sunk cost fallacy. Always take a moment, think, is the next step, if I hadn't gone into this decision to begin with, if I hadn't paid money to invest in the stock, if I hadn't taken those, that one class and that topic, would I still do that next thing? If the answer is no, stop, do something else. Just this is one of the most important things that behavioral science has taught us. I think the first thing that I said, don't worry about things that have very little probabilities of happening. Don't argue about those things. I think that's a very good lesson too. I use it all the time in my own life. The other thing that I've done research on and that's in the book is take time to deliberate. Fast decisions are not necessarily good decisions. System two thinking. System two thinking. And people know this, but it doesn't work into their everyday lives. A lot of states have cooling off periods before they can get a divorce. There's a reason for that. There's cooling off reasons before you can get purchase a firearm in many states. There's a reason for that. The reason is that we know that decisions are better if we think harder, we cool off, the emotions wear off, and we can consider all of the options. It's actually very easy to incorporate that lesson into your everyday life in terms of stopping and thinking while you're making important or semi-important decisions. Alex, I always love to ask this question. What does it mean to you to live a passion-struck life? I think I'm extremely lucky to be doing what I'm doing because I've stumbled into a field where I feel passion-struck and just passionate every single day, literally every single day, because there's just so much out there to explore and to learn about. And for me, living a passion-struck life is to keep my mind open, to read, to say yes all the time, instead of saying no. If I don't think I have time to do something and it sounds new and potentially exciting, just make the time and do it. That's really, and taking risks has led me to be quite interested and excited and passionate in my everyday life in terms of what I do every single day for work, as well as for fun. And lastly, Alex, where is the best place listeners can learn more about you? I'm active on X or Twitter, however you want to call it. So I have a Alex Seamus on that platform. And my website is alexseamus.com. And if you guys want to check out the book, it's got a very active website, winnerscurse.org. It's got a lot of these materials, it's got slides that take these sorts of concepts and break it down. It's got replication materials for the experiments if you want to learn how to run them by yourself. So that's another place. Awesome. Well, Alex, it was such an honor to have you. Thank you for joining us on Passion Struggle. Thank you so much, John. Thank you. That brings a close to today's conversation with Alex Seamus. What stayed with me the most is how quietly the Winners Curse operates, not just in markets or negotiations, but in live shape by escalation comparison and environments that reward winning without revealing cost. Alex showed us that good decision making isn't about intelligence or restraint. It's about clearly seeing inside the systems we're operating in. Meaning isn't about accumulating wins. It's about choosing what can be sustained without distortion. And that brings us to what's next in the Meaning Makers series. In my upcoming episode next week, I'm joined by Shanna Pearson, where we'll explore how Meaning is cultivated not through optimization or acceleration, but through presence, embodiment, and the discipline of slowing down. If Alex helped us see the hidden cost of winning, Shanna will help us explore what it looks like to live from alignment rather than escalation. It bothers me when people refer to ADHD as a superpower. It really does, because there's nothing about ADHD that makes life easier. And it's difficult to manage ADHD on so many levels, like in your relationships, career, personal health, name it. And so when people are like, oh, this is superpower, you should be able to do like all of these things so much, you've got this and you don't. And you know that life is really hard. And you know that you're struggling and you know you're working 100 times harder than every single human and longer than anyone. There's no superpower. And so then you just feel like there's something else that's wrong with you, because you can't even use your superpower. You don't even know where it is. Like, where's the superpower part of this? Before you move on with your date, I'd invite you to pause and ask, where in my life might momentum be substituting for discernment? If you want support applying these ideas, you can join me inside my substack at theignitedlife.net, where each episode in the series is paired with reflection tools designed to help you integrate insight into how you actually live. As we continue the meaning makers, remember, significance isn't built by winning at all costs. It's built by choosing what truly holds. I'm John Miles. You've been Passionstruck. Until next time.