SPEAKER 1: No problem.
SPEAKER 2: You know, I actually feel a bit better now that we have this alarm system installed.
SPEAKER 3: You know what? Me too. I mean, it’s not like there’ve been a lot of break-ins in the neighborhood, but I like the peace of mind.
SPEAKER 2: Yeah, for sure.
SPEAKER 4: Day one.
SPEAKER 2: OK. I’m on my way. Can you set the alarm when you go?
SPEAKER 3: Yep, will do.
SPEAKER 3: Day two. … Day five.
SPEAKER 2: Sorry. Forgot to set the alarm.
SPEAKER 3: No problem. I’m sure it will be fine.
SPEAKER 4: Day 10.
SPEAKER 3: Did you set the alarm?
SPEAKER 2: No, didn’t you?
SPEAKER 4: Day 15. … Day 227.
SPEAKER 3: Hey, I’m home. What happened?
SPEAKER 2: They took everything. They took the TV. They took your laptop. The silverware’s gone.
SPEAKER 3: Oh God.
SPEAKER 2: I know.
SPEAKER 3: Oh God. I can’t believe it. Have you called the police?
SPEAKER 2: I’m calling them now.
SPEAKER 3: Did they take the hard drives? All our photos …
KATY MILKMAN: Hopefully, nothing like this has ever happened to you. But maybe you can relate. You buy a home alarm system or maybe a bike lock or a security camera, and you use it religiously for a while. But then, over time, your house doesn’t get broken into. Your bike doesn’t get stolen. Your packages don’t disappear from your porch. So you start to forget to set the alarm or lock the bike or turn on the camera. And there’s a reason we do this, and it has to do with the way we perceive risk. Risk around everything from saving your work on a computer to checking your phone while you’re driving to solo rock climbing.
I’m Dr. Katy Milkman, and this is Choiceology, an original podcast from Charles Schwab. It’s a show about the psychology and economics behind our decisions. We bring you true stories involving high stakes, make-or-break moments, and we explore the latest research and behavioral science to help you make better choices and avoid costly mistakes.
JEFF ELISON: And when I opened my eyes, I’m looking at the rope, just going straight to the ground with no backup knot.
KATY MILKMAN: That’s Jeff, describing a terrifying moment in his rock-climbing career. More on that in a bit.
JEFF ELISON: My name’s Jeff Elison. I’m a 61-year-old psychology professor teaching at Adams State University in Southern Colorado. I’ve been climbing for 45 years.
KATY MILKMAN: It’s safe to say that Jeff knows a thing or two about rock climbing.
JEFF ELISON: I combined psychology and climbing in a book that I co-authored, Vertical Mind.
KATY MILKMAN: His home, in Alamosa, Colorado, is a perfect spot for a climbing buff like Jeff, who pretty much loves everything about the sport.
JEFF ELISON: Being with great people, being out in the outdoors, beautiful settings. Most of the cliffs where we go to are in just really, really nice areas. And the mental and physical challenges, the mental challenges are unlimited. Sometimes there’s incredibly complex problem solving.
KATY MILKMAN: If you’re like me, the idea of scaling a rock cliff is terrifying. The risks involved in the sport are pretty apparent. Climbers may have to dodge tumbling rocks or can make mistakes like tying knots improperly. And of course, there’s the risk of falling, something Jeff wasn’t exactly comfortable with when he started climbing at the age of 16.
JEFF ELISON: It was part of what scared me or made me hesitate in climbing.
KATY MILK MAN: Now keep in mind, falls are generally controlled. Climbers are caught by their rope systems and climbing partners. An experienced climber like Jeff falls a lot.
JEFF ELISON: I fall hundreds of times a year.
KATY MILKMAN: So over years of experience, Jeff became quite accustomed to falling.
JEFF ELISON: So these falls are relatively safe.
KATY MILKMAN: The key word here is relatively.
JEFF ELISON: I think it was December 20th, 2018, and I just finished the semester. So I was excited to have some time off and the weather was amazing. We live at 7,500 feet in Southern Colorado where it’s incredibly dry and sunny. So the thermometer’s reading like 15 degrees. I figured by the time I got to the cliff, it would be upper twenties or low thirties, which is just perfect with the sun blasting these cliffs that are fairly dark.
KATY MILKMAN: Jeff’s usual climbing crew wasn’t available on this particular day, but he was determined to push towards his goal of climbing a hundred days that year. He was almost there. It would be his 94th day of climbing.
JEFF ELISON: I texted several different partners and none of them were available. So I started to consider this idea of rope soloing. And when I got the last, “No, I’m not available,” I decided, well, that’s what I’m going to do. It didn’t occur to me to go back and let any of those people know that I was going to go out rope soloing. And I failed to mention that to my wife as well.
KATY MILKMAN: Not ideal, but he planned to go to a familiar area, and he had done some solo climbing before, even if he did prefer climbing with friends. It was a beautiful day out. After a warmup climb near a town called Del Norte, Jeff drove to the second climbing location of the day, an area with challenging overhanging cliffs.
JEFF ELISON: An area called English Valley. It doesn’t have very many climbs, but it’s taller. I think most of the climbs there are about 75 feet. It’s quite a bit harder. Just beautiful morning, it was warming up. Gorgeous views of 13,000-, 14,000-foot peaks. It’s high desert, cactus all around.
KATY MILKMAN: He got to work setting up his top rope system. Jeff used something called a stick clip: a long, extendible pole that lifts his rope up ahead of him. He used the stick clip to attach the rope to the anchor, which was already installed.
JEFF ELISON: So what this means is that the rope is anchored at the top of the cliff. It could be on a tree or something like that. In this case, it’s on a pair of anchor bolts that are good for thousands of pounds of force. And then from the ground, you attach an auto-belay device. So an auto-belay device is kind of like a ratchet wrench. It slides up the rope, but if you pull down on it or if you fall, it’ll lock, supposedly. That’s the idea, anyway. And typically, people take extra safety precautions. Sometimes they’ll actually be attached to two separate strands of rope with two or more auto-belays. You can tie backup knots as you climb. So if the thing would not lock up, you would slide down the rope until you hit your backup knot and then hopefully that would stop you.
KATY MILKMAN: The recommended system for this type of climbing is at least two auto-locking belay devices. Jeff chose to set up one auto-locking device and tie a backup knot.
JEFF ELISON: I wasn’t going with the recommended system, only having one auto-locking device. Having a bunch of devices is inconvenient. It can interrupt the flow, it can make it just so much harder that the climb becomes impossible.
KATY MILKMAN: So he got going on his second climb of the day, one that was a bit less familiar. It also had a pretty tricky crux, what climbers refer to as the hardest sequence of climbing. The crux can range from just a few feet to a much longer section.
JEFF ELISON: I’d only done it about six times before. And I knew the crux was kind of tricky. I didn’t remember it exactly, but I knew the gist of what you needed to look for. But I couldn’t find the key foothold because it’s so small, like the size of a penny basically. And I thought maybe it’d broken off, so I just decided to go for it. And I fell. The auto-lock didn’t lock right away. I slipped maybe 12 or 18 inches and that got my attention. I thought, “Damn, that’s not supposed to happen. That’s disappointing.” And it got my heart racing a little bit. And maybe I should have called it a day right then, but I was stubborn. So I finished the climb without incident and came down and rested for a while.
KATY MILKMAN: Despite the scare that his system didn’t catch him right away, Jeff got back on the cliff for the final laps of the day.
JEFF ELISON: So rested a little bit and started up the next one, and I knew it really well. And I got about halfway up past the initial section to where there’s one rest and I could tie a backup knot. So, at that point, I’m reassessing thinking, “Well, I’m feeling kind of tired. Maybe I should just call it a day after I finish this one.” So I’m hanging by these two big handholds, but again, it’s overhanging. You can’t let go with both hands at the same time, so it was pretty strenuous. And looking out, trying to see how I’ve got the ropes rigged, like can I just finish one climb and pack up all my gear and get out of here? And I decided, yes, I can do that. And I just dropped my head for a second to close my eyes and relax just one more time. And when I opened my eyes, I’m looking at the rope, just going straight to the ground with no backup knot.
KATY MILKMAN: At this point, the ground is 35 feet below Jeff. Rope dangling between his legs, no backup knot in case the system were to fail, an essential step he forgot to do until that moment.
JEFF ELISON: And that kind of gave me a jolt of adrenaline. I thought, “Oh (beep), that would have been bad.” So I tied the backup knot, launch into the first hard section and just fell right off. And the rope caught right away, and I was fine. So I get back on and I climb the rest of the way and I was having trouble resting where I normally would. Think I laughed out loud at one point, like “Holy cow, I am wrecked. It’s time to go home.” And the final rest was only about seven feet from the anchor.
KATY MILKMAN: But he kept going, choosing to push through the challenging but familiar climb.
JEFF ELISON: I’ve done this a bunch of times. And it’s a tricky climb in that the intuitive thing to do is to grab the handholds, whatever it is, left hand, right hand, left hand, right hand, right hand. But that leaves you in a dead end. You can’t do the final move to the anchor. So there’s a trick. When you want to grab right-hand at one point, you’ve got to grab left-hand instead. I think I was just so focused on calling it a day that I let that slip my mind. And I climbed myself into a dead end, just two feet from the anchor. And I decided, well, it’s not good style, but I can pretty much just jump and grab the slings at the anchor. And I did that and my foot slipped, and that’s when I fell. I just expected that I would stop right away, and it didn’t catch. So I thought, “Oh (beep), it’s not caching again.” And after I slid, I don’t know, four or five feet, I realized, “Oh (beep), it’s really not catching.” Is it going to catch?
KATY MILKMAN: Jeff’s auto-belay device didn’t catch him.
JEFF ELISON: And then I grabbed the rope. Visually, all I can remember is just staring at my hands and the rope above me and the anchor receding away from me as I raced toward the ground. I had time to think that my skin’s burning up, this really hurts. Even the thought that this might be permanent damage to my tendons. And I thought, “I’m going to keep holding on. Maybe I’ll just shatter my legs.” And then, “I can’t believe it’s going to end this way,” meaning my life, of course. I just screamed, “No!” with this mixture of fear, anger, and denial. And then all of a sudden, boom! I come to this bouncing stop, and it took me a second. And I thought, I must have hit the backup knot. I quickly looked at the gear and said, “Yep, for sure. This is the backup knot. The auto-belay’s jammed into it. The knot is good. I’m not going to die today.”
KATY MILKMAN: As Jeff dangled midair, about 45 feet down from where he fell, he inspected his hands. They were shredded from gripping the rope as it raced through his palms. His skin was torn down to the muscle on some fingers, and others were just covered in massive blisters, and nobody was there to help him get back down to the ground or to provide first aid.
JEFF ELISON: This particular cliff is off a dirt spur road off a more major dirt road. Probably one or two cars per day drive that, maybe not even that in winter. So I couldn’t expect somebody to just to come by. There were no houses in sight. My cell phone was down in my pack on the ground. So I was going to have to get myself out of this situation, basically what we would call a self-rescue.
Because of the way I had rigged the ropes, there was a second strand of rope hanging fairly close to me. And I was just barely able to kick it with my toes and get it swinging. And I grabbed it and I pulled it over to myself and I tied a loop in that second strand of rope at about chest height and inverted, put my foot in it and then hauled myself up with my hands, which was quite painful. And because the rope stretched, I only gained about a foot. But at that point I was able to get some slack in the rope and inch the auto-belay device up, which then locked. So I gained one or two feet toward the anchor.
KATY MILKMAN: After 45 minutes of completing that painful process over a dozen times, Jeff got to the anchor so he could safely repel down the cliff and collect his gear along the way.
JEFF ELISON: Got to the ground. I’ve never been so happy to touch the ground as I was at that moment. And even though my hands were screaming, I pulled the ropes, packed the ropes, packed my backpack, and did the five-minute hike to my truck. Threw all my gear in there, just elated and drove back out.
KATY MILKMAN: The drive to a local medical center was nearly an hour long. The staff there took a look at his hands.
JEFF ELISON: So my hands were pretty black. They were also covered in gymnastics chalk that we use to keep our hands dry. And then there was the blood and ooze and everything. So it was pretty hard to tell what was going on.
KATY MILKMAN: The staff sent him to an emergency room, a short drive away.
JEFF ELISON: And I picked up my wife on the way from work. I called her and started the conversation with, “Honey, I’m absolutely 100% fine, but I did have a big fall and my hands are kind of torn up.” Tried to give her the good news first. They took a look at my hands, and they had me clean them further and soak them a bit. And where my finger had been sort of welded down, finally loosened up and I was able to straighten it. They bandaged me up. I just looked like I had mittens on. Couldn’t see anything on my hands. And my wife drove me home.
KATY MILKMAN: Thankfully, Jeff didn’t need surgery, and his injuries didn’t result in long-term damage. Reflecting on it, there’s a lot Jeff could have done differently to reduce the risks of climbing alone.
JEFF ELISON: I shouldn’t have been doing what I was doing there, maybe pushing as hard as I was or not resting more. But even the way I did the rope soloing, that’s not the recommended method. Sometimes people will have two strands of rope and four auto-belays and even a fifth and a sixth backup. So what I was doing was fairly sketchy and I had justified it in a number of ways. I’d done it before, it caught before, I was unlikely to fall, I’ve got a backup knot. So I justified doing something that was not at all recommended, was riskier than it should have been.
KATY MILKMAN: He’s not entirely sure why his device didn’t catch him that day, but it’s not a setup he plans to use again.
JEFF ELISON: And there’s still days where I don’t have a partner, and I haven’t climbed for three days, and it’s really tempting to go do that again. But I promised my wife I wouldn’t. I would never solo with a single auto device again. So I have learned a little bit over the years.
KATY MILKMAN: Jeff Elison is an avid rock climber and psychology professor at Adams State University. He’s also the co-author of Vertical Mind: Psychological Approaches for Optimal Rock Climbing. You can find a link to his book in the show notes and at schwab.com/podcast.
When Jeff began climbing as a teenager, he was very concerned about falling, even in a controlled setting. That initial fear was based on his perception of the risks involved in the sport, but not on his experience. But over time, and through experience, his fear diminished, perhaps a bit too much. Often, when a person has experienced situations involving a certain kind of risk and gotten by unscathed, they lean heavily on that, and they underestimate the likelihood that a rare bad outcome will arise in the future.
In this case, Jeff was climbing a familiar route, felt confident he wouldn’t fall, and underestimated the risk that his auto-locking belay device would fail. There are many ways to explain Jeff’s risky decision to climb alone and with only one auto-locking device. For example, overconfidence or an excessive desire to reach his round number goal of climbing on 100 days in 2018. But I want to focus on another feature of the way humans perceive risk that might help explain his decision. It’s called the description-experience gap in risky choice. My next guest, Professor Ido Erev, identified this behavioral phenomenon in research with his collaborator, Ralph Hertwig. Ido joined me from his home in Haifa, Israel.
Hi, Ido, thank you so much for doing this.
IDO EREV: Yeah, thanks. My pleasure.
KATY MILKMAN: Ido, the first thing I wanted to ask you about is if you could just explain the experience-description gap in risky choice, what is it exactly?
IDO EREV: Yes. When people face the new choice task and have to decide based on the description of this choice task, they often behave as if they exhibit high sensitivity to low-probability risk. However, when they gain experience, often they exhibit the opposite pattern and start behaving as if they believe that it won’t happen to me. For example, when I bought my first new car in the nineties, I was told that I can protect myself against a car burglary if I spend another $50 on a car radio with a detachable panel. And I thought, this is a good idea. I paid another $50, and I was happy with my choice. But after a week, I stopped detaching the panel. So initially, when I was told about the risk of radio burglary, I was really concerned and I decided to pay the money. But after a week, I started behaving as if it won’t happen to me, and I stopped detaching the panel.
KATY MILKMAN: That’s really interesting and reminds me of the way a lot of my friends, who live in the city where I live, talk about the fancy house alarms that they have installed that at the beginning, when they get it installed, it seems like a great idea, and there’s this risk someone will break in. And they alarm their house every time they leave, for like a week. And then after that, they’re like, “No one’s broken into my house. This isn’t going to happen.” So that’s really, really interesting.
IDO EREV: Exactly. I also have an alarm like that, too.
KATY MILKMAN: Right, a very-useful-for-one-week alarm.
IDO EREV: Right.
KATY MILKMAN: Could you describe some of your research showing that people make these different decisions when they face a described versus an experienced risk?
IDO EREV: Yeah. Our typical lab experiments include many trials. And in each trial, as a participant is asked to choose between a safe and a risky option. In one example, the safe option always is a status quo. Basically, if you select this option, and you are told, if you select it, you’re going to get a zero for sure. The other option is a risky prospect. In this particular example, it leads to a loss of 10 shekels, which is about $3, in 10% of the trials. And a gain of one shekel in the other trials. So in 90% of the time, it’s actually pay one shekel.
KATY MILKMAN: OK. So participants can choose a risky option involving a one-shekel gain with a probability of 90%, but a 10% chance of losing 10 shekels. They could also choose a risk-free status-quo option that involves no chance to earn money, but also no chance of losing any. And I seem to recall that they find out after each decision exactly what payoff they’ve earned so they can learn from experience.
IDO EREV: Exactly. Before they get feedback, in the very first trial, most subjects tend to avoid the risks. They don’t want the risk of losing 10, and they go for the status quo. But after one or two trials with feedback, most of them move and select the risky prospect. Importantly, this is happening even if, despite the fact that in this experiment and many other experiments, choosing the risky prospect actually leads to a loss on average, and they could go with the status quo and get zero, for sure.
KATY MILKMAN: Why is it that people are doing that? What do you think it is that’s driving people to have this different reaction to the described risk, initially, than to the experienced risk after they’ve gone through these trials?
IDO EREV: I think that people always try to select the option that led to the best outcome in similar situations in the past. This effort is effective because often what works in the past is likely to work now too but can lead to two biases. One bias that you might recall a past experience that only looks similar in fact are not similar to the current situation. This bias is particularly important when you make the first decision from description, because you are not sure—you are still not familiar with the new choice task—and you might over-generalize from other situations.
The second bias is because we tend to think about the most similar past experience, we’re going to rely on a small sample of past experience. And when you rely on small sample, then in most cases, you don’t think about the rare outcome, the low-probability outcome. For example, a few years ago, I received a high fine when I touched my smartphone while driving near my university gate. Now I tend to think if I want to touch my smartphone when I approach the gate, now I think again, I said, “Hey, this is dangerous.” But I only do that when I’m near this gate. And in other situations, I often do touch my smartphone screen. So this experience of getting this high fine affects my behavior, but only in similar situations, and most of the decisions probably are not similar to these rare cases because rare cases are rare.
KATY MILKMAN: That’s really interesting. Does the order in which people encounter a description of a risk versus having experience with a situation that involves risk matter at all?
IDO EREV: Well, when subjects get both description and experience—and we have run many experiments of that sort—the impact of experience is much stronger than the impact of description. So, in a typical experience, when you give a subject a description, and now they make several decisions, in the first decision, they are sensitive to the description. The second decision, they’re also sensitive a little bit. But by the third decision, they are more likely to behave as if they are underweighting a rare event than overweighting a rare event.
KATY MILKMAN: Amazing that people only need to have a couple of experiences with taking a risk and having a good outcome before they get quite comfortable taking that risk again. So we very quickly moved to sort of forming some kind of statistical model in our heads with data that was described to forming one with our experience.
IDO EREV: Yeah. One explanation for that is that we have so much experience in real life with descriptions that are inaccurate. So, when you hear a description, if this is all the information you have, then you consider it. But after you get experiences, basically we feel that we can do better by relying on our personal experience than on that description that may be incorrect.
KATY MILKMAN: That’s fascinating. I have spent a lot of time in the last year, I’ll admit, thinking about how your research relates to the behavior we’re observing in the current COVID-19 pandemic. And I was curious if you could talk a little bit about that. And specifically, my sense is that people, back in March of 2020, when this threat was primarily one, if you’re living outside of China, that people were hearing about described but hadn’t yet really experienced, that people made pretty cautious decisions, obviously with some exceptions. But then later in the pandemic, after many months of experience with its risks, we saw people behaving differently. And I’m curious if you feel like that’s related to your work in the way that I’ve perceived it to be.
IDO EREV: Yes. Yes. I absolutely agree. And I think that the description-experience gap had contributed and still contributing to the spread of COVID-19. Specifically, the fact that policymakers thought that if they will just warn people and tell them about, I heard in the news about the old men dying in the street in China, that people will be panicked and will be very, very careful. And in fact, many people were careful. Policymakers in the West thought that will be enough to warn people about the risks, and then things will be OK. So I also plan to be careful. For example, when I just heard the news, and people were asked to stay at home, I told my mother, who is now 93, I told her that she should not leave home, and I will go shopping for her and will leave her the products outside her door. And then we talked by phone. So I did it one week. And then in the second week, my mother says, “I just heard in the news it’s only dangerous for people over 80. I’m over 90—maybe we can talk.”
Then we said “Well, we’ll sit outside.” We sit outside first week with a mask. Second week she said, “I don’t hear you well with a mask.” So we take off the masks, and then it was raining, and then we move inside. So I think I’m not the only one who initially planned to be very careful but is less careful now. I think that as this difficulty that I presented suggests that it’s not enough to describe the risk to people, but it is necessary to enforce socially responsible behavior. And the interesting question is, how do you enforce socially responsible behavior? Of course, you can use the Chinese way, which is, as you know, extremely effective, but it’s less likely to be successful in the West because privacy is more important than other things.
KATY MILKMAN: We just talked a bit about the pandemic. I’m curious because there are so many walks of life where we face risks that are initially described and then experienced. I’m curious if there’s other examples that you think are important to policymakers or that you’ve observed over your career where you think this particular bias looms large?
IDO EREV: Yeah. Well, the short summary of all this research that if policymaker wants people to do the socially desirable behavior, it’s not enough just that this behavior will be beneficial on average. It also has to be beneficial most of the time, because if people rely on small sample, then if you get prize for doing the right thing with small probability, most of the time, you will not think about the prize. And if you get punishment with small probability, you will not think about the punishment most of the time. We have to make sure that the socially desirable thing is beneficial on average. This is a good first step, but it’s not enough. We also want to make sure that the socially desirable behavior is better most of the time, because if people rely on small samples, they are highly sensitive to the most frequent experience.
KATY MILKMAN: It’s really interesting, and it suggests when we have policies like giving speeding tickets or giving tickets for texting and driving, or fining people if they aren’t wearing their mask, that you don’t want a really large fine with low probability; you want a small fine with high probability. Is that a reasonable way to think about it?
IDO EREV: Exactly.
KATY MILKMAN: My last question is just a really practical one. I’m wondering how you would advise our listeners to try to make better decisions in their own lives, in the face of risk, now that they’re familiar with this work you’ve done?
IDO EREV: Well, I think the most important thing I think is in designing your career. So basically, it’s a good thing, and I’m thinking about it when I talk with my daughters, that it’s important to have longshot goals, if you’re waking up in the morning. But when you think about different career paths to reach your goals, it’s a good idea to take paths that will be fun in most days, to reduce the risk that you’ll give up too early. So if you have some longshot goal that in order to do that, you’re going to suffer most day until you reach there, there is high probability you give up too early.
For example, think about young people who want to start a startup firm, or start working for a startup firm. So my idea that this is a good idea only if you think the startup in theory can help create a better world and make you rich. So this is a very nice goal that you should pursue. But you will only do it, and your probability of success is really dependent if every day that you come to work, you enjoy it. And also that you will learn something new every day, or most days, that will help you even if the startup firm is unsuccessful. So the idea, you want to have a longshot goal, a nice goal, but you also want to make sure that in most days, you’re having fun because otherwise you might give up too early.
KATY MILKMAN: I love the lesson, and it’s wonderful because we did an episode with Ayelet Fishbach and Dan Ariely last year where we focused on the importance of making it fun because of people’s tendency to overweight immediate rewards, relative to distant goals. And I love how this all ties back together with the experience-description gap in risky choice. So that’s a wonderful final lesson. And thank you so much for spending time with us today. Really, really appreciate it. This was just fascinating. I learned so much.
IDO EREV: Thank you. It was fun.
KATY MILKMAN: Ido Erev is a psychologist, professor, and vice dean of the MBA program at the Technion–Israel Institute of Technology. You can find links to his work in the show notes and at schwab.com/podcast.
It’s one thing to have the risks of trading stocks described to you. But as we’ve learned, that often isn’t effective. Experience matters more. But even then, if you don’t experience the occasional losing investment, you can lose sight of the risk inherent in trading. A recent episode of the Financial Decoder podcast—called “How Can You Manage Your Emotions While Trading?”—discusses those risks, including techniques that can mitigate them and help keep emotional biases from undermining your trading plan. Have a listen at schwab.com/financialdecoder or wherever you get your podcasts.
Remember how Ido Erev talked about buying a detachable car radio because he worried that his radio would be stolen and wanted to be able to take it with him whenever he parked? And how over time, he grew less inclined to go through the hassle of actually detaching the radio and taking it with him. Well, eventually, his radio was stolen—not once, but twice. Back in the day, radios were easily removable from cars. People would buy them with detachable face plates to render them useless to thieves. Fortunately, car companies now mostly produce vehicles with sound systems that can’t be removed. Consumers don’t have to worry about their radios being stolen or have to deal with lugging them around when they park their cars.
You may remember from a past episode of Choiceology that making the best choice the easiest choice—making it the default—often leads to better outcomes. That strategy also works well for limiting the impact of the description-experience gap in risky choice. Let me give you another example where setting a default can help mitigate risk. Maybe you can think of a time when you were working on a school paper or a project for work. Initially, you might’ve been very careful to regularly save your work because you perceived the risk of the software crashing or computer freezing to be high. Then, after working away without incident for many hours, you saved less frequently.
And then the worst happened—say, a power outage—and you lost hours of work. This is why many software applications now save your work by default, rather than waiting for you to manually save. And while Ido talked about the fact that people underweight rare risks when making decisions from experience, his research shows that people also underweight rare opportunities. There are many situations where people start working to achieve a certain goal, but if the experience they have early on as they pursue the goal is difficult, they may give up too quickly. Ido points to the value of making goal pursuit fun, the topic of another Choiceology episode, to ensure that the day-to-day experience is positive enough that you won’t give up too early and miss out on a rare but valuable opportunity.
You’ve been listening to Choiceology, an original podcast from Charles Schwab. If you’ve enjoyed the show, we’d be really grateful. If you’d leave us a review on Apple Podcasts. It helps other people find the show. You can also subscribe for free in your favorite podcasting app. And if you want more of the kinds of insights we bring you on Choiceology about how to improve your decisions, you can pre-order my forthcoming book, How to Change: The Science of Getting from Where You Are to Where You Want to Be, or sign up for my monthly newsletter, Milkman Delivers, at katymilkman.com/newsletter.
Next time, you’ll hear how spies use memory techniques to avoid detection, and I’ll speak with two of my friends and collaborators, Todd Rogers and Angela Duckworth, about the issue of forgetting and the importance of timing when it comes to reminders. I’m Dr. Katy Milkman. Talk to you soon.
SPEAKER 8: For important disclosures, see the show notes or visit schwab.com/podcast.
