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Did You Realize You Were Playing Tennis on Mars? with Dr. Robin Hogarth

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In this episode we bring on one of the father's of decision psychology to discuss several fascinating takeaways about how to make better decisions with our guest Robin Hogarth.

Robin Miles Hogarth is a British-American psychologist, author, and emeritus professor in the Department of Economics and Business at Universitat Pompeu Fabra in Barcelona, Spain. He has served as president of both the Society for Judgment and Decision Making and the European Association for Decision Making. He’s written several books around learning, judgement, and decision-making. His most recent work is a New York Times bestseller, The Myth of Experience: Why We Learn the Wrong Lessons, and Ways to Correct Them.

  • Wicked vs Kind Domains

  • Why are people confident in their judgements when their judgements are really bad?

    • Feedback is one of the BIGGEST Causes

  • The way feedback arrived depended on the structure of the environment

  • Under what conditions is an intuition GOOD? What conditions is an intuition BAD?

    • Intuition is learned experienced.

    • Experiences are learned in your environment

  • Kind environments

    • Learning to play tennis

    • Chess

    • Quick, regular feedback

  • Wicked environment

    • Long, delayed, or wrong feedback

  • Why do we fall prey to the illusion that our feedback is good when it's not?

    • A lot of our physical activities have very good, quick feedback.

  • How do you start to realize that you're in a wicked environment?

  • You have to become an intuitive scientist to understand the world around you.

  • The way that we're typically trained to think is to come up with a conclusion and immediately jump to it, we believe and then we don't look for discomfiting evidence quickly enough.

  • We're all a little bit lazy in the sense that we want to go with the first idea that we come up with.

  • If you don't take control over the situation you're in, your situations become essentially random and the outcome is random.

  • Are you in control of your decisions?

  • Do you like cricket or baseball? Your environment massively shapes your

  • How do we apply deliberate practice to fields like business, investing, etc with huge gaps between the decision and outcome?

    • Find substitute feedback or other sources of imitative feedback.

    • Keep your emotions under control

    • Break the decision down into parts and understand each component

    • Use tools like decision journals and decision audits

    • "The Future Perfect Method" - Ask:

      • What would have to happen for you to succeed? (in 3-5years)

        • Explain why the outcome was good, looking back from 5 years in the future.

      • What would have to happen for you to fail? (in 3-5years)

        • Explain why the outcome was good, looking back from 5 years in the future.

        • Similar to Gary Kliens PreMortem

  • One of the things you learn from poker is to appreciate better the effects chance has on outcomes

  • Intuition is a sense or prediction where you come up with something quickly that seems very quick to you.

  • What is the "Myth of Experience?"

    • We are built to learn from experience.

      • Observe, experience, learn.

  • "Experience can't handle changes." Things can get very dangerous when things are similar, but different, and we don't see the differences.

  • The "prevention/cure" problem and how we attempt to solve it.

    • Provide more recognition of the power of prevention.

    • Study things like the travel industry or airline industry that have done a really good job on having a culture oriented towards prevention

  • Homework: Recognize the situations you're in. Learn basic mental models. Develop 4 or 5 key mental models that can help you better understand the world.

  • Ask yourself: Why are meteorologists good why o many people aren't so good?

    • Quality feedback

    • Good causal models of the situation

    • Meteorologist makes a prediction, but the prediction does NOT affect the weather.

      • We often make predictions that DO impact the outcome, and that is a very important concept to understand.

Thank you so much for listening!

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Episode Transcript

[00:00:04] ANNOUNCER: Welcome to the Science of Success; the number one evidence-based growth podcast on the Internet, bringing the world’s top experts right to you. Introducing your hosts, Matt Bodnar and Austin Fable.

[00:00:17] MB: Welcome to the Science of Success, the number one evidence-based growth podcast on the Internet with more than 5 million downloads and listeners in over a 100 countries.

In this episode, we bring on one of the fathers of decision-making psychology, Robin Hogarth, to discuss several fascinating takeaways about how to make better decisions. I'm not going to lie to you, Robin is an OG of decision-making science. Seriously. He's an old guy. He doesn't have a professional recording setup. He doesn't have a podcast studio in his house, and so the audio quality may not be the top-tier standard, but the content was so good that I really felt you should listen to this episode.

Are you a fan of the show and have you been enjoying the content that we put together for you? If you have, I would love it if you signed up for our e-mail list. We have some amazing content on there, along with a really great free course that we put a ton of time into called How to Create Time for What Matters Most In Your Life. If that sounds exciting and interesting and you want a bunch of other free goodies and giveaways along with that, just go to successpodcast.com. You can sign up right on the homepage. That’s successpodcast.com. Or if you’re on your phone right now, all you have to do is text the word smarter, that’s S-M-A-R-T-E-R to the number 44-222.

In our previous episode, we brought on private equity expert, Perry Anderson and shared some incredible insights around the inside baseball of buying companies with no capital.

Now, for our interview with Robin.

[00:01:54] MB: Robin Miles Hogarth is a British-American psychologist, author and emeritus professor in the Department of Economics and Business, at the, I'm going to mispronounce this, Universitat Pompeu Fabra in Barcelona, Spain. He serves as the president of both the Society of Judgment and Decision-Making and the European Association for Decision-Making. He's written several books around learning, judgment and decision-making.

His most recent work is the New York Times bestseller The Myth of Experience: Why We Learn the Wrong Lessons and Ways to Correct Them.

Robin, welcome to the Science of Success.

[00:02:26] RH: Hi. Thank you.

[00:02:28] MB: Well, it's an honor to have you on the show. I've been a fan of your work for a long, long time. Decision-making is a topic that's very near and dear to my heart. All the work that you've done around decision-making has been really transformational to the field. Thank you for that and thank you for coming on.

[00:02:46] RH: Well, thank you for having me on here. You have a wonderful podcast already, so I hope I can keep it up.

[00:02:52] MB: Excellent. Well, I'd love to jump right into to the meat of things and talk about one of the themes that from your work, I found to be tremendously both impactful, and also, really not only misunderstood, just not understood at all by most people, which is the concept of wicked versus kind domains and how that impacts our behavior. I love to start with maybe a high-level perspective on that and then dig into the weeds a little bit.

[00:03:19] RH: The idea came from work done over 40 years ago, like Hillel Einhorn and myself. We wrote a paper, which we try to understand why are people confidence and the judgments are very bad. We used mathematical models, but we try to look and see, what caused this? One of the things we can’t do was it was feedback. The way feedback arrived, depended on the structure of the environment. Therefore, we had to understand the role of feedback. That model just basically said, “Look, there are situations in which people will make bad decisions, because the feedback again, is inadequate.”

I started thinking about this for a long time, because I didn't really write out about it, until 2001, about 25 years later on. There, the idea was that I was trying to ask that intuition. Under what conditions is an intuition good, or is an intuition bad? Well, first thing I'm interested and realized is that intuitions are mainly learned experiences. They are reactions that you've learned from experience. Therefore, if you want to figure out when it used to be bad, then through that, which environment which was quiet, what was the factors designed when it was quiet? Is it a good one in time, in which it was acquired?

This gives us the notion that you can characterize the environment in which you learn things, on a range from which it is very difficult, very, very, very hard to learning, to kind. That was the origin of all that.

[00:04:46] MB: It's such a profound insight, this idea that the environment and the structure of the environment that you're in, has a very important relationship to the feedback you receive, which then impacts your own decision calculus. Give me a couple examples of what you would consider the kinder domains and what you would consider the more wicked domains.

[00:05:08] RH: Well, example of the kind environment would be learning to play tennis. Learning to play tennis, basically, everything you do, you need a feedback from. Hitting the ball goes, it goes into the net. Hit the ball, it doesn't go into the net. It goes out. It goes out, it goes in, comes back, and so on and so forth. You got complete immediate feedback on what's going on. That's what I'm calling kind environment, where basically, you're getting quick and very good feedback.

A wicked environment is an environment where the feedback is long, delayed, missing, or perhaps, even wrong. A classic example of that is emergency rooms in hospitals. The emergency room physician usually has a very short time in making a decision. A patient comes in and has to be sent somewhere else. What happens in most hospitals is that the physicians don't actually get to see what happened to the patients. The feedback is long, delayed and could even be inaccurate.

[00:06:02] MB: Yeah, that makes total sense. I'm sure, you would characterize something like chess as another skill set that is very tight feedback loops. Very defined and clear parameters, where it's essentially a very kind learning environment.

[00:06:17] RH: Yes. Chess can be a kind learning environment. Kind doesn't mean that you're going to be the best chess player. It means that it characterizes environment. Tennis is also a good example, because you can also imagine a tennis player on the planet Mars, were the rules are different, where the biology and geography works differently. In which case, you use the same rules in Mars, you have problems.

[00:06:38] MB: Yeah. That makes total sense. Dig into that a little more, the analogy that you previously used in a lot of your work around this concept of in many wicked domains, it's as if we're playing Martian tennis.

[00:06:49] RH: Yes, exactly, exactly. It’s an interesting example of why that's so important. It's a wonderful, [inaudible 00:06:56] had a fantastic bicycle he wants to make. He called it backwards brain bicycle. It is a bicycle. He inverted the way the wheels worked. He said, when you turn left, you went right, and when you went right, you turn left. It was inverted. He gave his bicycle to people and asked them to learn to ride. People had a great, great difficulty in learning to ride it. They couldn't. It’s basically, they couldn't overcome this. He made it working for them, and they couldn't do it. Then, he also tried it himself. He worked and he worked and he worked and he worked and he worked and he worked. Eventually, he learned to ride the bicycle backwards, but he couldn't ride a bicycle normally anymore.

[00:07:35] MB: It's very fascinating. Such an important thing to really think about, this notion that a lot of field and really, most fields, in my opinion, that we really work in whether it's things like business, things like investing, as you said, emergency rooms, health care, most of the things we interact with in our daily lives, if we're not professional tennis players, or people that are focused on maybe even something poker, which is probably more on the kind side, though, has a few elements of wickedness. Most of the world, the feedback loops are long, they're murky, they could be wrong. I guess, the first question would be why do we fall prey to thinking that our feedback is good when it's often not?

[00:08:15] RH: Well, I think a lot of the things you do every day, you get good feedback from. For example, walking through a room, you get feedback from objects. You don’t hit them. Think of driving a car, you're getting feedback constantly when we get driving a car. You make immediate adjustments. A lot of our physical activities get very good, quick feedback. Just to get things to translate to our minds. It was frequently in our minds, we were actually making exact judgments. We're just living again, trough the moment. With that rough feedback, it doesn't teach us what's going wrong.

[00:08:53] MB: That makes total sense. One of the most dangerous parts about being in a wicked environment is that we often don't know that we're in one.

[00:09:02] RH: Exactly.

[00:09:03] MB: How do we start to recognize when we are in wicked environments? What happens when we don't?

[00:09:10] RH: Well, I think there's no substitute for hard work. People have to think about the environment they're in, ask themselves, what feedback they’re getting. Are there any other things that are in the way? Is the feedback accurate? Are they able to adjust to it, and so on and so forth? I think, in some sense, what one has to do is essentially, become an intuitive scientist. In the book, and we here, we talk about intuitive scientists. Intuitive, skeptical scientists. People who basically, when they see an outcome, don't even accept what is the question and actually, come up with other ideas about it. A lot of the time, well, this is the biggest problem of all is to get a self-awareness of when the environment might be bad. I'm not saying that to use you.

[00:09:53] MB: No, that makes sense. I want to come back to the self-awareness piece and how we can cultivate that better, but A little bit more before we do that about this concept of the intuitive scientists, or the intuitive skeptic. How do you start to train those muscles? What does that look like to you?

[00:10:11] RH: Well, the notion that pre-camp was the following. The way we are trained to think, or learn to think is immediately to come up with a conclusion, and run with a conclusion. It's very quick. We don't have an initiative to stop, look for a certain evidence, or certain other hypothesis. Basically, we're a bit too believing. We're not skeptical enough. The point we're making in the book is that you have to adopt a skeptical attitude towards your inferential life. If you're good at that, and then you can meet a scientist who actually generates alternative hypothesis and is able to find ways of testing them.

[00:10:50] MB: In essence, it's very important to instead of jumping to conclusions quickly, or just immediately leaning in on the first thing we think about, really spend some time stepping back, looking for both sides, looking for disconfirming evidence and things that may overturn a conclusion before you really lock in on it, and start to believe that it's true.

[00:11:12] RH: I think, we're all a little bit lazy, in the sense that we want to go with the first idea we come up with. Very often, the first idea you come up with is going to start, and you need to go to a few more ideas before you come up with something that’s better.

[00:11:26] MB: What happens when we don't have the right feedback mechanisms, and whether it's emergency rooms, or other examples? Give me a sense of some of the consequences if we don't take this idea really seriously, and start to understand when we are treading in a more wicked domain?

[00:11:45] RH: Basically, if you don't take control over the situation you're in, your decisions become essentially, random. Basically, you're no longer in control of what's going on. The outcome is random. You want to live in a world like that, where basically, the world is on the control thing else outside of your control. I think, the issue of control is very important.

[00:12:05] MB: Tell me a little bit more about that.

[00:12:08] RH: Well, are you in control of your decisions? Or are your decision just a function of the environment you happen to be? I’ll give you an example. Think of somebody who has grown up in the United States. Compare that with somebody who's grown up in UK, and ask them which sports they like. American is going to say baseball, say, and the English one is going to say, cricket. Now, there's no right answer. Why do I say that? It’s because of the environment they’ve been exposed to. They didn’t have a choice right at the beginning of their lives, because they aren’t getting, prefer a cricket or baseball. Basically, they grew up in environments where basically, they have to in their sport start turning. I mean, control is, are you in fact, in control of the decision you've taken? Or is it your decision actually made for you by the environment?

[00:12:56] MB: Yeah. That makes total sense. That's a great analogy. You could say the same thing about American football, or European football, or as we would call it, soccer. That framework really applies much more broadly to in most cases, if we really take a hard look at ourselves, our ideological principles, our political beliefs, our religious affiliations. I mean, all of those things are essentially programmed into us by our environment with very little conscious decision-making, or control on our part.

[00:13:25] RH: By our experiences. Yeah. Our tastes are formed by our experiences. We have to be aware of that. In baseball and in cricket, it may not be very important. For others, I think, it could be quite important.

[00:13:38] MB: Absolutely. The more we tread into some wicked domains, the more important it gets to really understand where our footing is. One of the things that I've always really struggled with, or thought about, or a fundamental question that I've played with in my mind for a long time is this notion of how do we apply the principles, the concept of deliberate practice, which I'm sure you're familiar with, in really wicked fields, where there aren't great feedback loops? Things like business, or management, or investing, how do we start to think about applying some of the tools or principles of deliberate practice? How do we level-up our own decision-making in those areas where we don't have access to quality feedback?

[00:14:26] RH: Well, we have access to quality feedback. One is see what you can do to get to substitute feedback. Can you get a better causal idea what's going on? Can you be more accurate in thinking about how much randomness is affecting your decisions? I think, humans have a great difficulty in estimating how much decisions, actually – outcomes, and then just some chance. I think, able to ask yourself the question, am I in a situation where there comes into the job by chance, or do I have more control over them?

[00:14:58] MB: Dance with Chance, which was one of your work that you had many years ago was one of the early books I read when I was in, I think, college, around this idea of probabilistic thinking, and how to understand that. The notion that you just touched on, which is another principle that is often misunderstood, is really, how much randomness truly governs huge swaths of our lives, despite the fact that we often think things are under our control.

[00:15:27] RH: Yeah. Taking the famous regression towards the mean. There’s a story of Sports Illustrated. The Sports Illustrated story is that people who get on the cover of Sports Illustrated are doing somewhat – don’t do some more of this. In fact, what's happened is, the people who go on the cameras have been selected when they're at the peak of their lifetime performances.

Therefore, it's not surprising [inaudible 00:15:50] the same time around. People want to attribute causal reasons all the time, where in fact, there may not be causal reasons that don't drive the situation, but just random events. We have great difficulty in accepting random events. Earlier, we talked a little bit about poker, poker players, things we may learn from poker is to appreciate better the effects, chance on outcomes. The problem is, though, in most of the real-world decisions, the world is not as neatly defined as in program.

[00:16:24] MB: Sadly.

[00:16:26] RH: Therefore, it's harder to understand exactly how much randomness have played a role.

[00:16:35] MB: Yeah. One of the most helpful mental models that has helped me conceptualize that more effectively is looking at any outcome essentially, as two dice rolls. One on the chance dice and one on the skill dice, right? Different activities, maybe one of those dice is more weighted, or has more numbers or whatever. In chess, the chance dice is almost nothing and the skill dice is the only dice that matters. In poker, maybe the chance dice is 70% of the outcome, or whatever. That idea that really, in most things in life, there's a component of randomness, and there's a component of skill, or ability, or causation. Trying to blend those two things into your understanding can be a really impactful way to conceptualize that.

[00:17:21] RH: I think, people want to do launch skill. They want a reward based on skill. Another sport, which has a big chance element in it is golf. We tend to think of golf as being a skill game. It is a skill game. Over four rounds of golf and tournaments are decided by one or two shots, one or two shots going into hole, it's quite a random event. People may lose a tournament, because somebody else got a hole in one, or a hole in two, just by sheer chance. The way it's not. It's not written of as if by chance.

[00:17:52] MB: That's right. A corollary of that is this notion that if you have two people whose skill is identical, whether it's on the low-end, the high-end, then really, the determining factor at that point is largely chance.

[00:18:07] RH: Exactly, exactly.

[00:18:09] MB: Which is another thing that is both non-intuitive and hard to grasp, if you haven't –

[00:18:15] RH: Well, it's hard to grasp. It's hard to rationalize to oneself. These outcomes, I think, turn by chance. For example, we just finished the weekend watching this PGA golf championship, won by Phil Mickelson. A lot of made up, about 15-years-old and etc., etc., etc. At the same time, he didn't win that much. Yet, there are also shots of his that went into the hole from the bunker. That again, would be almost impossible.

[00:18:44] MB: Yeah, that's a really good way to characterize that. Coming back to something asked a minute ago, with this idea of in fields with murky, or disjointed feedback loops, one of the concepts you recommended to improve our ability to learn from our experiences was to find substitute feedback, or feedback that imitates, or gets us some more information about decision quality. Tell me a little bit more about that idea and how we might be able to do that.

[00:19:14] RH: You're asking about decision quality. Well, there's nothing you can do, except be old-fashioned, and look at the way you're making the decision. Breaking it down into parts, keeping your emotions under control, and the list of things like that. I don't have a formula. I can just suggest you follow a procedure.

[00:19:34] MB: That makes sense. This notion of breaking our decision-making down, trying to analyze it, trying to pull emotion out of it. Really, a tool that I'm a big fan of is using something, like a decision journal to map out ahead of time. I think X is going to happen. Here's why. Here's what I think the risks are and here's my emotional state and so forth. Then revisiting that with some frequency in the future, to see really, how the decision played out, and what you foresaw, what you didn't and try to ascertain why.

[00:20:07] RH: One can do it decision on it, which is useful. Another thing I think is very important to think about is whether you can actually, when you're making a decision, think about what would have to happen if it were to be successful? What would have happened if you failed? One way of doing this, perhaps, is to use a little bit of what I call future perfect thinking. That is to ask yourself, imagine that decisions have been taken, the outcomes occurred as you're already five years in the future. Imagine that the outcome was good. Explain how the outcome was good, why the outcome was good.

Then another scenario. You do the same thing again, but this time, the outcome was bad. Explain why the outcome was bad. Use hindsight to explain why the outcome was bad in a future perfect sense, and so on, so forth. If you do this thing, I think, you get a lot of insight into what could go right and what could go wrong.

[00:21:02] MB: I love that example. Using tools of thought like that are very powerful ways.

[00:21:09] RH: Yeah. I call it the future perfect method.

[00:21:11] MB: The future perfect method. I like that.

[00:21:13] RH: Yeah. Other people have – [Inaudible 00:21:15], I think, I came up with what he called pre-mortem.

[00:21:18] MB: Yup. That's right. Very similar.

[00:21:21] RH: Very similar idea. I think, it's very powerful.

[00:21:25] MB: Earlier, you touched on this notion of how intuition is formed, and how our experiences shape our intuition. Tell me a little bit more about what intuition is, and why we often misunderstand, or don't understand what really goes into the creation of it.

[00:21:45] RH: Intuition is, roughly speaking, a sense of something about to happen, or a prediction you're making, where you're able to come up with an answer quickly, and it seems to be correct to you, as a sense of something happening. I give you an example of an intuition. A few years ago, I went out with my family, and we came back late to the house. As we walked into the house, I noticed that all of a sudden, that there were some lights on in the house that we normally don’t had on. I suddenly had a thought, an intuition that somebody had been in the house. It turned out to be correct. There was actually a burglar.

That was as an example of an intrusion. Basically, I didn't ask myself what was going on. I just saw the lights and the thought, “Wow, there’s somebody else in the house.” Then we found out – we haven’t found the burglar. Actually, had been through it. It was bad. Intuition is a thought that comes up. I don't know why I had that thought. Well, I guess what happened was, I was able to recognize very quickly, something different here. Because of that, I was able to come to a certain [inaudible 00:22:48] and a conclusion. Now, that’s one kind of intuition.

Other kinds of intuitions could be, I had a colleague once who was interviewing a job candidate. The job candidate was terrific. He had all kinds of fantastic records of things he'd done, etc., etc., etc. There were my colleagues interviewing, there was a something he couldn't quite understand. He was saying, there’s something missing. He was aware that he could not put his finger on it. He had an intuition that this candidate had some problem. Question is what do you do with that intuition?

Well, what he did was actually very smart. He went to the meeting where they were going to discuss the candidates. After he went and talked about this candidate, how good he was, he said, “Well, I had this funny feeling about this person.” It turned out, other colleagues had the same view. They were able to have a deeper conversation about all facets of causes of the funny feeling and whether the candidate was good or not. I haven't given you a sharp definition of intuition, because I don't think there's a sharp definition. We recognize it as having, come to a conclusion with that very quickly, and without having a secret at heart.

[00:23:56] MB: That's a great way to phrase it.

[00:23:56] RH: Anything we have all the confidence in it.

[00:23:58] MB: That brings me to the other side of the coin in some sense of intuition, but also, more broadly, how we can we can learn the wrong things from our experiences. Tell me a little bit about the concept of the myth of experience.

[00:24:13] RH: Well, the whole notion is we are built to learn from experience. From early childhood, we learn from experience. We observe. We experience. We learn. If we're living in an environment in which we are getting good feedback in a kind environment, basically, we're going to learn. The problem is that the environment that we are in may not be kind to us. They may be false information. They may be missing information. Maybe irrelevant information. If we don't take account of those missing information, we will make mistakes.

[00:24:51] MB: Tell me a little bit more about some of the ways that our experience can mislead us.

[00:24:57] RH: Well, experience can mislead us, if it takes us down the wrong road track. If we wanted to choose, and say, we want to choose between two alternatives, and the data we got from our experience gives us the wrong choice. I'm not explaining that very well. I'm sorry.

[00:25:12] MB: That's a good way to look at it. Some of the broader themes from myth of experience, around whether experience can limit our creative potential, or conceal dangerous outcomes, or danger in the environment. Whether it narrows our focus our options away from things that maybe we should be focused on. There's some really interesting insights that you've shared in your work around the ways that experience can often, while in many cases, it's extremely beneficial, can sometimes mislead us into risky or dangerous situations.

[00:25:50] RH: Well, for example, one of our problems with experiences, how do we handle disasters? We experienced disasters. We learned from disasters. We've experienced them, but we don't necessarily think fully in term afterwards. Consider disasters like Katrina. Katrina was a horrible disaster in New Orleans. A year before, two years before, there was another hurricane that came in and had similar characteristics. People just extrapolated all they learned from hurricanes, what was going to happen this time, and they were wrong. Basically, experience can't handle changes.

[00:26:27] MB: That's a really good way to succinctly describe that concept.

[00:26:30] RH: The environment changes in some way. Experiences are going to help us.

[00:26:33] MB: I really like that characterization. As we touched on earlier in a lot of these wicked domains, we often don't know the situation has changed.

[00:26:41] RH: Exactly.

[00:26:43] MB: Even coronavirus is a great example of – I mean, we've had swine flu, bird flu, SARS, all of these very characteristically similar outbreaks that had a massively different impact, we didn't know in advance that this was going to be such a different situation, and we were as a planet, really, poorly equipped to respond to it.

[00:27:03] RH: I think, that the current pandemic, is really an interesting example of some of the things that we talked about in our book. Basically, here is something that doesn't quite resembles a bit, some of the other things that you just said, but it's actually quite different. The numbers take off exponentially, which goes beyond our experience. The data comes in, the feedback we get is very strange, because we get feedback on different time series. All of this is very difficult to put together as regular citizen, also, you have to put together and a scientist.

[00:27:35] MB: Yeah. It's a great case study, actually. A lot of the themes we've talked about in terms of how, certainly a wicked domain, where the feedback loops are long, different timelines, you're not sure what variables matter, which variables don't, and the consequences are massively high stakes in terms of whether you get it right or not. Certain things have gone well, but many, many things haven't gone well. That's a lot of the things are as a result of that whole situation being such a wicked learning environment.

[00:28:05] RH: Yeah. I think, the pandemic was really a learning environment, that's true. I wonder what the world will do now, whether we will learn from it.

[00:28:12] MB: Hopefully.

[00:28:13] RH: Or what we’ll learn.

[00:28:14] MB: That's right. That notion that you touched on a minute ago, is another very interesting concept, which is this idea that, in some instances, perhaps, the moment of greatest danger could be when things are similar, but not the same. We don't see the difference.

[00:28:30] RH: There's another problem, which is a difference between prevention of a disaster and the cure for disaster. We evaluate them differently. For example, if someone comes up with a cure for COVID-19, they're considered to be a hero. If someone actually prevents COVID-19 happening, they are rewarded, but at a much lower level. Somehow or other, basically, we love the person who found the cure. We don't get the same reward for the person who prevented this disaster happening. How we set up systems to prevent things is actually very difficult, because experience and prevention may actually make the prevention seem less important.

[00:29:09] MB: That's such a fascinating perspective, that is really insightful. Whether you're looking at it from the perspective of business management, or even just your broader social structures, how do we effectively incentivize prevention over cures for lack of a better term? Because you're right. I mean, resolving the pandemic, you're a hero. If you stop something that could have been bad, but didn't happen, you get a slap on the back and a great job and 10 minutes later, it’s forgotten about.

[00:29:38] RH: Yeah, and I suspect that goes on, for example, in the economy, or do things just to save the economy, or doing new things that it could have saved the economy.

[00:29:46] MB: Explain that a little bit more.

[00:29:48] RH: Well, you said that the person who prevents a pandemic doesn't get as much recognition as the person who cured the pandemic. Well, the same thing can happen in economy, where economy is going along. If something is done, you save the economy. On the other hand, in other situations, and maybe you want to just do something different, which prevents something happening. People can't see the prevention and the outcome of the intervention. Actually, the prevention cure problem is quite general and difficult to handle.

[00:30:19] MB: What are your thoughts around how to more effectively structure organizations, or incentives to help mitigate that?

[00:30:26] RH: I think, first of all, there has to be more explicit recognition on the principle of [inaudible 00:30:31]. Secondly, I think, to all people who actually are enrolled in branches, by giving awards, by financially rewarding them and showing what occurred. There are some industries which are very good at these, like travel industries, where basically, you don't want airplanes falling out of the sky. You don't want to just repair them. You can't repair them afterwards. Basically, or incentives can be put in the prevention people to get rewarded.

[00:31:02] MB: That's a great example and showcases a really important framework that has worked extremely well over the last 100 years as aviation safety has improved. That's a very prevention-oriented culture, for lack of a better term, that I'm sure a lot of lessons could be pulled from. I'm curious, for someone who's listened to our conversation and wants to start to implement some of these themes or ideas into their lives, whether it's on the prevention care problem, whether it's learning environments, decision-making, etc., what would be one action item that you would give them to start to take concrete steps towards putting these ideas into practice?

[00:31:44] RH: I think, one of the things that’s important is to be able to recognize the situations they’re in. One of the things one could do is give people some vignettes of types of situations. For example, a regression doors has been used as a vignette. Learn the characteristics of the Sports Illustrated example we discussed earlier. Ask yourself, is this like a Sports Illustrated situation?

Another I like is meteorologists. People have been shown to have bad, inaccurate judgments. It turns out, the meteorologists have turned out to be pretty good. They predict the weather quite well. Quite often, they're well calibrated probabilistically speaking. You should ask yourself the question, why are meteorologists good, when other people aren’t so good? Usually, the answers are, well, I get feedback every day. Good, that's great. They have good causal models situation, that's great. What people don't remember, is a key aspect of a meteorologist’s job is the meteorologists makes a prediction, where the prediction doesn't affect the weather.

[00:32:44] MB: That's interesting.

[00:32:46] RH: In lots of other situations, your prediction could actually also affect what happens. Basically, one of the things you can do is a vignette, or meteorology and say, is this situation like meteorology? Are we in a situation where there is a chance of your prediction affecting that? What I would recommend is developing four or five of these kinds of vignettes, of classes and situations, then always, be asking yourself the question, am I in a situation which is like this, or like that?

[00:33:15] MB: That's a great piece of advice. You've probably come across this term in some form or fashion, but I'd love to characterize those, as you call them vignettes, as mental models is another term of art that you'll often hear, similarly describing those frameworks, right? Regression to the mean, and so forth. Really familiarizing yourself with a couple important and powerful mental models can really transform the way you approach the world.

[00:33:40] RH: I think, for most people actually, having a simple model, a simple example of a model is useful. Because it's easy to remember. It's like having a scenario, a story. If you have a series of stories, then I think it can go a long way analytically.

[00:33:58] MB: For people who want to find more about you and your work online, what's the best place for them to find those things?

[00:34:06] RH: Well, go to my web page, which is www.rmhogarth.com. If you want to write to me, grab my email, robin.hogarth@upf.edu. Those are the two places to go.

[00:34:22] MB: Well, Robin. Thank you so much for coming on the show, for all of your decades of fascinating work and research in the field of decision-making and for sharing all of these insights and all this wisdom with our listeners.

[00:34:36] RH: Well, thank you.

[00:34:37] MB: Thank you so much for listening to the Science of Success. We created this show to help you our listeners, master evidence-based growth. I love hearing from listeners. If you want to reach out, share your story, or just say hi, shoot me an e-mail. My e-mail is matt@successpodcast.com. That’s M-A-T-T@successpodcast.com. I’d love to hear from you and I read and respond to every single listener e-mail.

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