Dave Gray Mixed.mp3

[00:00:00] I think that Data is a really good example of how we put parameters around our beliefs, and you're only going to collect the data that you think is relevant, for example, whereas there's there may be data that's relevant that you don't even know is relevant unless you're connected. You know, unless you're collecting the data that you don't know is relevant, you may never figure out that it is relevant.

[00:00:40] What's up, everybody? Welcome to the artists of Data Science podcast, the only self development podcast for Data scientists. You're going to learn from and be inspired by the people, ideas and conversations that'll encourage creativity and innovation in yourself so that you can do the same for others. I also host open office hours. You can register to attend by going to Data dot com forward. Slash a d. S o h. I look forward to seeing you all there. Let's ride this beat out into another awesome episode and don't forget to subscribe to the show and leave a five star review.

[00:01:36] Our guest today is a possibility and who believes that anything is possible and if he thinks that's something he wants is impossible, he will devise an experiment to test that assumption. He's been involved in innovation and change initiatives in industry, government and small businesses. And through that experience, he's found that people have an astonishing ability to miscommunicate and misunderstand one another and often work at cross purposes to the very thing they're trying to accomplish. He's driven by the objective of finding ways to help people imagine create a better world individually and together. He's the founder of EXPLAIN, the visual thinking company that helps people develop shared understanding so they can make better, faster decisions and work better together to create more lasting, sustainable impact. There is no question he is afraid to ask about the universe, and if you want something to happen, you will find a way to make it happen. So please help me. Welcoming our guest today, author of A Liminal Thinking, The Connected Company and Game Storming Dave Gray.

[00:02:46] Dave, think you so much for taking time out at your schedule to come on to the show today. I really appreciate having you here and it's great to be here.

[00:02:53] Thanks for having me.

[00:02:54] Dave, before we jump into your book, Liminal Thinking, let's get to know you a bit better. So where did you grow up and what was it like there?

[00:03:02] Well, my dad had several different jobs when I was growing up, so I didn't grow up at all in one place. We moved around quite a bit. He was in college then. He was in the army. Then he was teaching. So we moved where he was working. But I would say for the most part, a lot of my upbringing, I was raised on the East Coast and Massachusetts were already like in high school.

[00:03:28] Like, what kind of kid were you? Like what you think your future would look like?

[00:03:32] I suppose I was very shy. I played basketball. I so I up, but I wasn't really super into sports. I'm tall, so that's why I play basketball. I think I was always I always enjoyed art. So I was an art student. And in fact after high school I went to art school. So that's how I was educated. There's something that defines me.

[00:03:57] Probably it's that subpar artist, artistic and creative type of individual. So how different is life now than what you had imagined it would be?

[00:04:09] That's an interesting question. I, I don't think I ever imagined. I thought, you know, as an artist, I thought I would always be scraping by to make a living. I never thought I never thought I would own a house, for example, which I do now. I never thought I'd be driving a relatively new car, which I am. So I think one of the things that surprised me the most is that I was able to to somehow find a way through creativity to be financially successful, which I never somehow never really expected.

[00:04:46] And what was that journey like then to go from kind of where you were to now like to a life that you had not even imagined to something you weren't even expecting to happen? What was your journey like from that high school kid to to now?

[00:04:58] I guess it was a series of discoveries that creativity was more than just, you know, making marks on a page or making paintings that you could be creative in many ways and up to and including creating for yourself the life that you want to live. So, I mean, there are probably a lot of small discoveries led up to that sort of big discovery, that creativity is a very powerful thing and can create your life.

[00:05:30] And was there one particular experience or something that really kind of helped you develop this this philosophy around creativity?

[00:05:41] Yeah, I think I mentioned it in my book when I quit smoking, I was twenty nine years old and it was something I had thought I'd always thought would be impossible for me. Somehow I had smoked for since I was 16. So, you know, for a long time and somehow I couldn't imagine myself and accomplishing something like that. And once I had and through I guess just determination, I was able to do it. And of course, you know, that was a breakthrough in a way, because once I had done that, it seemed like nothing, nothing was impossible at the point. And if I could do that, I could do anything. And shortly after I that I left the relationship I was in, I moved cross country. I left, quit my job, went to a totally different field. So I made a whole bunch of changes right after that. And I think they're related. That was kind of a it was a tipping point, as I say.

[00:06:53] Love to hear more about what creativity means, I guess. How would you define creativity and how can somebody who doesn't see themselves as a creative individual actually tap into the creativity that that they have naturally?

[00:07:09] Well, people tend to use the word creative as a way to describe a kind of a personality trait. Oh, I'm creative. She's creative. He's creative. That's a creative person. And I think there's a lot of connotations that go with that creative meaning. Oh, maybe a little flaky. Someone who's not really serious, who maybe not good at math, those kind of things. But when you think about what the word creation means to create something is to bring something new into the world, whether it's a baby or a business or invention or a house or a building or whatever. So creation is the process by which we bring new things into the world that weren't there before. And I think everyone has the potential within them to do that in different ways. And I think the question is whether what that means to you and what's the mark that you want to make on the world? What is it that you feel in the world needs to change or you want to see change for yourself or for the world or for the people that you love or care about or what what have you. And I think the more aware you are of the things that you want to see happen and the more self-aware you are about what your strengths and weaknesses are, the better able you are to bring that about.

[00:08:38] I think it's really interesting like this, that being aware you talk about in your book a bit later on in the book, where is this idea of connecting dots? And I think to me, when I think of creativity, I think it is having an awareness and connecting dots between things that probably don't, on the surface of it, look like they should be connected or have any connection. And then connecting these two to then can create something new out of two things that don't can go together. I don't know if that makes sense. I'm just rambling right now. But that's kind of my idea of creativity is colliding things that don't look like they belong together, but maybe they do.

[00:09:13] Yeah, that's certainly part of it. I think, you know, making connections or seeing patterns and finding ways to accomplish things. I mean, if you think about what inventions are, inventions are new ways of putting together old things to accomplish new, you know, functions. And so, yeah, I think that's a that's a good insight.

[00:09:39] I'm curious, like as somebody who's kind of came up as like artist, what do you think is the difference between science and art? Do you think there is a difference or do you think that there's anything that science can learn from our curriculum or from science?

[00:09:53] That's interesting. When I was in college, I lived in a kind of a rundown sort of apartment building, and one of my flatmates who lived nearby in the same complex was a physicist. It was I was living right next door to Caltech. You can if you know that school, say he was a physicist there, a really smart guy. And I think one of the things that I discovered in conversations with her, with him is that there's not a lot of difference between art and science in terms of being explorations, in terms of being kind of the splendor or a rigorous exploration of reality. Perception and how we how we understand reality and how we see it. So in some ways, physics and art, you know, a painting, at least what I was doing at the time, or equally useless or equally impractical from one point of view. But from another point of view, they were, I think, very similar. I think the closer you get to the cutting edge in science, the closer gets to art, because, you know, when you're in grade school science or when you're learning science, you're really learning the history of science. You're repeating experiments that have already been done. You're you're learning things that have already been discovered. But as you get to the leading edge of science, what you're doing is you're you're applying a lot of creativity, a lot of dot connecting to figure out, because science is really the discovery of things that we don't know yet, that we haven't figured out yet, that we're still working on figuring out. And so in that sense, science and art have a lot in common.

[00:11:43] So in science, we kind of have like that the scientific method. Do you think there's a method to creativity that can creativity be systematized? Can it be taught?

[00:11:52] Yeah, I think it's the same. I think, you know, the scientific method comes down to trial and error. You know, try try again, putting a little bit of discipline around that. And I think that's what all creativity is about, really, is to to try and, you know, to form a hypothesis. You think this will work or you think that'll work or you think given these conditions or maybe it didn't work before, but if you try a little bit differently or try to do different time or different place that it might work. So I think that's what I mean when I refer to myself as a possibility. And it's not to say that anything or everything is possible, but that anything is worth trying. Anything is worth giving, you know, setting up an experiment and giving a shot, even especially the things that you think are impossible, because those are the most likely areas where you're going to have a breakthrough.

[00:12:44] I think hypothesis has a really nice synonym, at least the way I view it as a synonym that you actually written a book entirely about. And that is beliefs. Right. So I kind of think of a hypothesis as a belief. Sure. So let's dig into let's dig into your book, Liminal thinking. I heard you've been listening to go pick it up. You have an audible. It is included in your audible subscription. If you like the premium version, download that book. Now, listen to it twice this week. It is great, but let's get into it. So what is a belief and how is a belief different from reality?

[00:13:21] Well, reality is unknowable, right? In some way. We all have different experiences of reality. Each one of us has a unique set of experiences, but none of us can know all all of reality. None of us can have. I can't know what it was like to grow up as you and you can't know what it was like to grow up as me. I can't you know, there's you and I both can't know what it's like to grow up as a woman, you know, so we're in a different country or whatever. And I think so each of us has some set of experiences. And those experiences are going to inform our beliefs because, you know, when we when I try to do something, it's I'm going to get a different result. And when you try to do something based on your experience, based on your background, based on your skills, what have you. So some things that you think are possible, I'm going to think are not possible and vice versa. So over time, as you have these experiences and you have successes or failures or, you know, whatever, you tend to form beliefs about that. This is just the way it is. For example, let's say you think your boss hates you. Well, maybe you've had some experiences with your boss. You've tried to be friendly.

[00:14:44] You've tried to please your boss for whatever. And you've at some point you say, I give up. My boss doesn't like me. I don't know why. And that becomes a belief. And then you start acting as if that belief or true, you stop trying. You you maybe you start acting in such a way that tends to reinforce your belief. And then before you know it, your belief becomes your reality, because in a way you've co created it with your boss. That doesn't mean that that has to stay that way. I mean, we get in throughout the world, we see conflicts and things where people have gotten into feuds or wars or, you know, ethnic conflicts or what have you that have lasted for generations and becomes self-perpetuating because they've always been that way. So therefore they will always be that way. But then. We also see examples, you know, for example, like the, you know, inspiring examples like the in South Africa, they had the Truth and Reconciliation Commission, and you do see sometimes examples where people can break through that. And that's really very powerful. Interesting stuff. When people can decide and you can make a decision to say, set your beliefs aside and say one of the things might possibly be true. What else could be true?

[00:16:12] Yes, interesting. The unknowable in this reality really struck me. I was reading this book simultaneously this week at The Island of Knowledge. I'm not sure if you had excellent the limits of science, something you had said really get really good at book, highly recommend it. And just there's so much because I mean, our our ordinary consciousness just it's a filtering machine, right? There's so much that it just filters out. And that's a few bits. And so I'm wondering, like without beliefs, like, can we make sense of the world?

[00:16:43] Oh, no. I think we have to have beliefs. If you didn't have beliefs, you would you would be like a baby. You'd be completely unable to act. So we need to have some foundation in order to make decisions and act and make our way in the world. But, you know, there comes a time when beliefs aren't working and as well as they used to where beliefs are not serving you. And the purpose of a belief is to help you make your way in the world like you walk into the grocery store because you believe there's going to be food in there. You know, you have your shopping list and you have a belief that when you walk in there, those things are going to be available. But then we have, you know, for example, we have covered come along and some things that used to be available in the grocery store suddenly are not available. We can't find them anywhere. And so that's the thing about the world. The world changes and faster in a way than beliefs tend to change. So you kind of establish your beliefs, most of the important ones when you're young and as you grow up, as you change, the world changes. And as the world changes, your beliefs slowly become out of date. And that's why, you know, we think the older people are the more set they are in their ways, the more outdated their beliefs are. The more you think about your parents, you know, and their beliefs. And like all they're you know, they're out of date, whatever. That's because the beliefs are so powerful. They they tend to have staying power because they're self reinforcing, because everything that you do tends to reinforce the beliefs that you already have.

[00:18:23] It's over. Time becomes harder and harder to change them. They become more and more reinforced. So that's why I think we have to be very attentive to which beliefs are working for us and which beliefs somehow you let's say you have a belief. I'm trying to think of an example. I'm failing to. But let's say I believe and suddenly things aren't working for you the way they used to. Well, this is the case in business a lot, where the business world changes, it becomes very digital, much faster pace. And people are not having the same success that they used to have and they doubled down. They do the same thing. They put more money into things that are failing. They they try and do the things that work for them when they were younger. As you grow up in the business, as you get older and older, you go tend to get higher up and more removed from the front lines of the business. So you're a little less the longer you've been there, the less in touch you are with the realities of the business and the more likely you are to make decisions based on what it used to be like. And so that's how companies go out of date. Those organizations have beliefs that we could call it culture, but organizations tend to reinforce certain cultures and beliefs in the same way that individuals do. And that can become a problem. And that's why most companies don't make it through.

[00:19:43] Many generate multiple generations definitely dig deep into everything you're just saying, because it's a lot of really important concepts and information there. But before we do that, that's the first kind of set some groundwork for for understanding in terms of the vocabulary term. And that is limited to thinking, like what is liminal thinking if we're to define that term?

[00:20:06] Well, the word liminal simply means threshold, a place between one thing and another. So if you think about the threshold or a doorway. Liminal is kind of like a line, so if you think of if you've heard the word subliminal subliminal below the threshold of consciousness, that's, I think, liminal, the first use of the word was in how how to do it with some kind of electrical threshold where something was able to trigger a trigger, a switch or something like that. That was from the eighteen hundreds. And then it became it came into a little bit more common use in I think, mid 20th century when I can't remember who coined the term. But people started using it in anthropology for rites of passage, going from boyhood to manhood or that kind of thing, becoming a citizen of the culture and the rituals that were, you know, where you're in the middle of the ritual and you're no longer a boy, but not yet a man kind of thing and.

[00:21:09] On that threshold, on that point, you know, in that doorway is where we're no longer in the old world, but we have not yet entered the new world, and that is a point of great possibility. So liminal thinking is being cultivating a mindset where you can.

[00:21:30] Find those thresholds, stand on those thresholds between one thing and another, let go. In other words, kind of hold two opposing ideas in your mind simultaneously well enough to sort of explore new territory while still being aware of the old territory. So, for example, one of the phrases that I really like in this context is to act as if when you have a belief that's no longer working for you and you have all this evidence for that old belief that you've accumulated over many, many years, you have all this supporting evidence in your mind why this is the only way it could be, why there's no other possibility. But you want to it's not working for you anymore and you want to try something new. You can try it. A new belief. You don't have to actually believe it's true to try it out. So we call that acting as if you can act as if it were true as an experiment. See what happens. Let's go back to your boss hates you. Well, what would happen if you as a hypothesis said, my boss doesn't hate me or maybe my boss. You hate me, but my boss doesn't feel that way anymore. My boss has moved on, etc.. What would happen if you acted as if that were true? As if you actually liked your boss and your boss liked you? Or at least you're starting from neutral. What might you do differently if your boss didn't hate you? Well, maybe I ask my boss to lunch. Maybe I would offer to do the extra work that I have not been offering to do.

[00:23:09] Maybe I would. And what happens is sometimes you can do these kinds of experiments and really surprised yourself. And that's what, you know, the idea that you're standing on a threshold between well, on one hand, I know that my boss hates me. On the other hand, I'm willing to explore the idea provisionally that maybe it's not true. Maybe this is a belief that's holding you back. Maybe this is holding my career back. Maybe this is something that I could give another shot to. And so that's a long answer to your question. But absolutely, liberal thinking is the way it is a way of playing with those beliefs and giving yourself a chance to explore them and maybe think twice about them.

[00:23:46] No, it's absolutely, absolutely love that I think is very applicable for my audience data scientist, because as a data scientist, you definitely have to be in that liminal thinking mode because you are the bridge between the technical people and the business people. So you have to be able to think with both perspectives in mind, like like a duality. Mindset is an excellent book that I was reading all about duality mindsets called the self-made billionaire effect. And it's really interesting to, you know, empathetic imagination is one of the things that sticks out for me in the eye. Anyways, I'm more curious about how we actually create beliefs. Right?

[00:24:21] So some beliefs they get handed down to us from our parents who got it from their parents and so on, so forth. Well, can we stick with Data for a minute? Yes, absolutely.

[00:24:31] I think that Data is a really good example of how we put parameters around our beliefs. And you're only going to collect the data that you think is relevant, for example, whereas there's there may be data that's relevant that you don't even know is relevant unless you're connected. You know, unless you're collecting the data that you don't know is relevant, you may never figure out that it is relevant. So I think there's this whole I guess there's I've heard there's a whole kind of debate between structured and unstructured data. I don't know if you could tell me a little bit about that.

[00:25:08] Yeah. I mean, typically, like, you know, when we're doing when we're using data for reporting purposes, like, for example, just kind of retrospectively looking backward, seeing how things are performing, we'd like our day to be nice and tabular and nice and organized. So you specify ahead of time, OK, these are things that we think are important that we want to track and monitor going forward that would be like that structure Data nice clean tabular data and unstructured stuff is just not in a format.

[00:25:35] It's right. Messy. It's you know, if you've heard of this site like Jason Blob's is this type of Data format. So it's just data that's really nested and yet it gets messy in that sense. And when we're doing data science, I think it's important to I mean, got it. We need to start with the hypothesis. Right? Like, it's super easy to collect all the data in the entire world and just we think it's going to be interesting what we think is going to be important. But then that could lead you down the path of always looking at me like you need to specify ahead of time. I think that these are things that we're interested in testing for. Right. So start with the hypothesis. Specify what it is that we're actually trying to observe and collect data that might support that. I don't know if that answered your question at all.

[00:26:25] Yeah, I mean, if you think about something like making a map. For example, there's this there's a you know, you think about, well, the ultimate map would be as big as the actual territory that's mapping, right? Because, you know, what do you what do people put on a map when they make a map? They put roads. But what about the trees and what about the animals? And, you know, there's no limit to what you might possibly collect. And then from if you think about even things like Google Street View, where you're photographing everything, well, it's that's out of date the second that you take the picture, because, you know, if you ever looked at your own house, it's probably, you know, if you depending on how long you lived there, might have someone else's car in front or, you know, might be different color or what have you. So I think in principle, there's no limit to the amount of data that we could collect and. But at the same time, if you impose your hypothesis on that Data, you're also imposing a kind of limitations on it. So if you're only looking at, you know, where cars go, you're going to there's a there's a great book called Seeing like a state Harp you've heard of it or read it. But the whole idea is that if you're a if you're a nation state, there are certain things you want to know because you want to be able to collect taxes.

[00:27:55] You want to be able to, you know, to rationalize the idea of the state from your perspective of what you need to know. You need to know who the people are, what they're doing and so forth. And I think it's almost impossible. If you're a data scientist not to be in some ways kind of an imperialist, you're imposing or colonialist, even kind of imposing your point of view about what's important on the world. If you're if you're a social oriented company, let's say like a social media, I mean, in that sense, then you're going to see the world in terms of, you know, tweets and posts and whatever else Tick-Tock videos. And you're going to see the world in terms of social networks and friendships and relationships and those kind of things. If you're a if you're an NGO focused on human rights, you're going to have a whole other framework that you're going to impose on the data that you're collecting. I think it's so to me, it's the same they're the same kind of ethical dilemma that you would have if you were a nation state or, you know, kind of a government imposing your point of view on the world that you have to be.

[00:29:17] This is where beliefs become important. You have to think, OK, well, if my Data is if I am the empire of my own Data state, then who are the counterrevolutionaries? Who are the people who have different or even opposing beliefs? And why would they have those beliefs? And how might I make sure that I'm not blind to those things that are actually going to be pretty important for me to know the people who are, you know, who reject my whole world view, for example. So I think there's a lot of you know, the thing about Data is we tend to think we tend to correlate it with reality. We tend to think it is reality. And of course, a lot of Data is reality. I think it was Einstein who said not everything that counts can be counted and not everything that can be counted counts. And I think it was Einstein. And I think that we should be aware that all, even though the things we are collecting may be facts, there's the whole set of facts that we're not collecting. And I think those are the kind of blind spots that that end up causing companies to go out of business. And a lot of cases, it's the Data. It's not the data that you are collecting. It's the data that you're missing.

[00:30:36] Yeah, because, I mean, the real world is messy, it's complex, you know, the Data that we do collect is just some artifact of whatever Data generating process actually created that Data. Right. So it's just they're like shadows of reality, if you think of it that way. Right. And that's what it is. When the data we're collecting data like we had infinite amount of storage, infinite amount of ways to describe reality, then I would probably collect all the data. But I guess that's important thing like mistaking beliefs for reality. Why is it that we do that? And what are some pitfalls of mistaking belief for reality that you've seen play out organizations?

[00:31:19] Well, if we stick with Data for a second, I think one of the things that if you're if you're collecting data or you're organizing data or you're putting it together, generally speaking, you usually have a source from the data and you have a customer for the data. And one thing I think maybe we can say, we all know about customers as customers don't always know what they want and they don't always have the language to ask for what they want or they may think they know what they want. But so there's a lot of art that goes into making the connections between the sources of the data and the customers of the data. And I think if you want to be a good service provider, you want to be thinking about ahead of your customer, not only what they want, not only what they say they want, but what you think they might need to know what you think might be useful, what you know, how might you be anticipating? What what might be going on in the world that they're not even thinking about that, and how can you be looking at the data or your sources? How can you be spreading those forces around to make sure you get as much triangulation as possible? Triangulation is one of the principles of limited thinking that, you know, you want to be you don't want to be having marginal sources of information. You don't have as many sources as possible. So you can overlay them and make sure that you see that, yeah, this one supports this idea, this one supports this idea, et cetera. And so, I mean, maybe if you talk to me a little bit about how you would form a hypothesis, I think. I sort of forgot what your question was, but I think that what the art of it, a lot of the art of being good Data science is not just being an order taker, so to speak, but being a kind of a consultant to your customer.

[00:33:19] What up, artists? I would love to hear from you. Feel free to send me an email to the artists of Data Science at Gmail dot com. Let me know what you love about the show. Let me know what you don't love about the show and let me know what you would like to see in the future. I absolutely would love to hear from you. I've also got open office hours that I will be hosting and you can register like going to Italy dot com forward, slash a d. S o h. I look forward to hearing from you all and look forward to seeing you in the office hours. Let's get back to the episode.

[00:34:05] Yeah, I think that definitely requires a great deal of empathy plus perspective taking for share and probably some diplomacy too, because people can be very adamant and demanding about wanting one thing, even though you may be aware that they're missing information.

[00:34:24] I think that's sort of the importance of asking good questions comes in. Right, because if you're able to kind of think what the other person is thinking, then you can. And the only way I think for you to really understand what the other person is thinking is through questions. Right.

[00:34:38] And what do you do when somebody doesn't want to hear it, when you have bad news and they don't want to hear it or somebody only wants to Data that's going to reinforce their point of view or I mean, that must come up, right?

[00:34:50] Yeah, definitely. I mean, people they would say that was that term, that self self confirming bias or something like that.

[00:34:59] But above all of belief or self self is not forcing you to take your terms self sealing a self feeling like. Yeah, yeah.

[00:35:10] I mean, that's tough to deal with actually. Let's take it there. Let's let's talk about this. Seeing logically, can you define that concept for us? Because I think it's super relevant.

[00:35:21] Well, once you have established a belief either as an individual or as a group and as more, it's even more powerful when it's a group. But once you've established a belief that something is true of, say, like the earth is flat or the you know, you can go back long enough that the the sun revolves around the earth and the earth is the center of the universe or what have you. But once you've established that belief, then you there are two ways that you make sense of new information. One is you check it against what you already know and you say, OK, well, does this fit with what I already know? Well, that's just going to reinforce the belief because you're going to discount anything that might prove it differently so that already you're sort of reinforcing an existing belief by only accepting the data that you already fits with what you know, anything that doesn't fit with what you know, you tend to discount as well. That's oh, that guy's a little tech that, you know, it's unlikely to be true. Can't be true. There's a great example from the car industry which we can get into in a while if you want. But and the second way we make sense of new information is to be subjected to a test, to perform an experiment, to try it and see if it works or test it in some way.

[00:36:44] The problem becomes problem comes in when we only tend to test those things that already make sense within our existing set of beliefs. So and the example from the car industry is when Detroit was first coming up against Japan and Toyota or Datsun and these other companies were first coming into the US. They discounted all the data about Japanese car companies, they didn't believe that they could make them at the quality they could make them. They didn't believe that the Japanese could make cars as fast as they could make them. They didn't believe that they could make them as cheap as they could make them to such a high quality. They just didn't think it was possible. So even after touring the factories and so forth, collecting data it took. Twenty years or more before they started to admit that these things were reality, that they were possible, you can imagine senior executives in tall buildings just saying, well, it can't be true. Capitalism possible. We are the experts in this. We've been making cars for longer than they have. We've we've got all the expertize. And that's the problem with expertize is when you have a lot of expertize in something, you start to believe that it's impossible for anyone to think of it any other way. Tesla's a good example of that kind of upending the car industry right now.

[00:38:18] And I think there's still a lot of car manufacturers who think, well, nobody can get up to speed with car making us that fast, that we have too much expertize. There's another example with the with the iPod. You know, Sony was making Walkman and they had engineers and they were thinking in terms of engineering, they're thinking in terms of knowing that Sony was thinking, well, we'll make a hard drive that will just have a computer to play the music. And that was how music players got from being the size of a a book to the size of a quarter, you know, that it became all went from being a mechanical thing with cassette tapes to being a digital thing. Well, that was so beyond the the mindset of people at Sony at the time is to thinking in terms of that this could be a microcomputer that's playing things they were all. And why would they have that expertize their engineers. There are mechanical engineers they were used to putting together. Tape players, so and there are examples like this throughout history where disruptive technology comes along and people just are completely prepared for it and not ready for it and. And that, I think, is because whatever those self sealing logics are, whatever those beliefs are, they're always going to eventually become Data to come out and become out of date.

[00:39:58] Yeah, it's like once you have a new theory of how something works or how something should work, everybody wants the next thing to be just like first, right? It's unfortunate consequence of this self-serving logic. Well, that's right, you also talk about the pyramid of beliefs in your book and I think that be important to talk about at this point as well.

[00:40:22] Yeah, to do it without drawing is a little bit difficult. But if you imagine at one level you have the world as it is. So imagine that as your base, the landscape on which you build your pyramid of belief and then at the level that you're standing on is the level at which you have your beliefs. In between is a whole chain of things. There's a guy named Chris are Argyris who calls it the ladder of inference. But it's a it's a chain of of thinking that leads you from your experience to your beliefs. And so the first level that is your experience, you have direct experience with reality, whether it's, you know, the taste of an apple or something that's a little more removed, like reading a book or watching the news or something you've experienced out in the world, you have that experience and then within that experience, you have a very, very tiny subset, which is what you actually have noticed. And, you know, we can only focus on a very, very limited number of things at a time. So you have a very, very small needle of attention, which is the things that you've noticed out of that experience.

[00:41:34] And from those things that you notice, you form your hypotheses or your assumptions. And from those hypotheses, you form your theories and from your theories, you form your beliefs, your theory that if I go into a grocery store, there's going to be milk in there or beef or whatever. And then depending on the country you're in, you might find that those things do not are not in the grocery store. I don't know how much you travel, but I've traveled quite a bit and I definitely know the feeling of walking into a place and not knowing I sit down or should I go stand in line? Do ah, is it is it is a kind of place to wait on you and will they even speak my language and what are the customs here.

[00:42:19] And that can be very disorienting you because you have sort of a set of standards and beliefs. But when you go to a different place where the culture and the norms are different, all that stuff gets turned on its head. And so you can you know, in one sense it's very disorienting, but another sense it can be very liberating because when you come back. To your own country, you can realize while these are things that are just decisions that people make, they are this isn't the way it is. This is just something that it's a convention. It's a custom.

[00:42:53] And you talk about these loops that we get into as well like that. They are really cool names. I'm learning loop to do loop in the loop. I talk to us about these different loops and and how they impact our belief systems.

[00:43:08] You think about the I guess the big ideas, a learning loop that you tend to do where and this is how we turn experiences into beliefs. You do something, you perform an action or you have an A you have a goal, let's say, and you want to achieve a certain thing. So you learn that to do that. If I what I do this this happens when I do this, I get this result. And when I do this, I get this result, which tends to reinforce the belief that I have, which tends to make me do it the same way the next time. The example I gave in my book was a dog. We had a dog who had and you have beliefs about other people just like you have beliefs about animals. And when we first got him, he had some anger issues, let's say, or some territory issues where we when we gave them food, he became very aggressive and kind of snarling in protective of it to the point of being really, you know, kind of scary. And so, you know, one way to deal with that is to say, OK, this just is a bad dog. Take back. The dogs are set in their ways. The dog's not going to change. But we chose another approach to take the idea that, well, this is the dog that can. Yeah. Has had a history. He's had a he's got beliefs that, you know, maybe where he was before he had to fight for his food.

[00:44:42] He has formed a set of beliefs around, you know, if I have something good, I have to protect it and so forth. So maybe we can train him that it's over time, that it's safe. And we were able to do that successfully. But that's all so do would be where you're reinforcing the negative beliefs about the dog, punishing the dog or treating it badly and reinforcing its belief that it needs to protect itself. And just digging a deep, deeper spiral, downward spiral is another what way to describe it? Or you could think about it as an upward spiral. Or, you know what I call in the Book of delight, look and say, well, let's do positive, let's reinforce all the positive things and let's form a new learning loop. And in other words, act as if act as if it's a good dog. Act as if you know how to just having a bad day or had a bad some bad experiences. Some had to be made aware of. And so we would whenever he would do good things, we would give them a treat just like, you know, how you train dogs. And this is the case not only with animals, but with people in your life. You can your actions can determine as much how they respond as their actions. So you have a lot more control over your interactions with other people than you think you do.

[00:46:07] So should we seek to like kind of had this question? Because, like, you know, going back to this concept of beliefs and hypotheses. Right. So hypotheses, we should a good hypothesis is one that should be falsifiable. Right. We should we should have evidence to either support it or reject it. How does that relate to beliefs like should good beliefs be falsifiable? Should we test to falsify our beliefs? Does that make sense?

[00:46:35] Well, yeah. I mean, I think you I mean, the the more valid a belief is, the less likely you're going to run into evidence that it's false. But I think you're you're referencing Karl Popper, who the philosopher of science who said a good theory should be, at least in principle, falsifiable. Yeah, exactly. And so he used the example of Freudian psychology as an example of pseudoscience in the sense that another way of saying it is a theory that explains everything, explains nothing, because the I think his example in the book that I read was, well, a Freudian analyst can explain why the father went to rescue his drowning son as a Freudian thing, but he can also explain why the father left his son to drown and use the same theory to explain both. So another way of saying a theory should be falsifiable. Is to say it should be able to make predictions, if you have a good theory, you should be able to make a prediction that if X, Y and Z circumstances are produced, then this is the result that we'll get. So, yeah, but I think it's it can be challenging to figure out what those parameters are and to set up those experiments, especially when you're dealing with the kind of modern Data that people are trying to collect, which is very anecdotal. You're trying to get a lot of people.

[00:48:10] You're trying to you're trying to get really understand how people make sense of the world and why they do things the way they do. And it's not always things that are easily counted or, you know. So one thing that's really, really hard to do in that kind of data collection is to have a beat us. Because you you really don't know, you know, your samples are similar or the same every time you're doing an experiment in the real world, you lack the kind of control over conditions that you might have in a laboratory. I mean, just think about the polls in the latest election, how or latest last few elections, how off they've been. And I think part of that is because the the the more digitally kind of aware you are, the easier it is to avoid people polling. So the sample sizes are getting more and more skewed towards those people who have an old fashioned phone or who think Old-Fashioned Phone. So they're tending to probably skew towards a certain, you know, you know, I don't know, two towards a certain demographic or a certain group. And so I think polling is a really good example of something, a science that or or if it's a science, but it's an art that needs to really have some new thinking applied to it.

[00:49:38] Yeah, definitely. Definitely. I think there's an important point you made there about like that sample selection bias and it's confronted with some results or some statements. And then we do some analysis, get some results. We conduct an experiment. We think it should go in one way or the other, what have you. I think this is where a core skill from liberal thinking is really, really important. And that's not navigating below that obvious. Right. So we get some results. And if you just accept it at face value, then you might not be making the right decision. You need to take a look.

[00:50:11] For example, you look at the research that's done by, you know, some people in sociology or anthropology or what have you. And all the vast majority of the experiments are done with college students as subjects because college students are the most easily accessible to the professors who are doing the research. And so and yet that's rarely mentioned is that, you know, that your is generally speaking, we got, you know, a very narrow a very narrow economic demographic, a very narrow age demographic, a very narrow slice of reality. And yet a lot of the research gets put into play as well. This is the way it is. This is what we discover. This is what we we figured out is what we learn. I think that's the case in a lot of domains, is that, you know, how many people are going to take an online survey? Well, they first have to be online. Second of all, they have to be the kind of people who are going to take a survey. So, again, you're always going to be very limited in your in your sample size. And that's part of what I was saying. And I think when I was saying, I think it's important for you to realize what your blind spots are because you're always kind of blind spots. And by definition, if they're your blind spots, you're probably not going to be seeing them very easily or you're not going to be easily aware of them. And so I think, again, that's where triangulation becomes important.

[00:51:43] He talked about this in your book is called The Data Harry or Johari Window or Matrix, yet where they talk about blindspots. Can you describe that first to my Professor Johari window?

[00:51:54] Yeah, it was. It was. It was. That's kind of a funny I don't know if there's a right way to pronounce it, because it was if I remember correctly, it was called that because the guys who'd been to read it, Joe and Harry. And so I've talked my head. I don't know if I can recreate it, but basically the idea is that there are things that, you know, you know, things that you know that you don't know, things that you don't know that you know, and things that you don't know, that you don't know. And so you can imagine a Quadrant four quadrant box that creates a window is like that about a, you know, four boxes put together and where you try and you think through those things. And it may be obvious, but the the box, the things that you don't know that you don't know is the hardest one to fill in. And that's the one they have an exercise that you can do with other people and where people might you might write down on sticky notes or slips of paper things about the other person. You pair up and you can put those things into categories of all the things that I knew that I didn't know. These are things that I thought about myself. And so, you know, but again, the only way you're going to fill out the box, a set of boxes like that is by getting new sources of data that you didn't have before, by talking to people that you haven't talked to before. By looking at. Places you haven't looked before, and if you don't know that, you don't know something, I think it was was it Rumsfeld who talked about I don't know. I don't know who was unknown unknowns, but if they're unknown unknowns, you don't even know where to look for them.

[00:53:50] Those are like the most dangerous type of blind spots. How do we absolutely know how even check for four blind spots? Is there something, a habit of mine that we can cultivate to make sure that if, you know, at the very least, we are constantly reminding ourselves that there are some blind spots.

[00:54:08] And yeah, I think one of the most important ways is to listen to spend your time listening to people triangulate and by triangulate, you want to spend your time listening to people that say things that don't make sense to you or that you want to listen to information that seems illogical or seems wrong or seems to not make sense. If you're listening to news, you want to listen to news from all over the world, not just from people who are like you, who agree with you. You want to if you want to collect information, you want to collect information from as unlikely or different sources as you can possibly imagine. I think that that's the most important thing, because the more the more people that you consult, the more different perspectives you can get, the more different experiences you can connect with, the more likely you are to find those things. One of the things that we have as humans, as we have a lot of different perspectives, a lot of different ways of seeing things, a lot of different ways of looking at things and collecting things. And if you can learn to listen, especially to those people who disagree or see the world differently or think about things in a very, very different way than you are, the more likely you are to become aware of those kind of blind spots in this.

[00:55:26] Is that idea or the exercise of trying on your beliefs? Correct.

[00:55:31] Is that kind of what you think about the old story of the blind men and the elephant? You know, they're all arguing. You know, it's the guy who's holding on the ears. It's a fan, the guy holding on the rope, the one who's holding the trunks of hose. Well, if they argue, then they're not going to ever come to a complete picture. But if they actually are able to listen to each other, then they have a better chance of coming to some kind of complete picture, even though it doesn't make any sense to the guy who thinks it's a rope, that it's a man or whatever, you know, sounds crazy.

[00:56:11] The more you're able to pay attention to that and listen to that, maybe kind of draw a picture of it, maybe try to figure out how it might make sense or put those things together, then you're more likely, I think, to. At least mitigate those blind spots a little bit, and especially we have such a polarized political climate and we have a lot of very, very splintered perspective and a lot of different groups with a lot of different perspectives. Very often, you know, strongly, strongly held the the more of those that we can kind of triangulate between, the more likely we are to come to some kind of understanding of even if people see something, something, it's completely off or completely wrong, at least for when we factor in that point of view or at least considering, OK, maybe it's not true, but why would people think that way? And we can maybe get some insight about them.

[00:57:13] How can we use this to talk about storytelling in your book? And it just reminds me of, you know, reminded by the black and holding an elephant to a part of the elephant. They're all kind of telling stories to themselves and to each other. Right. So I guess how can we use storytelling to understand people's beliefs, to understand our beliefs better, to communicate our beliefs.

[00:57:38] And I think part of it is to understand the difference between a story and a fact, a story is a fact, a story is a string of ideas, that a story is a way of making sense of experiences or facts. So stories are always going to be personal. It's always going to have a point of view.

[00:57:57] It's always going to be a way to turn experiences and Data into something that has meaning. And so when we hear other people, when we listen to more stories we listen to, the more we can understand what Data they're selecting, what facts they're selecting, what facts they're ignoring, what might be the self sealing logic that supports that, how those beliefs might have formed, what alternative beliefs might exist. I mean, the story is a packaged belief story usually has a point. And by asking yourself, well, what is the point? What is the belief? I remember, for example, talking to my dad, who's a climate change denier or not, he doesn't deny climate change, just denies that it's human, caused whatever. But I remember an insight that I had, which was to say, well, OK, he keeps he keeps ribbing me. He's poking me about, you know, climate change. But why does he even care? Why is it even important to him? And I remember asking him, I had a, you know, kind of moment of insight and I asked him, Dad, why do you care? Why is it important to you whether the climate change is caused by people or not? And he said, well, jobs. So I did a lot of things fell together in my head because.

[00:59:29] Oh, well, I see now he needs that fact to support some other story, some other set of beliefs that he kind of needs that to believe that there are people who are trying to use that to take jobs away or or whatever. And so I think the more we can listen to stories and you're not going to hear a story unless you at least show that you're open to hearing it a lot of times. But the more you can listen underneath the story and try to construct for yourself that pyramid, what were the experiences? What did that person notice about the experiences? What did they discount? What did they what are their assumptions? What are their theories? Why how does this what is this belief as a story supporting? I think the better chance you get of understanding the person and perhaps changing your own mind or theirs? I think it's equally valid to be doing either the kind of go back that we touched a little bit earlier.

[01:00:39] You know, once people have a theory of how something works Data, they want the next thing to be just like the first. And you pose the question to me, like, what do I do if somebody is, you know, they they've got a story. They're telling themselves about how something should be. So give me the data that shows me that this thing is how I think it should be. So how can we then? I don't even know how I'm going to say this, right. How do we infiltrate people's story to help them change their story, to kind of be more in line with our story? I guess I'm wondering, how can we use stories to help persuade people to buy into our ideas?

[01:01:21] Well, I think probably listening to stories is more important than telling stories. No. One, and I think cultivating the ability to ask questions in a way that's nonthreatening because people will defend their beliefs. And so maybe someone's looking for evidence to support some existing belief, maybe asking them questions about, well, what? Kind of Data should we be looking for what could help us make sure that we're getting the most accurate Data possible? What kind of questions can we ask that don't lead the witness? And maybe, I think, asking questions about what the person is trying to solve for asking questions about what their hypotheses are, how they came to this. I think not to pick apart a story, but to show that you're listening to show that you're trying to understand, to show that you're trying to get deeper into it. Maybe the person does have a point, maybe to have more of a point than you think. Maybe you're the one who has the the blind spot. And so getting people to try to get people to tell their story, try to get people comfortable enough to complain or bitch about it or to tell their story about, well, so-and-so doesn't believe this. I got to prove it to so-and-so and I've got to justify this budget.

[01:02:54] And I need money for this or whatever it is to try and understand those political or diplomatic or professional or personal issues, whatever they might be, and really listen and explore them. Sometimes it's good to get outside the office and away from the workplace and get into a restaurant or over lunch or something like that over coffee and try and dig in and show that you're listening. Take notes, run the notes by the other person. In other words, slow down, slow down your try and temper your own reactions, even if you feel like you might be triggered. If someone is saying something that and it doesn't make sense to you, then you're missing something. And what you're missing is what you want to kind of understand, and I think it's very easy to jump to the conclusion that, oh, this person is just crazy or an asshole or a lunatic or, you know, but for whatever reason, it makes sense to them. And the better you can kind of empathize to that point of view and and understanding that along with it, the better you'll be able to collect the data that either supports that or discounts it in a way that that person is going to be ready to hear.

[01:04:21] To his point of asking questions, you told a really good story in your book about I think it was like a military general Air Force general maybe, but the way he asked questions. So how can we make sure that we're not asking questions in such a way that we're almost setting up the response to get an answer that will conform to what we want to hear?

[01:04:43] Yeah, well, I think.

[01:04:47] The more specific, the better you don't ask people, you know, Kubernetes, how is your ride one to five stars? Well, on one hand, it gives them a good sense of the extremes. If someone had a terrible ride, they're going to give it a one. But most people are going to probably give it a five. They don't want to just kind of don't want to set people off. You don't want to want to make sure that drivers like them, whatever. So you're probably not going to get a lot of good Data if you're only asking for one to five stars, even though that's a very, very common way of looking at it. The more specific, the better, you know, what was your favorite thing about your ride? Oh, know if it's a restaurant review, what what did you have, what was good about it or now of course, the more specific the question, the less easily rationalize the borders to a tabular system, the less likely you are to get responses of people. Are, you know, one of the big challenges for data collection, I'm sure these days is that people just don't want to do it. They skip the survey. They don't do it. They everyone wants your opinion these days. It's the opposite of the way it used to be where nobody cared. And so you're getting equally bad inputs, probably because you're only going to get the extremes.

[01:06:16] Anyway, I think.

[01:06:20] Open questions are better than closed questions and open question is a question that is asking something that doesn't have a defined answer. Yes, No. One to five what have you, although, of course, the more open the question. The less easy it is to tabulate your Data, so I'm sure there's some kind of sliding scale between one and the other. Your listeners are probably familiar with the net promoter score, which does one of each and ask for a number. And then it asks for a simple question, what's the primary reason for your score? And I think that's a really good combination of quantitative and qualitative. But it's it's hard work, but I think the best place to ask those questions is when you're asking your customer, your Data customer, because that's the person that you probably have a personal relationship with. That's the person that you can sit down with, have a coffee with and really explore and maybe propose. Well, what if we had to say, you know, what if we had what if we asked this question? What if we asked that? What if we actually observed? Because behavior is more interesting than what people do is more interesting than what they say. What if we actually were going to take a day and go and observe users in a field or we're going to actually do some real deep, you know, observation? Whatever those things might be, I think there are so many variables, it's really hard, it's a hard job. I don't envy it.

[01:08:03] So speaking open questions, this brings me to my last question before you jump into a quick random round here. Um, it is one hundred years in the future. What do you want to be remembered for?

[01:08:14] I'd be happy if I remembered at all. That's my answer, I'll have better answer that.

[01:08:21] I said acceptable answer.

[01:08:23] That's open, open, open question. Right and wrong answer. There you go. I go into a quick random round here. If you were to write a fiction novel, what would it be about and what would you title it?

[01:08:36] I don't know, because I've actually been wanting to write a fiction novel and I've been thinking about that and I don't have any usera been thinking a lot about it might be science fiction. I like I don't have a title because usually the title comes after the book.

[01:08:57] When do you think the first video to hit one trillion views on YouTube will happen? And what will the video be about?

[01:09:06] I don't know what's there hasn't happened yet.

[01:09:09] No, not yet. I think the most viewed video as of like the beginning of November, twenty twenty is a baby shark. And that is something with like seven or eight billion views, billion years.

[01:09:24] Well, it'll probably be equally amazing and probably even dumber than that.

[01:09:31] But how about this?

[01:09:32] What do you believe that other people think is crazy?

[01:09:37] I think I mean, the things that I've noticed that have gone viral or viral like that are just really unique. I remember Gangnam Style. Hmm. Something it's going to be something we couldn't predict. That's all I can guess. Something that was totally out there. Baby shark is a good example. That's I can't depend on. Sorry.

[01:09:56] Yeah. No, no, no. No worries. So. So what are you currently listening to on repeat?

[01:10:02] You know, I got my white noise up to drown out whatever is happening around me. So what I'm listening to repeat is thunderstorms and rain showers.

[01:10:14] That's awesome. Let's go to a quick random question. Generated a couple of questions out of this thing. All right. So first question, another random question, generator. What was the last book you gave up on and stopped reading?

[01:10:28] I oh, wow. I don't remember to skip this one. Yeah, I honestly I mean, I usually finish what I'm reading.

[01:10:35] If you could live in a book TV show or movie, what would it be?

[01:10:40] Probably live. And this is us because it's my watch with my wife. It's such a such a meaningful family show. You know it.

[01:10:48] Oh yeah. My wife and I. It sucks that it takes forever to get on Netflix like it takes like a year and a half for the seasons to like show up on Netflix. But we definitely watch our show. I probably live in there. Yeah, yeah, yeah. And that cabin that he ends up building at the end of the fourth season, I'd love to live in that thing. What is one of your favorite smells. Coffee now. Same here. What benzer mind.

[01:11:14] Every time you think about it, it's got to be when I look up at the sky at night and I see all the stars now just far away, they are just vast. All the space in between them is.

[01:11:26] Yeah. And I definitely do. So how can people connect with you and where could they find you online.

[01:11:33] My website is explainer dot com xbla and e r dot com and you can send me email through there. I invite people to check with me on LinkedIn as well. You find me there.

[01:11:44] Dave, thank you so much for taking time out of your schedule to come on to the show. I really appreciate you swinging by and talking to us about your book.

[01:11:50] My pleasure. Thanks for having me.