The Human Behavior Podcast
Do you ever wonder why people act the way that they do? Join human behavior experts Brian Marren and Greg Williams as they discuss all things human behavior related. Their goal is to increase your Advanced Critical Thinking ability through a better understanding of HBPR&A (Human Behavior Pattern Recognition & Analysis.) What is HBPR&A? It's a scientific (and fun) way to understand and articulate human behavior cues so that you can predict likely outcomes and it works regardless of your race, religion, political ideology or culture!
The Human Behavior Podcast
"Anything Can Happen" is a Myth
This week, we're debunking the myth that "anything can happen."
In today's episode, we'll explore how adopting this mindset can increase uncertainty and cognitive load—especially in high-risk environments—and how it might set us up for failure. Instead of believing that "anything can happen," we'll focus on reducing uncertainty by deepening our understanding of human behavior and utilizing practical tools like game theory, probability, and Bayes’ theorem.
Join us as we dive into why strategic thinking, modeled through games, is essential for real-life decision-making. We'll discuss how you can leverage both the knowns and unknowns in human interactions to predict behavior more effectively, minimize ambiguity, and ultimately make better, more informed decisions. Whether you're involved in law enforcement training, making everyday choices, or viewing human behavior as a strategic game, this episode is packed with insights to help you think sharper and be better prepared for whatever comes your way.
Thank you so much for tuning in! We hope you enjoy the episode. Don’t forget to check out our Patreon channel for additional content and subscriber-only episodes. If you enjoy the podcast, please consider leaving us a review and, more importantly, sharing it with a friend.
Thank you for your time, and remember: Training Changes Behavior!
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Hello everyone and welcome back to the Human Behavior Podcast. This week, we are debunking the myth that anything can happen. In today's episode, we'll explore how adopting this mindset can increase uncertainty and cognitive load, especially in high-risk environments, and how it might set us up for failure. Instead of believing that anything can happen, we'll focus on reducing uncertainty by deepening our understanding of human behavior and utilizing practical tools like game theory, probability and Bayes' theorem. Join us as we dive into why strategic thinking modeled through games is essential for real-life decision-making. We'll discuss how you can leverage both the knowns and unknowns in human interactions to predict behavior more effectively, minimize ambiguity and, ultimately, make better, more informed decisions. Whether you're involved in law enforcement, training, making everyday choices or viewing human behavior as a strategic game, this episode is packed with insights to help you think sharper and be better prepared for whatever comes your way. Thank you so much for tuning in. We hope you enjoyed the episode. Don't forget to check out our Patreon channel for additional content and subscriber-only episodes. If you enjoyed the podcast, please consider leaving this review and, more importantly, sharing it with. Thank you for your time. And remember training changes behavior.
Speaker 1:All right, greg, we'll get restarted here now that I think I have my audio issues. Um, so, hello everyone. We're having some problems, uh, getting started in the recording this morning, but we have a great episode for you, and so, big picture topic that we're talking about is this anything can happen and how it's a myth as far as I'm concerned, and what I mean by that is you know, we talk about different interactions from humans and people make observations that, well, they could do anything or anything can occur. You know, we don't know what's going to happen and a lot of times it just simply isn't true. Now, if you're trying to predict you know some black swan event, some major thing, you know that's really hard to do, right, and you see that in, like you know economics or you know finance, different areas like that where they you know you're trying to someone capitalizes on something that that's a rare occurrence and they were like the only person that saw it coming and it's so rare. I mean, we're not talking about this thing. We're talking about, you know, basic human interactions, what you can predict, what, what's likely, what's unlikely, what's known versus unknown kind of thing.
Speaker 1:And the idea is, when you have this approach, my biggest problem with people saying, well, anything can happen, um it, it. The problem with that is that it increases the level of uncertainty, especially in anything like a high risk situation or some extreme situation, and therefore it makes it harder to anticipate likely outcomes. Meaning if I go in and I'm going up to contact someone, Greg and I'm going, oh man, anything can happen, I'm not sure One it increases the uncertainty level, increases the anxiety level, cognitive load and my brain's all over the place.
Speaker 2:Exactly.
Speaker 1:So it increases my cognitive load, and so this is the big thing that we talk about with our behavioral approaches, with HBPRNA and how we leverage it to reduce the uncertainty right.
Speaker 1:So I don't want to increase it, I want to reduce what's uncertain.
Speaker 1:I want to reduce what's uncertain, I want to get rid of unknowns, I want to focus on the things that matter. So that's what we do and what we train people how to do. But there's a lot that goes into it and I want to hit on some of the kind of big picture topics that we don't typically explicitly get into. But that's kind of what we can do here on the podcast, versus covering this stuff in course or like in a training course or something like that. But you know, we we use things like game theory and probability theory and and Bayes theorem, and we'll define what, what all that means for everyone, and because we stick to the science and we use it in a manner what I think for, for, for which it was intended, right and and an actual use case, in a sense that I'm not a mathematician, I'm not a high level expert in those areas, but I know them well enough to use them in what we do, right and I can point back to them and saying this is where this comes from.
Speaker 1:So there's a, there's a, there's a lot we're going to get into in there. But I really want to. The big thing is really sort of debunking this myth, this idea that, well, anything can happen, or you don't know that. It's like, well, yeah, no, you do know that, and then get into things.
Speaker 1:Um, what we get into human interactions is sort of as like using games as an analogy, and we'll talk about that not just game theory, but but games and how they reflect life, and then, in a certain manner, you know, in what we're talking about today, can help your ability to help your predictive analysis abilities, right. So, and when we're getting into everything I just brought up with, anything can happen sometimes, you know, knowing what you might not know what's going to happen next, but knowing what isn't going to happen or what's unlikely is helpful, Meaning going like well, I know none of this can happen over here, so I really only have to focus on these five things instead of these 50 things. So that's that reduction in cognitive load, that's a reduction in uncertainty that you're talking about, and now I can account for this. So I'm kind of talking about this, this big picture, but let's start with uh, I think we should start with games, greg, if that sounds good, so let's comment on it.
Speaker 2:Yeah, let's talk about what you just talked about first, because that's a great intro, and so this is my continued argument for improving law enforcement training and simulations, because what happens is we're focused on motor learning and motor control and speed all of these elements that are not going to affect your decision making when the time comes, and I'll give you an example of that. You just talked about reducing uncertainty. So I saw a guy yesterday on a LinkedIn post that was drawing from a paddle holster that was appendix carry, fired all the rounds safely and quickly, and it was in the two second range that he emptied his mag into a target. Okay, so do me a favor. When will that reduce uncertainty? That will reduce uncertainty at that one time in that person's life where the rotor hits the spark and that oxygen hits the fuel, and it's a thing where you have to draw, outdraw an opponent and fire all the rounds in your, in your weapon.
Speaker 2:You know, I was a cop for 30 years. That never happened to me. Now, how many cops on the street has that happened to? And the idea is that you think you're doing great training and I'm great with that type of training. But look at the Olympics. The Olympics is full of people that specialize in one thing for their entire life. For the likelihood that that's going to come around, and that's not how things work, and that's why I just want to throw that on the table and I want to say world according to Greg.
Speaker 1:That's actually a great way to, because we're using this games theory and games as an analogy. But that's actually a really, really important distinction and we'll get into how we define what games are Exactly. That's a very these analogies where it comes from sports performance to now we're going to talk and carry that over in like military or law enforcement or high risk situations. It does not translate it, just does.
Speaker 2:It can't translate because it's not the same. What you've done is you've taken Monopoly and you've taken checkers and you're reading me the directions to play Monopoly and handing me a checkers board. It can't converge, you know.
Speaker 1:Because what you talk about is the scope. The scope is so limited In a 100-meter dash, that's it. Like there's no—you get to focus on one thing and there's a ton going on.
Speaker 2:Don't get me wrong.
Speaker 2:It's not that it's not a complicated skill, but it's nowhere near as infinite as the potentials that could happen in something like human resources or police work or being a teacher. So my additional argument for improving law enforcement is that you have to understand the general limitations of a problem, limit the potential solutions, and what I mean by that is simply the probability theory. And most people say, well, probability theory, mathematics, this and that and the other. Well, I'll tell you this Discussing the likelihood of everyday events, like the chance of rain or the probability of winning a game, make these huge mathematical theories and principles more intuitive for the students to grasp. And that's why, when we're doing like a briefing, you always see me use a slide about snow and lightning and fog, and the reason I do that is if you can predict them, you can predict likely outcomes right. So what I'm trying to do is, instead of making the problem bigger, I'm trying to clear, make the outcomes more clear so you can better understand what probability means. So we talk about pattern recognition and analysis. That means we predict likelihood and teaching tools when you give a practical example like, we predict likelihood and teaching tools. When you give a practical example like uh, uh, you know how this is going to work makes more sense to a person. I'll give you an example. So you know, I go shopping every week and I go shopping at the same time, the same store. There's tens of thousands of choices that I could make in that store, but somehow I navigate every aisle, take the items that I want and want and I come back. So, even though there seems to be an infinite amount of choices, there's literally a finite number of items that I select from, and my predisposition guides me that way.
Speaker 2:Now you talked about games. So what's the difference in games? So the elements of a game are that you have decision makers, the players. Then you have their actions, so the choices that are available to them, and then you have the information or knowledge that they go in with or that they learn while they're playing the game based on their opponent. That's exactly what you're doing at the grocery store, but there's not an unlimited amount of choices. There's a finite number, even though it's a big number, brian.
Speaker 2:And so when we talk about that, why is that important? And that's just touching on games and game theory, very, very briefly, because we're going to discuss it. But what I mean by that is it seems overwhelming. Yet I navigate it every week. Law enforcement, with all the choices and the possibilities that could come up when you bail out of that car, from dispatch, from the RP, from the scene and the location and the weather and all those other stuff, seems unmanageable, it seems infinite. It seems like anything can happen, but at the end of the day anything can't happen. As a matter of fact. A great thing about probability theory, and I don't want to get deep into math. But it's zero or it's one, it's going to happen or it's not going to happen. Now you know how many variations there are between that zero and that one. But guess what? They're not infinite, they're finite.
Speaker 1:Look, physics limits the number of things that can happen, yeah, unless you want to get into the mathematical argument about infinity and our grasp of it.
Speaker 2:But how many?
Speaker 2:theoretical arguments can be made for that on the scene with an opponent, he's going to have a weapon. Well, a weapon can vary he's going to be aggressive or he's going to be passive. Aggressive or he's not going to be aggressive. He's going to be communicative or he's not going to be. When you start branching that, it's just like Wing Chun or just like martial arts.
Speaker 2:When you're practicing Akata or doing sparring, the person doesn't come in and drop a smoke bomb and then stab you with a sai and go. Hey, there you go, because that would be outside of the ken, outside of the realm of the possibilities that you're going to do on the mat at that time in the dojo. So training prepares us for as many of those contingencies as possible and it's up to us to choose which ones we want to do. So, instead of choosing the one-inch punch, you and I have chosen to spend our entire life on cognition, on thinking and out-thinking a cunning opponent. And that's literally what you're talking about is the difference between coming in with the mindset and you know I hate mindsets coming in with the mindset and saying anything can happen right.
Speaker 1:Yeah, you're setting yourself up for failure. So you started with games and you gave some of the core elements of the games and kind of defined them. About the players, there's rules there's information, there's outcomes. So can you, because games are a great analogy but far more significant than we think.
Speaker 2:In a sense, so can you give us like?
Speaker 1:the historical significance and what we mean by games.
Speaker 2:So, shelly and I just before Shelly left this morning, our CEO. I said, hey, I'm going to be talking about games today, and she reminded me that, 2007,. Uh, third Marine, connie Owee Bay. She said that's the first group of Marines you talked about, uh, with games, so bring that up. And I said, okay, I'll bring that up. Shout out back to the day, brian.
Speaker 2:But if you recall that class, when we walked in, we said that, okay, every culture on the planet has games. And then people paused for a minute and they started thinking about it because we had a. Marines are one of the most culturally diverse fighting organizations on the face of the planet. Right, okay, I learned the words I needed in Tagalog from a Marine, right, yeah, so games are also probably music is up there too one of the oldest forms of human social interaction.
Speaker 2:Okay, games are a way to teach and pass on knowledge and a way to store knowledge. That game on the shelf stores that knowledge, brian, just like a book at the library. And then, when we look at it ancient games, the oldest games that we know about. What did they teach? They taught farming and hunting and survival skills and social intercourse, how you meet other people, how you're supposed to act, and they helped develop this social and emotional and physical and cognitive skills, and so when we start talking about limiting stuff, okay, no matter how diverse games are, they all have a winner, a loser or a draw. They all have a set of rules that the people follow and no game is infinite. So somebody right now that's listening is going to go well, there's no rules in a knife fight. Fuck, yes, there are.
Speaker 2:You're just you know what. You went to the wrong dojo because there's a whole bunch of rules in that. You know, gravity still applies, physics still applies Distance time. So when you make comments like that, what you're doing is you're showing your naivety, and that's why we're still not happy with the state. Look, we partner with a whole bunch of companies and when we see the state of training in some places, we object to certain things that are still missing. Why? Because our locus of control is to this thing that's right in front of us, and then we forget, or absent thinking, because it's harder. It's harder, it's more obtuse, you know your, your locus of control.
Speaker 1:It goes back to actually, I was thinking of that with the mindset discussion we had this morning before we got on here. But, um, you know, what you're talking about is what humans think that they can control. So so if anyone's never heard term locus of control, it's just it's all external forces that they that plan out their life or or everything. I'm set up for failure and this. And people have a great, you know, internal locus of control. Really understand that like, no, I can change my life, I can I control the outcomes of my situation. So that that's what you mean by that. But you, you brought up some great points about games, because games are a. Throughout history, every culture has played different types of games.
Speaker 1:Right game, whatever chance skill, uh, physical skill, mental skill, whatever exactly and and with that, because they're, they're used as, like you said, a teaching point. They're, they're a model. They're a model for human interaction. So, you know, it's better if we just go do the, you know three day long booskashi tournament, rather than worrying about one another and fighting over everything, uh it's better because there's always an end state.
Speaker 2:Brian, there's always an ultimate goal in games.
Speaker 1:You're exactly right, spot on because it's when, when people go. I don't understand like people get so intense. Or how can you get so into football or soccer that you're going to be like? This is an extension of the values of your life, and and and yes, some people take that too far they let it. They let that sort of primitive reaction take over where, where they're all in on the game.
Speaker 1:And they're going to, you know you go to, like South America, where they I remember that, I can remember it was like the goalie uh, for one of the teams. It was murdered, you know, after he let up a goal where they.
Speaker 2:you know that happens often, yeah.
Speaker 1:And you're going like how does it get to that? This is insane. You're such a fan. It's like no, no, like this is a very primitive extension of the model of human experience and that person was so into that. Now they went too far with it, obviously, but it's not a large gap, it's not a big bridge to cross there.
Speaker 2:You wouldn't be surprised if you read that in an article. You wouldn't be surprised if you heard that and remember, look, shout out to Milo, because Milo was the first company to understand Hoberman and embrace it. And people are now coming around and thinking what's going on with it? Because we meaning Arcadia Cognorati, Brian and I and our partners we promote cognitive development in classrooms and in AI and in virtual, by role-playing and problem-solving and logical thinking. We value creativity. We force you to play it just like in a game, and in class we play those games. We involve strategy and planning and we encourage critical thinking and decision-making. We force them to recognize patterns and sequences so they understand the cues, so they can solve for X before they see X. And that's the difference. We're not seeing that in games now. No, no, Well, you know that's what training is. Training is a game.
Speaker 1:Exactly, I mean, that's what I just said. That's what training is. Training is a game. Exactly, I mean, that's what I just said, that's what it's a protracted game.
Speaker 1:Yes, it's a. It's a. It's a. It's a. You're modeling, you know, you're in simulating um, a likely future event, and you're allowing yourself that mental rehearsal. So you're, you're playing a game because you're, you, you, you, you're going to get to the championship maybe one day, or you're going to get tested on it someday, or there's going to be an opponent that's going to challenge you in said game. And so, game theory, I'll give it kind of like a quick definition of game theory, greg, and we'll talk about it because it's important to and real quick. You know, not getting into this to try to be like, oh look, how much shit I know, because that's not important.
Speaker 2:It's not what this is about.
Speaker 1:But it's about naming these things, because when we get into probability theory, game theory and especially Bayes' theorem, these are things you actually do unconsciously.
Speaker 2:These are already things that you do every single day.
Speaker 1:So if I can get some recognition and understanding of some of the elements of it, it can help me going forward. We'll get to that later, but I just want to. I don't want to come across as like no, no, no no.
Speaker 1:You guys just talking about some shit that doesn't matter, it's like these are things that you do. So, so, game theory well, game theory is, you know, sort of a branch of mathematics and economics studies strategic interactions between decision makers or the players in the game. So what it is? It's a framework for anticipating the actions of others and making informed decisions based on potential choices available to all the parties involved. So, at its core, game theory helps us understand situations where the outcome for each participant depends not only on their decisions, but the decisions of others. Participant depends not only on their decisions, but the decisions of others.
Speaker 1:So the idea it's a little bit more chaotic. Uh, in a sense, or or it allows for more contributing factors than just say, like a one-on-one, like your, your checkers game. Right, there's the is is nowhere near as complex as chess. Um, you know what I'm saying. So it's it's just a little bit different. So game theory really kind of can take that into account and the the same thing. You got the players and their strategies and information and it just like we talked about in games. But I just want to get that out there. No, no, no, no, so so allow you to discuss the. So what behind it? Really?
Speaker 2:Right. So so the the, so what listening to us? And so if the outcomes depend on the player and the actions of each participant, then it's exactly like police work, because you're a player in a game and you choose your action or your strategy and you have to take into account the choices of others. Now they may play their role first, and then you have to respond to it. So why is that any different? So game theory is a great way, and games are a great way to talk about that. So people will say, well, yeah, but on the mat, yeah, okay.
Speaker 2:So every game that has strength or coordination or endurance, it does the same thing and it's just as good for you cognitively and it forces you to do these things and requires manual dexterity and assist in your fine motor skills. So if you can find it in the world, you can find it in a game. You know what games do? Games evolve, brian. What does that mean? Games change as society changes and that means that as players get better, the paint and the amount of time you can spend in it changes, right, and there's a smaller goal and the goalie has a smaller area that he has to defend. So they make it more complex by adding these things to it, which is great. Which defines evolution? Yeah.
Speaker 1:The NFL right now. They just made big changes this season. For some of the kickoffs they just changed big changes this season for some of the kickoffs. Basically, they changed some of the rules on this for safety issues, because now people are bigger, stronger and faster than they were 100 years ago, when those rules came up with and they're going like. This is extremely dangerous now. So it had to evolve. The Olympics have changed.
Speaker 2:Things are added to the Olympics, Things are taken away from the Olympics and guess what? Just like in class, we're forcing them to challenge their memory. And then we have them perform when their concentration is challenged. And we force that in the class and in the training and in the practical application scenarios, and then we add different temporal elements to change the level of stress, just like in real life. Okay, and and you go. Oh well, every game does it. Well, jeopardy does it on TV. But you know what? The outcomes aren't that somebody dies. I've yet to see him take a two pound sledge and the, the person that comes in third, beat him to death on stage.
Speaker 2:The idea is that the consequences and outcomes are virtually interchangeable in life. Within a game, there's losers. The difference is that the loser doesn't die. Okay, we get that. But that's how you have to think.
Speaker 2:And the problem with a mindset don't get me started, but a mindset's powerful and it creates. I know I always start it Mindsets create realities and shape your thoughts and behaviors in very important ways. But the problem is they also create blind spots and they fuel biased thinking. And when left unchecked, they're harder to change because now it becomes a part of your behavior and your mindset starts to remain, even though you're consciously aware of other factors, and that's when it becomes an inhibiting factor. So if you start thinking of just the science, here's the number of reactions that might happen. Here's the finite number of things that could happen.
Speaker 2:I'm going to play this in a game because I understand game theory and I understand that there's finite constraints. There may be tens of thousands of possibilities, but guess what? That's still finite and it's a large set. But I can rehearse one of two ways I can rehearse 10,000 different moves in karate, or I can understand anatomy. I can go 2,500 punches with my right hand, or I can understand physiology, and that's the difference. The difference is that I can take a look at our training and our training is training us for every eventuality by improving our cognitive acumen and improving our ability to assume what might happen next, and create an ML and an MD co.
Speaker 1:And that's the idea of it is what obviously we want to get people better at, you know, predicting behavior. So you need some sort of tools to use this, and this is these are the, these. What we're talking about today are the, the foundational elements of the tools that we use. Right, and we go OK, knowing this, knowing meaning, knowing these things about science and math, right, yeah, this is what's sort of known, so. So then, how do we use them? Now you can use those different tools, right? So that's the idea, and that's where you have to come in with something. I can't stand there with a calculator you know what I mean in a situation, greg and figure out what's going on. So training is for. So training helps me. That's what you're doing Exactly.
Speaker 2:So training helps me Exactly, but training helps me understand that a calculator and a slide rule are amazing tools that I can have at my disposal, but they're not going to make the decision for me. It's still up to me to make the decision and to choose what the ultimate eventualities are of a situation, and you know that's why, when we do training, brian, it doesn't matter if it's raining or if it's snowing or if there's a tornadic situation that's going on. I'm moving my location.
Speaker 2:Yeah exactly, and it doesn't really matter about all those other factors, because those factors are going to occur in real life too. And that's the amazing thing is that a simulator can do so much and we're not using it to its capability many times. Right, because practical examples, simulations, experiments. They're very effective because that allows a student to see that there's randomness, that's surrounding chaos, right, but that certain patterns emerge, no matter how chaotic a situation is, and that's the magic.
Speaker 1:And I didn't really want to get into the randomness yet on this episode because there is another one, but it's an important thing to bring up as we're talking about all this and probability and what we'll get into next with Bayes' theorem. But the idea there is, there's a lot of randomness in the world and because humans are primed for pattern recognition and we want to put things together and understand it and we don't want surprises, we don't want uncertainty, you know we'll often attribute value to things that really have are insignificant and completely random, because there is a ton of randomness in the world and so we can, we can sort of get that can cloud our judgment, which is why I have to be able to account for that. But you know the big, you know again. So the, so what. On that game theory, what we're talking about is really just balancing those knowns and unknowns. Right, we'll define what that means. But you know that this is the predicting behavior.
Speaker 1:Understanding interactions as a game allows me to model that in a number of different ways. It allows me to to actually have these conversations and you know, because everyone does the, the what-if scenarios or we'll do. You know people call them tdg, sometimes a tactical decision games, or I'm going to give you a set of circumstances and a set of constraints and you tell me and we're just going to walk through on a whiteboard, okay, then I'll allocate these resources, resources here, then we can do this. Okay, well, what if then this occurs? Okay, so these are all all great, great things. Those, those are actually far more powerful than they're given credit for, because a lot of times they're just not set up correctly. So because, because I have to understand you know what are the what's the likelihood of these different situations occurring, and because I remember, even a few years back, even running or still running, some, some tactical training, and it was a big ending exercise, and there this, this team, the couple of teams that were going through it, were doing an absolutely phenomenal job and, like beyond what we thought, like surprised us during this final exercise, and we were like, holy crap, they're really, they are killing it and they had great comms.
Speaker 1:They had everything set up, they're task organized, they're doing so well and it's great plan, right, so then what do we have to do? We're just like, all right, well, let's just, let's just see how far this goes. And so we obviously started coming up with ridiculous stuff and even all these problems, to the point where they're like yelling and getting frustrated. And then at the end, when we went to do the debrief, they thought that they had failed. And you know, I had to start off with like all right guys, that was the best team we've ever seen come through.
Speaker 2:Wow through like confusing.
Speaker 1:Like what do you mean? Like, like guys, like we were making stuff up at the end, like we, just we had enough time and enough to do it. So we just said, like jesus, how far can these guys go because they, they did it so well? But but the idea is like that that we, we, we get that wrong. Sometimes we're coming up with a what-if game. So this is trying to help that that sort of what-if game to, to keep it within the realms of the possible, and then you know, you know you're going to get a lot more value out of it. So what?
Speaker 2:you did there too. No, no, just to add to that what you did there. Everything is evidence-based, just like you know. Absolutely overused term, right, but the?
Speaker 2:idea is we do, and I can see it and feel it and taste it. Okay, but the idea is that what you did is you were conducting an experiment. Yes, so what you did is the experiment yielded results and you can lift and shift fire based on those results. So it's not how much faster that you can get through the scenario or how quickly you can win. It's what you learned from that win or loss, what you learned from that tie game, what you learned from that win or loss, what you learned from that tie game, what you learned from playing against this opponent rather than another opponent. And if you can pay that knowledge forward, that's the key. Look, what's Bayes' theorem tell us and I know you're going to get into Bayes, but let's do it real quick.
Speaker 2:A street definition of Bayes is simply this you have to update your probabilities based on new and incoming information. And if you're not constantly doing that because we have certain assumptions, brian then all of a sudden we're in a situation. Dispatch told us this we get out of the car. Yeah, there is in fact an argument that's going on and you know what? The guy that we're talking to, that we think, is the RP. He's the guy that's killing everybody in this scenario or whatever real-life situation we're facing. So we have to update that, and we have to update that quickly because as that prediction, or as that information changes, your prediction of likely outcomes change. And if you can't do that and people go, well, isn't that like John Boyd Zootlew? That's like every critical thinker that's ever lived? Oogluck, when he came out of the cave with a wood sap, he had the same realization. If I don't update, then what's going to happen is I'm going to continue to stay on the gas coming into the turn, I'm going to overrun my headlights and guess what? I'm going to crash.
Speaker 2:So Bayes and Bayesian thinking has always been a root of Greg's experience. I hate to talk about myself in third person, but look, I'll tell you how profound it is. You and I met when you were coming in and out of combat zones and you were part of a training evolution that I was doing. And you go this guy's full of shit until you started trying some of these and then you found out wait a minute, it makes me faster, smarter, harder to kill. So it's not about me. I just happened to be the guy that introduced you to the right book in the library. That's what this is about, brian. What I think our primary job is is to create a legacy of opening eyes on people that didn't see it that way, before handing out those flashlights, so they can search the the box instead of going outside of the box.
Speaker 1:In all fairness, my, my reaction was actually oh my god, this guy's fucking hilarious and okay and he's completely full of shit.
Speaker 2:But he's the two-point standard that you had like. It was like okay like he's a.
Speaker 1:He's a bullshitter. I I got plenty of buddies like this.
Speaker 1:I've met people like this before and then I was like oh wait a minute is hang on, there's something going on here and to to to kind of um, to further define, I guess. Or we're talking about the cause, you, we brought up Bayes theorem and this is another great example of something you unconsciously use every single day of your life, right, no-transcript? Then you have an updated belief and there's a million different studies like this and I've used ones before in class where they'll give someone some information or they'll say find out what everyone's beliefs are, and usually in something that's a very like politics are a great one because a lot of people are very set in their ways and how they look at certain things. They'll take a political issue and then find out which side of it you're on, and then they'll force you like hey, do like a 500 word essay on the opposing viewpoint and then all of a sudden, when they have to do all that work, they kind of go their. Their initial viewpoint was like, oh man, like I guess I wasn't taking into account all of these other things, and even to the point where I did.
Speaker 1:The one from today was I'll put it in there. It was an interesting one because they use a great example about, about our prior beliefs and the different kind of how sometimes we we are overconfident and when wrong, or sometimes not confident in the things that we do know, and that's the two sides of the coin that we're talking about right here. Yeah, exactly, we're going, we're going. This is a lot more complex. There's a lot behind this and someone's listening going man, you're talking about all these mathematical stuff. I don't understand this, or what are you getting at? It's like no, no, no, no, no, no. You actually do know this. They use a great example is you know? You walk up to someone and they go.
Speaker 1:Hey, do you know, do you know how a toilet works? And they're like, yeah, and then they go, well, can you explain it to me? And they're like well, I, I just kind of push the handle and flush it. Actually, I don't know how a toilet works, Right? So so we, we have this. Yeah, I think I understand it. The cell phone is phone works. I mean how it actually works. Almost no one can, and we're past the point of even getting to the base, because it's evolved so quickly, past what original cell technology was, versus a landline Like. It's highly complex, but we know how to use it right and that's all that matters to us and that's actually what HPP RNA is really.
Speaker 2:It's simply.
Speaker 1:Exactly. I don't care if you can tell me all of this stuff. I want you to be able to use it, but understanding some of the big picture concepts are really important.
Speaker 2:Yeah, I absolutely agree. So let's go back to Bayes and Bayesian thinking and let's talk briefly about how it impacts your life every day. So I'll give you a fail in Bayesian thinking. Every single year that I've been alive, I've done an article or a report or talked about confined space entry death where methane gas has built up and the farmer goes down to clear out the vent. He dies, then his son, then his wife and the whole family is dead Every year. Okay, that happens Every year. During graduation.
Speaker 2:I do a story about a car full of kids that go out and they're not harming anybody, but the car hits a tree and rolls over and does it. So Bayesian thinking is a form of high-speed hypothesis testing that says, when certain pre-event indications coalesce, I have to update what I thought was going on. The kids are just going to a party, they're just going to go out for a drive. Maybe it's methane gas, maybe I don't see it. It's colorless and odorless and therefore that changes the likely interaction with the environment. Right, and so the? The adjustment of expectations is huge. So what do I mean by that?
Speaker 2:Everybody that's a cop that's listening to this, everybody that's HR, or if you're a teacher or administrator at a school, you saw a behavior change and it was profound and it was fundamental. And all of a sudden you said, well, you know, maybe it's just because it's Valentine's day or whatever else, and you didn't account for it. And then you saw another thing with the same person or situation, or environment or financial, it doesn't matter what the baseline is and you didn't account for it. And then, all of a sudden, here was this failure. Something went catastrophically wrong. That dysfunction showed itself. And then we looked back and we said you know what? Every one of those things was present. I just didn't account for them.
Speaker 2:So that predictive analysis to update your probabilities based on the new and incoming evidence is based. That's the root of Bayesian thinking, but it's also probability theory and the beauty is it's also game theory. So each one of these is intrinsically connected to how you process information. And if you fail to see how the breadcrumbs coalesce, if you fail to see that gosh damn cottage in the wood with a lady with a cauldron going, come in, have some candy, then you're going to die. I know we make that oversimplified, brian, but we do it for a reason. So you go.
Speaker 1:Hey, I know what he's talking about and with there's a thing to add in here with all of this, is that there's a few things One, you One, statistics, probability theory, even Bayes theory this is the most, I guess, the most newly defined parts of math, meaning math's been around forever, it's just existed, and then humans kind of understand it as time progresses, right. But the reason why it's important to understand some of this stuff, at least at a theoretical level and big picture level, is it's important to understand some of this stuff at least at a theoretical level, you know, and big picture level is it's one thing. I was saying class, like humans, we don't intuitively understand probability. We really don't like we intuitively understand physics. If you never got taught anything about physics, you still understand what gravity is. You still understand what force equals mass times. Acceleration means, right. You implicitly understand that because it governs the way you, you, you, uh, go through the world, right?
Speaker 2:Locomotion, balance everything. Yes.
Speaker 1:But with this stuff, it's, it's, it's, it's not. This is not an intuitive way of looking at things, because the intuitive way of looking at things is simple, it's survival-based, and it's what I know in front of me and sort of the reason why Bayes' theorem is so powerful too, because it's a little bit different, in a sense, of probability theory. That probability theory is very. There's a lot of rigor, it's very mathematical base and it's a lot of axioms. There's a lot of rigor, it's very mathematical base and it's a lot of axioms, right, whereas bayes theorem kind of allows for more subjective observations to be put in right meaning, you have different experiences than I do, so so you can use this kind of model, um and, and you might get a more robust or different answer than me and yes we're.
Speaker 1:We can both be right in a sense of what we think it is, but maybe yours is more right than mine.
Speaker 2:You know what I'm saying, right? But I can also use that same tool, those three tools, to transfer my knowledge and experience to you, and I do that by playing a game. You and I do that by playing a game. So what is a practical application scenario? It's a game. There are players on both sides, there's an outcome that we think is likely and people have to use strategies to negotiate the rules that we put into place. Okay, don't look now. Now watch. This is a day in the life, those type of elements that we put into it. And let's go back to how long this has been important. Musashi said Miyamoto. Musashi says you win or lose before ever drawing your sword. Musashi beat people with a bodor. Musashi beat the best samurais with the sheath from his gosh damn katana right.
Speaker 1:If you've read Sun Tzu, then that's Bayes' theorem, exactly Everything he says.
Speaker 2:So let's talk about that. So why is there such an impetus in in now that the curiosity and the training and everybody that we listen to that that's putting out great stuff? There's nothing that somebody's putting out that's wrong but it's locus is on motor control. Why? Because we understand motor control, we understand sympathetic and parasympathetic exactly.
Speaker 2:But the problem with when we're talking about cognition is we don't completely fully understand the brain. We don't understand all the corticles, we don't understand even what sections of the brain are responsible. So it's mysterious, but it's not. It is Because, if you look at science, if you look at nature, how does nature warn us about winter? It gives us fall. How does winter or nature warn us about the time to plant? It brings us spring. Do you see what I'm trying to say? So it forces us to learn by outside experimentation. And the more times that we go through those, brian, the hypothesis testing, the better we learn. And so Bayesian thinking is hypothesis testing. So I'm in this pursuit, but this guy's taken way too many chances. So what are my possibilities? He's drunk, okay, but he's holding it together pretty good. Maybe it's drugs on board, okay, but maybe he's got a hostage and maybe it's this. Now what happens is those few decisions become crystal clear on what might be going on.
Speaker 1:And you're talking about it right there in the moment. But I also have, in that specific example, historical precedent. What happens the longer that pursuit goes on.
Speaker 2:Does it get better? Exactly.
Speaker 1:Do the potentially good outcomes increase or decrease over time? Because what historical precedent says is that it gets worse the longer that goes on the more likely this is not going to go well. Right and so that informs the decision making, and that's a perfect example of how, right there in the moment, I'm constantly updating my hypothesis.
Speaker 1:Of course talking about is trying to be more aware, or, you would say, mindful, of this process so that I can actually uh get better at it and and and that's sort of the the, the way these things coalesce of, of games, the game theory, and bay, bayesian or bayesian thinking, and uh and you know that I I call it bayesian only based on the fact that's the way I was trained and taught, and you know that I call it BSing and only based on the fact that's the way I was trained and taught.
Speaker 1:You can use either one, I think.
Speaker 2:G-Rad and Amanda Miller. Right, I mean, I respond to the way that I'm trained. And, brian, I think your point is so important. I want to make sure that you clearly make it.
Speaker 1:Yeah, yeah, no, and when these things? The reason why we're talking about all this together, I think really is what you're constantly trying to do, especially in complex situations. Now, not just complex situations. Now add in that there's potential danger involved in that complexity because, like you know, a market system or figuring out what you want to do in life can be a complex situation, meaning there's a number of inter and intra dependent factors that affect yeah, of course.
Speaker 1:And you don't control them all. Right, that's the thing. Hey, the bet, the bad guy gets a vote too. You know what I mean. They, they get, they get a say in what's going on in the situation too, and you don't you? You, you don't get to how much influence you have over that is is finite.
Speaker 1:But what we're, what we're talking about is is balancing the knowns and unknowns in every interaction, in every human interaction, in every way, every situation you go into. So we've been talking about it from real situations, from training situations and just cognitively how we think as humans. And you know, you kept saying hypothesis, testing and that and that that's the best way to do it, and that's what games do as well. Right, so so that that the football game or the college NFL, whatever, when they're going up against their opponent, they've studied their opponent, they've studied what they do, what, what their strengths and weaknesses are, and then I have to compare that against my team strength and weaknesses and how I'm going to play against that and and and really play to my strengths and try to try to uh, uh, you know, eliminate them from exploiting my weaknesses. And then there's a little bit of randomness in there.
Speaker 1:If that temperature all of a sudden drops 30 degrees that day and maybe my team is more used to playing in warmer climate, the rain on the field, there's an injury right before the game where someone who's a top player gets pulled out and they have to sit that game out. That's where that stuff really starts to affect it. To sit that game out, that's where that stuff really starts to affect it. But it still comes down to at a basic level is if I get good at identifying knowns and unknowns. And so the knowns, that's just understanding and recognizing different patterns, established behaviors, environmental cues, everything that we talk about, and I want to increase as much as what I know about a search situation to reduce the uncertainty. So I don't want to throw in there anything and then I can compare that to what don't I know right.
Speaker 1:And now I have the comparative baseline. The question that you have to ask yourself, and this is Bayesian as well to update.
Speaker 2:The question that you have to ask yourself and this is Bayesian as well to update is what am I missing here? Okay, this guy's driving like I've never seen anybody drive before. This person's fighting harder than I've ever seen anybody. This person, no matter what I'm telling them, they want to jump off that bridge or hide that evidence or do whatever else. What am I missing? There's something here. There's an environmental, there's a piece of information, no-transcript. Okay, look, that's the jack in the box.
Speaker 2:We try to reduce the jack in the box every time that we do the training, but guess what? Because there's a spectrum of potential possibilities. That's always a possibility. But if you only train for that, how is that affecting your de-escalation technique or the use of cover or all the other things that are infinitely important as well? So if you just look at that and go, yeah, but that can happen, then we're right back to the theorem that you posited at the very beginning of this.
Speaker 2:Well, anything could happen. No, that's one of the things that could happen. So, yes, I need to be ready for that. But you know what? Every single day, there's encounters exactly like that that don't end in a fatal shooting. What we've done is we've upended the apple cart and we've only taken a look at those things because they're fun and they get clicks and people want to know them the fatal stuff. You see what I'm trying to say, and the more that you see that that limits your options too, because that creates a what Brian A mindset you know, yeah, and, and it, and it's, it's it.
Speaker 1:We don't implicitly, you know, recognize these things when they're laid out in front of us. It's a dude, this is not a big deal. Look, yeah, you rolled through a stop sign, but like that's not. You know, it's not the end of the world, it's just. There's a school here and I want to maybe talk to like, hey, did you get that stuff done for your math assignment or whatever. And then all of a sudden she goes off the top. I told you and I was like well, this is not a typical response. There's clearly something else going on and there's some other thing that she has on her mind versus the question that I asked. And that dissonance, that disconnect there means okay, there's something else here that I need to investigate, or get some time and distance and come back to that and find out what else is going on. But that's the thing, it's not just the well, that's weird. Or hey, don't talk to me like that, or what are you doing?
Speaker 2:Right.
Speaker 1:There has to be that instant recognition of I'm missing a piece of information that's critical right now. Right, I may need to get some time and distance right now and figure out what that is before I make my next decision. And that's the point where we don't, but we don't do that. In those we don't take the non-centered observations in general, as humans, those are most likely the marginal information.
Speaker 2:The space between the words and the paragraph that you're reading are as important as the words that you're reading. And we don't do that. We don't do that holistic approach. Again, back to Hoberman and why that Hoberman sphere is so important because we got to make that problem a 360. We've got to take a look at that. And when we talk about predictive analysis, we're talking about being able to recognize patterns that would tend to show a reasonable person that a thing's going to turn into a shit sandwich or things are going well, and Bayes tells us to constantly update that.
Speaker 2:And guess what, if you're in high-risk encounter after high-risk encounter and it's unknowns traffic stops are an unknown, domestics are an unknown suicidal subject, an unknown medical, mental all of these are unknowns. You've got to be able to make a fast, intelligent, informed decision. That's on an unpredictable set of circumstances and it has to be legal, moral and ethical. So where are you going to do that? On the street? Are you going to do that on the street? No, you do that in a game. And the more that you do that in a game and the more that you start at the academy when you're a kid and it matures during your FTO and when you're old. Now you're the gray-beard street vet and you reinforce those Brianrian. Now that becomes a way of life and habits are hard to break.
Speaker 1:Habit over mindset any day and I mean that you know me yeah, and and so let's, let's so. For the purposes of this discussion, then, um, we let's, let's talk about knowns, because my argument is especially like you know, you're giving these law enforcement examples and I tell this every course we go to or every time I've trained or worked with whatever. I mean that was even the first time when I uh, I mean like he's obviously had a military tactical government contracting background and then started working with law enforcement as well. Right, and I'm like my thing was holy shit, these folks know more than they realize.
Speaker 1:Like your knowns are. So you gather so much tacit knowledge and experience and that's anyone with any like subject matter expertise in anything right. I don't care if you're a pilot, I don't care if you've been doing you know HR your whole life. I don't care.
Speaker 2:Lawn maintenance. It doesn't matter. You're exactly right.
Speaker 1:You're exactly right, you know so much more and those get talked when you get into the science of, like you know, intuitive decision making and subject matter expertise. Right, that's all there. That's, those intuitive decisions that people make are based on their selected priors, based on those really good cognition biases that they've developed through experience. But I, you know, rather than because this goes into the argument of people like, well, what do I need to look for and what do I need to do, and it's like no, no, no, Focus, focus on vanilla. You even said it. The margins in the paragraph, the piece of paper.
Speaker 1:It's written on the title of the book, the name of this chapter.
Speaker 2:The dust on the spine of the book and where it's at on the shelf, in which room You're exactly right, those all are interesting and you can pull those out right.
Speaker 1:I can contextualize my knowns of my past experiences to carry me forward, right. So, rather than learning the lesson of okay, if I ever run into that situation again, you know I'm not going to do that, or I'm going to go to this right away, or next time I go to a call and I see that same, you know a woman in a mental health episode doing something I know I'm going to have to kill her. It's like no, no, no, no, no, hang on Wait a minute.
Speaker 1:That's. That's not what we mean, and I'm oversimplifying it in the sense of people go well, yeah, that's not really what happens, and I'm saying, yes, it is what happens. That's actually what happens is we don't learn those lessons because I don't unpack my knowns and so the better I get at articulating all of my past experiences and what occurred and the decisions that went into it, so meaning I'm getting this from, from taking everything we're talking about, and rather than trying to say, all right, I'm going to go out today and I'm going to use Bayes theorem, I'm going to use probability or game theory, so I should look at everything as a game. It's like well, hang on. Before we get to that, go back. Go back to your own personal experiences in your life. Now I can start to pull apart who the players were, what were the conditions that were set?
Speaker 2:What conditions did? I set when were the rules Unintentionally.
Speaker 1:Did I unintentionally put myself in a position of disadvantage and go?
Speaker 2:holy shit.
Speaker 1:What were the mistakes I made, what were those indicators that I should have recognized earlier and been able to draw a reasonable conclusion? Because I went through it and I went damn it. I knew that was going to happen. So that allows me that faster and better intervention strategy because I'm seeing things sooner, the recognition happens faster.
Speaker 2:So spot on, and that's such an important detail. Again, folks mark this part and go back and listen to it again. What Brian just told you is that when we talk about knowns and unknowns, we have a known where there's your definition, a high likelihood that it's going to occur, based on any artifacts and evidence that I'm witnessing, and you have an unknown where there's a low likelihood okay which means that if it's a low likelihood and it comes to surface, it's going to come out like a jack-in-the-box and you're going to have to respond to it rather than being prepared for it. So the game is to give yourself enough time and distance to balance high and low likelihood and then the likelihood goes into most likely course of action or most deadly course of action, dangerous course of action.
Speaker 2:If you can do that for your entire life, then you're going to be fine, like you can't lose weight with those Zempik and pills and not manage your diet and your workout. That's unsustainable. So what you have to do is you have to say I can't just get through my police career learning how to use my gun and my baton and my lesson lethal A lot of what you do. And this is Brian. You'll remember this argument. I think it was 2006 in the fall, when we were all at the back of the tomato cannery that became the IIT.
Speaker 2:Yeah, but you know what? It was one of you. You know what I'm trying to say. It was one of you and we were having the argument and General Amos was there and the argument came up about Greg. I've watched three back-to-back scenarios and they've all been non-kin, non-kinetic. And it's like, yes, sir. And he's like, well, I didn't pay all this effing money to watch a non-kin scenario. And it's like, yeah, but, sir, it's a game. That's how your brain learns.
Speaker 2:Your brain learns just as much from watching the normal daily baseline activity that's going on, because then an anomaly becomes immediately apparent and you know what? There was a gap for so long and they go holy shit. And then look at all the material started coming out about non-kin, non-kin village and all that other stuff. Now I love to say that I'm the start of everything. You know the sun coming up and this, and that because it's my massive ego. But I'll tell you what those arguments were going around out there and people didn't listen.
Speaker 2:And now take a look at the time that you have in a simulator. Somebody's going to go. Well, if I'm going to spend time in a simulator, it better be a gosh damn shootout, it better be there and I better feel a recoil and I better get shot once in a while so I can put on a thing. Trust me, those things are going to happen in your own life You'll do fine. But if you handle the mental portion and that means overcoming uncertainty by anticipating likely outcomes, that's the game. The whole game is which move is this person going to make next? And I anticipate three or four that I know. Then there's a couple that I don't know yet. But if I see the pattern form, then I can think that that pattern is suggestive of a likely outcome.
Speaker 2:Oh my God, I mean that right there. That should have been a book and not because it came from me. All I'm doing is I'm like a gosh, damn serenity. I can only shit out what I learned, and so I just learned this stuff. You get what I'm saying and it's what I know better than anything else. And that's why we have to reassess what we do in training, because training on the mat, of course that's important. Training on the range, of course that's important. But if you don't have an equal or greater amount of cognitive decision-making, of sense-making and of in extremis, uh, a critical decision-making, brian, then when the time comes and it's you and the spotlight shines on you, you might not sing, you might not dance, you might freeze up and and that's a uh, uh could be a detrimental outcome. That could be a shitty day for everybody involved. I uh because because, in your line of work, the failure to act may be just as bad as you acting in the wrong manner.
Speaker 1:Right, right and and um, you know, you're, you're, you're bringing up some, some very relevant examples and showing it from, uh, the idea of how, how do I sort of account for this plan, for this get better at it.
Speaker 1:Um, because that's that's the whole point with all of this. And to your point of you know, I only shit out what I learned. This plan for this, get better at it. Um, because that's that's the whole point with all this. And to your point of you know, I only shit out what I learned. That's that's. You know. I have the same thing. Look, I could always tell people.
Speaker 2:Look, I've never had an original thought or idea my entire life but you, you know, I'm one of the few that realizes that, that I haven't had it, you know where most people, you know that's it's a little bit different they're convinced um yeah, well, and, and that's the the another point of talking about these subjects is these are problems and tales as old as time yes these are nothing new.
Speaker 1:But we, as humans, what do we do? Well, there's got to be some technology. You know and, and you know, yes, when, when, whoever invented the wheel that was revolutionary? Okay, uh, the, the printing press, um, industrialization, you know the, the internal combustion engine. You can rattle off some things that have that, that are revolutionary, but most aren't like most things. Don't do that. You don't need some revolutionary solution or technological application. You need to go back to focusing on the knowns. Well, what do we know? That's consistently worked in every situation across time, ageless, timeless. Come on. So that's part of the. So what is why we like discussing this stuff?
Speaker 1:because it's like take a step back. It's time and distance. We're coming up with solutions to problems that don't exist, or we're coming up with solutions to problems that are the wrong solution because we haven't clearly defined what the problem is.
Speaker 2:Or are so sporadic that they're likely never to occur, never going to happen again. Happen once and let's put all our money there.
Speaker 1:And that goes back to we gotta have on whenever his book comes out. I know you've seen it on LinkedIn my cousin Pat he deals with.
Speaker 2:Oh, what a high thinker, by the way.
Speaker 1:That's his. He does kind of like a lot of this type of gaming and strategic level gaming and planning and his background and he's a harvard guy but then also you know some intelligence community and government work and stuff like that. Right, he is a consulting firm where he does this. But that was the funny point was you know some of the stories from immediately following 9-11. You know he's in with this group of people and you know the, the generals, and they're going. Okay, I mean I'm talking like immediately following 9-11, like like there's still smoke and they're going like okay, we gotta start thinking outside the box.
Speaker 1:We gotta look at everything. What other buildings do we think they're? Gonna hit and it's like right oh my god, it's like no, no, no, no, no, sir, that that ship is. That ship has sailed uh, it's the next problem but, but, um, it would just remind me of that example.
Speaker 1:But yeah, um we, we, we went over a lot. So I kind of want to read some of this stuff and and what I'll do too for for our patreon subscribers I'll kind of give you some outlines and some stuff from this that that we, we discussed, and with some of the information, so, so you can always go on there. But it goes back to the beginning thing. I want to debunk this myth of anything can happen. I think that really has a bigger effect than we realize when people start doing that, and it there's always, sure, a meteor strike, you know something random, a black Swan event, but you know, you can go back after those things and look and go well, here were all of the pre-event indicators, but because it was so rare or unique, that's a major contributing factor to why no one saw it coming. But but most things, 99 of the things you see in life, are never going to be like that. So human behavior, you know, while complex, it follows patterns.
Speaker 1:It can be understood and it can be anticipated, especially, especially greg, and this is why, you know, I bring this in in comparison to like different economic models or when you get into this with, with with market systems and game theory, like with when the clear, the more clearly you define the context of the situation, the less potential outcomes there are if you're looking at, and the less ambiguous it is exactly, exactly if you're trying to see where the market's going to be at in six years from now, with everything, that's really really difficult to do and I think a lot of people that are good at that.
Speaker 1:Um, a lot of that is luck and some unique intuitive or inside knowledge. And I don't even mean like at an illegal, like insider, I mean they, they have a unique, you know insight that they don't even realize that they have, and that's why they're getting good at making those decisions. But you know most things. Especially, the clearer you define the context, the the less complex it becomes and a great way to do this is is what we talk about with games, and games reflect life.
Speaker 1:You know there's fundamental aspects of games that help us comprehend and understand strategic interactions in real life. It's all about looking at games, game theory and decision making applying the game theory. It allows us to anticipate other actions, plan strategies accordingly the Bayesian thinking. That is what allows us to enhance our predictions and what we talk about all the time in this podcast. What we do for a living, what we train, is the HBPRNA is the goal is reducing the uncertainty, reduce the ambiguity, reduce the complexity. So I can. I can have a make a more uh, a, a more informed uh decision sooner and and be more confident in my decisions right.
Speaker 1:Because I have a leg to stand on, I can, I can show my work, I can, I can, I can show the teacher, you know my work. To get to the to, to get to the answer, and and maybe, even if the answer was maybe not the best answer, it's better than rolling the dice, right? I mean the other thing is is what?
Speaker 2:That's what informed means you know that you're going to be wrong sometime, but guess what? You're much more informed than the person that's constantly just guessing.
Speaker 1:You, because you're going to be right more than you're wrong.
Speaker 2:And when you are wrong, you're going to know.
Speaker 1:You're going to be able to know where it went wrong and we didn't even really get into, obviously, like, what does a correct decision or success look like? Because that's defined a number of things, because you're not looking for the right answer, you're looking for, like, the best answer, given the available information that I have.
Speaker 2:And at least know what right looks like. So I know that I was on the right path, you know, so you're exactly right.
Speaker 1:I would encourage everyone to kind of think about this stuff and use it in your everyday life, in the most simple interactions with you know family, friends, whatever and try to become more aware, or mindful, as Greg would say, of the different factors and characters that are at play and the different roles and the different rules that govern your everyday social interactions. There's, there's things in ways that are more appropriate to to you know, to say or do at a loud bar at midnight on a Friday versus you know, the church on Sunday morning. So think about those. So, greg, I'll throw you for sort of a final thought.
Speaker 2:Real quick one, brian. So we talked about Bayesian theory and probability theory and game theory, and so the hardest opponents to anything are always our law enforcement subject matter experts, because you learn one way and then the walls start going. And now all of a sudden you got a silo. So I tell you this all of a sudden you got that younger copper and you just called off a pursuit and they show up at roll call and they're like hey, this is bullshit. I drive every day. I know what's going on. I'm a street vet. I make a lot of felonies. And you look at him, you go did you check the oil on that car today? Did you check the tire pressure on that car? Is that the car that you've driven through all of the time? When was the last time you're training?
Speaker 2:The idea is that we make decisions and we think that it's in the best interest. If we don't go back and understand Bayes and probability and game theory, then what's happening is we're riding for a fall because we're allowing all that hubris to get up ahead of us and we're not crystal clear in our thinking. So making a better decision and sometimes no is the right decision is much better than getting into that roll-of-the-dice mentality and saying, look, I can beat the house. I know I can beat the house this time, because that's dangerous thinking. So all HPPRNA is reducing uncertainty in the most austere and complex environments in a speed that you should feel comfortable with. Meaning, with training you'll get faster.
Speaker 1:Yeah, and that's, the house always wins right. Physics, math, mother nature is always going, gonna, gonna win time in the, in the.
Speaker 2:Yeah, that, that's what's gonna come on right.
Speaker 1:It's people who go oh we gotta, we gotta, save the environment. No, we, we. The environment's gonna be fine whether we're here or not. It has a way of fixing things. No, it's good.
Speaker 2:It's good like we're the ones we need to fix, so do governments externally brian, so do governments, so do diseases, so does everything else. So we need to fix. So do governments. Brian so do governments, so do diseases, so does everything else. So we need to look at that. And all of those follow scientific theories. So we're more interested in building your mental acumen than your speed of returning your weapon to the holster or doing a tactical relook. So if you're looking for that stuff, we're probably not your game.
Speaker 1:Yeah, that's true, all right, Well, that was a lot, so we appreciate everyone listening, especially if you've made it all the way to the end.
Speaker 2:Holy smokes.
Speaker 1:Please check out our Patreon page and always reach out to us. The Human Behavior Podcast at gmailcom More than happy to answer questions and get into stuff on here. We do that all the time for our Patreon subscribers, who we do love and appreciate, and we get some good ones. We get them to come on sometime and bring their expertise as well. Shout out to Scott Kirshner from.
Speaker 2:Kirshner's fun. He's great.
Speaker 1:And I love the name of his company because there's a lot of meaning behind it.
Speaker 2:I believe that too.
Speaker 1:We thank everyone for tuning in. We appreciate it. Share the episode with a friend if you enjoyed it and um, don't forget that training changes behavior.
