Probability & Language; The Cost of Being Certain

Hello everyone and welcome to the Human Behavior Podcast. In this episode, we're talking about probabilistic thinking and why language matters more than most people realize. The central idea is simple. Most bad decisions don't come from a lack of information, they come from mislabeling information. When we apply labels too early, we collapse probability, reduce our options, and lock ourselves into conclusions that may not be accurate. Today, we'll break down how this happens, why your baseline matters, and how small changes in language can dramatically improve your decision making under pressure. Thank you so much for tuning in. We hope you enjoy the episode, and don't forget to check out our Patreon channel for additional content and subscriber-only episodes. Please consider leaving us a review, and more importantly, sharing it with a friend. Thank you for your time, and remember, training changes behavior. Alright, we're recording, Greg. What we're going to be talking about is probabilistic thinking, language and how that impacts it, and why we use a specific lexicon and how it frames things around thinking probabilistically. The general episode thesis is that most bad decisions don't actually come from lack of information, they come from mislabeling information. We've talked in other episodes about how an error in sense making leads to a poor decision, and language can really prime us for that, which is why we have a very specific lexicon and why we use certain terms and avoid others. But I think it's important to start out with a definition, Greg. If you could give a definition of what probabilistic thinking is, because probability and statistics are very counterintuitive to how humans think. We sort of use it, but at a mathematical level we're terrible at it. I've seen data scientists screw this stuff up because of how human intuition works. Statistics as a field was kind of the last one to really be clearly defined and articulated.

To that point, Brian, just as an opening volley. I read this morning somebody being critical about science and police work, saying scientists are coming out talking about police work. Things can be scientific and police-related. So what is probabilistic thinking? It's what we do every day. It's nothing more than a decision-making framework designed specifically to evaluate a situation based on likelihood — likelihood of potential outcomes rather than certainty. Using data, logic, and reasoning, you're estimating the probability of various future scenarios, which helps you manage uncertainty and then identify most likely and most dangerous course of action. That's what we do all the time. The difference is evaluation based on likelihood. If you evaluate based on certainties, you're going to get rolled over by the steamroller.

That's a great way to look at it. We're talking about likelihood, but not in a way you can calculate statistically in the moment — saying there's an X percent chance this person is going to run or pull out a gun. You can only really do that kind of computation after the fact. In the moment, you ask what's more likely, which comes down to based on what, or compared to what. You mentioned a fear of making a temporary event a permanent characteristic. Let's hit that up front, because it's important to understand the problem we face when we're not thinking probabilistically — when we've already come to a conclusion before we have the right information or the right way to label things.

If it's probabilistic, it's based on likelihood. Making a temporary event a permanent characteristic means we're knowingly creating a damaged file folder. Whether you intentionally or unintentionally create a universal description for a whole person or event, you're saying this is a thing rather than defining the behavior. Somebody says their gut is activated and this person is acting shady — what you're doing is creating an enormous ball of noise around an incident rather than specifying whether something is above or below a baseline. When we say you have to change your language, what we mean is your language to your brain, your lexicon. Give your brain a chunk of information it can process more easily, which decreases the complexity of the situation.

Language is how we articulate and label things. Sometimes I'll see people doing it wrong, or saying it's not important. Like, they're not homeless, they're unhoused. I get the intent. It's the same thing when it went from inmates to persons in custody — you're trying to say it's not us versus them, it's just a vanilla term rather than a loaded one. It will change the way you perceive, interpret, and articulate the situation. I get it. It's just that sometimes we go too far with it.

Let's give an example of cognitive load. You can increase your cognitive load past what's clinically normal for your brain when it's operating. If you give me three choices on a name card instead of Mr. or Mrs., what's going to happen is I'm going to stumble through a normal situation. Anytime your brain pauses, it has to go back, look at characteristics, weigh them, and make sure it has things correct before you open your mouth. If you're stuttering, that means something is wrong because it's not iterative and it's not intuitive. The least amount of language you need to open dialogue is actually better for reducing cognitive load. That's why we argue about biases all the time, Brian — there are now 37 different biases and none of them are helpful for understanding and articulating a situation in the moment.

Because now there are 37 different biases, and none of those are helpful for me to understand and articulate the situation in the moment.

And you can't use them in the moment.

They're unconscious and you don't even know when they're affecting you. But okay, I want to give one example of probabilistic thinking and how it's counterintuitive to the way humans perceive situations. It's called the Monty Hall problem. Imagine you're on a game show. There are three doors. Behind one is a car, behind the other two are goats. You pick a door, and at that moment you have a one in three chance of being right — about 33%. Now the host, who knows what's behind every door, opens one of the other two doors before revealing yours and shows a goat. He doesn't open a random door, he deliberately opens a goat door. Now there are two doors left: the one you picked and one other. The host asks, do you want to stay or switch? Most people think it's down to two doors, so it's 50-50. But it's actually not. When you first chose, there was a two in three chance the car was behind one of the other doors. When the host reveals the goat, that original two in three probability doesn't disappear, it shifts to the remaining unopened door. If you switch, your odds double. The mistake people make is not mathematical, it's cognitive. They look at two doors and label it even odds. They collapse the probability too early. They assume the structure changed just because the situation looks simpler, but it didn't. Probability didn't collapse — they collapsed it. In real-world decision making, most bad decisions don't come from lack of information, they come from mislabeling information. The moment we label something suspicious, shady, aggressive, or under control, we reduce the complexity — which is something our brain wants to do — and we stop updating that probability. We lock the doors in our mind and stick with our first choice. This is why language matters. Correct cognitive labeling preserves that uncertainty, even just long enough for you to be accurate. That's also why we focus so heavily on the baseline, because without a baseline, without a comparison, you can't properly assign probability. In the Monty Hall example, it all starts with knowing there are three doors, two goats, one car. You update everything from that known baseline, and most people don't do that.

So let's talk about this. Brian and I — and I'm not proud of it — one of the drunkest we ever got was at a Cheesecake Factory.

I don't recall this, Your Honor.

They handed me the menu, which is like the King James Bible — as thick as you've ever seen, with chapters and everything. If you're thinking about probability and not understanding complexity, you'll collapse it too soon. You'll open that menu, get overwhelmed by all the information, and just rip out a page from the center and choose from that. That's not how it works. What you've done is reduced your choices, and that's absolutely backwards to how cognition works. You've said I'm going to go for simplicity, and by doing that, you've taken the most likely course of action and most dangerous course of action off the playing field entirely. You can't fold the paper and say the complexity doesn't exist. You have to look at it. We end up prioritizing our emotional response, recency, how quickly things happen — and simplicity feels more important than statistical likelihood. You can't make decisions based on how you feel about the information.

You have to make it based on the information at hand, at that time and place, which is admittedly very difficult without some form of structured observation, common language, and some cognitive adaptability. It's difficult without practice. But once you start practicing, you start to see it everywhere. If I go back to the example of Greg and I having too many drinks — and if I were under oath, I would say that happened a non-zero number of times — but this gets to the language. Language can accelerate that probability collapse. That menu at Cheesecake Factory is a perfect example. I get anxiety there. There are too many options.

Well, we got drunk.

We got drunk as a coping mechanism.

There are too many drink options. Just bring me one of each.

Start at the bottom, go to the right. So this gets into why we use a specific lexicon and why we focus on baseline development. Our brain chooses recency, simplicity, heuristics, selected priors — it's constantly trying to do cognitively close enough. A good example is my son. I take him to a petting zoo and he goes running over going dog, dog, and he's petting a goat. It's got four legs, hair, floppy ears, and it's licking his hand. He's absolutely right by his level of education, training, and experience as a two-year-old. His brain went, I've seen this before, it's a dog. But he's wrong. So I have to teach him — that's a goat, listen to the sound it makes. Now he has a separate category. And even the category of dog ranges from a tiny yapper you'd trip over to a Leonberger at 175 pounds. In a complex, time-compressed, dangerous situation, I may not have time to get into the fine details, but getting the larger labeling correct is what matters. Does that make sense?

It's more important. In the classroom, we constantly carry around a Jack-in-the-Box and a Hoberman sphere. Those help us understand that if we promote cognitive rigidity and only rely on our own file folders, that probability collapse is going to come much more quickly. I have to be cognitively flexible. The stubborn unwillingness to see items as how they might be used stops me from seeing something as a street tool. A box cutter takes over a plane. A Phillips head screwdriver becomes an edged weapon because we didn't consider all those factors. You might say considering too many factors will cognitively overwhelm you, but that's not how your brain is set up. Your brain is set up to categorize those things, and your viewpoint matters less than what category something falls into. If you build robust baselines, your brain triggers on anomalies and says, I'm witnessing these things, I have to fully appreciate other things. With the goat example — there's a different smell, a dog will eat almost anything but not goat food, a goat will eat anything, the way each runs and lays down. Those finite nuances are what distinguish goat from dog. When you're making an observation and sharing it, that gives someone else robust, fidelity-filled information for their baseline. You're actually reducing complexity by increasing cognitive choices.

And instead of goat versus dog, it becomes wallet versus gun. A 45-degree arm bend to get the wallet out — that's how you get a wallet. No, that's how you get a gun. But you have to know the difference.

At first blush, when somebody gives that to you and they're a street scientist, you look at it and go, that makes sense, I could see that happening. But the problem is it then goes to peer review because you just endorsed the opinion, and now you can't get off that opinion. Without structured practice, rehearsal, testing and retesting, you're not relying on statistics or analysis — you're just coming up with something that happens to fit today.

Let me give some simple examples of probability collapse in real life and how it goes wrong. These are real life, not the Monty Hall game show. Games are great for understanding how humans make decisions under pressure and time constraints — it's almost an antiseptic way to look at things — but it is different from the street. So here are examples of how things go wrong: the dog hits, there's dope in there. Someone's being compliant, so the situation's under control. They have a calm tone, so they're not dangerous. They have an emotional tone, so they're escalating. Once we assume those things, it's very hard to walk back, simply because of how our brain is wired — cognitively close enough, it's a goat, I don't need to know anything else. Your brain wants the simplest answer in the shortest time that makes the most sense, but it can be wrong even when you're trying hard to be right. So how does language accelerate this probability collapse, Greg? Do you have a real-life example?

I do have a real-life example. There's a vast, uncertain reality in the high-dimensional space, and our brain is constantly trying to knock that down to just a few items to save energy and store calories so that when we have an emergency, we can jump to it. But the problem is we limit ourselves with comparisons. Fewer choices seems more efficient, but that's actually the mistake — we run toward an unreasonable conclusion because we didn't look at all the possible options. So I just got out of the gym — and when I say I visited the gym, I literally walk by and look in. I'm wiping up and I see a buffet breakfast between the gym and my room. Obviously I'm going to stop. If you've ever been with me in a hotel, you'll know I do things in twos. Two orange juices, two plates, one with fruit separated from everything else. I make like 19 trips and set everything up perpendicular. So I'm getting set up and Maren comes in. We're in Detroit. He walks over and goes, holy shit, how many people are eating here? He meant it completely unbiased and unfiltered — he was laughing at how many pairs of things I had out. I immediately got upset and thought he was talking about me eating too much, which, fair. But I immediately opened the emotional file folder, and by doing that, I limited my options. Instantaneously I reached the wrong conclusion, and I failed to come off of it even an hour later, even after I came down and actually thought it through.

From my perspective, I'm walking past that area and I see you sitting at the table, but I see plates on both sides, cups on both sides, settings on both sides. I'm looking around thinking, who the hell are you eating breakfast with? Who did you meet? How many people are joining? And you just lost your inside voice.

I was so pissed.

That's a great example of how we do that. The words can do a few things: they compress complexity so the brain can process it, they start to signal certainty — nothing is certain, as my old man used to say, only death and taxes — and most importantly, they reduce alternative hypotheses. Even you, reacting to my reaction, you're already on internal Greg going, you son of a bitch, you think I eat too much.

Cognitive labeling is a method to make sure we're appreciating the complexity and allowing the options. I have to describe my thoughts, emotions, and data points in a way that my future attention will focus on relevant information and anchor those memories, rather than reducing cognitive load in a bad way. If you filter so tightly that you remove error accumulation, then ambiguity can't be used as a comparison and you only have one file folder — which may not be the best one. By reducing mental fatigue, I think I'm increasing my chance of being right, but the two have nothing to do with each other. I have to be wrong once in a while, or my brain doesn't understand what right looks like. I have to accumulate some scar tissue, or I don't know what a corrupt file folder feels like when I get to it.

I would say that happens almost daily — there's always a little something like, oh, I didn't know that part. I try to do that even with the kids. With the little guy, he's two and a half now. Me and my wife are both good about keeping a specific schedule. We do these things before bath time, these things before bedtime — very routine-focused because kids need that. Now he goes along with it even when he doesn't want to. He'll start to throw a fit, and I'll say, okay, but what do we have to do now?

And he's crying going, get dressed for school.

Exactly. But it's funny watching how my wife reacts versus me. She'll say, oh, he didn't do this, he didn't do that, I think he's sick, I think he's allergic to this. And I'm like, hang on — we're both seeing anomalies, but she immediately wants a conclusion or a causal relationship, where I'm saying, okay, that might be, but we need some sustained observation, it could be these other things. And then we go back and forth and I just say, yeah, you're right and I'm wrong. But that's a different episode.

What you're jumping to is two things: reduction of alternative hypotheses, and signal certainty. When signals get shorter, we think they're more robust. My granddaughter Baby Z decided things she doesn't like are just oui. We told her that's not good enough, you have to say I don't like that. So she walked around all day saying I don't like that, I don't like that — but she was misapplying it. She's testing the environment. In higher-demand environments, correct labeling allows us to reduce the mental effort to interpret information. That's why Brian and I, because we travel together constantly, speak in such short bursts that people sometimes say, wait, what did you just say? It comes out in chunks. We do that in emails and memos, and we always talk about signal brevity. Higher-functioning teams can resort to signal brevity because they understand that reducing complexity doesn't mean reducing cognitive load — it actually increases it. What you have to do is better cognitive labeling. I stop and say, wait, that's not exactly what I meant, Brian. I meant this.

Let me give some simple examples of why we use the language we use. We don't say that's suspicious, we say that's interesting, because interesting can mean all kinds of things — it's just caught my attention, it's worthy of interest. Then there's aggressive versus elevated. We don't call it a threat indicator, we call it a pre-event indicator. When you say pre-attack or threat indicator, you've eliminated every other option and drawn a conclusion before you have enough evidence. That's why we don't use those terms. And even compliant versus currently cooperative — when I hear currently cooperative, I go, okay, great, because you're allowing me to keep an open mind and consider alternative hypotheses. When you transmit information that way, you're preserving the options. Those terms sometimes change in a high-demand environment, Greg — what are your thoughts?

You said most bad decisions don't come from lack of information, they come from mislabeling information. The threat of mislabeling is that you can't find the right file folder when you need it. In a game of nanoseconds, imagine that almost-everything drawer in the kitchen — some tools, some matches, a piece to something you don't remember.

Random coupons expired a year ago.

Whatever. Each time your focus changes and you use a word like suspicious, your attention narrows and you can't get off of it. You're not updating a baseline because you already found the bad guy. You don't look at most likely and most dangerous course of action because you've already assigned it. Imagine driving with me — I say do a flip, what do you got, and you say something suspicious. You're going to violate traffic laws and maybe get us hurt to get back over there because you're already convinced. You say out loud, that's interesting. And think about what Brian and I say when we call 911. We've had some things happen right in front of us and had to call, and we always open the same way: listen, this is probably nothing.

This might not be anything.

We always start there, then we give our probable cause or reasonable suspicion and let them decide. Because if we don't, the hypotheses that should be considered are null and void, and you're not conducting an experiment with reality anymore — you're not seeing reality as it actually is.

You brought up the everything drawer. One of the things I notice is how my son puts things away when he's cleaning up — he's got his own little methods and preferred areas. Same thing with my wife putting things away in the kitchen. She packs the dishwasher like there's no system at all. When she puts things away and I ask where something is, I ask why she put it there, and she thinks I'm arguing. I'm genuinely curious. She'll say it's with those other similar things, and I'll say I put it over here because it's a tool used right here, for proximity. She matched the item with similar items, which I get. But if you're listening and you live with someone — spouse, partner, whatever — that whole situation is fascinating.

That is the root of most arguments — small things like that. What you're describing is cognitive labeling. Because your cognitive labeling differs, you're trying to force a baseline on each other instead of assimilating one. You're going binary: it's this or it's not, we're doing it my way or we're not. That's how relationships work, and relationships are based on perception. The perception of that item in the drawer matters more than the objective reality of the situation.

I think I cracked the code on where it comes from. For my wife, it's more about aesthetics and look, where for me it's all about functionality — where is this most useful, how are we going to use it. When we moved into this house over the summer, I spent hours putting the kitchen together and explaining why everything went where. She looked at me like I was crazy. I explained the whole workflow, and she said, what is wrong with you, why do you put so much thought into that?

But let's go back to preparing soldiers, sailors, airmen, and marines for war. I was going into a very rigid environment because I knew how to find things and I was good at it. Then the military handed me an RPG or an AK and said, when doing sensitive site exploitation, they have to understand myriad versions — AK-74, AK-47, AKMS, AKS. I said, no they don't, because it's called match. I'll show you how easily I can throw you off kilter. We had an RPG leaning against the wall, so I took about a six-inch piece of reflective tape from my gear bag and put it from the nose cone toward the piezoelectric cell. On the AK next to it, I blew up a balloon and tied it toward the front, stuck between the cleaning rod. I said, okay, have those Marines walk by the courtyard and keep going. We did a limited objective experiment. When I came back and asked what was in the courtyard, they said a balloon and something flapping in the breeze that looked like a piece of electrical tape. They focused on the file folders they were most familiar with, and the item attached to it never registered. We walked over and the scales fell from their eyes, because it was mislabeled. Mislabeling is more dangerous. Misinformation is accidental, disinformation is deliberate. I engaged in disinformation just by interrupting their processing. Can you imagine why the wallet becomes a gun? You'll fall on the wrong file folder and run with it. That's why we take such great care in the classroom to make sure you clearly understand the lexicon. If you don't understand the lexicon, you'll build a corrupt file folder and draw all your inferences from that.

This is kind of why we use the specific lexicon in our program. People who've been listening to the show for a while know a lot of it, and if you've been in class, it's very specific — we'll say no, there's a difference here, and once people get it and it clicks, they go, okay, I see it. For example, when we talk about access: for a crime to occur you have to bring the subject to the target or the target to the subject, so there's always an element of access. A ladder gives access. If I need to get into a facility and hide in plain sight, I'll use social camouflage — put on an orange vest and a hard hat. Thinking about access in a broad sense allows you to make connections about different possibilities and hypotheses versus just thinking about a blowtorch or a card reader. We don't use certain words because they prematurely close probability. Our language is descriptive, conditional, context-aware, behavior-based, and probability-preserving — meaning it's meant to be open to interpretation because it has to work across a number of situations. There's always an element of uncertainty, sometimes more, sometimes less, and you're never going to know if you were 100% right until after the fact. That's the hard part. We emphasize correct cognitive labeling because it doesn't eliminate uncertainty, it acknowledges it. That's why we use this terminology and these descriptive phrases — so the end user isn't drawing a conclusion before the evidence supports it, or going in with a conclusion and finding evidence to support it. It's the exact opposite.

What you're talking about is cognitive maturity — the ability to choose based on a number of options rather than coming in with a reductionist mindset. Probabilistic thinking is up and out rather than down and in. Another term we use in the lexicon constantly is context-dependent and conditional. If you've ever played a pinball machine, if it was just the ball, the plunger, two paddles, and the hole, it wouldn't be much fun. The ball would come down and fall into the hole half the time. But there are also bumpers, and those bumpers light up and make a difference — that's life. If we restrict the machine thinking it'll be easier to hit 100 points by removing those detractors, we've limited our choices while thinking we've limited complexity. You sent me a Brian quote for this episode: accuracy increases when certainty decreases appropriately. You didn't say proportionally, you said appropriately. What that means is you're going to produce more correct results by acknowledging your limitations and reducing confidence — having lower certainty when you're faced with ambiguity or a lack of information. Being almost right is always better than being absolutely wrong. You can't be absolutely right all the time, but you're going to be cognitively close enough if you look at the full panorama of potential decisions. If you don't, you're going to be absolutely wrong and running on broken information. Everything you touch from that point is tainted — like not getting a search warrant, where the exclusionary rule takes all that potential evidence away from you. Cognitive labeling doesn't eliminate uncertainty. It acknowledges that uncertainty exists, and that uncertainty is absolutely essential to working out probability through comparison.

You said something like being almost right is better than being absolutely wrong. Can you go into that a little bit deeper? All these podcast episodes and everything we do in class is one big sense-making exercise — how to make sense based on contextual cues, the relevance of your observations, how to compare and contrast those, how to use probabilistic thinking and label it so that you can make better, more informed decisions faster, sooner, at a greater distance, without overreacting or underreacting. It's supposed to be this cognitive operating system that's in use all the time. You have to practice it at first, but eventually it becomes the intuitive, iterative skill set you get better at. That's a big concept, especially with your background in law enforcement — situations that escalate out of seemingly nowhere. It can go from something simple to a chaotic multi-state pursuit, and it started as a guy not signaling when he turned. But you said being almost right is better than being absolutely wrong, where a lot of people would say we have to be right all the time and the bad guy only has to be right once.

You know what that is? That's justification — because I have to sleep at night and I feel shitty because I did something bad. I'll give you an example. Every police agency I've ever worked with, audited, done a ride-along with, or taught at has a version of a heavy car — a car with a couple extra officers, or a van ready to jump out. They put them in a high crime area, they prowl looking for a series of events to coalesce, and then they jump out and say Yahtzee. While I understand why you do that, without proper training it can go right into the trick bag, because now everybody is primed to look for a specific type of information. We're in an ambiguous environment, we're only looking for felonies, and that makes me look at everything as a potential felony. All of a sudden we see a person standing near a door in a high crime zone and I say, maybe that's one of those felons we're looking for. As we close in, the person's behavior changes — because there are four of us, we're armed, we just jumped out of a car and we're moving rapidly at night toward them. So we're creating this self-licking ice cream cone of likelihood, rather than having an off-ramp that says let common sense prevail. My baseline says there are a lot of people out on the porch because it's a hot night and that's where people spend their evenings in this area. If the reasonability meter is stuck to one extreme, I'm probably seeing the situation as I want it to be, and I've automatically limited my options compared to what's most likely actually happening. Acknowledging uncertainty makes me more careful — I'm going, what else could this be, what else are they showing me? We named that the gift: the gift of time and distance, the gift of seeing things as they really are, the gift of not getting too close before the situation unfolds past your ability to draw reason from the artifacts and evidence.

There are a couple of examples of this. People reach out to us or ask us questions, and I'm listening to them explain the situation and they already have the answer — they're just talking it through. We've had cases where they end up going, oh wow, I didn't look at it that way. Remember that one along the border where we got that search warrant and they said they'd be late to class on Friday?

Because of the class — informed by what they learned in the class.

All it was was restructuring the cognitive labeling. Saying, so you're saying this — yeah, but it's kind of circumstantial. What's the likelihood that person is responsible? And they'd walk through it. What's the likelihood it was anyone else? Well, it couldn't have been. And it's like, okay, so you're calling it this and calling it that — and they go, I get it. This ties into understanding the baseline. Everyone wants that list of things, the missing piece in a case, that one thing. Can you look at this and see something I didn't see? And I'm like, you're really good at your job, you've been doing this a long time, and I've never worked a criminal investigation like this before, so you know a hell of a lot more than me. What I really helped with was framing it differently — using those lenses, that correct cognitive labeling, so they could go, wait a minute. It all goes back to the baseline. If you're in law enforcement, your baseline for what's normal is going to shift over time. You ask a normal person on the street, they say most people are good. You ask a cop and they say most people are terrible, because they deal with the bottom one or five percent of the population that no one else wants to deal with — so the baseline has shifted. An anomaly without a baseline is meaningless. There's no relevance without context. If you don't know what normal expected behavior is, what the environmental pattern is, the anomaly is almost a projection — a psychological projection. That's where we get to.

If you're looking for a specific anomaly, your brain is fixated on that and you're not going to look at how patterns work. Patterns suggest things, and then it takes you looking at the information and making it intelligence. An anomaly alone is meaningless in an environment. Anomaly against a good, robust baseline — now I can start searching. I have this, I have that; if those two are together and a third one comes into play, we might be in a bad situation. You cannot do that if you're searching for a specific anomaly or if you don't understand what an anomaly looks like in that region. It's like going to the doctor and telling them nothing about your symptoms and the doctor goes, does it have to do with your foot? Your eye? A robust baseline lets me get right to the situation. I've been in a thousand interviews — this one is somehow different. Well, how is it different? What are the factors that came up for you in that interview?

When someone says they want to run a few things past me because they saw something interesting, I tell them: stop. Before you tell me what you think is interesting, tell me what you normally see in this case. And I just keep pulling it out. Then they say, I typically see this, then I typically see this. Then I ask, okay, so what was the interesting part? And the light bulb goes on — they say, holy shit, it's so obvious, I don't even need to ask you about it. That's why I keep bringing up the parking lot principles. There are maybe three, four, five reasons why someone parks off to the side — single digits, not a million. So there are only a few reasons, and now it's up to you to figure out which one applies. The thing I want to hit on — and we talk about it more in class — is something a lot of people get wrong, though well-intentioned. It goes back to the Monty Hall example: humility and uncertainty. We are primed as humans; we have an ego system, we feel like we need to be in control. When I use the term ego, I don't mean it negatively — we all have one. But you have to be in control of yourself and how you perceive things, not in control of the situation. If you misunderstand the structure, you assume symmetry where it doesn't exist. We are uncomfortable admitting we're wrong. That's why I always say I'm a knuckle-dragging dumb Marine — I type with my fists, I turn my computer on by head-butting it — because I'm less likely to jump to an unreasonable conclusion. I walk into a room assuming everyone there knows more than me, and I let people show me whether that's true or not. Admitting you're not sure feels weak. How many times do I say I don't know, and then a minute later go, oh yeah, I have heard of that? It's because I don't need to know everything.

Exactly.

That language ties into probabilistic thinking. It allows me to leave some uncertainty in, to continue gathering information. Not needing to be in control opens up the potential for other hypotheses, other avenues of approach. It keeps that little bit of openness in there. We don't get into this because we look at it as a functional thing. This is a structured process — if you follow that structured process, like you said, you're going to be right more than you're wrong, or closer to being absolutely right than absolutely wrong. If you want to talk about feelings and ego and thoughts about the world, that's fine, but it's not practical or functional in the moment. It doesn't help me go, what's going on here, how do I predict what's likely to happen next? That kind of stuff may actually get in the way. That's what we mean by the language of it.

Let me further refine your thoughts with a street example. There's a film — Alice Eve, the kid from How to Train Your Dragon — and one of the subplots involves a friend named Stainer. You can imagine why he's been called that since junior high school; he lives up to it and owns it. The mislabel led to a future cognitive distortion that person can't get away from. A specific temporary behavior you witnessed becomes a permanent trait. I've been in rooms full of detectives where somebody says, the Waldorf got hit, and someone goes, that's Jimmy Jack, he loves those high-rises. Shut the hell up. What happens is we think that by labeling the complex environment we're making it better. Cognitive load shapes our performance, so information has to rely on our predictions — we run on predictive analysis. Can I chunk the information? If I do, I have to chunk it right. The labeling allows me to take in the information as it is, reducing cognitive load and increasing efficient performance using time and distance. If I don't do that, I'm learning from bad examples, and the corrupt file folders keep coming up. That's why you see people who marry the same type of person over and over. You see officers who are more likely to escalate force over and over. The same thing happened early in Iraq — military-age male. That label screwed everybody. You can learn to operate in an environment you've never been in before just by using appropriate cognitive labels and applying them in sequence, because you become more efficient. That's wrong. This is right. Update the baseline. These two things work together. That doesn't fit. Update the baseline. We're doing that in nanoseconds. Your brain already wants to do the pattern recognition.

That's the biggest point out of all this — your brain wants to do the pattern recognition. So if you do it correctly with the correct cognitive labeling, you're just going to iteratively get better. With each exposure to a new environment or situation, you update your file folders, update your experiences, update what you're drawing from and recalling in the next moment. You won't be forced back into fear and uncertainty and anxiety — you'll actually be able to adapt to a novel situation because you're drawing from all of those past experiences. Going back to the language part of it: instead of saying this person is aggressive, it's that their behavior is elevated relative to the situation or relative to the baseline. It's incongruent with what I typically see in this environment. Now you can figure out why, or what else there is — but you can't challenge the word aggressive.

A defense attorney can challenge that. They were aggressive? Are you a subject matter expert on aggression? What level would you give it on a scale of one to ten? You see how that opens it to the wrong interpretation. You don't want to collapse the uncertainty — you want to navigate it. You want to make sure that uncertainty has boundaries. If I organize my information more accurately, I'm improving retrieval, memory degradation goes away, and I'm comparing knowns and unknowns at a higher level because I have a better basis for comparison. The better the baseline, the better the comparison.

That goes right into the intervention strategy. This guy is throwing tables at the fast food restaurant because they got his order wrong — that's completely unacceptable behavior. But rather than go, this is unacceptable, I'm going to pounce, you say, hey man, what happened? They got my order wrong. Damn, that sucks. I hate when that happens. That pisses me off. I know what that feels like. Now, okay, I get that — after a long day, hungry as hell, and they screw up your favorite order. Now we're talking. It informs everything, how you label the situation. It all goes back to updating the baseline and avoiding emotionally loaded terms, like every politician loves to do — especially now.

Let me give you another street one. People who don't like shaking hands — one instance a long time ago, or one instructor, soured them on it, and that's a form of human communication. So if you're not going to shake hands with me in this situation and you don't have a good reason for it — you're a germaphobe or something —

Yeah.

Or, hey, the last three guys who shook hands with him got their teeth knocked out — I get it. But that's different; that's updating your baseline with knowns and unknowns. I had a defensive tactics instructor at an academy a long time ago who always carried a big multicolored mouthpiece. Just before going hands-on with somebody, he'd show it to them and say, hold on — put it in and go, okay, I'm ready. Can you imagine taking that apart on the stand? De-escalation and the whole process is a labeling exercise. If you're going to use an emotionally loaded term, understand that behavior is going to change because of it. What do we keep referring to Hippocrates for? First, do no harm. Label it right the first time. You're going to retrieve it better, you're going to have a cleaner sample to compare against, and you're going to be more efficient. You might not reduce the complexity to the level you think, but you're going to be more accurate in your decision making. I think that's important.

That's a win over time. Everyone wants to know the right solution, but you're not going to know that until after the fact. You just need a framework to sense-make, to understand the situation so you make the best decision possible with as little information as you have, at the furthest observable distance, with the most time you can get. People say that's a nebulous goal, but it's not — because if you have that as a strategy, then over time, individually, your team, and the organization are going to get exponentially better at this. It takes time.

If you're thinking probabilistically, you're thinking the right way. The most likely and most dangerous courses of action are going to come up no matter the encounter, and the more you do it, the better you get at it. If you're looking for absolute certainty — that's death and taxes. You are paying for accuracy in your predictive analysis; there's no question you're going to do that, and it's going to make you more efficient. What does efficiency mean on the battle space? Safer, harder to kill. Those are wins.

Big takeaway: I'd recommend checking out the Monty Hall problem, but it's not a math problem — it's a cognitive problem. Most bad decisions don't come from lack of information; they come from mislabeling information. Language is how we either lock doors in our mind or open more doors. Correct cognitive labeling doesn't make you certain, it makes you accurate. The goal isn't to eliminate uncertainty, it's to navigate it without collapsing it — to make a good enough decision right now based on what we know. So being almost right.

I think with that.

We'll do some more on Patreon — some cognitive labeling exercises and of course the episode cliff notes for Patreon subscribers, and we appreciate those who are. Greg, any final thoughts on this one?

I'll bring up one of your quotes: you can't identify anomalies accurately if your language is distorting the baseline. It's as if you're looking at a baseline for apples and oranges and somebody hands you a lawn chair and says, where does this fit? Correct your cognitive labeling, do it early, do it often, and incorporate it in your training — including virtual reality training. You'll be happy that you did.

We appreciate everyone for listening. Please share it with your friends. We've got some good guests coming up in future episodes — it's going to be some good conversations. For those of you who are already sharing the episodes, we appreciate it; that really helps get the message out there. If you enjoyed it, reach out to us. There's more on Patreon, and you can always connect with Greg and me on LinkedIn. It's actually Greg's only social media, so if you want to get a hold of him, that's the place. It was illegal to say that by design. Anyway, we appreciate everyone tuning in. Thanks everyone for tuning in. And don't forget: training changes behavior.