The Real OODA Loop Is Ecological: Optic Flow, Orientation & Constraints | John Flach, PhD

A pilot does not calculate a mid-air collision. He reads it. The horizon sits at your eye height, so an aircraft above it is higher than you and one below it is lower. The target that demands everything is different: the one holding a constant line of sight, fixed in your canopy while it grows. No relative motion, closing range. The optics specify it, no math required. Cognitive systems engineer John Flach returns to No Way Out and pulls that thread from James Gibson and Stick and Rudder all the way to how leaders decide on Wall Street and in elite sport.

The information is already out there. In the cockpit the environment hands it to you as optic flow. In business it is real but poorly specified, so the leader's job is to build the optical flow field that does not exist yet. That is ecological interface design, and it is also what a coach does when a drill lets a player see what took experts ten years to notice. Flach and Ponch trace it through Gary Klein and naturalistic decision making, the constraints-led approach, Rasmussen's decision ladder as a non-linear read on the loop, and Flach's own reorientation on John Boyd: once he looked past the caricature, he found Boyd on the same path as Gibson.

OODA loop, John Boyd, orientation, optic flow, James Gibson, affordances, Stick and Rudder, constraints-led approach, ecological interface design, naturalistic decision making, Gary Klein, situational awareness, decision making under uncertainty.

Guest: John Flach — https://www.linkedin.com/in/joflach/
Perspicacity: https://perspicacityll.wpengine.com/about/

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Transcript

John Flach returns: from affordances to the OODA loop

Brian "Ponch" Rivera 0:20

All right. John Flack is with us joining us again. He's been on the show in 2024, right before all the madness with the constraint slot approach hit the the NBA, the WIBA, and things like that. In fact, uh it was John who uh talked about Gibson and affordances, and and I looked at him like, what the hell are you talking about? And since that time, we've really come to not really understand it, but really put our arms around it in a way that we can actually see the connection to Boyd Zoodaloop, Mission Command, and Ted Base Leadership and things like that. So, John, hey, welcome back, man. Good

Inside Naturalistic Decision Making with Gary Klein

Brian "Ponch" Rivera 0:52

to see you.

John Flach, PhD 0:52

Yeah, great to be back.

Brian "Ponch" Rivera 0:54

I know you were in Virginia recently, right? Yeah, at NDM. Yeah. Uh naturalistic decision making. I think David Woods was there, Professor Woods, right?

John Flach, PhD 1:03

Dave was there. Gary Klein, of course.

Brian "Ponch" Rivera 1:05

Gary Klein. Yeah. So how was that? Do you give us some background on that?

John Flach, PhD 1:09

Well, it's so um, you know, Gary Klein started his company in Dayton, and I'm also in Dayton at Wright State, and actually his wife was on the faculty with me in psychology. And so I've known Gary since the very earliest work on naturalistic decision making and his his recognition primed decision model. And so this group and many of my PhD students worked for Gary and he taught adjunct courses at Wright State. And so so that that whole community is a small group and I have lots of friends there. But the the thing that I really like about an NDM is not only are there academics there, but people in the world who are actually making real decisions. So, you know, I connected with a group of firefighters in this meeting and talked to policemen and people who are training decisions and who are performing in complex situations where they have to make potentially life and death decisions. And, you know, that's where Gary started was interviewing firefighters. And so it's it's kind of interesting to get so, you know, talk to firefighters who are real-time firefighters, training firefighters, and working on PhDs and uh related to their work on decision making.

Brian "Ponch" Rivera 2:27

Or how I mean I haven't been to one out.

John Flach, PhD 2:29

It's it's generally single, maybe two tracks. So it's not like the big meetings like human factors where there's 20 tracks in and the and the and the three three things people you want to hear are all talking at the same time in different rooms. Uh, you know, and so they they had two tracks, I think, and all the keynotes were there was no opposition to the keynotes, so everybody's so it's one of those conferences small enough so that you know that you know when you go to lunch with a bunch of people, they've all heard most of the

Optic flow, Gibson, and Stick and Rudder

John Flach, PhD 2:58

same talks that you've heard, and you can discuss it.

Brian "Ponch" Rivera 3:00

That's great. So uh if you uh a while ago I reached out to you because you knew this, and I don't think I did, but the connection to affordances, Gibson, and optic flow. Uh I think some people we call it optical flow. I think it was on our Napetops manual as optical flow. I remember reading chapters about this, you know, going through flight training. And even when you take a test to become an aviator, you have to kind of look at these things and figure out where things are and all that. It's a weird test, but I never made the connection that it can't that the idea of potentially the afford the idea of affordance is is connected to Gibson's work in aviation. Can you talk a little bit about that and see where that where that can take lead us to?

John Flach, PhD 3:39

Yeah, so so the one thing that I think a lot of people don't under don't appreciate is that these ideas didn't originate with Gibson.

Speaker 1 3:49

Hmm.

John Flach, PhD 3:49

They actually originated with Langeweissia, who was a pilot who was an expert and very intuitive about how he could do what he did. And if you look punch at the page 270.

The horizon at eye height: reading a collision before it happens

Brian "Ponch" Rivera 4:04

So I'll just share with our audience. We're reading one of the books that every aviator was given, and it's called Stick and Rudder, right? And I remember in flight training, if you didn't read this already, you you're kind of a behind the power curve. So that's what we're looking at. And you want to go back to the uh what what page are we looking at again?

John Flach, PhD 4:19

So if you if you look at page 271, and then the whole the whole section on the approach, the the following pages 272, 273, he diagrams, you know, what it looks like if you're on a safe approach to an airport. And one of the key what he points out is that you know the horizon, the optical horizon is always at, yeah. So what you see there is on the right is Gibson's depiction of what a moving what a pilot would see, what a bird would see, bird's eye view. And on the left is Langeweicher's picture of what a pilot sees. And one of the interesting things about that, because of the optics, the horizon is always at your eye height. So it's at optical infinity. And so when you look out at the world and you see another plane and it's above the horizon, it means it's gonna pass over you. And and that's specified. It's not a it's not an inference. That's the physics of light. If it's there, it's gonna pass over you. If it's below the horizon, it's gonna pass under you. And if it's at the horizon, then that's you gotta really worry because that means it's the same altitude that you are.

Brian "Ponch" Rivera 5:31

Right.

Information specifies, it isn't a cue: Gibson breaks with cue theory

John Flach, PhD 5:32

And so so, you know, and classically in psychology they talk about these are cues that you can use. But what Gibson is saying is it specifies, the information specifies the relationship between you and the world. And and so what he what he proposed, and at the time he proposed it, there was really it was difficult to test experimentally. But he proposed that there's structure in the light, because of the rules of optics that allow to specify, you know, where you are, everything in the world at relative to your height. So, you know, if you're terrestrial and you're on the ground, um, any you know, the horizon specifies the the distance below the horizon, if something's comes up from the ground halfway to the horizon, then it's half as tall as you are. If it cuts the horizon, it's taller than you are. And in fact, the pro how much taller it is is a proportion above and below the horizon. So if it's if it's you know, if if if the horizon cuts it in half, it's twice as tall as you are. Yeah. And that's and that's totally specified in the optics. I mean, because light moves in straight lines, that has to be true. And so, you know, before Gibson, the assumption was we got a two-dimensional retina, but we live in a three-dimensional world. And so

Testing Gibson: the first interactive flight simulators

John Flach, PhD 6:54

what we have to do is we have to take these cues on the two-dimensional retina and build internally a model of where things are, how big things are, you know, what what how far away they are and stuff. What Gibson said is no, it's totally specified. The the height of the object is is specified by the horizon line. The the imminence of collision is specified by how fast something grows in your optical field. The angle and angular rates specify in, you know, they specify what the imminence of collision is. And so, you know, when you're landing, you know, pilots describe this as ground rush, but as you come down, get closer to the surfaces, the rate at which it expands is is much, much faster. So Gibson had proposed this in the you know, 60s, I guess. And and but when I was getting my PhD at, and I was being my primary advisor was trained as an electrical engineer first before he got his PhD in psychology. And we were modeling tracking performance, you know, simulations relative to making inferences about pilots and helicopter pilots with different displays. But what we do is they were tracking and tracking some assigns, and we were building models of the bandwidth of the, you know, the pilot and how good they are. At the same time, in parallel, uh, one of the faculty at Ohio State, Dean Owen, was a Gibsonian, and they were building the aviation psychology lab at that time, and graphical computing was just coming online. And in fact, this was pre-Silicon Graphics computers, but they actually, the Computer Science Department at Ohio State built a graphics board that allowed us to have interactive graphics on the in a flight simulator. So you could actually see, and and there were very primitive worlds, checkerboard worlds and things, but using those for the very first time, we could actually test Gibson's hypotheses interactively. So we have interactive graphics, we could manipulate edge rates on the ground, we could manipulate the flow rate. And so I was learning control theory. Dean Owen was looking at the optics, and and a guy named Rick Warren came as a visiting researcher, and Rick Warren was the last student to get his PhD with Gibson. Rick Warren's dissertation was showing that you could see where you were going, even if the point at which you were heading wasn't in your field of view. So, for example, if you look at your the side window of your car, the lamellar flow, the nature of the flow, tells you the direction you're going. You don't have to look where you're going to see where you're going. And in fact, if you look out the back of the train,

Optic flow and controlled flight into terrain

John Flach, PhD 9:35

it it specifies the direction of the train, the flow. So you could sample the flow field anywhere and see the direction in which you were moving.

unknown 9:43

Yeah.

Brian "Ponch" Rivera 9:43

I remember when I was a kid, you know, hanging in the back of a truck with the gate down, because we used to do that when we were younger, looking backwards. I I that's the first thing I thought of when you brought that up is you knew which direction you were going, right?

John Flach, PhD 9:55

Right. And Gibson actually describes that from riding in a train, you know, looking at the caboose of a train when he was growing up as a kid, too, same experience.

unknown 10:03

Wow.

John Flach, PhD 10:03

But the idea is the optic flow field, and you know, there's interesting things like the moon illusion, you know, when you're driving, the moon is so far away that there's no angular change. Right. And so it seems it seems like the moon is stationary, but it's not, it's not. It's just that that the angular change is so small relative to because of the distance the moon's far away. It's it seems to be stationary while you're moving in the car. Well, the things close to you on the road are going by really fast. The mountains in the distance are going by relatively slow. And so actually, the the speed of flow specifies how close you are to surfaces. And so Gibson began, and so Rick Warren, what he had done is he had actually modeled it the mathematics of optical flow. So he showed the angular relationships and he had that mathematics. They were interested in interactive control with the computers, and they reached out to me because I was doing control theory. And so they wanted to look at interactive displays and stuff, and so they wanted to connect the action, you know, a model of action to a model of perception. And then we, Rick Warren and I, then Rick went to Wright-Patterson Air Force Base, and he he continued to collaborate. We did a lot of research on optical flow and pilots and things where we where what we did is we looked at structures in the optical flow field and then had people control it. And we can do things, interesting things like we could manipulate the frequency of you know of different changes. Like we could have them move up and down at a certain frequency and also change their speed at certain frequencies. And see, we tell them to control their altitude, and it turns out that and we have hypotheses about controlled flight into trains. So it turns out that the speed of flow when you're a car, the faster you go, the faster everything goes because you're at a constant eye height. Right. But if you're in an airplane, it's different. It's different because the flow depends on how high above the surface you are. Yep. So due to this altitude, flow increases, even though your speed doesn't increase.

Brian "Ponch" Rivera 12:10

You're gonna love this. People always ask when you go over Mach 1 and you're flying at Mach 1.4, people are like, how what's it feel like? I'm like, nothing.

John Flach, PhD 12:17

Yeah, because you're so high above the surfaces, it's the world's going by really slow.

Brian "Ponch" Rivera 12:21

But you get down low on the deck, you get down at 200. Yeah, as well. Right.

John Flach, PhD 12:30

Well, and you know, what I have a hypothesis, you know, there's a lot of control flight, you know, if you look at control flight and train, you know, sometimes they obviously stall, they pull up at the last minute and stall. Or but in some of these accidents, they actually nose into the ground. And our hypothesis is what happens is they get below the energy curve, basically. And what happens, we think, is when pilots are doing nap of the earth or low altitude, the flow rates are so high that they're very comfortable with the speed. They feel like they have a lot of speed. Yeah. And if they're not paying attention to their airspeed indicator, because you're because you're at that moment when you're low, you're usually outside the cockpit.

Brian "Ponch" Rivera 13:13

Yes. Yeah. You're looking, you're looking at the case.

John Flach, PhD 13:15

And so so you feel like you're going very fast, but you you may not be. And and it and and so what happens is you're if you're unaware of your speed as you get lower and lower, you know, there's a point where you're gonna stall. And of course, if you're if you stall at high altitudes, what you do is nose down to pick up speed, because you have lots of room to catch up the energy. But if you're at a low altitude and you hit a stall speed, you know, you either the grounds come at you and you pull back, or or you do what you what you would do at a high altitude to recover from a stall, which you nose in. So what we what we think is is that pilots you know lose track of their airspeed. That that is, they just it just the flow is so fast that they feel comfortable and they're not really attending to their gauge, their airspeed, which is the only reliable indicator of their speed, and they get outside the you know power curve. They they lose the energy they need to keep the plane up.

Keep your eyes on the horizon: a leadership metaphor

John Flach, PhD 14:11

Yeah.

Brian "Ponch" Rivera 14:12

So I want to share a uh leadership story with you that happened to us uh at Udavar Hazy. We were with a uh a large hedge fund, uh, and the CEO actually went flying in an extra 300 with one of my one of the guys I used to fly with. And he came back up and he grabs me and he goes, Ponch, I need you to go grab Preacher, bring him up here immediately because he needs to brief everybody on what I learned in the cockpit. I'm like, okay. So I went down there and I grabbed Preacher. He had a few free minutes and I bring him up there. I'm like, hey, just answer the CEO's question, right? So the CEO goes, tell them what we learned about keeping our eyes on the horizon, you know, just like what you what you and I just talked about. And he made that into a leadership analogy or a metaphor that that uh it transferred over. And I'm like, well, this is fantastic because most, and I gotta I want to go in this direction too with you. When you're flying or you're in sport, uh soccer, basketball, whatever it may be, you have an environment that you can see, right? You're you're right there in it. But in business, you really can't see anything. And and I I think, but the metaphor and analogies transfer over. And I just read a paper on teamwork from some folks out of Portugal that talked about a little bit different access to the environment that you have in sport than you do in business. But anyway, um, the point there is we we here we are just flying around these folks in Northern Virginia and an extra 300. They went up an extra 300, or he did. Uh, then that that evening we went to Udvar Hazy and we showed him the World War II aircraft, a B-17, B-47, P-51, and we walked through where this optic flow comes from, right? So I think it's safe to say, based on this conversation, that aviation, again, brought us something that we may have discovered later, I guess, but but again, a strong connection to aviation leadership and keeping your eyes on the horizon, looking in the distance. And I think the last time you and I had a conversation, I was talking about CBDR, constant bearing decreasing range and how dangerous that is. Uh and we and since you and I have had that conversation, we've had that accident up at uh not Dulles, but at Reagan, right? Yeah. And if it and when when you see that and you you think about CBDR, a constant bearing decreasing range, and at nighttime through goggles and you get a light out there that isn't moving, right? It's just floating right there like a star. That's a dangerous situation. So right. So again, these are these are important lessons that can be carried through sport and business about paying attention to the environment. But the biggest gap, I believe, is in business. You don't have much of an environment to look at.

Why business has no optical flow field

John Flach, PhD 16:40

Well, so that's the direction that I ended up going. So, you know, the early stuff with Gibson was the things we already do well. So control locomotion, birds can do it, and everything. But but he wanted to specify, he wanted to, he was challenging this Q theory, you know, that you have to build up this internal representation of the 3D world with what, you know, what he and actually his wife was leading on this, is you learn to tune in to that information like the horizon, like the edge rate, and you know, you tune in to the information that specifies the important functional relationships. So you don't have to create a 3D world. The imminence of collision is totally specified on your two-dimensional retina. The the angle, you know, the fact that the CBDR, the fact that two things are on a collision course, are specified because the angular relationships stay constant. And if the angular race, if it's not, you know, moving ahead or or moving back in your field of view, it's on a path that's going to lead to intersecting your path. And it's it's totally specified. I mean, they're not hints, that's a function of the optics. It has to be. Now, the only thing I would check, you know, and in sports, you know, what you learn to see, so you know, if you've never played soccer, it's a booming, buzzing confusion out there. And you offside, what, you know, you know, you get in the game and you learn to see these things. You know, if you're you, you know, you grow up playing baseball, I mean, you're watching things about, you know, the pitch count, you know what the why the pitcher goes into a stretch and thing. All of this stuff is not visible to somebody who doesn't learn to speak, but it's all out there to be picked up if you have the experience. The only thing I'd say is I don't think business is any different, but it's the information, it's just not well specified. There is information out there. And so what we did, so

Ecological interface design: Three Mile Island to energy displays

John Flach, PhD 18:32

we went from looking with pilots, and then three mile happens, and now you have a nuclear power plant, but your only interfaces at that time was knobs and dials on a wall. Right. And so we came up, my student Kim Bassani, came up, and Jens Raspus and came up with the term of ecological interface design. And again, graphic computers are just becoming available, but now what we want to do is how do you specify to an operator in a nuclear power plant how do you allow them to see the constraints that are important? And so there's not a natural optical flow field, but we began to look at you know thermodynamics and the kind of representations that physicists use to understand the mass and energy balances. And then we use that to build graphical interfaces that allow people to see not, you know, what this, you know, the temperature and the pressure, but to see the pressure and the relationship between pressure, pressure and temperature that tells you whether this system is stable or not. So the energy, whether the balance is the energy is balanced or not. And it turns out, you know, later than our work in nuclear power of look at energy balances, we came up with a new landing display. And again, it was based on an automatic pilot situation that rather than looking at speed and altitude, it looked at potential and and kinetic energy. And basically, when you're landing, what this problem came up with is we're looking at landing and we're developing a flight simulator, and we're talking to pilots, and we had a normal long runway approach, and pilots tell us, well, here's how we fly down. We set our throttle and then we fly our stick down. And our primary reference is airspeed.

Managing energy on approach: potential vs kinetic

John Flach, PhD 20:14

So if we have our throttle set to right place and we keep a constant airspeed, the plane will gradually fall out at a gym little thing. But if we're landing on an aircraft carrier, if we're landing on a short field, we do something very different. In fact, we set our attitude, we set our stick, and we fly the throttle down. Yep. And we said, Well, why? And the pilots knew the procedures, but they couldn't tell us why. And so then we go to the aeronautical engineers and they say, Well, you know, actually what they're doing is balancing energy. And so when you if you set your throttle at the right point, you don't have enough energy to keep your your plane's gonna gradually fall out of the sky if your throttle is right. And and so as long as you keep the airspeed constant, your loss of potential energy is gonna be constant. And so you're gonna fly at constant angles. But when you're flying when you're managing energy on a short, you want to set your attitude and you want to directly control your kinetic energy with your your throttle. Right. And so so when you've put in energy terms, it turns out, you know, this was inspired by a a Dutch researcher who had had discovered that if they build the autopilot around potential kinetic energy, it's a much more stable controller than if they try to use the the state variables of altitude and speed. Hmm. That's fascinating. But we built a graphical interface that actually allowed pilots to see what their total energy was. And so we directly specified on the ground on the pilots and and and the interesting thing is when they can see total energy, the pilots flew like this.

Speaker 1 21:53

Yeah.

John Flach, PhD 21:54

Because they just want to keep their energy total. So they didn't have to set the stick and the throttle, they just want to maintain a constant total energy that is consistent with a soft touchdown to landing. And and they didn't have to, you know, if you could see total energy, then you could do it actively. You didn't have to, you know, but if you can't see it energy and you only see speed, then you you want to set your throttle, so you only have to pay attention to speed.

Brian "Ponch" Rivera 23:19

So is it safe to say that HUD design, uh heads-up display design, was built after all of these uh inputs of like affordances and the little tadpole and the velocity vector and all that, that you guys looked at all that to figure out what needs to go in there so we have so when you're landing at night, you can see what's happening?

John Flach, PhD 23:35

Yeah, I mean much of our research and and so the HUD was one of the first analog displays, and

HUD design and why you have to learn to see

John Flach, PhD 23:40

in some sense, the HUD mimics the optic flow to a certain extent. Yeah. It mimics it. So it's capturing some of the optical invariants to specify the approach. And again, in a sense, you what you're doing is the the HUD was really an analog of the optic flow that you'd see outside. So you put the horizon in, you put the you know, the optics.

Brian "Ponch" Rivera 24:03

But if I if I showed my kid the HUD and she she looks at it and goes, Dad, I don't know what any of this means, everything's specified in there. She just has to learn to understand it, right?

John Flach, PhD 24:11

And and that's that's one of the myths. So, you know, and and I when they came up with the ecological interface design, I told Kim Vicante that I thought that was a bad name because, you know, as you said at the beginning of the program, you know, when we mentioned Gibson, it's like, well, what's that got to do with anything? And most of the world thinks that, still thinks that way. And except for a few people like Robert Gray, it's a is a good example. But uh the when that people think as ecological interface design should be natural, and so anybody should be able to sit down and look at a HUD and understand what it is if it was ecological. No, it's not. You you have to learn to see.

unknown 24:47

Right.

John Flach, PhD 24:47

So this is true with the things. You have to learn to see. And yeah, the best way to learn is by doing and discovering the interactions in the coupling.

Brian "Ponch" Rivera 24:54

Yeah. Right, right. So so when I watch a basketball, I don't play basketball, my kids do. I I can't tell them what they're you know, they I don't know what they're seeing, right? I don't know what the coaches see. And when you when you learn from a good coach and you see them coaching things and pointing out things that the the kids are doing, I'm like, I didn't see that. But you guess what? You come in my environment, my old environment, I'm gonna see things that most people can't see anyway, right?

John Flach, PhD 25:14

Like and and I think it's the same in business. So that you know, people are really good at business. It's not that there's no information, you know, they don't have an optical flow field, but the people who are really expert know what to attend to. So they know what metrics they should be paying attention to. And that's so with ecological interface design, what we do is the first thing is we do is work analysis. That is, go into a domain, talk to the experts, and say what are they attending to? What are the variables, what's the information that they're using that allows them to very quickly make decisions and see things that the rest of us can't see.

Brian "Ponch" Rivera 25:52

Well, let's pause there for a second. Go back to NDM, naturalistic decision making of Gary Klein. What I learned from him is uh uh cognitive task analysis, sometimes experts can't

Cognitive work analysis vs cognitive task analysis

Brian "Ponch" Rivera 26:00

tell you what they're uh paying attention to, right? Is that right? Yes. Okay.

John Flach, PhD 26:05

And so so that, yeah, I mean, that's part of the one of the great things about Gary Klein is you know, what I love best is his his stories about ESP. You know, he has a story about the fire ground commander who they're in this building, and all of a sudden he gets a sense, this feeling, and he orders all these guys out. And seconds after the last guy comes out, the floor collapses. And he's like, you know, I just had this spidey tingle, you know, this ESP. And he there's another thing with Scud missile detection, where that during the Gulf War, this guy's watching and he sees this blip on the radar and he's like, it's a scud missile coming out of at us. And immediately he's no shoot this down. And then afterwards the commander comes in and says, Who ordered that shoot? And he said, I didn't. And he said, How did you know that that was a Scud missile? Are you sure that was a Scud missile? Because the A-10s fly back and they look exactly on the radar like a Scud missile. And he says, How do you know you didn't shoot down one of our planes? And the guy could not explain how he knew. He said he just had the strong sense, and they spent, you know, hours waiting to hear that maybe they got shot down in A-10 or something. And it turns out it was a Scud missile. He saved the thing. And when Gary interviewed him, he's like, How did you know? How did you know? And he's like, It was just CSP. I just had this feeling. Well, after talking about it, what they discovered that what he saw is he's looking at the radar, and the blip didn't show up at the edge of the radar, it showed up partway into the radar.

Gary Klein, the Scud missile, and the firefighter's ESP

John Flach, PhD 27:27

And what that means is so if it was an A10, you would see it come on the edge of the radar. All the way down. Yep. But if it's a scud missile, it's coming out of the ground. And so it's below, and and if it appears all of a sudden, doesn't come from the edge, but appears on the scope, off edge, well, that's something that's come up from the ground. That's not an A10. And so, so oftentimes, and the same thing with the fire, you know, in the room, you know, when he started interviewing the firefighter who, you know, had he started saying, well, you know, the sounds were coming from this, and I, you know, my feet were sweating and stuff. And so they had thought the fire was in the ceiling in the attic, and and but but once he started really thinking about, and Gary discovered that there was information, but it was kind of below conscious threshold that was driving this feeling that something's dangerous and stuff. So so what we do, you know, what we do, but what we don't call a cognitive task analysis, because, and and this is, I don't want to put this in Gary Klein's, but I think a lot of people look at Gary Kind work and it's about expertise and it's about what's in the expert's head. But we look at the experts as a as as a lens on the domain. So what we call it is cognitive work analysis. And what we're trying to do is discover the constraints in the domain. So, you know, when we talk to the expert pilots and somebody like Langeweicher points out that horizon is very important, and the aim point relative to horizon kind of specifies the angle of approach, the H angle specifies the angle of approach. We're those are facts of the domain flying that anybody should pay attention to. And so what we what we try to do is first of all find out what the experts are tending to. And, you know, oftentimes these are things that you know it takes 10 years to discover in the process of doing it, you know, to become tuned to those things. And what we want to do is then take those and make them easier to discover those things. And you can do it either through training, training the pilot, telling the pilot, you know, here's what you want to be looking at when you're landing, and these are the cues that that should line up if you're on the right approach. If these things line up, you're on the right approach. Or, you know, if you see the spot and it's stationary, as you move, you're not moving past and stuff, it's moving and it's moving on a course that's going to collide with you. You begin to, you can, you can train people to start looking at those things. But you can also build interfaces like a head up display that makes those things more easy, more explicit. And so, like in the business world, what ecological interface design approach would be doing is building sort of dashboards, but taking the variables that that the experts say are important and making those visible to the people who have less experience, make it make it easier for people so that it doesn't take 10 years to discover these variables, that by looking at this display and with some some instruction and some learning, you can begin to see things that it took people 10 years to learn to see.

Brian "Ponch" Rivera 30:25

So I want to what I want to do is this. I want to come back to business and strategy in a moment. So I'm gonna write that down. Um, and I do want to talk about sport and and uh experts and expertise and coaches and things like that. And I'll give you an example. So when I was an instructor in the Tomcat, uh, we take, we go out to the boat and you find out uh just how little awareness, I'm gonna use situational awareness, the pilot had on it on a downwind approach. So we're going downwind on the boat, you know, and in the brief, I'm like, okay, if we see the elevator open, we see this type of wake, we're gonna start our turn there. And I remember this, I'm like, hey, I forget who I was flying with, but I was said, hey, look over there, what do you see? And he's like, I don't know what you're talking about. So the wasn't ready for that, right? It was like, just give me to the turn, give me to the 90, and I'll get us where I need to go. I'm like, got it, man. I won't go back and debrief this because everything we talked about in the brief, I'm pointing out to you now. You can look outside and see it, but he wasn't ready for that. And it's just what is what are you capable of? So that'd be an internal constraint, I think, on the person. That that's not what they're ready for at the moment.

John Flach, PhD 31:20

Well, yeah. It's you know, what we talk about, that constraint is attunement. Yeah. Not in terms of you know facts that you store at a thing, but but you learn to look to see things. And, you know, a colleague of mine, Gavin Lintern, you know, talks about when he was learning to fly, he said, you know, when I was coming down an approach, you know, if uh, you know, I was too high, the instructor would tell me you're too high or you're too low, and you know, controlling it, moving it up and down is no problem. He said, But my instructor could see whether I was too high and too low, and I didn't I couldn't see it. I had to learn to see that. So, you know, I mean, so you know, gib Gibson was, you know, a lot of the affordances, grasping things, are things that we learn as infants through interaction with the world, through grabbing, you know, picking up balls and picking up objects and interacting from the world. But when aviation is interesting because we weren't designed and we don't we didn't evolve to fly, to move over the and you know, the chain now we're now we're in a thing where we can change altitude. Whereas, you know, when we were fixed to the ground, our altitude was determined by our height. Yeah.

Brian "Ponch" Rivera 32:23

So let me let me ask you this. Uh so you know, we're constraints led approach is big. There are folks that are really good at helping people understand that. At the

The constraints-led approach: giving coaches the language

Brian "Ponch" Rivera 32:30

same time, there are coaches out there that can you meet and you're like, you already know this. And like, I I never read a book. You don't need to read a book to know this. This is kind of intuitive sometimes, right? So even though um CLA is out there, there are coaches that are already doing this 50, 60% of the time, right? But they need the language. In my opinion, if you give them the language and and and the structure around this, that amplifies what they already know and dampens the things that they're they're they they they probably shouldn't be doing. Can you talk about like your role in going into a place and doing the cognitive work analysis? That's kind of what you're there to do, is help the experts see and and what they and help them articulate what it is they're seeing. Is that correct?

John Flach, PhD 33:10

Yes, yeah. And and again, a lot of expertise in sports is is tacit, you know. And so the people, the people who are the best players are not always the best coaches. That's tuned to it, but they couldn't tell you, they couldn't tell you what they're tuned to. Right. But they did they do it. It's it becomes automatic, and it and it's it's a result of hours and hours of practice. You know, you're you're gradually tuning your coordinated system. Golf is easy because it's it's explicit, but you know, you're learning how to lock out certain degrees of freedom so that you can drive a golf ball hard. And and so but you can't necessarily tell you know what's being locked out and stuff. You just know you hit the ball well. You know, some but but other coaches, and oftentimes they're not the best players because they're also they're often people who struggle to figure out these things, and so they're much more mindful about how they do it and what why they're not doing it well and stuff. And so so those often become the best coaches because they learn to articulate. But Gary Klein, I think one of the artful nature of what he does is he's just very good at getting people to talk about situations and things in which they discover. And what we just find in work analysis, we go to the experts, but we don't trust any individual expert. So different pilots will tell you different stories and say, you know, some of it, some of it, the things that are really important to them is tacit, so they they don't even know they're using it. But also there's some stup there's often superstitious behavior where they think certain things are are supporting them, but but they have a story around it, but it's not it's not very accurate in terms of what's really happening. So, but when you get two or three experts in the room and they start talking about it and stuff, then you begin to discover, you know, the the things when somebody says something that connects that it can often help other experts who are using it tacitly to articulate what they're doing. So, you know, we read Langeweisher, you know, you know, lots of pilots could land safely before Langeweisher, but they didn't know how they were doing it. Now Langeweisher was Greek, and he can say, here's why you can land safely, and you can see where you are because of these aspects of optics. If you look at the angular ration, you know, Langeweisher, if you look where he he describes that bowl and the the the bowl, he he says, you know, if you ask a passenger and you show them them sp a spot on the ground, and they say, you know, where is that spot? You know, where is that town? And the passengers say, Well, it's you know four miles ahead of me and you know so many feet below me. He said, if you ask a pilot where that that point is, he's gonna say it's at twenty degrees, or you know, it's thirty degrees below the horizon.

Speaker 2 36:03

Yeah.

John Flach, PhD 36:03

And he says, now it's different languages, but he said, the thing is the passenger is guessing. So they're not you're not good at judging distances, and you're not good at judging altitudes. The pilot, you can measure it as I the angle is totally specified. There's no doubt about what the angle is. It's totally specified. And he said, he said, but you know, so so first of all, the pilot, you can valid validate what he's saying right there. You don't have to you don't have to transfer anything to a mental model and convert, you know, angles to distances and stuff. The angle is this but it but Langweisha goes on if you read him, he says, and but most important is the angular relationships are the things that are most important for controlling your your plane. So it's the angle of the optic angles that you know it's a it's the distance below the horizon that tells you whether you can reach a point or not. And so if it you know there's a there's a range of angles that you can reach, and if it's if it's too steep, you know, you can't get there.

Brian "Ponch" Rivera 37:06

And if it's too shallow, you you know, you're you're gonna It sounds to me like this that most of these high flow sports are games of geometry.

John Flach, PhD 37:14

That's well that's what you're Well, vision, everything visual is a function of geometry. So, you know, you uh I think you've mentioned before catching baseball. You know, and you know the work on that is if as long as you when you if you align and the ball's going up at a constant speed, you know, even though the ball's actually going in arc, but if optically it catches you actually catch if you're in a position so it's rising at a you're at the spot to catch it. It's totally specified where that ball is, where your glove needs to be to intersect that ball optically. There's no there again, it's it's and that and that's the key, is these are not hints that have to be converted from your eye to your to a three-dimensional model of the world. This specifies where your hand needs to be if it's going to intersect the flight of that ball. Totally specified. There's no doubt about it. And and you know, you could build an automatic controller. And and you know, in cars, you know, optical braking systems that use the optics can tell you whether collision is imminent based on the angle and angular relationships. So when you look at that car, the headlights or the you know, the taillights of that car, you know, when they're expanding at a high rate, you know, if you're ever in a collision, the last thing you see is this whoosh, you know, as as expanding. Um, that angle and angular rate tells you the imminence of collision. If you can keep if it's a constant angle, it's not changing, then you're constant distance away. If it starts expanding, you're getting closer to it. I mean, expanding at a high rate, then then you're going to collide with it very soon if you don't do something, if you don't break. And uh, you know, and if it's if it's getting smaller, that thing is leaving you, is going away from you.

Brian "Ponch" Rivera 38:53

So I wonder if you can uh help out a little bit on the idea of constraints in your world, just so uh our listeners can understand what's happening in ecological dynamics. And you're you're seeing constraints pop up more and more. And we've we've known about like a to me, a red teaming technique is a constraint. We had Alicia Giraro on here who brought up that feedback is a constraint. So an effective debrief is a good constraint. For pathways are constraints. There's all kinds of constraints out there. But can you talk about constraints in the context of of your world and and uh uh what that means?

John Flach, PhD 39:22

Yeah. So so what I and if you in our in our book, A Meaning Processing Approach to Cognition, what

Three classes of constraints: affording, specifying, satisfying

John Flach, PhD 39:30

we what we talk about is we think there are three classes of constraints that you have to pay attention to. And each constraint is a relationship between you and the ecology. Yes. So the first, you know, that people are familiar with is affordance. So affording. And I don't like the noun affordance, because it's it's a coupling, so it's affording. And that affordance is a a function of a relationship between you, your you know, so the classical example is graspable. So graspable is a size relative to your hand, and it's a relationship. So you there's two points that it's a it's a dual, it's it's a duality that the hand has to be at a certain size, it's the size of the object relative to your hand. And that's the same for all people, right? So you can say that ratio that's graspable, and and it might change something with ages and ability, but in general, you can say that as you grow up, your hand changes size, and what's graspable changes size, but that relationship is constant over hand sizes. So a certain width of your hand, you can specify objects if they're like with 80% of that width, then it's easily graspable with one hand. If it's more than 80%, but it's relative to your hand. So that's that's affording, and people know that it's you know the act the limits on action, what what the possibilities for action are. But what we've been talking about with optics is that's specifying. So that's different, that's information. And so what is the information that specifies the size of that object relative to you? And that's where the optics come in. And so what is the information? What is the relationship between what you see, what you hear, what you can sense, and that relationship with graspable? So how you know what is it that allows you to see whether the object is graspable or to see whether the gap is you can go through it or not?

Speaker 2 41:27

Mm-hmm.

John Flach, PhD 41:28

Okay, and so it's so it's all but it, but the the affordance is relative to your width or the width of your vehicle and the size of that gap. But the information is the optics that tell you whether that, you know, that gap is gonna open up for you or whether that gap is not opening up fast enough and you're gonna it's gonna hit the edge of your so but that's separate. The information is is an another set of constraints. And if and what Gibson showed is that for a lot of control locomotion, the information, the invariance in the optic flow field specifies the affordances. But in but in business, you know, you don't have the as you say, you don't have the optical flow field. So it's not specified unless we do something to make it visible or make it, you know, there are variables out there that if if I were going to build a an automatic business machine, I would want to know what the state variables are. Those are the variables I need to pay attention to. And then I would have to make sure that those variables are fed back in a way that I could control them.

Brian "Ponch" Rivera 42:25

And and so what Well that that might that might connect to that strategy thing that I was just talking about uh earlier, right? So in order to build a strategy, our view is you need to have a map.

John Flach, PhD 42:36

Right. You you need to have some kind of feedback. You need to close the loop around what the key variables are. And the the problem is with when we go into a new sport or new domain, we don't know what the state variables are. We don't know what to pay attention to. We don't know what differences make a difference.

Brian "Ponch" Rivera 42:52

But that's why that's why you need people in your organization, in our opinion, you need people in your organization to help you map that out, identify the constraints. Exactly.

John Flach, PhD 42:58

Okay, right. Yeah. And that's what, you know, what in terms of ecological interface design, well, we if we know what those variables are, then we can use graphical computers to make those more visible. You know, you maybe you build graphs, you build relationships to show so instead of showing the pilot airspeed and altitude, you show them potential and and kinetic energy or total energy. There you go. Okay, we're back. That's great. That's a great connection. And that's the same. And then the third thing, and and this is somewhat of odds of Gibson, but when Gibson defined affordance, he said the you know, the capabilities and the consequences. So he he confounded the consequences with the action limits on action. But we we think, and that's what we call satisfying, and and that's also a relationship. So satisfying is is, you know, well, for example, and the easiest example is food. You know, it food can appear attractive and stuff, but it could be, you know, it could be a poison berry or it could be a nutrition berry. And that's a relationship between the chemistry of that thing out there and the physiology of your body. And so, you know, a dog might find chocolate to be very attractive and want to eat it, but then discover that that's it's poison for the dog. Right? And and so, and so we think that's another thing is, you know, so and that's that's a value system. So, like, you know, one of the you know, when you talk about managing risk in business, you know, the values, the consequences are, you know, well what are the potential errors? And and by the way, there is no errorless, you know, we know from signal detection theory and signal noise that you know you can balance hits against misses or false alarms, but you can't eliminate error altogether. And but what an expert who understands the values, he knows what the consequences are, what the payoff matrix is. And certain errors have very low costs, and so you can afford. So if you're a doctor oh and you're diagnosing, you know, there are certain things that if if you treat this, you know, the treatment won't necessarily have any will have minor side effects. But if you're you don't treat it, the effects could be catastrophical. So so you want to be aggressively treating. There's other things where You know, there's some cancers where the the consequences of the treatment are worse than the progress of the of the disease. And so if you treat it aggressively, you're actually creating high costs. And so that's separate. So you need to know what you can do. So all the possible things you could do. You need to know, well, how can I differentiate them? How can I see what I can do and stuff? And then you have to know, well, what are the values of doing it or not? You know, if I do it, you know, are the consequences worth the risks of being wrong? And so so we think those three classes of constraints are separate. And each one is has a, you know, that's what we try to digress to represent in that puzzle diagram on the cover of the book is to show that there's a there's a physics side to it, you know, there's an ecological side, and there's a cognitive side. So, you know, in terms of satisfying, there's the intention, what I think is good for me, what my goals are, but then there's the real consequences of what happens if and so so part of you know being a good rock climber is understanding, you know, the what risks are worth taking or and what risks and how do you protect yourself, how do you put in protection so that if you do fall, you're not gonna you're not gonna have the consequences are not gonna be awful for you. So just finish. So we tend to think the classical view is that the right side, you know, those things in the world that are described by physics, so you know, the poison nature of the of the consequences, the structure of light, the the action constraints, those are things, those are truth. And and then these things on on the left side are subjective. So there's the objective and the right and the subjective ring. What what we say is experience is actually between those things. So if you want to understand experience, you have to know what the pilot thinks he can do with the airplane, what he can see, the cues that he uses to determine what he can do with the airplane, and then the real consequences of the physics of what's going to actually happen if he does that to the plane. And that we're thinking, and this this goes back to William James and Peirce and the pragmatist psychologist, is saying reality is not on the right of this diagram. It's not like objective, and here's subjective, but experience is in the center. Experience is relational. And what we experience is what the possibilities for action, the kinds of information that I should be attending to to decide which possibilities to realize, and the potential consequences of doing those things. John, this is ecological interfaces trying to make those things visible to people.

Brian "Ponch" Rivera 48:12

But this is timely. I I don't know if you saw the substacket I went

Experience is relational: Hoffman, William James, and orientation

Brian "Ponch" Rivera 48:15

out this morning about experience in connection to uh perception, decision, action loop by Hoffman. But everything you just said resonates with what the neuroscientists are saying.

John Flach, PhD 48:25

Yeah, is that Robert Hoffman?

Brian "Ponch" Rivera 48:27

Uh Donald Hoffman uh Donald Trump. Donald Hoffman.

John Flach, PhD 48:30

Yeah.

Brian "Ponch" Rivera 48:30

Yeah. So so that everything you just said lines up to that. So that experience that we're having is kind of internal, right? What you and I are experiencing right now is not the reality, but we're having this experience at the moment. That's internal to our orientation or the way you just described it with your puzzle there. That's what the neuroscientists are saying, too, right? That's that's exactly. So this convergence is awesome at the moment that these different disciplines are all kind of converging together. And yeah, there's some stress about perception and action. And do I need this? Do I need active inference? It doesn't matter, right? It's context-specific. So in sports, I don't need to teach a coach about active inference. I need to teach about perception action coupling with the environment. And I can use, in our, in our case, part of the OODA loop that matters to them, right? But with the str with the business leaders and and uh those that are, you know, the C-suite, they're probably gonna want to know a little bit about risk management and active inference to understand mapping the things we just talked about. Right. So again, it's not it's not uh this or that, it's it's both, and right? We need we need these things in its context specific. So very timely discussion in this book. When did this book come out?

John Flach, PhD 49:33

Is this you said this So actually we self-published it as What Matters, and then the the current version then was uh we got a publisher, and they didn't they didn't like the title What Matters because they didn't think people would know what it's about. So we had to change the title to the a meaning processing approach to cognition.

Brian "Ponch" Rivera 49:52

So let me so people always ask, what are you gonna do with this information? Um, you know, yeah, we talk you talk about theory a lot on here, and people are like, oh, it's great. You know, I'm gonna go talk tell everybody about mindset and get up at 4 a.m. and get after it. Okay, that's great. But what can you do with this book? And let me let me kind of preface this. Yesterday I had a call with Transforming Basketball, some of the guys that work with Alex Sarama, who's the head coach at Portland Fire. Here's a person that read Ecological Dynamics, right? And when he was 21, 22, and now he's a head coach in the WNBA, and he's dominating. Yeah, it's not a not a winning organization yet, it will be, but they're competing, and he's using the ideas that you and I talked

What a leader can use tomorrow: building the dashboard

Brian "Ponch" Rivera 50:33

about. But I want to go back to the question: what can a leader learn from your book that they can apply tomorrow?

John Flach, PhD 50:40

Well, so the intention of our book, I mean, and and the intention of all our work is the audience we want to reach are not other psychologists, but designers.

Brian "Ponch" Rivera 50:49

Okay.

John Flach, PhD 50:50

So the the whole and and our focus has largely been on graphical design, you know, designing interfaces that allow you, so like in a nuclear power plant, building a safety parameter display. And to build that, you need to know what the variables are that they should be attending to, what are the relationships across those variables that are diagnostic, and how to put them on a screen in a way that that you can not analyze the situation, but you can see the situation whether it's safe or not. And there was a early uh a guy named Coakin built a safety parameter display that you might have seen, an octagon display. And essentially it was an octagon, and it there were eight variables that they identified that was key to stability in nuclear power plant. All right. And what they did is they scaled the display, so if those parameters are in the right relationship, you got a symmetric octagon. So it was, you know, it'd be symmetric. But if if it was going like a loss of coolant accident, it would start to deform in a very recognizable way. So when you saw so symmetry is something that people are really good at picking up. Yep. Okay. And so if you build a thing where the desirable state is symmetric, and you can begin to see that when it becomes asymmetric, certain kinds of asymmetries are associated with certain states. So a loss of coolant accident looks, deforms in a very recognizable way. And so now you're having, in a sense, you know, again, the way we thought about it is the operating nuclear power plant doesn't have an optical flow field. So if we were going to build an optical flow field that had invariants that specify the affordances of nuclear power, the constraints that they need to pay attention to, what would that flow field look like? And basically it's things like building symmetries and relationships, you know, putting in landmarks like horizons in the display and things that allow you to, again, it's it's creating a visual language to communicate the things that are in the in the expert's head. And we think by building that visually and you know, using that language in things that are easy for anybody to detect, like a change in symmetry is something that people can pick up very quickly. And so, you know, so if you if you say so, if if like if a business leader says, these are the if I want to know what with the state of our business, whether we're healthy or not, these are the variables I look at. And there's trade-offs among these variables, but if a good balance among these variables, this is what if you can represent those three variables in a graph, and so when those things are in a healthy state, the graph looks nice symmetric. Well, but when something gets out of balance, now you see this symmetry, you know, and it could be as simple as a bar graph, where these things are these four bars are scaled so that when it's healthy, the bars are even. But if one gets too much of one or too little of one, now it gets that relative to the others, it gets starts to get high or or get small. Then you can actually see, you can see, wait a minute, we're not in a healthy state. And the reason we're healthy is we're not healthy is this variable is too high. You know, we we re we did a display for cardiac health that we took took the the models, the mathematical models of cardiohealth, and reverse engineered it and took all the variables that are in that model, the the Framingham model. And so, you know, right now you can go online and find calculators that will tell you your Framingham score. And they can tell you whether you have a good, if you have a score, a certain score, then you know you're you're you're not healthy heart-wise. But what it doesn't show you, it shows you the computation, but that's based on an equation that has like eight and nine variables. So what we showed is we took that equation and you can see each of the variables. So not only can you see that, okay, my Framingham number is high, but you can see the thing that's out of balance is my LDL cholesterol. Or, you know, we sent this display to Don Norman and he said, Oh, you know, he said, said, you know, according to this, I'm I'm at risk. But he said, it's because I'm 78. If I change my age on your display, and and again, one of the things ecological allows you to manipulate variables, if I put my age to 42, I'm undergreen on everything. So I can't change my age. I know, you know, so yeah, yeah. So so not only can I say I'm I'm at risk, but the reason I'm at risk is age. And of course, medicine can't do anything in that. Now, alternatively, you know, somebody's 40 and they're at risk, but they can see is hey, my cholesterol, it's my LDL cholesterol. Or one of the things, the big variables is smoker. So you're a high risk and you switch from your smoker, but you switch non-smoker, all of a sudden your number goes down, and you can actually see that that variable has a the reason my score is high is because I'm smoking. And we also believe that if you can show that to a patient and say, look, your numbers are at risk, but guess what? If we, you're smoker, if like let's just switch, see what would be if you're a non-smoker, and all of a sudden everything drops. We think that's a powerful message to give to a to a patient.

Brian "Ponch" Rivera 56:10

Well, you could do the same with uh athletes and uh and teams and give 100%. So now you're getting this optical flow field, which could be strategy for business leaders.

John Flach, PhD 56:19

I mean, that's another way to it's how to visualize that strategy. As and again, what you want to do is take so what are the variables important? What are the relationships important? And if you can create a graphic where the relationships on your screen show whether things are in balance or out of balance, and not only show that you're unhealthy, but show what variable is driving that, you know, that that's causing you to be unhealthy. You know, is it is it is it my employees' attitude? Is it is it my you know, you know, my I don't know, financial health, you know, the amount of reserves I have, is it, you know, what is it that's that now is is causing me to our system to be a little less stable than we'd like it to be.

Brian "Ponch" Rivera 57:06

I'm wondering if this is going to be more important in the age of AI, like human machine teaming, well, you know, having these kinds of okay, so this has to happen.

Human-machine teaming: making the AI's computations visible

John Flach, PhD 57:15

So, well, so what happens, the problem with AI is the AI computations are invisible. So there's no flow field.

unknown 57:27

Okay.

John Flach, PhD 57:27

But if you can, and so the AI gives you advice and says you need cholesterol medicine, but why? Why do I need cholesterol medicine? You know, what is it? What is it if if you can if you visualize so what the flow field is trying to, so the the AI is weighting all these variables and there's some equation kind of driving it. If you can let the person see how the AI is doing its computations, then they can not only understand what the AI is thinking. So, you know, a metaphor is, you know, you think about it an advisor, and so a student comes into me and is getting ready to get their PhD and says, you know, I got these job options and stuff. What should I take? And what does a good advisor do? Do I tell them, okay, you should take this job or that job? But a good advisor says, Well, what's important to you? And what kind of things? Here are some things you should be thinking about. You know, what about your family? What about, you know, what about the money compensation? Well, what about your health, who you're gonna be working with? You know, you ask them questions and you never tell them what decision to make. But if you get them to attend to the right variables, they walk out of your office knowing which job they're gonna take.

Brian "Ponch" Rivera 58:41

Well, that sounds like what a coach should be doing in sports. Exactly.

John Flach, PhD 58:44

Exactly. And that's and that's what the constraints led approach does, is it, you know, by, you know, when you pitch, you know, you put the ball under your arm, and so when you release your arm, if the ball is goes forward, you know, then it's good. But if the ball goes backwards, it's but but that ball, what you're doing is, you know, there's this complex relationship, coordination relationship, but he can't see it. But when you put that ball there, and now if you do it right, the ball goes one direction, but if you do it wrong, the ball goes a different direction. Now he now it's visible. And and now the player can experiment and figure out what they have to do to make the ball go forward instead of backwards when I when I release the ball. And you know, this the secondary ball, when I'm coordinating, now I can see it, and so now we can do it over and over again. And then when they get very good at making the ball, this ball on your go forward when you release it and throw, then your core, your your coordination is is right, is your mechanics are right. But you you can't describe the mechanics in language in a way, but if you can put the ball, they can begin to see it. Now, you know, I I often, as a teacher, somebody thinks about teaching and stuff, I I always think about the difference between teachers and coaches. And when you're teaching in a university, the teacher tells you what's important, but he also writes the tests. And so if you don't agree with the teacher about what's important, then you fail. Okay, the coach tells you what's important, and the coach makes you do a lot of things that might feel foolish and stuff, and you want to just go out and play, and they tell you to do these things and stuff. But the coach doesn't write the test, your opponents write the test. And if it's a good coach, you discover that what he's calling was important because now you begin seeing improvements in your performance against the against opponents. But if it's a lousy coach and he's telling you to do silly things, you discover that again also. And so that the point is that teaching the way we currently design it is a totally closed system. So it's all about what the teacher thinks is important. But coaching is an open system. So the test of whether the coach is telling you things are good is the opponent. It's outside the tests, are outside the teaching thing. And that's the same thing. You know, we discover all the time, and the oftentimes when we build these ecological displays, you know, people look at them and say, Well, that doesn't make sense. And then they start using it. And it's, oh, wait a minute. Ah, that's lots of cool. I can now see things that I could never see before. And they discover the value of the display in using it. Not because we say it's important or it's a good, but all of a sudden their performance. And and the problem is that classical education, there's no external grounding. It's totally closed system. But but coaching is an open system because performance in the World Cup tells you a lot about whether that coach is a good coach or not.

Brian "Ponch" Rivera 1:01:49

I never heard that before. That's a great way to frame it. Hey, you you sent me this um, I'm gonna share it here with you, make sure I get this right. You sent this to me the other day, and you wanted to talk about this and how it connects to uh diagrams and and modeling. You give us some background on this?

John Flach, PhD 1:02:04

So, you know, the default way that we that we often represent these processes,

Rasmussen's decision ladder and the non-linear OODA loop

John Flach, PhD 1:02:11

you know, is the oodle loop and uh, you know, and you can you can expand, you know, the diagrams on your board behind you there, the more complex diagram of the oodle loop. And you know, a diagram that I like, and a lot of this, the whole uh concept of ecological interface design goes back to Jens Rasmussen and the whole idea of cognizant engineering. And and one of the things that I very much like is Jens's abstraction hierarchy. I mean, not sorry, the decision ladder. And that's that's this diagram here. And people in cognizant engineering, a lot of people are familiar with Rasmussen's work and stuff. And one of the things that it shows, this is a variation of the more complicated version of Boyd's diagram of what's happening. And one of the things that this shows by showing the perception is one side of this hierarchy, and the action is the so the left side is information coming in, the right side is information going out. But what he shows is that what he observed when they looked at expert performance is there's lots of shortcuts. You know, you don't always take it and analyze it and go from, you know, you don't go from the horizon and stuff to infer what this two-dimensional retina is telling you about a three-dimensional world, and then both based on that, you know, analyze it and decide, well, is this gonna hit me or not? What you do is you begin to see, you see an expansion rate, and you say, hit my brakes. And so there's lots of shortcuts through this system that experts learn to take. And these shortcuts are the heuristics that experts learn. So, you know, when you go into a domain, it's all analytical. You got to figure, well, what's where why is he doing this? What's doing that? And you got to figure it out. But pretty soon you begin to see the landmarks, you know. So you know if you're in a Dutch town, you know, if you know where, if you can see the church, if you know where your hotel is relative to the church, then anywhere in that Dutch town, all you have to do is look up and see where the steeple is, and you know where you are and get back to your so you learn what these shortcuts, all these are all shortcuts that experts, and and that's what you know what I think when we're talking, interviewing experts, we're we're looking for these shortcuts that allow these experts to do things that are impossible for mere humans. Okay, so I like this, and and that you know, and and there are qualitative distinctions that a lot of people recognize, and and you know, in this, you know, he talks about skill base and rule base and knowledge base. But when we represent this as boxes, again, as similar similar with the diagrams you have on the board behind you, there's an implicit assumption that you're that's decomposable. You know, like I think these discussions about what is it orientation or observation or where you know what goes first and what it's I think these are very unproductive.

Brian "Ponch" Rivera 1:04:55

Okay.

John Flach, PhD 1:04:56

And this is this is where I would redraw the abstraction hierarchy. And the the point is, is that that information is coming in and that there's layers in cognitive systems. And you have skills, automatic, you know, if I see this, do this. But you also have heuristics like rules, like if I'm, you know, if I'm in a small town, look for the steeple, you know, that's a that's a heuristic that I know. And then that allows me to directly navigate without having to, and and then you have knowledge about, you know, that you know, in certain towns this this works. Other places like New York City, you can't see the landmarks from, you know, you get into the canyons of buildings and you can't just pick out one landmark to get to, and then you then you begin to learn to use the rivers to navigate. And you say, Oh, I know these boundaries, these are hard boundaries. If I know where my post is relative to the river, I go to the river and I know which direction to go to my hotel and and things. But and so what I think is we visualize this is your

Standardization, planning, mutual adjustment, and the ATO

John Flach, PhD 1:06:01

knowledge kind of sets up the context that tells you under what circumstances certain heuristics, certain rules are gonna be applied and can be used. And then those rules also set the the boundary conditions and tell you what you should be, what accused, what should be the trigger of your actions, what triggers you should use when you see this. And that's what you know, I think Langeweicher is describing some of the some of the trick the the triggers or heuristics and based on information that allow you to skill skillfully control your plane once you know those so and all of this is relative to a work domain. So that does you what you're trying to find is what the constraints are. And interestingly, actually, we we came to this re-representation not from looking at individuals, but looking at organizations.

Speaker 2 1:06:51

Okay.

John Flach, PhD 1:06:52

And we were we were looking at at emergency operations and organizational theory. And Thompson talks about standardization, planning, and mutual adjustment as layers in organizations. So the standardization is you know what you're trained to do as cops, and you get standard procedures, and and firefighters have different standards and sting of operation. And then, but when during an operation, then that's Sets a context for how you plan and you lay down the plans. And then the plans set the boundary conditions for how the firefighters and police work together in in real time based on what they can see and what's happening at the situation. And so, so, you know, it what Thompson would say is the knowledge base would be the standards that the policemen bring to the situation. The rule base is the incident command, and they're setting up the plans and the resources. And then the mutual adjustment is what's happening by the individuals on the ground, immersed in the situation, seeing what's happening on the ground in real time and making adjustments. And each of these loops, these loops are all happening simultaneously. So one of the things, one of the misconceptions people have about the decision ladder is well, this is skill-based or this is rule-based or this is knowledge-based. You know, they take them as categories, but your knowledge doesn't go away. Your knowledge sets the context for which heuristics you're going to pay attention to, which tells you what to attend to and what to trigger. These things are all happening, but they're happening in, you know, the mutual adjustment is happening in milliseconds to minutes. The planning is happening in hours and days, you know, like the, you know, the the air air tasking order, ATO is set up at, you know, is going to be like an eight-hour cycle or something like that, you know. And the thing is, is once that air tasking order gets out and they're now they're working a mutual adjustment and the planes are flying around, the planning doesn't stop. The next ATO is already being planned and stuff, and and they're monitoring what's happening and what their expectations are, and they're building the plan. It's and but it's happening at the time of eight hours.

Brian "Ponch" Rivera 1:09:00

You know, you know I was a map chief in a combat plans division.

John Flach, PhD 1:09:04

No, I didn't know that.

Brian "Ponch" Rivera 1:09:05

Yeah. I spent a lot of time in an aerospace operations center. I went through all that training, so I totally understand what you're talking about. This is awesome.

John Flach, PhD 1:09:12

We did a project on time-sensitive targeting where we looked at the ATO and and looked at the real-time kind of feedback and things, what's happening for the you know, targets of opportunity and how things outside the plan some kind of the that's how they do the mutual adjustment.

Brian "Ponch" Rivera 1:09:27

Right. So we create optionality in the air in that plan. But I want to go back to your your knowledge rule-based and skill-based. In an organization, generally most organizations don't know how to plan. They don't have the optical uh flow field, like you already talked about. They're already behind on all this, right? Yeah. And that's that's what we're suggesting to organizations is um learn these, learn a good planning process, make it standardized. It doesn't mean it's you know, it's it's it's it doesn't have to be perfect all the time. You just need something that's uh I'm gonna use a concept shared mental model.

John Flach, PhD 1:10:00

And that's a big part of Boyd, is that you know, what does it, you know, what kind of how do you plan in order to allow

Command and intent: don't over-constrain the people on the ground

John Flach, PhD 1:10:07

the people on the ground to adapt in real time so so that your plan doesn't over-constrain them, that it gives them the degrees of freedom and the resources they need to make smart decisions. So you've got to trust your the people on the ground to, you know, this is the whole idea of command intent. You don't want to over-constrain them. You want to give them the degrees of freedom that they need to adjust in real time to what's happening underground. And and and that's, you know, and and that's why you have doctrine is at the knowledge base level that tells you what good planning looks like. And that's, you know, and that's what Boyd had a lot to do with the the marine doctrine on command intent and how how you you know that you don't over-constrain what your junior officer are doing by a central planning committee.

Brian "Ponch" Rivera 1:10:57

That's the speaking of the constraints in the ATO, I just realized this. If you think about going back to, you know, building out the Master Air Attack Plan in an Air and Space Operations Center that delivers the air air task in order, the constraints that I had to deal with being a Navy guy coming into the Air Force is I understood the flight deck constraints, right? Most people are like, oh, just fly anytime you want. I'm like, that's not how a carrier works. I don't know if you ever been on one. Yeah. And then then you then you get into pairing. The longest pull in the tent, I'm using that as an example, is fueling. We could design an air, you know, a scheme of maneuver pretty not fast, but we could do it a good 30 of us can do it pretty in a in a nice speed. But the the slow part was the pairing, the the tanker pairing. Well, and that's actually what drove that's what actually drove the cycles in the air task in order. And they when they came to us and asked that, I said, well, look at them right there. It's taking eight hours to do pairing for tankers, right?

John Flach, PhD 1:11:51

We did uh we participated in a Jeff X exercise out at Nellis. They used to run these Jeff X joint air operation exercises and stuff. And they bring in new technology, trying to experiment in real time. And and you know, this is like a year-long process, and at the end they have the live fly event and stuff. Well, and we were out there observing because well, one of the things is they were part way into the process and they realized that they didn't have any human factor people involved.

Speaker 1 1:12:20

Wow.

John Flach, PhD 1:12:21

And and we actually they allowed us to observe for free. So we just wanted to get in and see what's happening and stuff. And so we said, well, we'll do it for free if you let us in the door. And and they did, and we got to go observe. But one of the things that happened in that live fly event is they discovered in the process that they in the whole event, they were never able to pair a tanker with a with a with a jet outside of the ATO. That is, if it wasn't planned, if they had to, you know, if they had a time sensitive target, but it required them to pair a tanker with a fighter to do a new uh something other than outside the air testing order. They couldn't, they couldn't, it wasn't possible with the technology and the software and the way the things were set up. They never were able to do that pairing.

Brian "Ponch" Rivera 1:13:09

Yeah. So this is interesting. Uh I'm I'm glad you brought this up. I was working with a JFAC, and you know, we had to train the JFACs as a map chief because we had to bring them in and go through those uh operations, exercises. And one of them had a um a logistics background, so like a uh you know, C-5 pilot, and his his view of the world was, I wanted I want to know the tail turns on this. I'm like, well, that's I don't I don't know, man. I've got F-16 squadrons, F-15 squadrons with maybe six or seven up jets, and they're rotating 30 some aircraft a day with their 15 pilots or whatever, right? I'm like, I don't know which aircraft they're using, and you shouldn't be worried about that either. But they what ends up happening is people these people start getting so tactical. They want to know exactly what aircraft's gonna fly in three days. I'm like, dude, I have no idea how what's gonna fly in three days, right? But it's it's the orientation again, their background is driving their view of the world, and you're like, well, hold on a second, man. That's not how that works here. And but being a I think I at the time I was a senior 04, I had to go to a mentor of the JFAC and go, hey, how do I talk to him about this? Because what he's asking me to do doesn't make any sense, right? So again, it's it's that that aerospace operation experience has driven me and actually created a lot of things inside the flow system because I got to experience that in for four years, right? I mean, that that's what I did for my my life for four years.

John Flach, PhD 1:14:35

And and that's exactly that's what we mean by work analysis. Okay. That is, you know, so what we're talking about is, you know, what variables people think are important versus what variables are really important. And and that's where, you know, discussing with experts have it, you know, and again, experts have disagreements, and some experts, you know, will and and again, because first of all, the world is too big. You know, the complexity, I mean, this is where complexity comes in. And each of us see part of the elephant, you know, and what seems really important to one person standing here may be very insignificant to the in terms of the big picture. And so, so what we try to do is, you know, work analysis is not so much what's in the expert's head, but we want to know is what are the things uh that the expert we use the experts as a lens to think about candidates of what it's important. But but then we need to work out, and and sometimes you can work this out with discussions among the experts. So when they talk to other experts and something can discover things, but but expertise is sometimes, so if you're interested in nuclear power plant or you're interested in aviation, sometimes the pilots aren't the best source. Sometimes you got to talk to the aeronautical engineers or the the designers of the nuclear power plant, the physicists who built this thing, who understand thermodynamics at a level that the operators don't. You know, when you're training as a pilot, you've got to do aerodynamics and stuff and things, but that's not what you want to do, and that's not your main focus as your pilot. You're taking you want to go out there and fly. But an aeronautical engineer, that's all you think about is those constraints and what those constraints is. And much of aeronautical engineers have great rep ways of representing the energy balance and things and stuff, and they can that allow you to visualize things and understand constraints in a way that you that are not easy to discover in the process of flying, for example. And and so, you know, when we're doing the work analysis, it's not just go out and talk to the experts, it's talking to a range of people to find what the perspective, what do the the you know, nuclear engineers think is important, and what do the thermodynamics physicists think is important, and then talk to the operators and see how what the operators see that that and and then think about well, what could we help the operators see things that the thermodynamic engineers think are important and as our ways and our graphics to make these visible. But you want to talk to a variety of people. So you know you want to talk in the businesses, you don't just talk to the CEO, but you talk to the people who are on the ground managing inventory and the people who are interfacing the customers, for example.

Brian "Ponch" Rivera 1:17:10

Right, right. But most business leaders don't do that. They will not ask and I see I've seen this, and I actually just had a conversation yesterday with an oil and gas company about this. That you know, I went up to Canada, sat down and tried to do some work with them, and I realized that the 30 people in the room didn't know what they did as an organization. They they knew their little thing, right? I'd I do this. Yeah. I'm like, but but what do you guys do?

John Flach, PhD 1:17:30

Yeah, and that's the thing is is you need to again, and that's what complexity theory tells us is that you know, that that you need to take multiple perspectives on this thing. And that that, you know, that and that a small deviation, you know, a small butterfly can make the difference between whether the tornado happens in Illinois or whether it happens in Ohio. And so, and and and again, again, and part of the experience, you can't see all the butterflies, but part of the experience is knows that there are some things that are useful in telling, you know, whether conditions are favorable for new for tornadoes or not favorable for tornadoes, and what are the what are the possibilities? And so again, that's what you want to do is is you know talk to everybody as many people in the domain as possible. And what you want to understand is what are the real constraints, what are the what is the information that's most diagnostic, and and what is the value system, what are the trade-offs in terms of you know that's why we're talking about affording, what can be done, how do you differentiate the possibilities, how do you see, how do you control the actions in a way, and then what are the consequences of area or failure and things. And so we think those are the three things that that you know, the kinds of questions you want to understand, to understand not expertise, but a work domain. What are the ground ground you so you know the challenge is is to ground what experts think in the reality of the domain. Right.

Brian "Ponch" Rivera 1:18:59

Wow, this has been awesome. Uh hey, I appreciate you uh coming on again today. Uh, I know you and I have been trying to have this conversation for a while, and I do appreciate the background on on optic flow because that came in handy when we were at working with a client to have that conversation, to actually be in a museum, to talk about it, to have them fly. You can't, you I mean, that is probably the coolest experience uh we've ever put together for an organization was to to do it like that. And I would say even the simulation we use is a simulation that has poorly designed interfaces for a reason, because we want them to communicate at a at a different level and and work together. Obviously, that's not how you want to design systems, but that's how we want to design a system that's gonna enable us to create teamwork. And I ought to show you that someday on how we use that simulation to and the flow system and all that to work on the teaming skills, because it is basically the constraints-led approach for non-technical skills, which is universal, I think. Um

Social sensitivity and team performance: Pentland's social physics

Brian "Ponch" Rivera 1:19:50

Yeah.

John Flach, PhD 1:19:51

And I mean, so the other thing is is what we discover in organizations is that the social dynamic is critical. And you know, there there's some work out of MIT that looked at group problem solving creativity, and first of all, they discovered that IQ of the individuals did not predict performance of the group. And average IQ didn't predict performance. The highest IQ in the group didn't predict performance. One of the variables that actually predicted the quality of performance of the group was whether there was a woman in the group. I've seen that. And groups with women per outperformed other groups. But what that they found is the most important thing, or or the the variable that predicted performance and ranking of this group performance was social sensitivity index. And, you know, so you know, if you want a quality team, you not only have to know the domain and the work, but you also have to know how to communicate that in a way that doesn't destroy the dynamic. You know, you know, you can be the best player, but if you're an asshole, your team is not going to win the Social Sensitivity Index.

Brian "Ponch" Rivera 1:21:01

So we talk about behaviors, we talk about non-technical skills. We also talk about from a complexity perspective, it's not the quality of the agent, it's the quality of interactions. So social sensitivity index, what is that exactly? What does that mean?

John Flach, PhD 1:21:11

Yeah, so so that's actually uh like an IQ test. And so, and and it's purportedly measuring your sensitivity to social cues and things like that. So Okay, okay, yeah. You know, so that that's just uh, you know, and so Like body language? Well, well, the SSI is an actual test. It's like a it's like an IQ test.

Speaker 2 1:21:32

Okay.

John Flach, PhD 1:21:33

But you know what what they you know, Pentlin and and his group did this research and they looked at the at the and the the their goal was to build a IQ test for teams.

Brian "Ponch" Rivera 1:21:42

This is social physics, right? I think that's yeah, social physics, yeah.

John Flach, PhD 1:21:45

Yeah, and he pentlin, he has a book on that the social physics and stuff. Okay. I'm tracking now. But again, you know, what he f you know the communicate the relationships within the team are really important. And and because, and again, it has to do with this information is is making information public. And, you know, if the information is in your head, it's not of any use to the team. It's gotta be communicated effectively. And and and if one of the problems is is sometimes we think that what's obvious to us is obvious to everybody else. So it goes without saying. And and so, I mean, that's and that's you know, one of the key things for business success. Your business has happened in a not just a physical environment, but a social environment. Right.

Brian "Ponch" Rivera 1:22:31

So I just saw um I just saw uh David Epstein write uh for time an article on him this past week that talked about basically a

After action reviews make constraints visible

Brian "Ponch" Rivera 1:22:39

pre-mortem as a constraint, right? So and you think about you brought up feedback as a constraint, we use red teaming as constraints, and the reason we use them is because we want to uh make sure that information um is shared, right? Yeah. Uh yeah.

John Flach, PhD 1:22:52

But I don't, you know, I wouldn't exactly s articulate that way. So I think your point is right, but but you know, but after action reviews and and pre-mortems and things, what these are effective is making information visible. That is if what it what those do, and and those they're not the constraints, but what they do is they help people externalize what is inside their head in a way that others can also relate to that. Right, right. Yeah. So so so what I would say is, you know, the after-action review is not the constraint, but that's a very effective method of making constraints visible within the team. And the after-action review, I mean, that's one of the things, and when we watched Jeff X, one of the things I was really impressed with is after the live fly, the after-action review that the pilots did. When they have a you know, a junior pilot, you know, goes through it and just and and you know, it just relative to what I experienced in academic faculty meetings, I just thought, oh, this is, you know, in faculty accura meetings, it was all about whining and why this was no whining. It's like, here's what happened, here's what was wrong, here was what was right, here's what we got to do better next time, you know, is I I just thought, like, wow, that's the way to run an organization.

Brian "Ponch" Rivera 1:24:09

Yeah. So and uh shortcuts, there are shortcuts in an after action review, and people gotta know this. It's it's context, right? So if you're used to the domain you're in and you're used to seeing these things, I don't need to go through the list of what is everybody seeing. I can as a leader I can go, here's what we got, you know, here and boom, boom, boom, boom. But most organizations can't get to that unless they go through the the basics, you know, what happened? Why are we were why were we here in the first place? Yeah, most times they can't answer that, right?

John Flach, PhD 1:24:34

Yeah, yeah. I mean, it it's part of the standardization that you guys have been trained from, you know, it's part of the the knowledge base, sets the context for you guys to do after. But but you know, people in business don't have that background and that common training. They don't have the standards that allow them to do the the after-action review. But but the thing is, is those things are again, when you bring the experts in and they talk about it, most of the time, you know, what often happens, I mean, I can just talk my own experience is you know, you were at the same place, but somebody says something, and all of a sudden it's like, oh shit. Now I see, I now I understand what happened. I didn't know, you know, either this was happening in a different part where you didn't see it, or this was a cue that you didn't realize was really significant, important. But as soon as somebody else says it, it's like, oh, yeah.

Brian "Ponch" Rivera 1:25:25

Here's where I want to end today, and I think it's a snowmobile. So taking everything we talked about on the technical skill side from CLA, and you bring the non-technical skills in, and you bring

A low-energy approach for the organizations that will thrive

Brian "Ponch" Rivera 1:25:33

in the uh the approach for understanding design in a system, and of course the optical flow field for strategy development, you bring this all together in a low energy approach for our organization. Those are the organizations that are going to thrive in the future, right? But I think I think everything's kind of fractured at the moment. They're like, well, we got this over here, we got this pseudoscience over here. To me, they're all connected. It's just first principle based.

John Flach, PhD 1:25:55

Yeah, and that's the thing, you know. I mean, my whole career is so I don't think many people in NDM understand why Gibson is important, for example. Yeah, and and and again, I mean, and I think a lot of people in NDM are thinking, again, cognitive task analysis is finding what's inside people's heads. But they don't uh they don't understand the subtle difference between cognitive work and cognitive task analysis and cognitive work analysis. And the point of work analysis is to ground those things that are in people's head in the realities of the domain of the situation. So we're not interested in what the operator in the nuclear power plant thinks is important.

Speaker 2 1:26:36

Right.

John Flach, PhD 1:26:36

What we want to know is whether the things that they think important are actually important when you talk to the physicists and that, you know, that you can get validated. So we're trying to trite, you know, onto what are the real state variables. And this is what a controls engineer does. The first thing you need to know is what are the state variables? What are the variables that are diagnostic? And if I know what those variables are, then I can close the loop around those variables and I can feed those variables back. And and, you know, when you're when you're building the gains in your control system, those gains are telling you how important one variable is relative to the other. And so when you have this weighted, the optimal control model is going to weight the variables in a way that gives you the minimum time solution or the minimum path solution and stuff. So you can define that. But but you know, in complex world, you can't do the kind of mathematical specification that you can for a simple tracking task and optimal control. But the the problem is the same. You're trying to understand what the state variables are. And then when you're building interfaces or training, you're you're trying to make sure that that feedback is visible to the people who are making the decisions, the what the variables are, that they're making their decisions based on the diagnostic variables, not you know, not what they think is important, but what's really important. And again, all our intuitions about controlling locomotion built on the terrestrial thing, that those aren't going to help us fly. They're actually going to be misconceptions. Because if you treat flow as a measure of your your speed, then you're going to get in trouble because the flow is changing with altitude. It's not just changing in speed. So it's not flow is not a reliable indication of your speed if you're in an airplane. But it's very reliable if you're in a car because your height doesn't change. So the flow, the faster things are flowing by you, the faster you're moving in the car. But that's not true in an airplane. But if you carry that information into the plane as a pot from a driver to a pilot, one just uh story. We we were doing work on head-up displays versus track up displays a long time ago. And this was in context of helicopter. And and Chris Wickens and I got an opportunity to fly nap of the earth in a helicopter with a with a pilot out in California and stuff. And we were debating based on our experiences driving, you know, what do you prefer, head up or track up and stuff? But you get in a helicopter and you fly in these hills and stuff, and you got a topographical map and stuff. There's no label that tells you that's a hill number thing out there on the hill. The only way you can tell about that is the the relative angle that that should be given my direction. So you you've gotta look at track, you you can only do a track up. You can't do it north up. You can't do those rotations your head. But all you have to do is fly in the backseat of the helicopter with a pilot and looking at them navigating, and you know what the answer is.

Brian "Ponch" Rivera 1:29:28

On that, I'm going to build on that. So when helicopter pilots were transitioned to fighter jets, they struggled. Because uh I mean they're used to being low and slow, and now you're high and fast, or you know, a 30-mile, 40-mile setup to them in a helicopter was a couple of minutes. To us, it's yeah, it vendorized into a completely different yeah. Yeah, yeah. So that it is a big shift, and you see that. Even even pilots that were trained as civilians um didn't do as well as those guys that had zero training coming into the Navy. So again, it's it's just that orientation that that your context matters, right?

John Flach, PhD 1:30:00

Yeah, yeah, exactly.

Brian "Ponch" Rivera 1:30:01

Well, hey John, I think it's a great place to wrap up. I appreciate your time today. Uh I've been looking forward to this conversation. Can you tell our listeners where they can find you uh and what you're working on next?

John Flach, PhD 1:30:12

So I'm very active on LinkedIn, so that's that's probably the the easiest way to connect with me. We have an LLC called Perspicacity, my brother and I, but it's it's not really a business, it's just a means to link up with interesting people and do interesting things. So so I'm I'm retired. I have uh academic pensions. I'm not doing this for a salary anymore. I'm just doing it because it's fun.

Brian "Ponch" Rivera 1:30:35

It is fun.

John Flach, PhD 1:30:36

And yeah, I I just love, you know, it's just it's just I'm curious. It's just great to talk to experts, like, you know, and to figure out what are the what are the little tricks that they know, the heuristics that they use that allow them to do things that are impossible for me or for mere humans, this way I say it. But yeah, so that's you know, I I have a blog called Perspicacity, too. You can link that. And uh I have a lot of books out there, so you can look at Amazon and you know, we wrote a book on control theory a long time ago. All the kind of famous control.

unknown 1:31:06

Yeah.

John Flach, PhD 1:31:08

I don't know. I I some people say that, but I, you know, it always surprises me that anybody even knows has ever read one of our books or seen one of our books.

Brian "Ponch" Rivera 1:31:19

But your name keeps popping up in things in the that I've looked at in the past. I'm like, I had no idea you're involved with this.

John Flach, PhD 1:31:24

I'm always an outsider, you know. I mean, the thing about going cross-disciplines is you're always the outsider. And I always, and I I actually don't know how to behave as an insider. I'm always a rebel. I'm always like I think it's good. You know, when I go into Gary Klein, when I go to NDM, I go to NDM as an ecological psychologist, you know, tell them about why Gibson's important. When I go to the ecological meeting, I go I told them why they should be paying attention to Gary Klein, you know, and they dismiss because, you know, I'm always, I'm always, yeah, I'm always a visitor in these domains.

Brian "Ponch" Rivera 1:31:55

Same. That's how we look at things too. Yeah. Hey, I appreciate it.

John Flach, PhD 1:31:58

That's the interesting stuff. Yeah, that's where all the fun is. Between between Yeah, it is.

Brian "Ponch" Rivera 1:32:02

It is. All right. Hey, John, I appreciate

Boyd, Gibson, and Rasmussen: everyone on the same path

Brian "Ponch" Rivera 1:32:04

it. Uh, we'll end it there. I'll keep you on here for a few moments.

John Flach, PhD 1:32:06

Yeah, and and I I just also want to thank you because, you know, I had dismissed Boyd because the Oodle loop. I didn't know that much about Bouden, but uh, you know, you do in the Miller, everybody talks of the oodaloop, and they talked about it in such a naive way that, and it was really you and Mark that said, you know, you ought to look a little deeper into Boyd. And when I look into Boyd, I see everything, you know. I mean, he he's on the same path Gibson was on, as far as I'm concerned, the same path Jens Gibson was on. That all these guys were connecting. And I mean, I I think it goes back to James and the early functional psychologists who said, you know, what they wanted to understand is how does cognition help us survive in the world? And so it, you know, you have to ground your psychology in the the pragmatics of survival.

Brian "Ponch" Rivera 1:32:54

Yep. Uh it's again, uh huge connection to what what I just wrote this morning on the uh, you know, is it fit or uh, you know, is it about survival or is it about uh reality? Which one do we want to pay attention to?

John Flach, PhD 1:33:05

And it's yeah, and it's it's uh it's always surprising and a pleasure when you find people who've come to the same place that you are in your thinking, but they've come from completely different directions. And that always that gives me more confidence that what we see is actually valid out there, you know. You know, when you when you're with the people who've always followed the same path and stuff, you can't trust their judge the validation you get from them you can't really trust because they're in the same path, they're gonna have the same biases you have. But when you run into people who've come from completely different grounds and they're pointing to the same kind of stuff, that's when you feel like, Oh yeah, this this might be useful and valid. Yeah.

Brian "Ponch" Rivera 1:33:44

All right, we'll wrap it up there. I'll keep you on here for a few min uh moments. Thanks again, John. Appreciate it.

John Flach, PhD 1:33:49

Okay, thanks.