Taking Flight: Exploring the Intersection of Design, Aviation, and Engineering Psychology with John Flach | Ep 56

Are you tuned in to the spellbinding world of design and aviation? Well, let's buckle up for an exhilarating journey as we navigate through the skies of human factors and engineering psychology with our esteemed guest, John Flach. Starting with the origins of engineering psychology, we'll take you through the intriguing story of John Denver, whose tragic end was prompted by design constraints in his experimental aircraft. We also turn the spotlight on human-centered and use-centered design and the integral role of situational awareness.

In the later part of our conversation, we shift gears to discuss control systems, cybernetics, and their massive impact on the scientific community. Our guest John will guide us through James Gibson's path-breaking work on affordances, which revolves around the concept of viewing the world in terms of action systems. Hold your breath as we unravel the intricate relationship between optic flow and control flight, and how environmental factors can potentially influence a pilot's perception of speed, leading to catastrophic consequences.

As we reach the runway, we will reflect on the role of technology in problem-solving, drawing inspiration from the Wright brothers and their innovative approach to aircraft design. Get ready to be fascinated as we explore the world of neuroscience and John Boyd's doodle loop. We close our discussion by pondering on Boyd's work, the power of synergy, and the paramount importance of channeling action towards a shared objective. So, fasten your seatbelts and get set for a riveting and enlightening conversation!

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Recent podcasts where you’ll also find Mark and Ponch:

Eddy Network Podcast Ep 56 – with Ed Brenegar
The School of War Ep 84 – with Aaron MacLean
Spatial Web AI Podcast – with Denise Holt
OODAcast Ep 113 – with Bob Gourley
No Fallen Heroes – with Whiz Buckley
Salience – with Ian Snape, PhD
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Transcript

Mark McGrath: 0:57

So, john, why don't we start the story with discussing human factors and the origin of it and your experience in it, around it, and how others can learn it and apply it in their settings?

John Flach: 1:10

Yeah, so again, i started down this path as a graduate student of Ohio State and my advisor there was Rich Jagazinski, who was a student of Dick Pugh, who in turn, was a student of Paul Fitz, and Paul Fitz is generally credited as being the father of engineering psychology was what he called it at that time. But it's come to be human factors, and the key thing for Paul Fitz was, you know, the famous story is, he was watching his pilots were coming to landing and they were going to lower their landing gear or lower their flaps, and they were reached for the lever to do that and unintentionally retracted their landing gear and came in on their belly. And you know. So the obvious human error. Right, the stupid humans. But what Paul Fitz did is looked at it and the two levers were identical, they were in close proximity, and he said this is not a human error, this is a design error, because any good designer should be able to look at this and see that in a thousand you know 10,000 landing, every once in a while, a person is going to reach for one and grab the other. We know that, we know that's going to happen, and so it's totally predictable.

John Flach: 2:31

And he really, you know, formulated the field of engineering psychology is, it's our responsibility as human factors engineers or cognitive systems engineers to understand that that's a lot likelihood of that and then to design it so that that doesn't happen. But it's not a pilot's fault, it's a designer's fault. And so he shifted the problem from, you know, interaction to design. And you know they did really nice research and now all those, the controls and levers have our shape coded so that they feel different. So if you reach for the wrong lever and grab it, you will feel that it's wrong. It won't meet your expectations. So you know, they reoriented in a sense, and that's you know it's a. They reoriented the problem from a human problem to a design problem And then they realized it was kind of a disoriented station of the pilot that could be prevented by good design.

Mark McGrath: 3:34

Yeah, How did it And what I'm reading about? I mean, people are familiar with John Denver and he was an enthusiast of experimental aircraft and it was the Routans that built the plane and whoever had the aircraft before him had modified the switch in the front where you would switch fuel tanks, and it was intuitive as right in front of you, but they turned. They redesigned. The first owner that he bought it from redesigned it to have it over his left shoulder such that you'd have to switch fuel by turning and inadvertently he stepped on the right pedal and it put him into an uncontrollable dive And that's actually how he crashed, because the design constraints of the aircraft that he was in was such that it wasn't. It wasn't intuitive, but B it forced him to do something else. That ultimately how he met his fate.

John Flach: 4:22

Yeah, I didn't know that story, but yeah, but that's.

Ponch Rivera: 4:28

Yeah, There's tons of stories like that through history, especially in aviation. Ever since we got the black box and the cockpit, we started to understand it's not necessarily the humans or the. It's not a mechanical failure, it's a design failure. And then we looked at human factors. A question to you on human factors. There's a lot of talk about human-centered design. Can you make a connection between human-centered design and human factors, or is there a connection?

John Flach: 4:53

Well, so I wrote a paper in contrast to that, called Use-Centered Design, and so my background is ecological psychology, so human-centered design. So what that means is people go out and talk to people and ask them what's in their head, and the assumption is is that you design it to around the human? Well, i'm an ecological psychologist and apologies bunch to neuroscience, but I say it's me, it's all me right, but the intelligence comes from resonating to information in the environment. So what we need to do is not human-centered, but use-centered. We need to understand what are the constraints of the problems or the domain that people are trying to solve, and then let's make it easy for people to see the things that they should be seeing, the most important things.

John Flach: 5:50

Our job as designers is to make the information that's useful, salient and easy to pick up. And again, we're talking about sports. But if you're playing a sport, when you sit on the sideline and you're watching, try to explain baseball to a European who's never played it and stuff, and they think nothing is going on. But you're saying, oh yeah, the pitcher is talking to the good, can we catch her? He's going to a stretch because there's base runners, so he's not going into his full wind up And you've seen players shifting for a certain coming in for a double play And none of that's visible to European, just as Americans complain about their off-sides car they can't get it. But I mean, all the information is there, it's visible if you know how to look And for me that's been the whole program of our design is we start with the problem, the situation You know that's, you know the situation awareness. So I've been a critic of that because I think everybody's right?

Ponch Rivera: 7:03

Well, let's pull on that thread a little bit. So situation awareness goes back from my understanding, goes back to World War. I Maybe you're an aviation connection as well Like Ansley, did a lot of great work on that. A lot of people quote her work as well In aviation, naval aviation safety mishaps. What we would find is situation awareness always came up as the causal factor behind the accident, right? Because the pilot lost situational awareness and it's an easy thing to blame on them and just walk away from that. So we use situational awareness quite a bit. Going back to your point about baseball, you have to be aware of what's going on to build more awareness so you can anticipate what comes next, right? So I want to make sure I have that history correct and then kind of see where you diverge from. I don't know if you'll, if you disagree with Mike Ansley or where you are on that, but I definitely want to hear more about your view on situation or situational awareness.

John Flach: 8:02

Yeah, so. So first of all make very clear situational awareness is a great description of what's happening, but it's a lousy explanation of what's happening. So to say, the pilot lost. Situational awareness is absolutely is not an explanation at all. It's just a description of what happened, but it's not an explanation. And to me the problem is in the way and and you know the reason Michael Mike is is popular is she framed it in the dominant paradigm, so she framed it in terms of boxes in the information processing diagram, and so situational awareness was framed as in terms of awareness. And she added, you know she, she expanded on kind of the orientation aspects of the information processing model and it fit the dominant model.

John Flach: 8:59

I come from a different tradition, ecological psychology, and what my critique and the reason why I say youth centered instead of human centered, is more important to knowing what's in people's heads, is knowing what's the situation. We need a theory of situations, that is, we need to know well, what did that person miss? What information did they miss that could have been useful if they had picked it up? So situational awareness means there was information out there that they missed. So so saying they missed the information is not very useful to designers. The question is, what I want to know is what did what did you know? what was it that they missed? Is there information that if they had it, that accident wouldn't have happened?

John Flach: 9:46

And as a designer, can I do something at the interface to make sure? So so I mean, let's go back to Paul Fitz. Paul Fitz is saying Hey, is there information those pilots could have had, would have presented them retracting landing gear? Yeah, i shape coded the knobs. Then when they reached over there, they're going to be, but but it's, it's understanding that constraint. So what you know, Paul Fitz said you know, it's kind of it's not in the human's heads, it's, it's in the design of the interface. And here's what, here's information that was lacking in that information. They made it, these things, indistinguishable. And if I could make them distinguishable, then the pilots are not going to make us make retract the landing gear.

Ponch Rivera: 10:29

Quick question here, john. So connection to the extended mind theory of how we work. You know like the cockpit is an extension of the mind, it's you know what's within its boundary here. It doesn't mean everything's made up. All decisions are made up here. They're, they're made with our interaction with our, our tools.

John Flach: 10:45

Yeah, so, so again, and this gives again a criticism of classical models of the Oodaloop and and and even some of the more expanded models. You're missing one thing The loop is closed through the world, the feedback. If there's no world to interact with, there's no feedback. The feedback is not in the mind. You have to act in the world and probe the world. Then the information is what effects does it have? Again, in competitive environments and stuff. You have to probe your opponent on the tennis court and find out where their weakness is. In stuff You can activate. In stuff. What you're learning about is the opponent. You're finding their weaknesses in stuff. What is it that a top-level tennis player is able to see that allows them to anticipate where that serve is going to come and hit it For me by the time. I know it's gone. It's a really good server. It's gone by the time I know what to do.

Ponch Rivera: 11:59

You're hitting on the action perception loop. There We sense the world using our observations and we emit some type of action to change that external world. That's foundationally what I believe the loop is useful, explaining what's going on internally to that boundary and what's going on externally You have which gets back to nested ootloops too.

John Flach: 12:20

What happens, though? Punch is in our diagrams. We don't include the world in the diagram. Oh, i do, i do. It's often not explicit. Anybody who understands controls understands this, but the problem is that, well, from the cybernetic, from Wiener's model on, psychologists drew the boxes, they gave them permission to talk about intention, but in all the research and stuff they cut the loop. It was the first thing they did in the laboratory, because they wanted control of stimuli. They didn't want the human to control the stimuli.

Ponch Rivera: 12:57

Got it.

John Flach: 12:58

Then they built explanations about linear causality rather than in terms of dynamic. Concepts like stability don't come up, because stability is a property of a closed loop, not a property of an open loop.

Ponch Rivera: 13:13

A way I understand stability with an open loop is dynamic equilibrium versus. Yeah. I think that's what the neuroscientists are calling it.

John Flach: 13:21

No, there is no stability, the dominoes, just one thing hits the other. But a system you can't get oscillations out, you can't get the pilot-induced oscillations from an open loop system, only closed loop system. Give you those kinds of things.

Ponch Rivera: 13:35

That means you have to include the external world inside of your when you draw the ootloop. Am I getting that right?

John Flach: 13:42

Where the loops close through. There's got to be For humans. it's a world as a medium that licks the hands and the eyes.

Ponch Rivera: 13:50

Yeah, John Boyd looked a lot upon cybernetics and control theory. Can you give us a rundown of? in the way I understand it is, you have an internal model of the external world. This gets into a requisite variety as well. Can you walk us through what that looks like from your perspective and how you can potentially explain orientation inside the ootloop?

John Flach: 14:14

Well, i'm not sure if I get exactly the point, but historically Norbert Wiener had his cybernetic hypothesis and there was a whole series of conferences the Macy conferences I don't know if you know that history and stuff Once he started talking about and, by the way, it was instability, it was motor tremors and motor disabilities that mimicked instability in his automatic control systems. That led him to hypothesize that biological systems were also closed loop systems as well. But as soon as he presented that, the neuroscientists, anthropologists, all the people at the Macy conference would say, yeah, we see loops everywhere. And here's what happened. So everybody drew the loop, everybody accepted the cybernetic hypothesis. But then you had early papers.

John Flach: 15:18

The first kind of presentation to psychology was plans and the structure of behavior. They used the cybernetic model to say, oh, intentions, these things that the behaviorists said were mental and not mentalism and things. Here's a physical instantiation of intention. So it gave psychology the license to talk about. and then with the computer metaphor for internal processes and mental processes, now talking about mental processes could be scientific, but they framed their science around the boxes. So let's isolate the O out of this line and cut it out from the loop, and we're going to determine what goes into the O and let's see what comes out the other side. And so they framed their psychology in a way that, first of all, they can't go unstable, so they cut the loop And they lose the holistic aspect of control.

John Flach: 16:23

They framed all the research so one person studied perception, another whole group of people studied perception but know nothing about action. Another whole tribe of people go and study motor control And, interestingly, the people who studied motor control could not avoid perception. So I can actually come from a motor control background. So as soon as you talk about motor control, you can't miss perception. But people who studied perception could totally ignore motor control. They put people on bite bars and they fix the eyes and they give trivial button press responses and things. So they could totally trivialize the motor system and study perception and isolate it.

John Flach: 17:06

And there was one person, though, who understood the importance of coupling from the perception side, and that was James Gibson. I don't know if you've ever guys run into Gibson or ecological psychology, but he's the word that you probably have run into as affordance. So he coined the idea of affordance, and basically what he said is, when we look at the world, we're not looking at objects. And, like the physicists looked at it, we're looking at things relative to action system. So the difference to us is not how big it is It's graspable. How big is it relative to my hand? How big is it relative to my hand? Is it reachable, is it graspable?

John Flach: 17:46

And he made the audacious claim that is not only that that's not derived in the mind, but that's actually what you see. You see the world in terms of it. You can then go from you know graspable, and then think about size and do the computations and stuff. But the way the physicists look at the world in terms of size and mass and things, that's derivative, that's not primary. The way the world is, the real world is the way we see it Most directly, most basically is is it graspable, is it reachable? Is it? you know, is it bigger than I am? Is it or is it smaller than I am? You know, do I need to run away from it?

John Flach: 18:31

You know, and that's the first thing, that's not based on processing. That's the raw data of perception And then we can process on top of that. But that's the thing And you know. That's, i think, what skill behavior is is in domains. You know. You begin to see directly those things that aren't salient to people who don't have a lot of experience, but gradually, as you get more and more experienced in domain, the differentiators, the things that determine the winner from the loser. You know the guy who plays tennis every day, you know for 10 years, he sees the things that matter in terms of success And those are the things, the first things he sees, not the rives. He doesn't learn to process to get those things. He they're there And he picks them up. What Gibson would say directly So we used to do And so they're not the products of mine.

John Flach: 19:25

They're the raw materials of perception.

Ponch Rivera: 19:28

So we still do a lot of teaching with relative sizing And we use a lot of the cognitive science behind it, and I think that's a little bit of what he explained. So back in aviation and we were doing close air support, we would look at a unit of measure Hey, the distance between this building and that stadium over there. Using that as the unit of measure, go four units of measure to the north of this spot. Right, and it doesn't matter where you are, if you're 20 miles away or five miles away. You use that relative distance to figure out where the target is, and it's a great way to get your eyes onto that target.

Ponch Rivera: 20:18

Now in agile, what we've been doing is using Devonacci's numbering system to point right. It's just relative sizing. Here's some previous work. Does this look like that? Is it relative to that? And we use numbering there? That's kind of going by the wayside because most people do it improperly, so we don't really coach it that much. But is that the connection? Is that the connection? is what's going on in the brain? We can see different piles of sand and say that one's three times the size of that.

John Flach: 20:43

Well, yeah, so they're all relative judgments, but the basis for most of our judgments is our body, so this is part of embodied cognition.

Ponch Rivera: 20:54

Yeah.

John Flach: 20:56

So what we've learned, the first primitive, is what you see. So, baby, learn very quickly. It doesn't reach for something with one hand that it can't grasp with one hand. If it's bigger, it can see the difference between what's within their grasp versus which. And, by the way, the thing is is the graspable is all relative to your size as you grow, and so it's not objective, but it's real because it's a relationship. So as you grow, what's graspable? And actually, as you age, as you get arthritis and stuff, your graspability changes and things. But it's the most real.

John Flach: 21:42

It's not visible to physics because they're talking about the size independent of observer. But what Gibson says is no, the sizes that matter are the ones dependent on the observer. And so when you approach the world as physicists, as an objective thing, you're taking the human out of the equation. And to assume that the world described by physics is reality, gibson says there's an error. It's not reality. My hand is as good a metric as the wavelength of light, and that they keep in Greenwich and stuff The meter. There's nothing sacred about a meter Right, but the meter is introduced. So the fact that, so you and I and everybody who have different size hands can all agree on what the size is, but the meter is derivative, but size relative to your hand is immediate and real.

Mark McGrath: 22:42

So, in other words, you have to continuously reorient and challenge and revise your assumptions, right Yeah?

John Flach: 22:49

and you do that. You automatically do that, for example, as you in the world, by interacting with the world. That's how you learn how things are relative to your hand and what's graspable and what's reachable, what's liftable. You know, and you're really good at that judgment Punch. Have you ever read Langovice's Stick and Rutter?

Ponch Rivera: 23:11

Yeah, a long time ago, 30 years ago, 20 years ago.

John Flach: 23:15

So Langovice describes the approach to landing And he describes how a pilot uses the aim point, the expansion point on the runway relative to the horizon to judge whether they're on the right glide slope. Well, langovice was an inspiration for Gibson, and so Gibson came up with the idea of optic flow, that there are invariant, like the horizon ratio that specify the safe path of travel, and that these things are totally specified. So another thing you'll appreciate is you know, what he showed is a perception of speed is based on the optic flow rate, and optic flow rate is determined based on how fast you're going, but also how far you are from the surfaces. So when you're flying at high altitudes, it feels extremely slow.

Ponch Rivera: 24:09

Right, and you have more time to look inside the cockpit. Right, you can look in your cockpit more often When you're down closer to the ground. you can't look inside often. you have to be outside Right, and that's you're right.

John Flach: 24:20

We had a hypothesis that some of the control flight and the terrain situations are because when pilots are flying close to terrain, they're very much aware of their speed, because now things are flowing by really fast, but it may feel much faster than it actually is, and what happens is people. What happens is, you know, when you look at these control flight and the terrain, sometimes people are nosing in and sometimes people are obviously stalling. Our hypothesis is that people get outside the energy envelope, that is, they're low and they get too slow. Well, how do they get too slow? Why they should be aware of that. Well, if they're looking at their instruments, they would know.

John Flach: 25:06

But the world is flowing by so fast that they get comfortable and they're not checking their instrument. And so when they realize they're too slow, if they were high they would nose down and get up to power, but if they're low and the rogants come, they pull back. So half of them look like they stall. But it's the same reason they get outside their energy envelope And it's because the energy depends on your height and the combination of height and speed.

Ponch Rivera: 25:35

Yeah, john, there's an interesting connection here. When I was flying air shows in the F-14, you know you're high performing, you're at the edge of the envelope all the time, down low 200 feet. You go through that for about a year and a half two years I was an instructor the last instructor in the F-14, to coach the next demonstration team. Then you start going back to normal flying And what I noticed is that I became more dangerous, right, because I was so used to being close to the edge all the time that when you get, you know, when you start doing basic fighter maneuvers and things like that, i became more aggressive.

Ponch Rivera: 26:09

And that scared me, right, because generally, when you get enough time in the cockpit like five, 600, 700 hours that's when you're really dangerous. Right, when you get about 200, 300 hours in the cockpit, you're pretty safe. So I think I was around the 1,400, 1,500 hour standpoint there when I was flying air shows. But all the optic flow stuff you're talking about you brought back all the images and books and we're talking about what it looks like to be on the deck when you're instructing new students, what it's like to fly low levels and pop up 40, 50 degrees, 60 degrees, nose high, roll inverted and roll back towards the ground, which is absolutely terrifying for folks when you do it inverted, especially in an air show. So thanks for that.

John Flach: 26:52

So interesting. So when I started we were doing the tracking stuff, but also at the same time at Ohio State there were the aviation psychology laboratory was coming up, and so this was the late 70s, early 80s, and we didn't have interactive graphic computers at that time, so they actually had to build their own graphic computer so we could do flight simulation. But that's was so. My early research was actually tying properties of the optical flow field that Gibson described to interactive control. So I was working on the one hand with Dino and Rick Warren, who were Gibsonians, and they had the geometry of optic flow And they specified what are the optical cues that people use. And so what we were doing is the first simulators. We were using the invariance of optical flow fields as the independent variables and then using control modeling to look at people's skill and try to identify what are the cues that Gibson hypothesized were actually driving performance.

Ponch Rivera: 28:02

Right. So I try to teach my girls a little bit about driving and CBDR constant bearing, decreasing range And when things are going to hit you and they're not going to hit you. Of course they're 12 and 13. This goes over their head, but CBDR is kind of fun to explain to folks. Can you walk us through what that looks like or what that means from an optic flow standpoint?

John Flach: 28:20

CBDR.

Ponch Rivera: 28:22

Constant bearing decreasing range, when you know you're going to hit something, right Yeah?

John Flach: 28:26

So in psychology we call it tau time to contact.

Ponch Rivera: 28:31

All right.

John Flach: 28:34

And there's a classic joke I couldn't figure out why that car was getting bigger and then it hit me. But so David Lee was at first to really specify this. But it turns out that if you look at an object as it approaches you, it expands. Well, it turns out that if you take the ratio of the expansion rate to the size, that specifies invariantly time to contact, ok, and it's acceleration pattern, so what it's far, it's kind of growing small, but before contact, all of a sudden you get this explosion in size. And if you've ever been sliding into a car on the ice, there's that point where that just, and you know it's going to happen, it doesn't matter what.

Ponch Rivera: 29:29

I do.

John Flach: 29:29

Collision's gone there at that time. But you can really think, but we actually, that's what our early research does. We have a lot of papers on time to contact, but we link the mathematics of the flow field to control strategies and show how And you can actually design an automatic on your car, an optical sensor, and if it senses the size and the rate, you can use that as a feedback and design an automatic braking system that will work perfectly. The normal engineering solution is you have position and velocity, but it turns out that if you use size and angular rate, they're one to one. They're not exactly one to one, but they cover exactly the same functional space. And so people are not good at judging size or speed, but they're really good at judging angular size and angular rate. And that's exactly what you're saying, pancho. You're looking at the word. It's all angles And that's what Gibson's angular terms.

Ponch Rivera: 30:39

That's like catching a football, right Catching a football is the same thing. It's all angular right. It's great. So you're just trying to put it in one spot of your body. That's all you're trying to do is put it one place, and as soon as it stays in that one place, you're going to catch it.

John Flach: 30:51

So there's some really nice work about catching baseballs. So the outfielder has to run to the first place, and it turns out that if you move so that the height and the ball in your optical field goes up at a constant rate, you will be right where your hand will be, right where the ball is. It's ironic because you think of the ball going in an arch, but optically it just goes up because as it's coming down it's getting closer to you, and so you're going to catch it. If you move to a place where it's rising at a constant rate, you'll be at the right place to catch it.

Mark McGrath: 31:31

Back to the We're talking on aviation. Why don't we start at the very advent of aviation? You're in Dayton, which, contrary to popular belief of many, it didn't start at Kitty Hawk. It was literally all done in Dayton and the one flight in Kitty Hawk took all the credit. You had a piece that you put up on March 17th of this year called Polycentric Control, getting Off the Ground, and it really seemed to resonate with what Pontch and I talk about all the time with our clients is people, ideas and things. All is in that enviable order that there has to be a unity of those things and people always have to come first because they're centered around them per se. But you give the story of Langley and the Wright brothers. Would you mind sharing that and relating it to what we're talking about? how people think that technology is going to solve all their problems and it won't.

John Flach: 32:23

Yeah, well, actually this is a great Oodleoo story because when the Wright brothers became interested in flight and first of all they were attracted to it because it was supposed to be impossible but they wrote to the Smithsonian and Langley was the curator of the Smithsonian and stuff and they want to know what work has been done on how you're going to control an aircraft in the sky. And the Smithsonian wrote back and nothing has been done. And before the Wright brothers, everybody assumed that you would control an airplane the same way you would control a boat with a rudder. That is, no one could imagine why you would want to. why would you want to be unstable in the roll axis? Why would you ever want to lean?

John Flach: 33:17

The Wright brothers started by thinking about the control problem and the story goes that they were watching the buzzards at Hinckley, ohio and they're watching how they soared and they were watching them bend their wings and that gave them the idea that well coordinated turn. and some people contributed to the fact that there were bicycle designers. So bicycles, you need to lean and balance is a problem. So they understood a little bit about balance and so they developed wing warping as a way to control the roll axis. Again, everybody else was designing in Europe and they designed the plane to be stable in roll. So they didn't want to let the pilot why would you want to build a vehicle that you're in? No one could imagine why that would be. So anyway, that's what they and so they went and they came up with this hypothesis that we got a roll and stuff. They practiced it with kites and then gliders, and it wasn't until they felt confident in controlling their kites and gliders that they would put an engine on the plane. So, in contrast, langley was building model planes and he was showing, he was working on the lift and stuff. By the way, the Wright brothers also discovered that the lift coefficient, the standard lift coefficient, was wrong based on their wing tunnel. So they were very precise in their analysis.

John Flach: 34:52

But Langley showed and demonstrated with Zerodromes that he could build wings big enough to give sufficient lift to get the person in the air. But and so and then he scaled up his Zerodromes and he launched it over the Potomac the first time and put a human in the cockpit. But that's the first time. that person had no experience with kites, no gliders. They didn't do any practice in control. They sat the person on top of this plane and wings, and I'm not sure what kind of control system they had, they might have had a rudder, i don't know But launched him and he went straight into the Potomac. And then two weeks later they tried it again and this more or less the same thing happened. And at that, when that happened, you know, papers said, you know well, man will eventually fly, but not for another 100 years, because Langley just proved it's too difficult. And then a couple days later, a week later, the Wright brothers flew at Kittyhawk.

Mark McGrath: 35:49

You say that the Wrights the problem was the design was. They're probably to design a joint cognitive system that included the pilot as a critical component of that system.

John Flach: 35:58

They want to know how the pilot. so in sense, you know they were, they took a user-designer design approach. They were, they were always, and they also understood that this was a skill that they had to learn, teach themselves, just like they had to learn to ride a bike. But so they taught themselves how to use the control system, again with gliders and kites. they experimented, you know, they were steering kites in the sky using the same principles And until they've worked out the principles of control, you know the closed loop dynamics, they didn't want to put an engine on.

Mark McGrath: 36:32

So we coach and we tell people you know it's people, ideas and things. That's an enviable principle And it's easy to spot in competitors that don't focus on people, ideas and things. They focus on things usually, or technology. And you have this quote saying they're framing the problem around technologies and forgetting that ultimate success depends on the quality of the joint cognitive system. And that seems to really reinforce what Ponce and I talk about frequently with guests and with clients that you can't break that order. It has to be a joint system, as you say, a joint cognitive system.

John Flach: 37:09

That idea that the term joint cognitive system actually comes from Dave Woods.

Mark McGrath: 37:14

Okay, yeah, it's. I mean, what do you think is the? as a psychologist, i guess you know what's the. Why do people always have that penchant to think that technology is going to solve all their problems? Like, why do they dismiss the nature of humans within the system? as the recent examples say, ai And we've heard the term that you know everybody's afraid AI is going to replace people. I've heard other people's counter that and say other people rather counter that and say AI is not going to replace people. People who understand AI and how to use it will replace people.

John Flach: 37:54

Well, you know, i'm not sure it's a, i'm that kind of psychologist that knows what's in, but but you know it's. We tend to fixate on what's in front of us And you know, even the people who are, who are building these technologies and stuff. They get intuitions and they see things and they have these new powerful things that are obvious to them, how they use it. But what they don't realize is that the things that they see and that are intuitive to them and and and their understanding of you know. So people who are building AI understand the limitations and the risks and the things and stuff, but they, of course, they have to sell it to get funding. So they're going to emphasize the value propositions and not the risks. But but a lot of the times I think they assume that what they see in this technology that they've spent 20 years developing, everybody else can see because it's so obvious to them And so, and so they don't take into account the fact that that somebody's going to be using this in their kitchen who's never took a course in computer science and doesn't know how it was built and doesn't know that they know what you know, they all they know is how it responds to their you know in, you know when they engage in their first doodle loop. But they don't have that long history of engagement with that technology that the developers have And so So you know, they just assume you know.

John Flach: 39:20

Again, i think part of it is is the people who embrace the technology and built the technology see things. Things are obvious to them and they expect it. Well, they can't unsee them right And so they just think everybody can see them And so they don't bother to work on the interface and try to bring out those things that they think are important for somebody to use. That took them 10 years to see. They don't realize that other people are only going to have 10 minutes before they're using this and they're not going to have that 10 years of experience.

John Flach: 39:59

But I think you can capture, you can do things in the interface that make both the opportunities and the risk more evident to someone who hasn't spent those 10 years. If that's where the design comes in, that's where that's the designers rub. So you know the people who built the plane that where they were attracting the landing here and the landing I mean, they knew what the functions were, those controls, and it was obvious to them and why. You know who would be stupid enough to pull this lever when they were trying to pull this lever. Can't they see how we're wired up? Don't they know what's connected to what in this thing?

Ponch Rivera: 40:35

Yeah, It's like the fob in the car right now, right where you accidentally leave the car running.

John Flach: 40:41

Yeah, I've done that.

Ponch Rivera: 40:43

Yeah, I've done that.

John Flach: 40:44

My car has a key and my wife's have the fob, but whenever we're together we drive her car because she always has a new car right. But so I always go in and start oh, i don't have the key in, and then forget to turn it off because I'm switching back and forth between the two.

Ponch Rivera: 41:01

So can we go back to that closed loop And the reason? it's kind of stuck in my head and I want to make sure I have this correctly and what I think I heard. So when we look at Boyd's little loop or any type of system, we want to make sure we include the external, what's inside and what's outside, a generative model, if you will. That's what you're calling closed loop, correct, correct?

John Flach: 41:21

Yeah, so the thing is is I don't see the world as outside, i see it as inside. It's part of the system.

Ponch Rivera: 41:28

That's what you're saying It is the loop?

John Flach: 41:29

Yeah, the loop is closed. There is no loop without the outside world.

Ponch Rivera: 41:35

Okay, okay, okay. So that's clear to me now. It's part of the system we're talking about.

John Flach: 41:40

So if we and that's all you're saying is, that's that closed loop And that's why we again and it's so Mike Ansley, when I see her work and stuff, she's very careful about learning about her domain and stuff. So it's not actually the work that she does, but the way she articulates situational awareness, what, in my view, over emphasized awareness and didn't. And then the way a lot of psychologists and studied it. Well, they love that. So they're all studying awareness and it's all about what's in the person, people's heads, and I'm more saying hey, but if we want to put, if we really want to create good situational awareness, we have to understand situations and we have to know what is the information that that experts depend on to do well, and let's make sure that that information is well represented in our interfaces.

Ponch Rivera: 42:42

Okay, and to be clear, we're not talking about the difference between open systems and closed systems. Can you make sure I'm clear on this too?

John Flach: 42:49

No, And that's people can. So these are. These are open systems, but they're closed loops And, in fact, closed loops are the best way to survive and be stable in open systems.

Ponch Rivera: 43:02

Okay, so let's go back to Boyd's Oodleoo. You look at the. The diagram that you have in your most recent article is the traditional view of John Boyd's Oodleoo And, if I hear you correctly, the way it's drawn there it's missing the external environment. Am I saying that correctly? Or it's missing the? it doesn't have that closed loop part to it, it just says here's John Boyd's Oodleoo.

John Flach: 43:24

So all the feedback loops go through the world. So you know, in the diagrams we connect the output of the action with perception and it's just a line. And of course you know that that line is the consequences of the actions in the world that are then picked up by perception. but but people don't make that explicit There we go, that's it.

John Flach: 43:50

So you put a box there it said situation there, then now you have the full system. But if you don't have that box situation, if you don't have that situation represented, then you're only diagramming part of this whole.

Mark McGrath: 44:05

Perfect, you need to have the boundary. is what you're saying, right? You're saying you have to have the boundary between the internal and external.

John Flach: 44:13

No, no, no, there's no boundary.

Ponch Rivera: 44:15

There's no boundary, it's one system, right, and so so I get this view. Now it's just add whatever the external world is called that a closed loop, and that's good And I like that Yeah.

John Flach: 44:28

That's a generative model.

John Flach: 44:30

Yeah, so so in, if you, where you have the feedback loops, if you put a box there and say this is your problem domain or this is your problem space, this is your situation space, so so you know. So, mark, if this is economics, you put the economy The economy is that is in that feedback loop right, because you do actions, it impacts the economy, you see the effects on the economy, local, at both different levels, and then that's what feeds back. But you know, if you, if you make a buying decision, there are no consequences. If that, you know if it, if it doesn't, if you don't make a bet and it doesn't impact the world anyway, then there are no consequences to that action. And so there's no way, there's no way to differentiate a right action from a long wrong action unless you can see the consequences it has in the domain, and it's the consequences that are fed back, not the action that's fed back, it's the consequences of the action that's fed back.

Ponch Rivera: 45:30

Right, yeah, so there's a connection to neuroscience.

Ponch Rivera: 45:35

I brought up the generative model, which I believe you're describing, with the closed loop approach And then, when Mark brought up with the with a boundary within the, so we put a Markov blanket around, statistically separate the internal to the external right, so you're still within a closed system, and then you can layer that on.

Ponch Rivera: 45:53

So that's what neuroscience is telling us too about, or what we're gaining from neuroscience, and applying it to John Boyd's doodle loop, Because we you know John Boyd didn't have a lot of this language that we have now, with constructive law or free energy principle or active inference or constructive theory, things like that are that are emerging. But because the science all comes from the same place, like cybernetics, quantum physics, what we knew about neuroscience and complex adaptive systems 30 years ago, i believe we can make a connection to John Boyd's doodle loop And I think what you just shared with us, john, is absolutely critical in the way that doodle loop needs to be explained, because if it's not explicit, in my view the little loop just looks like some loop that's stuck inside your head, right, and it's just magically doing things. When you make it explicit now, you can have a conversation about what's going on the outside that closed loop and what's going on the inside, and you can make that separation get back to your mortar control theory and perception too. So there's a solid connection.

John Flach: 46:54

Yeah, yeah, and you know, with regard to neuroscience, you know the thing is, is, and, and you know, with the emphasis on awareness and situational awareness, the implication is is all the interesting constraints are in the head. You know neuroscience, it's in the structure of the brain and stuff. But I think one thing we learned from neuroscience is the brain is incredibly plastic And so you know, even if you have significant damage in the brain, you know, to an infant, other aspects of the brain will take over that functionality. Well, right, how does that function? I developed, Well, i think, that brain forms in that closed loop interaction with the world. So the the most of the constraints in our head are not from our biology, but from our interaction with the world.

John Flach: 47:45

That is, you know what learning is, that we're learning to see, and, and you know, and I think I think this has both you know learning in your lifetime, but I think you know there are. There are species learned. You know changes, but those changes are, you know it's, you know what, what gets in and the other people you know. Looked at evolution, you know, i mean, it's the same thing in evolution, that that you're, the functionality is not, it doesn't happen independent of the coupling with the environment That is the select. Natural selection depends on and and you know the brain is is natural selection at a, at a. You know it's like a fractal of what's happening at the species level is happening at the individual level. That your brain is selecting is picking patterns in the world and attuning to things in the world that lead to good consequences for you.

John Flach: 48:47

That's, I think That's you know it's picking up, what are the threatening things and what are the opportunities. But your brain, from the time it's being structured in the womb is is being informed by the flow through it and what it's hearing, what it's, what is picking up and the consequences that that feed back on what, what's going in, what it's doing As we, as we continue to interact with our environment. Yes, yeah.

John Flach: 49:14

Yeah, So the so the control, the structure comes from the dynamic, yeah, and we produce that, you know that. The coupling, that you know. So you know again, as an athlete, you know you, as you begin to tune in things, then the opportunities come out of that and they're real. That's, but it's, but it's, it's changing.

Mark McGrath: 49:38

The control is from the outside. It goes outside and bottom up. Right, it's. It's. It's the environment that we're, that we're interacting with, where we're pulling those those things out that we're maybe, maybe, not expecting. But the control comes from the, from the outside and bottom up.

John Flach: 49:57

Yeah, i'm not exactly sure how, but I would say they emerge from the dynamic. So skill.

Mark McGrath: 50:03

That's what I'm saying.

John Flach: 50:06

Like the emerging the emerging properties of it. Yeah, yeah, they come out, they're, they don't pre-exist and and you can't find them in the head and you can't find them in the world. So you know. So when we talked about this optic flow, and you know, for collision and stuff, so if you study light, you don't, you'll never find optic flow, and if you study eyes, you'll never find optic flow. Optic flow is what happens when an eye moves through the world. The expansion happens when you move toward an object, or an object moved you, but that pattern, those invariants are, come out of the interaction and they don't exist if there's not an eye. If there's only an eye, then there's, then there's no light, there's no optic flow. If there's light and there's no eyes, there's no optic flow. Optic flow requires both an observed you know it's, it comes out of the observer, it's, it's a it come, it emerges from that loop. Dynamic Yeah, It doesn't pre-exist, the dynamic.

Ponch Rivera: 51:05

Yeah, is there a connection to Ashby's law in here of requisite variety And I think I have a couple definitions of it. But if I understand it correctly, we must have a number of repertoires inside that equal to the number of different challenges presented as to us on the outside, so that closed loop again, is that? is that what requisite variety is about.

John Flach: 51:26

Yeah. So there's two, two aspects of that that's important to me, And one is, you know, the, the control. So the requisite variety is set up by the problem. So that's the situation, And you can think about it in a competition. If I'm a tennis player and I have more shots in my arsenal than my opponent, then I have more requisite variety. That means I'm going to be able to find a shot that's going to be that my opponent can't counter. So if I have more variety in terms of how I can hit the ball and stuff, if I'm good at the net and from the baseline, but my opponent's only good from the baseline, then I'm going to take advantage of that because I have more variety in my game than his. So in any competition, the competitor with the greatest variety is generally going to win. Okay, so that's Okay. Let me try something with you. Now. Let me say one other thing.

Ponch Rivera: 52:25

With that variety. Yeah, go ahead.

John Flach: 52:28

In the world the variety is infinite, So we never have the requisite variety. But success is always relative. So more variety on your capability. the more options you have, the more different directions you go, and this is part and why multidisciplinary is important stuff. The more ways you have to frame a problem, the more likely you are going to find a framing that makes it intuitive or easy to do. So high variety is desirable, but I don't think we ever live long enough to have the requisite variety, because the world is infinitely complex.

Mark McGrath: 53:10

Yeah, in other words, you have to keep exchanging old models for new ones. You have to keep revising the models. Variety, rapidity, harmony and initiative those are some of the things that Boyd classified as requirements if you wanted to continue to improve that capacity for free, independent action. But variety as you think you have it now, it can't stay stagnant, you have to continue to develop and revise and refine.

John Flach: 53:38

In that advising and refining process, it's always going to be more. The better models are always going to be the models that are more flexible or give you more options.

John Flach: 53:50

So it's not just one-to-one replacement, but it's more like adding different ways, and so sometimes a reframing opens you up to things that the old framing didn't. But in general, the more possibilities you can realize, the more likely, i think, the more stable you're going to be with the world, because if one thing doesn't work, you've got a backup plan, you've got another plan When they start getting really good at returning your forehand, then you begin to develop another shot that they're not going to be ready to, and the more shots you have in your arsenal, the more competitive you're going to be in the environment.

Mark McGrath: 54:36

You can't just be a one-trick pony. in other words, In economics.

John Flach: 54:40

you want a diversified portfolio, right Yeah, You don't want to bet on any single horse, And the more horses you can bet on, the more stable. it doesn't mean you're going to be a winner, but you're going to avoid catastrophic.

Mark McGrath: 54:53

Catastrophic loss. That's the key.

Ponch Rivera: 54:55

You're going to survive.

John Flach: 54:56

And that's at the end of the game. And it's not about winning, it's about surviving.

Mark McGrath: 55:02

Well, ponce and I have a lot of interest in discussion about markets. I'm really into trend-falling trading and understanding their perspective. And that's exactly what they say. Because that optionality, or that ability to be completely agile in situations that you don't have any control over and you can't predict I mean, we're talking at the beginning about how certain styles of investors feel that they can look at the balance sheet of an annual report and fail to realize that those figures are from a fixed moment in time that's long since passed and has nothing, no bearing on what's to come with the unpredictable things in the uncertain world that we live in. So, having that variety, that's an edge, and if you don't have it, you're in trouble.

John Flach: 55:59

So to me, Ashby's law of requisitive variety is an aspirational goal that we all should have.

Mark McGrath: 56:05

Yeah.

John Flach: 56:07

Which just means the more flexible you are, the more stable you are, the more diversified you are, the better able you are to deal with surprise and unexpected events.

Mark McGrath: 56:19

So when you look at that folder that I sent you with some of the handwritten notes of John Boyd that Ponce and I found when we were in the archives that you'll see VHRI, variety, harmony, rapidity initiative. You'll see a lot of different abbreviations, but that's going to be a big one, so very cool. Hey, John, this has been an awesome time with you.

Ponch Rivera: 56:47

Yeah.

Mark McGrath: 56:49

I'd love to close it with just sort of how we started this conversation. You've been listening to Ponce and I discuss with other guests from a wide variety of backgrounds. In discussing with you, it seems that you went through an evolution of your understanding of Boyd and how he's often framed misframed as Ponce and I would probably suggest and really get us to the point, like we've done today, where we can develop and really discuss his ideas. Maybe walk us through a little bit of that as we close. What was your first knowledge of Boyd and how did you get interested and what you like to do with it going forward.

John Flach: 57:30

So, as I think I told you, baby, before we started recording is, my first day in graduate school was I was sat in front of an analog computer and my advisor, who had been an electrical engineer, said well, you put two integrators back to back in a circuit, you get a sine wave. And I didn't know that. Of course I went home and told my wife I'm in big trouble, but as a result of the situation I was in and the advisor was working for, i spent a lot of time trying to learn the language of control theory And actually we wrote a book on control theory by Visor and I and there's links to it in my blog And I guess I went through much of my career thinking, well, everybody has to learn this, the way I did For me, trying to figure out the mathematics and trying to understand stability and stuff. It took me a real long time to realize that the differential equations were not. You couldn't follow them sequentially. The differential equation was a constraint that applied to the at the system level, that described this and that allowed you to to to understand stability systems.

John Flach: 58:42

But so I've sent most of my career kind of preaching to other social scientists that you know. You got to do more than draw loops in your diagrams. You got to think about the nature of dynamics And what I saw is just lots of causal kind. You know, as soon as you understand the loops, the loopiness of the world, you got to throw away the idea of causation, this idea that you know that this idea of a root cause, it doesn't work in dynamical systems. There is no. You can't find the kind of. You just can't find that It's not a matter of a sequence of dominoes, you just have to get to the first domino. It's not that simple. And again, when I was first exposed to you know I'm preaching control theory and then people say, oh yeah, you should see John Boyd. But the people who are pointing to John Boyd, they showed me the four circles and the circles and they said oh yeah he said some stuff And I say they were kind of doing all the wrong things, i thought, with regard to control systems.

John Flach: 59:47

So I wasn't, i didn't see any reason to dig into Boyd. I just thought, well, you know, this is stuff, i know and I get background and stuff, but it's really actually, you know, seeing you guys on LinkedIn and seeing you guys kind of critique the trivialization of Boyd, it said, hey, this is interesting, i might listen to these guys, and that's how I started paying attention to you guys on LinkedIn and learning a little bit. And then, you know, when Mark reached out to me and I started looking at your going through all your podcasts, i'm like wow, every time I say oh, yeah, yeah. And you know, i keep hearing you guys referring to people that are kind of, you know, like in economics, to Hayek and things of people I thought were really cool and got what dynamics were, but nobody else was making that same link. You know, nobody else was seeing those connections. So it felt like we were seeing common threads in weird places.

Mark McGrath: 1:00:51

We say it all the time you know how we all come to the same conclusion from different backgrounds and different disciplines. It is amazing how, when you dig into Boyd and we'd love to take you to the archives someday if you can make it to Quantico Virginia, we'll take you in there It's just amazing to see the scope and scale of the areas that Boyd explored. It's everything you could think of It's chemistry, it's physics, it's evolutionary biology, it's history, it's economics, it's math, it's physics, it's engineering. It's off the page.

John Flach: 1:01:30

Yeah, just the stuff you said.

Mark McGrath: 1:01:32

you know it's like Christmas here, yeah it works for everybody, because it only applies for humans who are making decisions. So you could bring a teacher in there that teaches grade school kids, or you could bring a quarterback or a coach of a football team All of it applies.

John Flach: 1:01:52

So one season we followed the football coaching staff through the whole season, that is, we sat in all their planning meetings and then we sat in the press box and on the field and listened in on the radio as they adjust the games and stuff. I learned more about leadership and the dynamics of organization in that season with a high school football team. It's incredible what even a high school football team does in terms of planning, going over video of their last game and their opponent that they're going to play in their next game and breaking down the videos and planning for the next game and then replanting during the game when things don't work out exactly like they anticipated.

Mark McGrath: 1:02:32

Being able to have that discourse in a psychologically safe environment where they can advance learning and get effective debrief. It all ties together. I think that's the big thing.

Ponch Rivera: 1:02:46

It's the same. I repeat that I mean coaching.

John Flach: 1:02:50

NFL teams has been pretty cool. It's just life. You're saying at the beginning, mark. Somebody asks you, where does this apply? I'm saying everywhere. It is what life is. You don't understand life until you understand the dynamics of circles, of closed loop systems and the public of perception and action through the environment. That's what people forget is through the environment.

Mark McGrath: 1:03:16

Sean, we'll make sure that we link to your blog so people can see a lot of the stuff that you're putting out. Then, from the blog, they can access all your papers and writings and things like that.

John Flach: 1:03:32

If I can promote a little bit, right now we're working on a book. I'm collaborating with Fred Vorhorst. You've probably seen the cartoons on LinkedIn that he's the artist of those cartoons. Fred is in Switzerland and Adam Walls. Adam had started a book, kind of an outline for a book, on system thinking, but we're kind of using the cartoons as a way to open this, to see what's going on, to open this discussion to a broader audience and make it more attractive to the style.

Mark McGrath: 1:04:03

Something like a graphic novel.

John Flach: 1:04:05

Well, the cartoons will open each one. It's kind of a conversation as we walk through Zurich. But then we'll write essays from Adam's writing from the perspective of a management consultant, i'm writing from the perspective of psychologists and Fred's industrial design engineer Very cool. So for each of the chapters we'll have essays from three different perspectives. The cartoon will be kind of the kickoff, the opening for the chapter.

Mark McGrath: 1:04:36

The illustrations are excellent.

John Flach: 1:04:39

Fred is amazing. I've gone through some of this.

Mark McGrath: 1:04:41

It's absolutely excellent. Well, hey, for the sake of the recording, John, we'll say thanks for coming on. We'd love to have you back at some point. We look forward to working with you on developing these ideas further.

John Flach: 1:04:54

Yeah, now we're connected for life, i think. The other thing is, this is so obvious to us, but there aren't that many of us who it is that obvious, and when you find people, i feel like you're in the wilderness. And you find somebody from your hometown there, all of a sudden you're best friends And that's how I feel like, and I'm reading your stuff and listening to you, i feel like wow.

Mark McGrath: 1:05:22

Well, I mean, I completely agree. I say, all the time is like when you put the signal out there, it attracts the right people, the right people hear the signal and you're able to coordinate action and direct action together. And we said this a lot, I mean, once you see it, once you get it, you can't un-get it. You know you can't un-see it. And there in lies the beginning of your development, of your edge. So