Douglas Engelbart, "Bootstrapping Our Collective IQ and the Aerospace Industry”

ENGELBART: I had just left it set up, the laptop, and the projector was on too. Then I was sitting there and I noticed that I had not plugged in any power. So my batteries would probably run out halfway through the presentation. So when I came up here to find a way to plug it in, I inadvertently unplugged that. And so this would make a great start to an interesting environment between us here. And I'm going to have to reboot and--

AUDIENCE: It's working now, sir.

ENGELBART: Pardon? Oh? Oh! Thank you very much. That's the story of my life.

Okay, we'll be in there in a minute. One of the one of the things that caught my ear where Tom Ferguson talking about is the basic shift in paradigms that occurred in the launching of LAI, about the way in which organizations work and what you do your productivity, et cetera. And this is something that, by the early '60s, I had realized was a very big plus, that the paradigms that prevail with which to sort of guide the way people look at the world just have a surprising impact. And they've always been there. And there's a slow, basic change in paradigms that's sort of part of the evolution of a culture.

And it's very likely that it had a survival value in having that be relatively slow, so a segment of society didn't shift all of its beliefs and orientations too rapidly and fall apart. So perhaps that's the case. But it does take a long time for paradigms to shift.

Well, one of the things I really am coming to in this situation here is looking at the scale of change that the technology is catapulting us into, and that all of our paradigms are sort of very slowly emerging from the old days in which things changed relatively slowly. So how we and social bodies-- organizations, institutions-- how we cope with the future, you know, the real perspective of explosive changes in technologies, is sort of out of date. And that's a very basic thing.

And I learned it in spades by being fired and things like that. And applying for universities and corporations to come and get started in these things in times in which they just clearly said, well, no-- one very prominent computer-oriented industry actually turned me down in 1957 when I said I'm assuming you're going to go into digital work with computers. No, Doug, sorry. Not a chance.

So these really, really brought home to me this question of it. And so, if there were any kind of thing that could get across here from my perspective, it would be how do you get your perspectives and your paradigms to start readapting, really reassess the way they are? So one of them here is in time, the external environment-- which in this case, a lot of it is spurred by the digital technology and nanotechnologies that are emerging-- in which, over and over and over again, we sort of feel that's come here. And yes, there are a few adaptations and such. So our job is to take what the vendors offer and learn how to adapt it. It's sort of like that. But the changes that are available and the potentials are just way over that, and their impact on organizations is a really central, central issue in change.

And the organization's evolution in adapting to that stuff is going in these kind of jerky steps, including what LAI has done like that. And so how do we shift and cope with that really, really significant change in there? And this is just one of the very basic things. And with it come real problems. So it's just inevitable that, when all that collides throughout the world in all sorts of aspects of its business, of its economies, and the defenses and all that, that they become really strange situations and very big, very big.

So that's one thing. They said, well, how are we going to cope with those? Well, we cope with those by collective action and thinking about it, adapting our ways of doing it such, and finding ways to solve problems like that. So there are opportunities with all of this, too. And one of the big, big opportunities that just I seized upon-- you won't believe it, but it was 1951. I was saying computers. And we could interact with them on displays and shifting. The way you can couple your head in brand new ways to knowledge, the way you can collaborate with others in there, is just a huge potential there for boosting our capability for effective collective action in there like that.

Well another thing that, as a few years went beyond that like that, it's also, say. We can plug that kind of new capability back into the improvement infrastructure and improve the way we improve, which, with the challenge of how rapidly things are changing and the complex need for that kind of improvement, looked like a sure winner. And I just used the term bootstrapping. So that was driving me through those early years.

And then I ran into this paradigm in the mid '70s that, on one hand, the artificial intelligence people were saying, oh look. The computers are going to get so smart that the humans sitting in front of them won't have to learn anything. The computer will adapt to that. And on the other hand, the people were talking about office automation. What we're going to do is automate the way we do work now. And the real user is the secretary. And those two things just pushed me right off the research map.

But fortunately, we had enough doing-- we were already supporting, mostly, DOD units over the ARPANET and learning how to use this. So we had a small business. And we got that to be sold. And I went to the commercial world with that, which was a really good lesson. It just clamped the research down because the people who know how to run businesses says, no. You don't get involved with the customer. They'll just want things.

So then another very fortunate thing is that McDonnell Douglas with, perhaps, a foolish sort of thought or something like that, had been successful in commercially getting access to its CAD systems. So it wanted to go into the information services business in a bigger way. And it started acquiring companies, including the one that had bought me from the research outfit. And so bingo. I was part of McDonnell Douglas, which gave me a new freedom to start going inside their design, development, manufacturing people without seeming like a vendor. I was a cousin. And that was a real thought.

So it just became very clear to me then that there was just an immense value, that what we were offering in the way of collaborative work, with hypermedia, that we could do quite a few more things then than you yet can do with the web stuff, because it's really based upon where you can go. So anyway, these are the things I'd like to talk about in this sort of order. And this was an experiment, to give you an order that wasn't just exactly linear.

So the first thing to talk about is what we call the co-evolution frontier. And it's like saying, well, where does organizational capability come from? Well, it's just based upon your basic genetic capabilities, you know? You've got sensory, perceptual, mental, cognitive, motor capabilities. And these are the things you exercise.

Well, yes. But if you take a somebody that's never grown up in any culture at all. They're totally helpless. They're about like this.

So he says, well, why don't you look at the kind of things that do help produce more capability for people? Well, you've got a whole long list of that, including all the technologies you can think of. And so I was making a list of that back in the early '60s just to get organized about how you really can amplify human capabilities.

And oh, my gosh. But always, I began to realize, oh, look. There are a few other things, too, that are there. So there was no name for that. So I'd been calling it the human system. And then it becomes pretty clear that there's a huge amount of what we call augmentation over here, as well as that and the tool system.

So the thing [INAUDIBLE] talks about an explosive technologies on this right side, and one looks at how things such as the plow or the weaving looms or the printing press came in on the right hand side. And the ensuing evolution on the left hand side in order to harness that created big changes in there. So that the scaling thing is becoming really important.

And I'd actually done a study of scaling stuff in the late '50s, knowing that digital technologies were going to have to get smaller and smaller and faster and cheaper, and that was going to come by learning how to build them much smaller. So I got a chance to do a few months of study about scaling. Because once I had worked at Ames Aeronautical lab, my first job out of school like that, and had known aeronautics people and talking about Reynolds numbers and things like that, and that you had to get the same Reynolds number in all the pressure, so that the scale model would give you relatively valuable data, so I learned a lot more about all of that.

And one of the real things that came out of that was, if you're used to building and working with devices at a given scale, and suddenly a change of scale in some of the important parameters, as it changes slowly, some of the quantitative characteristics will change. But past a certain point it gets qualitative, and things won't work anymore.

And so I would try to give lectures. And I would just tell people, well, suppose everything in this room, including all the people, just suddenly scaled up in size by a factor of 10 and have three dimensions, would you notice it? And so everybody says, well, let's see. It'd be the same angle subtended by anybody's-- they'd be 10 times as far away, but 10 times as big. So I probably wouldn't notice.

But then you start pointing out, how much more do you weigh? Well, 10 times 10 times 10. That's a thousand times as much. Oh.

How much stronger are you? I don't know. Well, somebody in there would know that the strength of your bones and muscles is really proportional to the cross-section area. So you're only a hundred times as strong, and your chair is only a hundred times as strong. So that means, unless your chair is designed with a safety factor of 10, you're doomed. So you fall on the floor. So your bones will break because they can't stand it. And your lungs are only a hundred times as large for a thousand times metabolism needs. So you'd be dead pretty soon.

But anyway, this surprising set of things, when you're not used to thinking about that scaling, so that really came home to me in that study. So I looked at this diagram, and I said, wow. With the scale of change that's erupting and forthcoming here with the nanotechnology and the digital stuff, that the changes over here that are going to be taking place, some force-- because as you adopt all this and this it gets all of the turmoil here. But some of the change is to take advantage of that. There are going to be a lot of surprises in that. And so that's what I started really to pursue, and especially in this language in the getting your concepts symbolized, externalized, manipulated in brand new ways, and realizing that the way we're used to things as they're done in print, that's just got very little to do about how effectively you're harnessing your basic mechanisms in there.

So you ought to be able to read much more flexibly, getting the views you want, moving around. Much leads on there. But pretty soon you're doing things that look hard to learn and it's unnatural to use. So the mantra at the time was easy to learn and natural to use. And that's been inhibiting our exploration of this just immensely.

And even in the the Defense Department, I would go into DARPA and try to talk about some of the things, and they'll say, oh, you gave us this great system that will help people in a crisis. But they have to be able to learn how to use it in 20 minutes. See? And he says, oh. Well, let's see.

You've got some other important missions during times like that, like perhaps interceptor planes, right? Yeah. So with an important mission like that, do you expect any Jeep driver to learn how to fly that airplane in 15 minutes? Well, no. But--

So anyway, the perspective about how important missions would be in handling complex knowledge work, it just says, hey, wait a minute. It will be very important to go after high performance stuff. And there's just a lot in this domain that we could talk about all day. But we're not going to.

And so, any capability your organization has depends on the co-evolution of that thing, which includes stuff in your world, but also even in athletics world or just general business operations. So there is this something that I did was say, oh-- very crudely, because each tool system has many dimensions to itself, and so does the human system, but if you just do it a little bit roughly like this, you'd say, I've got a human tool space. And one's organization would fit in there someplace. So what if we go around the world looking at different societies and see where they fit?

Some use more or less technology, and more advanced human system development like that. And we say, okay. There are distributions, right?

And someplace in there, there's the organization you belong to that you're probably pretty proud of. And you think, it's right out near the frontier. See? We can anticipate today these different changes in the technology and in the human systems stuff. And we're a little bit lagging in the human system. But boy, LAI is taking care of us, moving us into here, right? Well then, let's just say there is a distribution like that.

And then let's talk about the scaling business a little bit. It says, well, now wait a minute. What if we really think that technology is moving at a rate that's faster?

Well, our whole way of changing our organizations evolved over centuries and thinking about where these boundaries weren't that far away. But what if-- this is why the paradigm shifted in people's minds. And they realized, oh, wait a minute. Here we are with our distribution. And here's all that you can anticipate today and the technology, with commensurate changes in here. We suddenly have a new frontier. So we should have different paradigms about how we move our organizations into that.

And then somebody else will come and look at it, like this guy from California, and he'll say, well, why don't you just be a little bolder about that? And you says, hey, we haven't really seen what nanotechnology will do. And it's just, that scaling things down, it's just going to produce capacity and capabilities and bandwidth and everything else that we never dreamed of. And oh, I see. And that's something. How is that going to affect the world?

Well, okay. What about computers and things will get so small that you could surgically implant them and they can get the energy to drive them from your metabolism, and they could connect to your nerves, and they can also have sensor things that go beyond what your sensory capabilities can do? And all that connects in. And boy, you could become, what do they call them, cyborgs or something? That's really tremendous. But the scale of things is going to be able to do that. Just a couple examples out of the air here like that, see?

And then intelligent agents are really just inevitable, going to come in. And they're beginning to. And hey, how are you going to learn how often you've got a whole crew of slaves? It's not realistic to think of them just sort of bumping along and helping do a spell check or some things like that. They're going to be things that you can learn how to steer and guide and will interact with. And it will take skill and learning how to do that, but boost your power a lot.

So he says, oh, that frontier is more like this. The relative scale-- and none of our processes for social or business adaptation, they all were evolved with the frontier being very near like that. So it takes a real call to re-examine what's the processes? What are the processes by which our organizations can adapt and start harnessing this thing, and our societies learn how to cope with it? So we need to look at different processes for our evolving. And this has led me to that bootstrapping. And then it leads to things like, oh, let's re-examine the infrastructure by which our organizations improve and see if the improvement infrastructure can be improved, and then if you can bootstrap it.

So that's the message. And it turned out that, for the formulation we evolved, that one of the key elements in that improvement infrastructure is what we called an improvement community, something to have special focus on. And LAI is an improvement community.

And then it's saying that look, if we can bring the modernization work, especially in collective knowledge work, into appropriate improvement communities, this is going to give us that extra second degree acceleration or something like that. It gives extra strategic leverage in the improvement process. And so that's one of the reasons why, when I talked to Earl, I thought oh, boy. There's a high tech improvement community and it's based in MIT, which has a few people that are used to working with information. And it's a great model. So let's talk a little more about that.

So one of the strategic things that somehow there have to be is ways to establish outposts out in that frontier. And it isn't a matter of going out there and setting up a group of people that, by themselves, are just doing startling things. The way that that's going to show organizations how to go is if those are doing real work. And it'd be very handy if the real work they're doing is a visible part of the work the organizations are doing already. So that means you don't set them up in a laboratory in a glass bowl doing their special things. So there are a lot of thinking about that.

And how do you get the high performance groups that are going to be doing that? How are they composed? What are they going to do? So all of that is an important part of thinking this way.

So we've talked about this picture of the co-evolution frontier. And let's talk about, then, one of the very important improvement categories-- the strategic, in there-- as a collective intelligence. So let's say you have a bunch of people, and they're involved some organization in this mandala kind of thing in here with all of the cross connections implying that every member of this organization needs to have a channel for communicating with every other one. And so that's the way they work together.

Then it's obvious that if they're going to get collectively smarter, they have to manage the knowledge in there and, in the traditional sense, treating a document as a container with some authored knowledge in it like that, you said, well, it's going to be documents. And with the way the web has taught people like that, it's easy now to tell them that the web is a beautiful way to start managing their knowledge. And how do you go about, then, making them smarter? Well, that's something we could talk for hours and hours about, too.

But the experience and the motivations and the things we experimented with just really show up a lot. And so it's how do you really move beyond the knowledge work capabilities that the vendors can offer you, because the user organizations aren't yet proactively up ahead enough to say, I want to start learning about the really far out things, rather than the way it is now that what we're going to think about is what we can implement today or tomorrow? And we have the political problems of conflict inside our organization of people that don't want to have to change that much, or are suspicious, all kinds of what you end up realizing are very natural cultural impedances for that.

And so in the end, there's going to be a dynamic knowledge repository that's electronic, hyper-media linked, like that. And the ways for organizations to manage that, they want to be a lot more alert about the outside world. So they're going to have to be able to go out and actively ingest and assess and organize the intelligence about what the outside world is doing. And this social organism that you call an organization is going to be judged on its IQ a lot by, oh, how sensitive and perceptual is it about what's going on in the outside world that offers opportunities or threats? And when either of those occurs, how smart and clever are their plan for how to cope? And how well do they, then, marshal their resources and coordinate them in coping? And how quick are they to re-adapt and shift?

And you begin realizing the way the future is going to go, that the annual yearly budget thing is probably going to have to go by the boards and become a much more dynamic. And a lot of things are changing. The recorded dialogue and the knowledge product are just, they're a way to say, oh, any given time you really want all the plans, the designs, the current state of things, the current state of your understanding about the outside world, the current state of the scenarios that you're depending upon, is all sort of what you call knowledge products, available for people to use in there. And how they study it and how it's organized is a whole field and exploration itself.

And then at any given time, there's a lot of dialogue about it. And you're in the midst of a dialogue exercise right now, this morning. And recording that-- well, what I say and what I present here like that, the technology is already available for that to get nailed down and be on a web, and automatically transcribing my speech as much well enough at least so that you can scan for that. So you can go back and then find out what I said and look at it again, and say, oh yeah, that's interesting. And then the way you can make comments on it are the links that you'll be able to provide can point to a particular passage that I spoke-- and its associated diagram-- or run up and down that.

Or cleverly say, hey, I want to hear what he says and then show the three kind of slide pictures that he showed that went on that. And then I'd like, when you follow that link, to highlight something there because that's what I like to talk about. Well, that's the kind of linked things that were part of our plan. And the basic underlying standards for the extended markup language as such will provide things like that.

So then people make comments on this and questions, and the dialogue's comment on the comments grows. So these are all things that technology can offer today. But it's just a introductory example of this recorded dialogue is a dynamic part of integrating intelligence and arguing about what's there now, by which your knowledge product evolves and changes. So every organization that survives into very far in the next century it's going to have to start living like this.

So there are a few other things to think about in this and say, oh. You know, if I'm a division or a part of a bigger organization, my division or project or program is going to have its own knowledge repository that's got to be dynamic and totally relevant to what we're doing. And yet, the whole organization does, too. And so every one of these nodes around here has its own dynamic repository, as well as the whole thing. And so all of those are evolving concurrently, and yet need to stay in sync, that none of them is looking at a future of something that isn't in any way contrary to any of the others.

So it's that concurrency thing that really hits the demand. Yet you don't hear that very often. You know they have to have interoperability, but not scaling. So the challenge is large. And the challenge there is something that you don't just get by getting a new product out by a given vendor or something. It's got to be something that evolves in a very different way.

And so we ended up with this acronym CoDIAK, saying that describes a core set of capabilities in the future smart organization, that they concurrently develop, integrate, and apply knowledge. It's the best we could sort of do. So we use that term a lot, and say, how do you go about improving that? And you can just guess that every one, almost every objective you'd like to set up for what LAI can do, can do a lot better if the organizations were better at this. And a very important thing-- oh, LAI could operate a lot more effectively. So where should you put your initial exploratory energy about doing outposts that are trying to learn how to do this? Well, strategically speaking, LAI is the place to start investing in learning advanced how to do this.

So I got some great lessons interacting with the McDonnell Douglas people. So they were showing me that, well, so you have a couple thousand people working inside of the McDonnell plant for on a fighter plane. And look at what you have in these tiers of suppliers and the kind of interactions and design coordination that have to go on there. So there's a real example for concurrency and interoperability requirement. So these are things that you very rarely, very rarely hear about when vendors are selling you things. But this is the real marketplace.

So anyway, this open hyper-document system is something that evolved in our minds like 14 years ago at McDonnell Douglas about saying, you really, really have to come out with a standard, open, hyper-document system. And the HTML offered a beautiful way to get a standard way for publishing. And the XML is starting to advance it. And most of that is being done by vendors, the evolution of standards. And what is critically needed, really, is the proactive involvement of the end user organizations in the evolution of the standards for this thing. So these are sort of the properties that all these things.

And then it becomes pretty clear that there's a huge amount of what we call augmentation over here, as well as that in the tool system. So the thing then, if one talks about an explosive technologies on this right side, and one looks at how things such as the plow or the weaving looms or the printing press came in on the right hand side, and the ensuing evolution in the left hand side in order to harness that created big changes in there. So that if this scaling thing is becoming really important-- and I'd actually done a study of scaling stuff in the late '50s, knowing that digital technologies were going to have to get smaller and smaller and faster and cheaper, and that was going to come by learning how to build them much smaller.

So I got a chance to do a few months of study about scaling. Because once I had worked at Ames Aeronautical Lab, my first job out of school like that, and had known the aeronautics people and then talked about Reynolds numbers and things like that, and that you know that you had to get the same Reynolds number and all the pressure so that the scale model would give you relatively valuable data. And so I learned a lot more about all of that.

And one of the real things that came out of it was, if you're used to building and working with devices at a given scale, and suddenly the change of scale in some of the important parameters, as it changes slowly, some of the quantitative characteristics will change. But past a certain point, it gets qualitative, and things won't work anymore. And so I would try to give lectures. And I would just tell people, well, suppose everything in this room-- including all the people-- just suddenly scaled up in size by a factor of 10, and have three dimensions. Would you notice anything?

And so everybody says well, let's see. It'd be the same angle subtended by anybody's-- they'd be 10 times as far away but 10 times as big. I probably wouldn't notice.

But then you start pointing out, how much more do you weigh? Well, 10 times 10 times 10. That's a thousand times as much. Oh.

How much stronger are you? I don't know. Well, somebody in there would know that the strength of your bones and muscles is really proportional to the cross-section area. So you're only a hundred times as strong, and your chair's only a hundred times as strong. So that means, unless your chair was designed with a safety factor of 10, you're doomed. So you fall on the floor. So your bones will break, because they can't stand it.

And your lungs are only a hundred times as large for a thousand times metabolism needs. So you'll be dead pretty soon. But anyway, this surprising set of things when you're not used to thinking about that scaling, so that really came home to me, that study.

So I looked at this diagram, and I said, wow. With the scale of change that's erupting and forthcoming here with the nanotechnology and the digital stuff, that the changes over here that are going to be taking place, some force-- because as you adopt all and this it gets all the turmoil here. But some of the changes to take advantage of that, there are going to be a lot of surprises in that. And so that's what I started really to pursue, and especially in this language and in getting your concepts symbolized, externalized, manipulated in brand new ways, and realizing that the way we're used to things as they're done in print, that's just got very little to do about how effectively you're harnessing your basic mechanisms in there.

So you ought be able to read much more flexibly, getting the views you want, moving around. Much leads on there. But pretty soon you're doing things that look hard to learn and it's unnatural to use. So the mantra at the time was easy to learn and natural to use. And that's been inhibiting our exploration of this just immensely.

And even in the Defense Department, we'd go into DARPA and try to talk about some of the things, and they'll say, oh, you give us this great system that'll help people in crisis. But they have to be able to learn how to use it in 20 minutes. See?

And he says, oh well, let's see. You've got some other important missions during times like that, like perhaps interceptor planes, right? Yeah. So with an important mission like that, do you expect any Jeep driver to learn how to fly that airplane in 15 minutes? Well, no. But--

So anyway, the perspective about how important missions would be in handling complex knowledge work, it just says, hey, wait a minute. It will be very important to go after high performance stuff. And there's just a lot in this domain that we could talk about all day. But we're not going to.

And so any capability your organization has depends on the co-evolution of that thing, which includes stuff in your world, but also even in athletics world or just general business operations. So there is something that I did was say, oh-- very crudely, because each, the tool system has many dimensions to itself, and so does the human system. But if you just do it a little bit roughly like this, you say, I've got a human tool space. And one's organization would fit in there someplace. So what if we go around the world looking at different societies and see where they fit?

Some use more or less technology and more advanced human system development like that. And we say, okay, there are distributions, right? And someplace in there, there's the organization you belong to that you're probably pretty proud of. And you think it's right out near the frontier. See? We can anticipate today these different changes in the technology and in the human system stuff. And we're a little bit lagging in the human system, but boy, LAI's taking care of us, moving us into here.

Well then, let's just say there is a distribution like that. And then let's talk about the scaling business a little bit. It says, well, now wait a minute. What if we really think that technology is moving at a rate that's faster? Well, our whole way of changing our organizations evolved over centuries and thinking about where these boundaries weren't that far away. But what if this is why the paradigm shifted in people's minds, and they realized, oh wait a minute. Here we are with our distribution. And here's all that you can anticipate today in the technology, with commensurate changes in here? We suddenly have a new frontier.

So we should have different paradigms about how we move our organizations into that. And then somebody else will come and look at it, like this guy from California, and he'll say, well why don't you just be a little bolder about that, then? And you says, hey, we haven't really seen what nanotechnology will do. And it's just that scaling things down, it's just going to produce capacity and capabilities and bandwidth and everything else that we never dreamed of.

And oh, I see. And that's something. How is that going to affect the world?

Well, okay. What about computers and things will get so small that you could surgically implant them and they could get the energy to drive them from your metabolism, and they could connect to your nerves, and they could also have sensor things that go beyond what your sensory capabilities can do, and all that connects in? And boy, you could become, what do they call them, cyborgs or something? That's really tremendous. But the scale of things is going to be able to do that. Just a couple examples out of the air, and you're like that, see?

And then intelligent agents are really just inevitable, going to come in. And they're beginning to. And hey, how are you going to learn how, if you've got a whole crew of slaves, it's not realistic to think of them just sort of bumping along and helping do a spell check or some things like that. They're going to be things that you can learn how to steer and guide and will interact with, and will take skill and learning how to do that, but boost your power a lot.

So he says, oh. You know, that frontier is more like this. The relative scale-- and none of our processes for social or business adaptation, they all were evolved with the frontier being very near like that. So it takes a real call to re-examine what's the processes? What are the processes by which our organizations can adapt and start harnessing this thing and our societies learn how to cope with it? So we need to look at different processes for our evolving. And this has led me to that bootstrapping.

And then it leads to things like oh, let's re-examine the infrastructure by which our organizations improve and see if the improvement infrastructure can be improved, and then if you can bootstrap it. So that's the message. And it turned out that, for the formulation we evolved, that one of the key elements in that improvement infrastructure is what we called an improvement community, something to have special focus on. And LAI is an improvement community.

And then it's saying that look, if we can bring the modernization work, especially in collective knowledge work, into appropriate improvement communities, this is going to give us an extra second degree acceleration or something like that. It gives extra strategic leverage in the improvement process. And so that's one of the reasons why, when I talked to Earl, I thought, oh boy. There's a high tech improvement community, and it's based in MIT, which has a few people that are used to working with information. And it's a great, great model. So let's talk a little more about that.

So one of the strategic things that somehow there have to be is ways to establish outposts out in that frontier. And it isn't a matter of going out there and setting up a group of people that, by themselves, are just doing startling things. The way that that's going to show organizations how to go is if those are doing real work. And it'd be very handy if the real work they're doing is a visible part of the work the organizations are doing already. So that means you don't set them up in a laboratory and glass bowl doing their special things. So there are a lot of thinking about that.

And how do you get the high performance groups that are going to be doing that? How are they composed? What are they going to do? So all of that is an important part of thinking this way. So we've talked about this picture of the co-evolution frontier.

And let's talk about, then, one of the very important improvement categories that's strategic in there, is the collective intelligence. So you said, you have a bunch of people, and they're involved some organization in this mandala kind of thing in here, with all of the cross connections implying that every member of this organization needs to have a channel for communicating with every other one. And so that's the way they work together.

Then it's obvious that if they're going to get collectively smarter, they have to manage the knowledge in there, and in the traditional sense, treat a document as a container with some offered knowledge in it like that. You said, well, it's going to be documents. And with the way the web has taught people like that, it's easy now to tell them that the web is a beautiful way to start managing their knowledge.

And how do you go, then, making them smarter? Well, that's something we could talk hours and hours about, too. But the experience and the motivations and the things we experimented with just really show up a lot. And so it's how do you really move beyond the knowledge work capabilities that the vendors can offer you, because the user organizations aren't yet proactively up ahead enough to say, I want to start learning about the really far out things, rather than the way it is now, that what we're going to think about is what we can implement today or tomorrow? And we have the political problems of conflict inside our organization of people that don't want to have to change that much or are suspicious, all kinds of what you end up realizing are very natural cultural impedances in that.

And so in the end, there's going to be a dynamic knowledge repository that's electronic hyper-media, linked like that. And the ways for organizations to manage that, they want to be a lot more alert about the outside world. So they're going to have to be able to go out and actively ingest and assess and organize intelligence about what the outside world is doing.

And this social organism that you call an organization is going to be judged on its IQ a lot by, oh, how sensitive and perceptual is it about what's going on in the outside world that offers opportunities or threats? And when either of those occurs, how smart and clever are their plan for how to cope? And how well do they, then, marshal their resources and coordinate them in coping? And how quick are they to adapt and shift? And you begin realizing the way the future is going to go, that the annual yearly budget thing is probably going to have to go by the boards and become a much more dynamic. And a lot of things are changing.

The recorded dialogue and the knowledge product are just there, a way to say, oh, any given time you really want all the plans, the designs, the current state of things, the current state of your understanding about the outside world, the current state of the scenarios that you're depending upon, is all sort of what you call knowledge products, available for people to use in there. And how they study it how it's organized is some whole field of exploration itself. And then at any given time, there's a lot of dialogue about it. And you're in the midst of a dialogue exercise right now, this morning.

And recording that-- well, what I say and what I present here like that, the technology is already available for that to get nailed down and be on a web, and automatically transcribing my speech as much, well enough at least so that you can scan for that. So you can go back and then find out what I said and look at it again, and say, oh yeah. That's interesting.

And then the way you can make comments on it are the links that you'll be able to provide can point to a particular passage that I spoke and its associated diagram, or run up and down that. Or cleverly say, hey, I want to hear what he says, and then show the three kind of slide pictures that he showed that went on that. And then I'd like, when you follow that link, to highlight something there, because that's what I'd like to talk about.

Well, that's the kind of link things that were part of our plan. And the basic underlying standards for the extended markup language and such will provide things like that. So then people make comments on this and questions, and the dialogue's comment on the comments grows. So these are all things that technology can offer today. But it's just a introductory example of this required dialogue is a dynamic part of integrating intelligence and arguing about what's there now, by which your knowledge product evolves and changes.

So every organization that survives into very far in the next century is going to have to start living like this. So there are a few other things that you think about in this and say, oh, if I'm a division or a part of a bigger organization, my division or project or program is going to have its own knowledge repository that's got to be dynamic and totally relevant to what we're doing. And yet, the whole organization does, too. And so every one of these nodes around here has its own dynamic repository, as well as the whole thing. And so all of those are evolving concurrently, and yet need to stay in sync, that none of them is looking at a future or something that is in any way contrary to any of the others.

So it's that concurrency thing that really hits the demand, yet you don't hear that very often. You know they have to have interoperability, but not scaling. So the challenge is large. And the challenge there is something that you don't just get by getting a new product out by a given vendor or something. It's got to be something that evolves in a very different way.

And so we ended up with this acronym CoDIAK, saying that that describes a core set of capabilities in the future smart organization, that they concurrently develop, integrate, and apply knowledge. It's the best we could sort of do. So we use that term a lot, and say, how do you go about improving that?

And you can just guess that every one, almost every objective you'd like to set up for what LAI can do, can do a lot better if the organizations were better at this. And a very important thing, oh, LAI could operate a lot more effectively. So where should you put your initial exploratory energy about doing outposts that are trying to learn how to do this? Oh, strategically speaking, LAI is the place to start investing in learning advanced how to do this.

So I got some great lessons interacting with the McDonnell Douglas people. So they were showing me that well, so you have a couple thousand people working inside a McDonnell plant for on a fighter plane. But look at what you have in these tiers of suppliers and the kind of interactions and design coordination that have to go on there. So there is a real example for concurrency and interoperability requirement. So these are things that you very rarely, very rarely hear about when vendors are selling you things. But this is the real marketplace.

So anyway, this open hyper-document system is something that evolved in our minds like 14 years ago at McDonnell Douglas, about saying you really, really have to come out with a standard, open, hyper-document system. And the HTML offered a beautiful way to get a standard way for publishing. And the XML is starting to advance it. But most of that is being done by vendors, the evolution of standards. And what is critically needed, really, is the proactive involvement of the end user organizations in the evolution of the standards for this thing. So these are sort of the properties that all these things--

My watch ran out of battery. So you can just tell how well I'm connected to today's world. So I had to borrow Earl's. So this means he can't tell me when my time is done. And that was a very clever tactical thing, don't you think? I should have borrowed everybody's watch there so he would have no way.

Anyway, here again, it's that sort of strategic need to get the end user organization, or the real customer is the organization, in the IT world that's coming up, and that's here now. So how do your organizations move into this space? And it's only going to happen if there becomes a real standard for the knowledge packages, that it's not a standard set by a vendor that this is my kind of file, or something.