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NerdTV #11: Doug Engelbart

Bob: We're back again at Doug Engelbart's house, trying to do another edition of Nerd TV. Doug, thanks for having us here.

Doug: You're welcome.

Bob: And part of this discussion to give our audience an idea about you, as a person, and where you've been and what you've done and where you're going and where your vision is. And another part of it is to get some sense of how you've seen the world that you've worked in and give us a shared vision of the outside, because your experiences have shown you parts of our culture and especially our scientific culture that most of the rest of us haven't had a chance to see. Now, you're one of the few people - I was about to say you're the only person - but you're one of the few people I know who's actually had an epiphany. I had an epiphany myself in the back seat of a Desoto in about 1967, but that was a different kind of experience, I think, than the one you had, but yours was also in a car, wasn't it?

Doug: Oh.

Bob: Your epiphany?

Doug: It's a double-ended - I mean, several months apart the two stages put together. First of all, I was driving to work on a Monday morning and I had gotten engaged that weekend so my head had been just so full of all the excitement of I'm going to settle down, I'm going to have a family, it's this and that, you know, a home and then all of a sudden I realized, hey, I'm getting near to work, I better focus on it. And then what made me wonder is oh, I don't have any goals for that.

Bob: No goals.

Doug: Well I just - in growing up in the depression and then I had a community where I had no picture of how professional people or any sense of people that were business oriented, about building a business or anybody that had any - oriented about the - even the politics of being in an organization or something. So, but I just though I'd steady job and so I had one. Well, what's a goal? It's a strange thing. I got an image - just popped up in my mind of a long, long, long hallway, brightly lit, no features - just featureless - going on and on and on and on to the future. That was my - what I'd set up as a career. I'm just going to go plugging along forever. So, I said, gee, I better design a goal and something appeared within the next hour that one I don't know where it came from, is oh, how about this for a goal professionally? Why don't I pick a professional goal that'll maximize the value my profession would have, my career would have, onto mankind.

Bob: An altruistic goal.

Doug: Yeah, but. And I have no idea where that came from. It just was there, very clear and so I started really working on that. I could only see my fiancée on weekends 'cause she worked 90 miles away and she'd stay with friends when she came down. But, between weeks, gee, I'd have to write the daily letter and then I had time to start looking at libraries and things about well, what does the world need? After a few months, I just really became to realize that hey, those real contribution things are associated with problems that are big and complex and oh, they have to be dealt with collectively. Oh, and our collective ability to cope with complex, urgent problems isn't increasing particularly well at all.

But technology and all is just going to make the complexity and urgency in our world situations just go escalating like that. So if we don't learn how better to deal collectively with these complex urgent things, the only thing you could picture is finally there's going to be something that will just collapse mankind's ability to cope on earth. And so, oh, well that's a good goal then and then a mixture of the kind of engineering training I'd had in college and the technician training about how equipment and such worked in the Navy that was very valuable. And reading one book about computers of which, for example, there were like three maybe in the country at that time. This was 1951, the spring. And I just put together a picture that hey, radar screens, electronics and radar put all sorts of things on there or if the computer can punch cards or print out paper, I just knew instinctively as an engineer, you could put the electronics together to make whatever happen you want to on the screen.

And if a radar set could interact and watch what this operator would do and a computer can read punch cards and such, you could certainly watch keys and do things so you could - you just got the picture. That's the way, because people can be on the same computer complex working together, so I just nailed in that commitment to go after that. And I had much to learn about that I took quite a while to begin to realize and as I would get such a buffeting and people would laugh at me and in the early days when there were so few computers, it would be like in the early days of helicopters or even worse now that hey, everybody will have his own helicopter. Oh, sure. So it was sort of that wild and I empathized, but later more and more as computers started to be, sets that people were talking about interacting with them and in the '70's they began to be serious about it.

But the picture was office automation. And it says, "the real user's the secretary and you have to make it easy to learn for her." And I said, "Gee, the real user's tomorrow knowledge worker; you have to get ready for that." It didn't work. So, and people read the term paradigm - I started learning what that meant and realized that boy, the paradigms of the day just viewed computers as a clunky thing. Yes, they could crunch numbers or something but the thought of interacting with them just - it didn't fit. And when they did start getting so you could interact with them, oh, "It's kind of very easy to learn because who's going to use it otherwise?"

And I started saying, "Hey, wait a minute. There's not many other artifacts we have in our life that in the end become very easy to learn." You know, there are all sort of things associated with their use and so I just tried to characterize that like saying on their approach then everybody would still be riding tricycles because they're so much easier to learn than a bicycle. And in fact, I did a lot of work with bicycles and learning how to ride all sorts of ways - backwards, standing on them and everything and really determined how you really do ride a bicycle, which nobody I know seems to have learned about.

And so anyway. It's just - there are all kinds of examples in how the artifacts appeared in our society and then they make society change because of other things. So I developed a way of thinking about it as more focused on capability. See you really look at capability - collective capability like an organization can design and produce these products or something or that a society can set up schools or we may be able to educate the kids that these things - these capabilities end up just being a big infrastructure of capabilities that no one stands by itself. It may be enhanced considerably by some technology, but when that technology appeared, that capability was elevated while other actions that you did which utilize that capability, then could change, which would require subordinate capabilities they depended upon to change instead.

And so throughout all this infrastructure, there'd just be a steady evolution of changes. And as they change, then the opportunity for the artifacts would appear in a different way. So it's a co-evolution of all of that that really affects it and when you're thinking about the real potential, as I've got more and more into doing is to how the technology could really make a really global impact of very significant size on our ability to learn and read and work with knowledge. And that's sort of like the scale of what printing - the alphabet and printing did. But people continue to look at it with all the paradigms they've assimilated with the printed word, etc. And if you even say hey, it's very clear, I bet you anything that books are going to essentially become obsolete and they're going to be replaced by the technology of display and interaction with the computer behind it and the knowledge base that you can get there, and the way that the things will be portrayed to you with much more flexibility and potency than the printed page.

And so we actually worked on examples like that beginning from the '60's of saying oh, yes, I'd like to see all those things, but here, I'm going to go some really quick thing and have the computer just show me the first line of every paragraph. That was the first thing we tried as a special view. And it was remarkable - the utility that would have. Looking at like that and you'd say, oh the first line and oh, that's the one I want. It was strange how the - some of the young programmers would say, gosh, pretty soon you start - when you write a paragraph, you start wanting to have that first line be meaningful about what's going to be in the whole paragraph. Oh, your teachers in English never told you that?

Anyway, all those kinds of changes come about and there's something - it's like the paradigms also don't appreciate what kind of machinery we have inside our head that I've latched onto the term of perceptual machinery that you get visual stimuli and audio stimuli coming in and they - your body takes care of picking those up, but what turns those into recognizable - oh, I recognize those objects and I recognize the concepts that that particular array of funny symbols is representing and so one would have thought when it all began is you'd have to go through and piece that all together and not put - after while this machinery just goes beep-beep, I don't recognize not only that that's a word that's pronounced da-da-da, but the meaning of it. And so wow.

So that machinery adapted to the printed word, etc to get us that kind of capability. Well, the computer can not only print like this, it can do all these optional views you want. In fact, it could say hey, I want to have you do a syntactic analysis of this text that's here and the computer and then when you show it on the screen, I want the different parts of speech to be in different colors. Here's the coloration I want that I'll be willing to bet significant amount of my net worth the fact that you read it like that, people don't have to explain it to you. Something like that.

But after a while, you start adapting 'til that reading accelerates your reading and your understanding. And then you could say well, I want some views in which in only show me this kind of clause or something like this because when I scan for something, that will be a big help to find it, or make it brighter or blink or something. And so give it to people and they'll read it. But that's not part of the prevailing paradigm. To me, that's just totally the kind of reality that that is there to do. So how are you going to get the world to start exploring those kind of options and if you have the computer come also that we were making links in the '60's before anybody else was. And we didn't call them hypertext links, we called them links.

But I noticed that when you're reading some academic document or something that says oh, as frigidly reported and certain - they missed a certain journal in a document. Oh you have to go get that and read through it. So it says hey, when our links ought to be able to not just to the document, to the passage where that appeared or maybe a view that shows you how it was worked. So we started doing that with our hyperlinks could do that and gee, that's just terrifically valuable and yet the web got going and it tangentially let's you do that if you've prepared the document for it, I guess. But then there're many other things. So one of the things I've sort of conceived of that I hope I can get some money to build or something is a way to start integrating those kind of high resolution addressability and optional views right there as options that people can attach to their way they work with the web.

So anyway, it's - the paradigms - it's amazing to see that - to try to think of what it is that really affects and guides the evolution of our paradigms in our society. And the very obvious thing that if you think about that long enough realize that if our paradigms don't sort of shift to the unrealistic mode with the needs, the possibilities, the threats, the options, etc of the way our world is changing and what technology can do, etc, then our ability to harness all that effectively just drops way off because it's - people still shrug and say that's to learn.

Bob: So what we have is paradigms that we strive for and then having achieved them to a certain extent, they hold us back from going on.

Doug: Well, yeah, the paradigm is kind of like your ability to see what's really feasible and oh, would be well worth while and the past of things about it's different from today, oh that would be hard to learn or something; it's like saying, oh, it's going to be a different world. We're going to have different customs, different skills, a whole bunch of things like that and no one thing is is going to fix it; it's going to be a concurrent evolution that's just got to progress and the best thing we could possibly do is not think of somebody's gonna tell you what THE ANSWER is, but somebody that says, hey, here's a process that would help facilitate optimally that evolution and then try to help the paradigms go about how much improvement can you make in what I call our collective IQ, which is collectively being able to develop a maximum useable knowledge about this domain of knowledge and the future and how you would go about doing it, etc. That to me is a central thing.

Well, if people's perception of that is at all five percent interest increase or something of that sort, we'll get to it. You know this guy over here, out here, he's got this real neat computer system that will do such and so on. That's probably the answer instead of the kind of evolution that's there and the potential. It's like you know, I'd really like to have a dialog with somebody about the relative potential increase in our collective capability that if we talk now about what - in just the last 100 years - what technology has provided with physical mobility - transport mobility - and that people 100 years ago wouldn't believe you.

I make stories up about that and I remember - because I was interested in old cars when I was a kid and found one that was years and years older than I was and got it working. So I was reading about that and you know, in 1904, say 100 years ago, you find a lot of people with such, well 35 miles an hour would be the maximum speed that people can manage. And as for women drivers - oh, hell no. They would never be able to do it.

And I just make up a story about trying to explain to them the way the freeway works. You go along the freeway and it's fixed so you can peel off, or merge, so you don't have to stop. 'Cause I've already explained to them about the way intersections and stop signs work and you wait; you got to right-a-way thing like this and stop lights and oh, that sounded like a good idea and he says of course when you get there and the light's red and nobody there you just go. Is that right? No, no, don't go. Oh, you're kidding.

And you talk about the freeway and then you kind of say, hey, how fast do they go? 60 miles, 70 miles an hour. 70 miles an hour? Yeah, oh wow. Well, gees, how do you get on and off. Well, you got these curving things like this. Well, you're coming on and somebody wants to get on there, there's not control. What happens? Oh you just take a look at each other and just instinctively decide that he's ahead enough and I'll slip in behind him. What if there's another guy right behind that guy? Well, he'll drop back. Well, how do you know? Well, you're committed when you're coming in that fast, so he realizes that and he'll drop back. Oh, I see. And by the way, how fast they going? 70 miles an hour. How much do your cars weigh? I don't know, maybe 4,000 pounds.

And so you slide in there between them and some guy behind you going 70 miles an hour, 4,000 pounds, and you're sure he's going to give you room? Oh, sure, you just check in your rearview mirror. Check in your what? Well, you got a mirror up here and you look at that and you just. Whether you slow down, kind of like that. That would just be unbelievable to them because 100 years ago, what was a mirror used for? To shave or powder your nose. The thought that you could learn how to look 20, 30 yards behind you, at something going that fast and just bet your life. Oh, sure, we do it all the time. It just would be unbelievable.

So there's be many, many other things about it that they think about the scale, the requirement, how much you'd have to learn to operate in this driving environment like this, all of the rules. It's just one of the - kids grow up riding in the backseat and seeing all this and just unconsciously they know that they're going to stop at a stoplight; they're going to do this and that. And come to a four-way stop and people take their turns without - they just look at everybody and kind of know what the situation is - now it's my turn. There's a lot of skills. So that's the kind of thing that the paradigm before all that was available wouldn't believe and so how did it evolve?

Well, the kind of thing about the mobility capability in our environment that came in the last 100 years, well the pace of things now, that's going to be a 10 years equivalent for our knowledge environment and that is if we start actually evolving like crazy. And the potential would be tremendous.

Bob: And we're not realizing our potential?

Doug: That's right. If you asked people, hey how much more is it going to go, they'll just really tell you about, hey, somebody's got this hot shot thing that'll do this or that. Maybe one in a 1,000 you'll find that is oriented about thinking beyond that.

Bob: So let's drop back for a second, 'cause you did this soliloquy, really went on endlessly there explaining about these paradigms and if we drop back in 1951, the spring of 1951, you're driving to work; you are - you've just become engaged. Had she said yes, yet?

Doug: Yeah.

Bob: So she said yes.

Doug: It took her - she had to go - anyway, took her about 12 hours to say yes.

Bob: She finally said yes and you're saying okay, now, I'm committed to changing my life course and what am I going to do with my life and you've decided to do something that is - maximizes your benefit for mankind -

Doug: Then some months later, a picture of how to do it.

Bob: And then a picture of how to do it. And the picture that emerges in your mind is one of essentially cooperative networked, multi-user, graphical computing. Is that about right, for that moment?

Doug: Well, I - I mean there's, you know, that's okay.

Bob: Okay. So it's 1951; you're having this vision and admittedly, just think about it, by 1951 and you turn to your neighbor and you said I predict 50 years from now, our young people will have tattoos all over their body and lots of piercings and they would say, well, will that be after the nuclear holocaust and we're all aborigines again? Well, no, that'll be - it's just a part of our cultural development. And they would say, you're crazy, Doug Engrlbart. You know there's no way 50 years from now our kids and their crew cuts are gonna have tattoos and piercings; it's just not - that's marines and they don't get pierced. And yet that's the way it develops and your point being that the paradigms - it's hard to be a visionary from one paradigm to the next and beyond. But you were one, so how is that - how did you decide to move forward with that and how was your decision greeted by the people you were traveling with?

Doug: Well, somehow I was naïve enough and impolitic enough and ignorant enough about the way the world really works to just say oh, that would be a very great goal to make. That sounds like it'd be worth a great deal. So good. That's something I think I can go after because I've got the kind of engineering background; I can do something with the technology and just go. So -

Bob: So you accepted the challenge. And so given that this 1951, there are three computers in America. What do you do? What did you do next?

Doug: Well, I decided I'd - one thing is I need to know more about how research is done and I understood that's what you get if you get - go to university and take graduate courses. And besides the University of California here at Berkeley had a contract to build electronic computer and it would be with vacuum tubes and great big like this. So that would be a logical place to go. So I applied there and got accepted and within about a month and a half after we were married, we were on our way.

Bob: Wow.

Doug: And my poor wife had been thinking about settling down in very nice ways so here we were, working for our room and board. So anyway.

Bob: When you went to UC-Berkeley, were you able to immediately apply to yourself to achieving your goal or is this -

Doug: No way. It's - I could just start learning - I got accepted graduate school and okay, I can start saying the specialty would be on computer systems design because they were actually building one and that's what they were teaching the courses. And most of it's hardware, because there were so little programming and people hadn't even yet quite invented an assembler, much less a compiler, if you know the difference of that.

Bob: Sure.

Doug: And the thing was going and we'd have debates about do you think that a computer will ever be able to operate at a million operations a second? Oh this was very questionable or something, but anyway, so I couldn't really talk about what I had in mind all through graduate school and then I was training. I was teaching; I really enjoyed teaching - teaching the junior class electrical engineering. But after about a year of that, I was told very clearly by a very friendly senior professor in economics or something that we'd made friends with socially and he just happened to ask me what I was interested in, so when I - telling him like this, he got more and more silent and finally he said, do you know how promotion is handled in universities?

So that still naïve country kid says well, I never thought about it. And so he explained peer review and that promotion is depending upon on how many high-quality papers you've gotten and the highest-quality journals and you don't get there unless they get peer reviewed by peers and such. So he says if you keep talking like this boy, peers will just jump this right away because it sounds so screwy. He says and so you'll just be an acting assistant professor forever, that's all. And all of a sudden I believed him, understood. So I left university.

And two other things I tried - one - when I was in the Navy, I'd been using equipment that was built by Hewlett-Packard, so I knew the story of them being formed down here and this was well before there was any Silicon Valley, I guess, but Hewlett-Packard were there, so I thought oh. So I went down and interviewed. Oh, they've - because of patents, inventions and stuff I'd done in my PhD research was totally something different. Oh, they offered me a job right away and that's great. Then after I'd gone through all that and everything and was driving home, I said, oops, wait a minute. So I stopped like in Redwood City and phoned back to the head of research, said, hey Barney, I was just thinking, I'm committed to really working and innovating and such as that with digital computers, etc, so I can only, if I've been assuming that you guys would get into the computer field pretty soon. Pause. Oh sorry, Doug; not a chance. I says, oh, sorry. I think I will not take your job because I'm committed to doing that.

So that I actually tried getting into Stanford, too. It's like I wrote a letter to the Dean of Engineering telling him how I can give courses in designing computers, etc and he wrote back and says well, thank you for your interest. He says, however, Stamford is a very small university and has to specialize in highly advanced academics sort of domains of interest. And since computers are only a service activity, we don't contemplate ever having courses in the design or use of computers.

Bob: Was that Fred Terman?

Doug: No, it was a guy who was very high quality guy etc, but that was the prevailing picture.

Bob: Yeah.

Doug: So when I said well, I'll apply to SRI 'cause they had a project to build a computer system to support Bank of America's accounting and so they would be in there, but one of my friends who'd gotten out of Berkeley a few years before was working there, was the first one I saw when I came in on interview day and he says he'd never heard - because I've never been able to talk much at Berkeley about this - said he heard what I was interested in and he listened to me and he says, well, have you told anybody else all this yet? No. Well, look, not to be negative or something, but here's my advice. You tell them all about the patents and the research you've been doing like and don't tell them about this and I guarantee you'll get hired. But if you start talking about this, you probably won't. Oh.

So I just talked about the patents and I got hired. And they - I got told that you just wait. So well, okay. It was - I'd wait for the chances in the coming years to find out if I could interest research grantees, grantors, etc and like that one on scaling was the first one that I found and then I found one that okayed me to start writing something. So I got a chance to muscle along with that for a year and a half and finally produce the think piece in 1962. And I called it Augmenting the Human Intellect: A Conceptual Framework. And that's where I just sort of really pieced together that hey, it's capability you're after and you don't automate the things, you augment the human's capability in all these various ways, etc. And it made a marvelous sort of base for the whole strategy. But there -

Bob: How was that received?

Doug: Well, great big thundering.

Bob: Silence.

Doug: Right. And in fact then, ARPA, what's now DARPA, was starting their information processing techniques office and then - and the guy that was starting it - that they brought in to start it had been writing about man-computer symbiosis, etc. His orientation was strongly about AI, etc. But anyway, he actually gave me my kickoff grant. And then - oh that was exciting. But then I get called in by the man who ran my laboratory I was in like that, who told me that and he had been guided by the division meter and so on to. Well, that's very interesting. It's sort of - you keep talking like this and we're going to put John in charge of the project. Well, stutter, stutter. And John is a programmer and he just was very, very much that paradigms have passed and it just was a horrible year because when the guy from DARPA came by to visit some seven or eight months later, he called me up later and says what in the world. He says if my boss saw that result, they'd fire me. Now what happened? I tried to explain to him and boy, he was really pissed off.

Bob: So you went a decade from your epiphany, essentially keeping your light under a basket while you were preparing your skill set to do the work you really wanted to do.

Doug: Well, I was trying to do whatever I could do to keep writing. But also try to see where I could get it sold.

Bob: Exactly.

Doug: It was still two more years after that because there were several other things that were almost as bad as that that happened.

Bob: So it was a real uphill struggle.

Doug: Oh, just unbelievable.

Bob: And yet, in the '60's, you accomplished a great deal, so there must have been moment where things got a little bit easier. What - was there?

Doug: Well, yeah. Finally after the third shot, like in the third shot of getting something going where the first one was at - what that other guy had to do. The second one was something that was trying to build the system in a client server way of using a server in Los Angeles over the telephone down there and that was - that's computer wouldn't get working well. The third one was we had our own - and I could get enough to get a computer that's - desktop like this that would be - looked like a total toy compared to anything today - anything, your laptop. But it had enough disk memory and speed such that we could start building a system and I counted on our - three or four of us in the group, doing all of our work on that.

So then what happened is that other people in the institute started saying, oh, we always wanted to try using a computer interactively too, so they talked to my boss - was a different boss this time - and the institute had this internal R&D, which the institute would sort of pay people, time and such to try something that looked like a promising thing. So on IR&D, they gave access to my - that one computer to these other people to try what they want to try because you want to give them a chance and I was counting on it being what we could work with. So we ended up with 13 hours a week of time on that -

Bob: On your computer.

Doug: Right. And stuff. And so we - one of the things then was that was very frustrating. But it was just a sign of the kind of uphill struggle, just because what we were trying to do was just not discernable by other people at the time as being a real research.

Bob: I think that this little scale project that you did is interesting. If we could do back and you could explain that because it kind of predates Moore's Law and yet it's essentially the same thing, isn't it?

Doug: Pretty close.

Bob: Could you tell us how that came about?

Doug: Well, because when I'd worked in Ames Laboratory as helping keep the wind tunnels going, they'd explained to me I had been curious about how you scale and so I was conscious of scaling as a thing. But not too much so I got the chance to study about it and then really learned a lot about how the scale has affected and like the people that do dimensional scaling assessment. They came up with saying we think the tallest tree you'll ever find will be 200, 300 feet, I forgot which it was. And sure enough, the figure. And so when I got pretty much through this thing and I had a chance to give a presentation at a conference.

And so I had this kind of a thing to tell them - ask them. I said okay everybody, suppose this room and everybody and everything in it suddenly got 10 times bigger in every direction like this. Would you notice? See. Well, engineering guys look around like that and they said let's - he's going to be 10 times taller, but he's 10 times farther away, so visually, he'd be the exactly the same angle. And you know, you look around, you wouldn't notice any difference; you wouldn't tell the difference. And I said, well then, how much more would you weigh? Oh let's see. You're 10 times by 10 times by 10 times - you've got 1,000 times the volume, so you'd weight 1,000 times as much.

Gee, if you could just imagine. Okay, how much stronger would you be? Well, turns out the strength was proportional across section area of your muscles and bones, so you'd only be 100 times as strong. So it didn't take long for them so I could say that would be the substantive equivalent to your suddenly being 10 times heavier with the same strength. How heavy would you be? Well if you were 150 pounds, you'd be 1500 pounds. God, you're only as strong as you are now. There's no way you could stand up. Well the chair's the same thing about its strength. It couldn't carry you. So you'd be helpless.

Bob: But if you apply that same idea to the miniaturization of electronic components, it goes the other way, doesn't it?

Doug: Exactly. But the same thing that different phenomena in the there depend upon the linear length of something, the area, some volume, so these different phenomena that you've engaged in your device changed at these different rates. So most devices use decreased of size will get to a point where they'll stop functioning. But the thing is there are other phenomena that can be interrelated and as they change by their nature like that, you find if advantageously that the speeds of everything is going to go up. And you look like a squirrel sitting there with how quick it is and a squirrel is like say, it's six inches tall when it sits up. And somebody gets alerted and boom, it runs straight up a tree to maybe 25 feet out there, looking at you, not even breathing hard. So that's like 50 times its height in a few seconds. So could you run up 50 times your height in a few seconds?

Bob: Not any more.

Doug: Never anyway. Humans can do that. So just the speed and mobility really increases as you go down in size and the ability for something to fly gets up unavailable and all kinds of things change. So the phenomena that every - engineers could start looking about how could we use different phenomena at some small scale to work together to make a device. And it just - intuitively you say, oh, there's going to be all kinds of them down, down and as you go down in size, the speed goes up and the power consumption goes down, etc.

And so the fact that you can carry a little tiny tube like this and plug it into your computer that can store megabytes like this is because of that. And the way that computers just go up and up and up in megahertz and all of that and so then there's this thing of nanotechnology, which gets down to such a small scale that very basic thing and you start moving molecules around so you just know that the speed and the capacity of computing devices in the future is going to be limitless.

Bob: So you anticipated that computers were going to become much smaller and must faster and presumably cheaper and that that would - if you aimed further out, down the timeline, if you tried to anticipate where we would be at a certain point, with your research - was that what you were trying to do?

Doug: Oh, I was trying to help tell the world "Let's get ready to use it," 'cause the pictures we have now of what to do with it are just on a very primitive sort of level. So we're gonna have that capacity. Well, you look at - suppose you have that capacity to start harnessing it inside our communities and our cultures and it's just a hell of a lot to learn what you do with it and the skills that it would take and the way it would play a role and the key kind of thing I kept trying to talk about was this sort of thing of the Collective IQ essentially or the dynamic knowledge repository thing and the scale and capability of making that be such an effective dynamic part of country's life. I'd say things like, "Hey, documents, books are going to be out of date." Oh boy. What a thing to say in academia; they just turned and -

Bob: So they viewed knowledge as absolute and why would it be out of date because -

Doug: Well, not the knowledge, the form - the knowledge containers.

Bob: Oh.

Doug: See, the knowledge containers of a book.

Bob: The book itself, not the knowledge it contains.

Doug: Oh yeah. So that type of knowledge container will be obsolete and they say oh, but there's something about the feel of a book and I'll say don't you think the technology can provide it? Besides it gets a little dark, you'd like the font to be larger, you turn up the font. It refers to something else out there like that. Oh you can just go get it, you don't have to go hunting a library for it. And in the kind of thing that we'd learned about cross-referencing with such accuracy and the way you view it and -

Bob: Now there's something I need to understand. Between 1962, when you wrote your augment paper, and 1968 when you did your big demo in San Francisco, you accomplished a lot but what we've been hearing is a basically a litany of complaints that you were held back, that people didn't recognize, they urged you to be quiet.

Doug: I wish you wouldn't say it - complaints. This is just what life was like.

Bob: Yeah, it was what life was like. So obviously you overcame something there. There must have been something between '62 and '68 that allowed you to -

Doug: Well, we just happened to be able to get the money to do it.

Bob: It was the money.

Doug: Right.

Bob: Where did the money come from?

Doug: The biggest part of it came from what's now called DARPA. And then we got some from the Air Force Office of Scientific Research and we actually got some from NASA, I guess.

Bob: And what did they think they were buying?

Doug: You need to think about what the paradigm face is for somebody that's charged with being a - somebody that's given money in some agency to invest in what is the future. And the kind of culture they were in and what it is, so it's sort of like investing in a wild market. And so -

Bob: Well, they spread their money around - investing in a lot of things, I presume.

Doug: Right.

Bob: But what were they thinking they were buying from you? What was the vision that you sold them that they said yes, we'll put money into that.

Doug: Well, you're talking a lot like I was just describing to you and to some people it's let's give it try and others - and then as the field of office automation emerged and got stronger and also the field of artificial intelligence, which just really did a snow job in selling so they ended up getting hundreds of millions of dollars over the decades like that with almost no - none of the things that they were trying to say that they were going to be able to achieve could get there. So it's just sort of proceeded. But in the meantime though, they both were very strong factors in, as far as peers are out there going and what their attitudes were about what I was doing and they both went like this about what I was doing.

Bob: Once you finally had the money, or some money, and you could hire people and you could pursue your research, was it exciting?

Doug: Oh yeah. And it would develop its problems also but we could actually then list the system that I named an On Line System and we abbreviated NLS. People say wasn't that OLS, online? We had an Off Line System too.

Bob: And that would be OLS.

Doug: No, that'd be FLS.

Bob: FLS!

Doug: Anyway so NLS. And so it grew and I just get some very - programmers, the hackles would go up on some of the things that say to do, so like this. But it turned out that pretty soon they start living on it like that and then they'd get really excited.

Bob: So it become, actually, a computing environment that they would function in and that hadn't existed before, had it?

Doug: Right. So that's the whole idea. They can't do with without evolving so you build it and start working with it and using it. And then get everybody involved in the evolution.

Bob: And what could the NLS do? Or what could you do in it?

Doug: Well, that's what - we have a DVD copy of that 90-minute presentation that we put on and that was about a year after we finally got _____ something about that program manager saying everybody - lots of people were interested in time sharing and computers and so there'd be groups of meeting with them like this and the strongest core of that was at MIT, where the DARPA people put in quite a bit of money because their guy, Joe Licklider, came from Harvard/MIT. But he was giving me money too and one of the early times, just show an example is by proposing this kind of research, the kind that actually won me these awards I get now, see.

Bob: Yeah.

Doug: And so it turned out that the National Institutes of Health were getting into the business and giving grants for computer stuff, too. So I had a proposal and they - five guys came out to sit down, watch and they were all bright guys and they all got really interested. And so it looked great. They went back and mulled over and finally there was a letter that says, oh, it's a very exciting, interesting idea and it's going to require some complex computer programming. Well, since you're way out there in Palo Alto, where there aren't any complex computer programmers, guys who know that, we can't justify putting the money out there. So people had a hard time now believing that. But yeah, that's before there was anything like that.

Bob: That's funny. Organizations sometimes it's easier to say no than to say yes. You know.

Doug: Oh sure. But for them, they really thought about it. And then some years after this guy, Joe Licklider had been getting us money, and I was at some meeting back there in which there were a lot of computerniks etc and after the meeting, there were drinking sort of sessions, talking at us like this and I was talking with some guy who we didn't really know each other etc, but he was just talking away about Licklider. Well, Licklider was - it was one of his old buddies, see, and he was saying well, he's a bright guy and got all these ideas but for Christ sake, this one time he did, you know what? He plunked out a whole bunch of money to some guy way out in Palo Alto to do something. Well, who ever heard of anybody out there having any programming capabilities, I mean, hey Joe?

Bob: And yet Licklider wrote papers that actually were sort of in accord with some of the things that you had written.

Doug: That's why he was giving me support. And however, there came a day in which we found out that we had very different ideas about it.

Bob: Oh really. Tell us about that.

Doug: Well, the '68 presentation we kept evolving the system right on up into the '70's and in '74 I could really say okay, let's set it up where we can establish some real servers on the Arpanet and we could - we had a client server way of running our system at the time and the start - really getting users out there because if we don't get this evolution going, we can't just attempt these things without users. And so we set up the business and it actually kind of grew very well and I hired -

Bob: That was Tymshare?

Doug: Not yet.

Bob: Okay.

Doug: That was out of SRI. And so I developed not only a software development part of my lab, but an applications support system out of that and hired four or five bright, young women, liberal arts graduates from universities to say you guys are going to be the application support and trainers for this. I didn't want programmers. And boy, it turned out they just - they were so imaginative and had to work in such strange ways. If they'd been guys they would have had a harder time or if they'd been programmers. But somehow they just were out really helping and getting people by all kinds of problems and issues like that. It was just terrific, just so that we started going and we actually had the idea of I kept saying if you're going to have a knowledge workshop, which this is, it's really different than the past, you need the equivalent of a knowledge workshop architect. Somebody who understands the tools, the workflow, the kind of thing what people have to learn - had helps adjust the balance of its evolution of that thing.

And not a programmer. So we pushed each one of the organizations that was buying service from us to appoint somebody for that role. They did. So this was really great. And we really liked that. And so we had all that kind of stuff operating and then in 1957 I think it was -

Bob: No, not '57. You were in the '70's.

Doug: '77. Excuse me. Thank you. In '77 Licklider had sort of done his stint at ARPA and was back up in Cambridge area and they hired him back as a consultant to go around and talk to all of the principle investigators just to give a summary of what he felt the program had gotten to be. So he came out to see us at SRI, my big brother. It was just great to see him and so we sat together; I was in the conference room and he was there and I was starting telling him about drawing on the board and telling him, so I just got telling him about this great thing how the application support team had worked so well and I turned around and looked at him and he was sitting there, just looking like this.

I said Lick, what's the matter?

You just told me your system's no damn good.

Just dead serious. Well, what do you mean?

If it was any damn good, the computer system itself would know what the people need to learn and teach them; you wouldn't need any of these damn kids out there teaching them. That just tells me your system's no damn good. And he was unshakable in this - his belief in artificial intelligence stuff. I couldn't stop to ask to him well, do you know any systems that do that yet or something? So it was just like this.

Bob: The light went from on to off.

Doug: Yep. So within months we were out of - and then what also then really killed us was our applications for research, renewal, etc go in and what we learned later was they get reviewed by peers, Office Automation types, AI types, both of whom would say hey, that's hopelessly hard to learn. Office automation - the real users are secretaries - it's got to be that easy. I could try to say the real user is tomorrow's knowledge worker, but the AI people say the computer's going to do it again.

Bob: So there is no user in their view.

Doug: Oh yeah. AI people, yeah there were users, but the computer's going to be so smart, it'll teach the user what the user has to know all the time and adapt it and stuff. And none of that's ever shown up and with that, we were just totally our research money ran out.

Bob: What was the relationship between your lab at SRI and the computer science lab at Xerox Park?

Doug: Pretty much alienation. They didn't seem to accept what we did, that quite a few of my people went over there and one of the natural things "unnatural" something that happened is that there quite a few - quite often somebody in my lab would really say we ought to really build this and go this and they'd be just very turned on, excited and I'd say, no with my framework and the strategy, we need it to go this way and I just had to say no, you know. And at some points, the boss guy above would say the policies at SRI are the researchers needed to decide which.

Well, I thought I was a researcher. I had gotten the money to pull it together, but they made me let some of those people go their directions, which was just very painful. There got to be enough dissension. It's like one time I learned that all the programmers were having secret meetings to decide. Since we're the programmers, we program the thing; we ought to be the ones that decide what it should do and not part of how the evolution would go. And it was very stressful but by then I'd really started getting to realize that paradigms are the issue and that I had no way of managing the paradigm evolution among the people and just moved.

So that's when things set down and that then we got a chance to sell off the actually remote users support service, the Tymshare and it - Tymshare had said, well, we'll take whoever wants to come and work with this - they assumed everyone else would go to Xerox, but Xerox didn't want me. And so I showed up with them and that - and it was then slow things because they were very totally interested in business and after a few months, they called me in to say, we understand you've been talking to the user organizations. Oh yeah. It's about how the evolution is going. He said, well, look; we want to tell you some of the realisms about business. He said, you tell them like that and they'll just want us to improve and change the thing and that's not the way you run a profitable business. So we don't want you talking to the customers. That just - a lot of things that are real life evidence about the paradigms and if they can't start evolving appropriately and -

Bob: What are your goals today?

Doug: Let's see, I've worked on a lot more about the whole strategies and realizing that you have to accept the paradigm things so part of what you have to help is evolve the paradigm and because of the scale of how many organizations and countries have to change, they're going to change and work together and so on that you need a real strategic way in which practically you can start facilitating the evolution. And so I've worked out kind of how that can do and where best to start, etc and that's some innovations to the technology that will help that sort of facilitated evolution happen and a lot of targets for the evolution. And I'm looking for support.

Bob: Wow. Do you have a white paper or a document that we can put on the website and that people can refer to?

Doug: It's in pieces.

Bob: Well, we'll get it together.

Doug: All right. One of the problems is I don't really know how to make a document such that will get it across. See, like there's quite a complete publication from 12 years ago that the whole picture's in there but if I just get no dialog, no reaction at all. And so I give these presentations and I've been trying to facilitate meetings of people that would get the dialog going, questioning and answering and all to sort of get it so everybody there finally said, yes, oh all of us seem to be - he doesn't, he doesn't, he doesn't so on seem to be how understanding what your picture is and I keep saying I don't need you to say you believe it, I just - you understand it. And so far, that stuff hasn't been able to happen. And so before that happens, it's pretty hard because people enthusiastically want to help you and they'll start charging off on that direction.

Bob: Okay. I think we're done.

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