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Interviewer: ALAN, WHAT DO YOU THINK ABOUT THE FIRST COMPUTERS WERE LARGE EXPENSIVE MACHINES THAT HAD BEEN BUILT TO DO CALCULATIONS. 
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Interviewer: HOW DID PEOPLE THINK ABOUT THIS NEW TECHNOLOGY?
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Kay: Well, I think that some people thought they were never going to get any smaller. 
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Kay: There were calculations about how many Empire State buildings you needed full of vacuum tubes to do this and that. 
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Kay: And other people at Bell Labs who had been working on the transistor had a sense that this could be used as a switch, cause AT&T wanted something to replace vacuum tubes. 
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Kay: And so I think there are several perceptions of how big the thing was going to be. 
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Kay: I think it wasn't until the sixties that people started thinking that computers could get quite small.
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Interviewer: PART OF THE PROBLEM WAS THE SIZE, THE OTHER PROBLEM WAS JUST WHAT IT WAS SUPPOSED TO BE FOR....
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Kay: Yeah I think that when they were doing ballistic calculations there was this notion that you would run a program for a very long time. 
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Kay: It was really after UNIVAC in the 1950s that people started thinking, "Oh, there, might have to do some programming." And people, most notably, Grace Hopper, very early on started thinking about higher level programming languages. 
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Kay: So that was sort of one, one flow. 
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Kay: And I think the other thing was the urgency of the Cold War got people thinking of air defense. 
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Kay: And so scientists at MIT started working on systems that could assess radar and show it to you on a display. 
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Kay: And those are the first computers that had displays and pointing devices.
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Interviewer: FOR THE MOST PART THOUGH THOSE WERE KIND OF EXCEPTIONS, CAN YOU DESCRIBE WHAT THE BATCH PROCESSING EXPERIENCE WAS LIKE, WHAT IT WOULD HAVE BEEN LIKE?
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Kay: Well, I always thought of it as something like a factory. 
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Kay: You have this very large thing and there are raw ingredients going in the front and there are some very complex processes that have to be coordinated, then sometime later you get what you were hoping for on the out of the rear end. 
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Kay: And you can think of them also as like a railroad, somebody else is deciding the schedules. 
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Kay: I can certainly remember having maybe one run a day, or two runs a day, and you could only get your results then, and you had to work around it and so forth. 
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Kay: And so it was very much of an institutional way of thinking about computing.
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Interviewer: DID THIS PUT MANY PEOPLE OFF COMPUTING?
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Kay: I don't think so. 
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Kay: I think you, you know the happiness is the how much expectations you know, the reality exceeds expectations. 
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Kay: I think that most people were happy, you know in the '50s there were still in business predominantly business computing was done with punch card machines. 
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Kay: And IBM was the company that made those punch card machines. 
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Kay: So there was an enormous disparity between what you could do with computers and what most people did.
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Interviewer: BUT STILL FOR MOST PEOPLE THE PHYSICAL SIZE AND APPEARANCE OF THE MACHINE WAS A COMPELLING THING AND THAT GAVE IT THIS MYTHOLOGY?
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Kay: Well, I think, yeah my feeling is, is that anything that is larger human scale invokes mechanisms concerned with religion so you have a priesthood with white coats, you know all the paraphernalia were there and some people thought it would take over the world and some people wanted it to take over the world, and some people were afraid it would take over the world, and none of those things happened. 
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Kay: But that was what it was when it was this large thing and, and towards the late '50s many people in different places started saying, "Well, this thing has the potential of being more like a partner maybe a complementary partner. 
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Kay: It can do some things that we can't do well and vice versa, so we should find some way of bringing it down to human scale.
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Interviewer: THE COMPLEMENT TO THE INDIVIDUAL?
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Kay: The partner to people, not so much directly connected to the institutions. 
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Kay: Although of course, the first way it was done using time-sharing the mainframe was still owned by the institution.
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Interviewer: OKAY NOW, OF THE PEOPLE, OF THESE SORT OF VERY EARLY VISIONARIES I MEAN YOU YOU'VE DIVIDED THEM INTO SORT OF TWO GROUPS, HAVEN'T YOU?
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Kay: Yeah.
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Interviewer: COULD YOU TALK A BIT ABOUT THAT?
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Kay: Which two groups? Give me a cue.
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Interviewer: WELL, ONE GROUP WAS THE ONES WHO WERE INTERESTED IN AMPLIFYING INTELLIGENCE, SORT OF...
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Kay: You know there are lots of lots of different groups... 
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Kay: Okay, must be okay because we're still rolling, right? So, well I think in the in the late '50s there were a variety of different conceptions of what you should do with it. 
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Kay: Some of those conceptions were had by the very same person. 
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Kay: So for instance, John McCarthy, who is a professor at MIT both wrote memos suggesting we should time-share the computer, and he also thought more into the future that we'd be all networked together, and there would be these huge information utilities it would be like our power and lighting utilities that would give us the entire wealth of the knowledge of man, and he suggested on that what we'd have to have is something like an intelligent agent. 
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Kay: An entity not maybe as smart as us, but an expert in finding things, and we would have to give it advice. 
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Kay: He called it the "advice-taker."
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Interviewer: TELL ME ABOUT TIME-SHARING BECAUSE OBVIOUSLY ONE THING PEOPLE WOULD SAY IS, "HOW COULD EVERYBODY HAVE THEIR OWN COMPUTER?"
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Kay: Well, I think that was it. 
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Kay: They cost several million dollars back then and people had been fooling around with things little bit like time-sharing before sort of the official invention of it at MIT. 
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Kay: And part of it was just to debug programs. 
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Kay: The idea is that debugging is one of the most painful processes. 
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Kay: Incidentally you probably know that the there was actually a bug. 
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Kay: The first bug was one found by it was a moth, I think found by Grace Hopper. 
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Kay: So it actually has an official, and a friend of mine, just recently was having trouble with his laser printer. 
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Kay: And nothing that they thought of could possibly work, and, and finally somebody decided to open it up and look in it, and what it was, was a mouse. 
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Kay: The mouse had moved in, it was nice and warm. 
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Kay: It had, on top of the circuit board had set up various, various places you know so it was like a real...and course nobody understood what it meant when it said that this guy's computer has a mouse problem. 
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Kay: Cause mice don't have problems. 
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Kay: So, you know. 
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Kay: So it's an ill wind that blows nobody good.
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Interviewer: TELL ME ABOUT THE BASIC CONCEPT OF TIME-SHARING. 
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Interviewer: WHAT WAS THE IDEA?
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Kay: Well, time, the idea was that when humans use computers the best way of having them use it, is instead of using all the power for five minutes a day, is to take those five minutes of computer power and spread it out over several hours. 
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Kay: Cause people are slow at typing, and when you're debugging you don't need to do long runs of things. 
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Kay: And what you want is lots of interaction, lots of finding out that you're wrong and this is wrong, you can make a little change and this is wrong. 
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Kay: So you want to go from something that requires enormous planning to something that is much more incremental. 
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Kay: And this is the urge that the people who developed time-sharing had.
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Interviewer: BUT HOW COULD YOU GIVE AN INDIVIDUAL ACCESS EXCLUSIVE ACCESS TO A COMPUTER?
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Kay: Well, you couldn't. 
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Kay: So the idea is that if the thing cost several million dollars as McCarthy pointed out one of the things that you could do is roll in one person's job and do it for a couple of seconds, then roll in another person's job and do it for a couple of seconds. 
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Kay: And if you had a fast enough disc for holding all of these jobs then you would be able to handle twenty, thirty or more at once and they wouldn't feel that the lag of a few seconds was going to hurt them.
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Interviewer: SO THE COMPUTER IS SWITCHING BETWEEN THE JOBS SO FAST, IS THAT THE WAY IT WORKS?
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Kay: Right, right. 
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Kay: Well, that's the way it's supposed to work. 
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Kay: And of course, the thing that drove personal computing in the '60s into existence was that it proved to be extremely difficult to get reliable response time.
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Interviewer: BUT THIS IS LIKE ONE OF THE EARLY IDEAS OF THE USER HAVING AN ILLUSION.
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Kay: Yes, indeed. 
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Kay: Right, in fact the best one of these was a system called JOSS at RAND Corporation in which the system was devoted entirely to running this single language. 
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Kay: That made things much better. 
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Kay: The language was designed for end users. 
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Kay: It was the first thing that effected people the way spreadsheets do today. 
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Kay: It was designed -- it had eight users on this 1950s machine, but the guy who did it, Cliff Shaw, was a real artist, and the feeling of using this system was unlike that of using anything else on a computer. 
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Kay: And people who used that system thought of wanting all of their computing to have the same kind of aesthetic, warm feeling that you had when using JOSS.
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Interviewer: IF YOU HAD TO LIST -- IF YOU WERE, I MEAN A VERY CLEAR THINKING PERSON BACK THEN IN THE LATE '50S, YOU KNEW EVERYTHING THEY WANTED COMPUTING TO BE, WHAT WOULD THEY HAVE, SMALL, INTERACTIVE, REALTIME...?
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Kay: Well, I think in the '50s the emphasis, you know these things go in waves, the emphasis in the '50s was first on being able to do things incrementally, second, people wanted to share, so the idea of electronic mail was very early at MIT, and at some point people started thinking that the form of inaction started to have a lot to do with how good you felt, and how puzzled you were and so forth. 
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Kay: The invention of computer graphics, modern computer graphics, by Ivan Sutherland in 1962 had a lot to do with people's perceptions. 
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Kay: Cause once you saw that you couldn't go back. 
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Kay: It established a whole new way of thinking about computer interaction, and to this day it has remained an inspiration.
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Interviewer: TELL ME ABOUT THAT PIECE OF WORK. 
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Interviewer: HE WAS A GRADUATE STUDENT, WASN'T HE?
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Kay: Yes, he had gone to Carnegie Tech, now Carnegie Mellon, and came to MIT to do his Ph.D. 
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Kay: work. 
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Kay: One of his advisors was Claude Shannon, and another one was Marvin Minsky. 
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Kay: And as he has told the story several times, is that they were then in just the early stages of Jack Licklider's dream to have the computer be a sort of a symbiotic partner. 
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Kay: And when he went out to Lincoln Labs people were starting about that, and there was a marvelous machine there called the TX-2. 
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Kay: This was one of the last computers in the US large enough to have its own roof, you know, it was one of these enormous machines originally built for the air defense system. 
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Kay: And Ivan made friends with people there and started thinking about something having to do with computer graphics. 
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Kay: This you know, the air defense system used displays for putting up radar plots and so forth. 
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Kay: And light guns were already around and so forth. 
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Kay: And so he started thinking about maybe doing a drafting system, and as I recall it one of his original reactions when seeing the kind of graphics you could put on a screen -- because the screens couldn't even draw lines. 
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Kay: When they put up a line it was put up with lots of individual dots. 
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Kay: And done fairly slowly, so it would flicker and it was pretty awful looking. 
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Kay: And Ivan at that point said the best words a computer scientist can ever say, which is, "What else can it do?" And so he got, in fact having the display not be great helped what he tried to do on it, because he started thinking of what was the actual power and value of the computer. 
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Kay: Now today we have a problem because the displays are good so our tendency is to simulate paper. 
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Kay: But what Ivan started thinking about, is what could the computer, what kind of value could the computer bring to the transaction so it would be even worth while to sit down and use such an awful looking display. 
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Kay: And the thing he came out with was that the computer could help complete the drawings, so you could sketch -- this is where the idea of Sketchpad -- you could sketch something in. 
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Kay: You could sketch in, if you were trying to make a flange, well you just put in the lines for the flange, and then you would tell Sketchpad to make all of these angles right angles. 
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Kay: And you could make these two things proportional to each other and so forth. 
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Kay: And Sketchpad would solve the problem and straighten out the drawing in front of your eyes into something that was more like what you wanted. 
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Kay: So that was a terrific idea. 
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Kay: And then he took it another step further, because he realized he could solve real world problems. 
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Kay: So you put a bridge into Sketchpad it'd never been told about bridges before but you could put bridges in and tell Sketchpad about pulling and pushing of things and hang a weight on the bridge and Sketchpad would, would generate the stresses and strains on the bridge. 
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Kay: So it was now acting as a simulation. 
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Kay: You put in an electric circuit. 
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Kay: Sketchpad had never heard about electric circuits before, but you could put in Ohm's law, and what batteries do, and it would in order to settle the constraints -- or one of the nicest things was you could put in mechanical linkages. 
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Kay: So you could do something like a reciprocating arm like on a locomotive wheel; for going from reciprocating to circular motion. 
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Kay: And Sketchpad's problem solver if it had a problem that it couldn't get an exact solution for, there wasn't just one solution, and of course there isn't for this. 
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Kay: What it would do is iterate through all the solutions, so it would actually animate this thing and right on the screen you would see this thing animating, it was the very thing that you were thinking of.
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Interviewer: AND THIS IS VERY EARLY, IT SOUNDS VERY MODERN.
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Kay: '62, yeah. 
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Kay: Well, you can't buy a system today that does all the things that Sketchpad could back then. 
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Kay: That's what's really amazing. 
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Kay: It had, the first system that had a window, first system that had icons. 
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Kay: Certainly the first system to do all of its interaction through the through the display itself. 
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Kay: And for a small number of people in this community, the Advance Research Projects Agency research community, this system was like seeing a glimpse of heaven. 
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Kay: Because it had all of the kinds of things that the computer seemed to promise in the '50s. 
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Kay: And practically everything that was done in the '60s in that community, and into the '70s, had this enormous shadow cast by Sketchpad, or you could maybe think of it better as a light that was sort of showing us the way.
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Interviewer: AND THAT'S ONE GLIMPSE OF HEAVEN, ANOTHER GLIMPSE OF HEAVEN I SUPPOSE IS THE WORK OF DOUG ENGELBART.
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Kay: Yes, and he was also funded by the Advance Research Projects Agency and his original proposal I think was also 1962. 
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Kay: 1962 is one of those amazing years. 
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Kay: And Engelbart had read about the Memex device that Vannevar Bush, who was President Roosevelt's science advisor and a former professor at MIT, he had written an article in 1945 called "As We May Think." And most of the article was devoted to predictions of the future and one of them was, he said that sometime in the future we'll have in our home a thing like a desk and inside the desk on optical storage will be the contents of a small town library, like 5,000 books. 
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Kay: There'll be multiple screens, there'll be pointing devices, and ways of getting information in, and pointing to things that are there and he said that you can form trails that will connect one piece of information to another. 
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Kay: He invented a profession called "Pathfinding" that there'd be people called Pathfinders who sold paths. 
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Kay: You could buy a path that would connect some set of interesting things to some other set of interesting things. 
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Kay: And so this is a complete vision in 1945. 
00:16:53.813 --> 00:16:56.098
Kay: And a lot of people read that. 
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Kay: I read it in the '50s when I was a teenager because I had seen it referred to in a science fiction story. 
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Kay: Engelbart had read it fairly early, when he was in military service. 
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Kay: And once you read that thing you couldn't get it out of your mind, because the thing that anybody who deals with knowledge would desperately like to have. 
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Kay: And so Engelbart in the early '60s started writing proposals, and he finally got ARPA interested in funding it and they started building a proposal of his. 
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Kay: And a couple of years later, 1964, he invented the mouse -- to have both a better pointing device than the light pen, and a cheaper one. 
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Kay: And they built a system that by 1968 was able to give a very large scale demonstration, to 3,000 people in San Francisco.
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Interviewer: AND YOU WERE THERE.
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Kay: I was there.
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Interviewer: TELL ME ABOUT IT.
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Kay: Well I had, I had seen the system beforehand, because of course I was a graduate student in this community. 
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Kay: But still even having seen the system, the scale of the demo and the impact it had, it was unbelievable. 
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Kay: I remember it started off, there was about 3,000 people in this auditorium. 
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Kay: It was at one of the, I was the Fall Joint Computer Conference, I think and all you could see on the stage was this figure with something in his lap and a box in front of him and a couple of things that looked like TV cameras around him. 
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Kay: And he had on a headset and he started talking he said, "I'd like to welcome you to our demonstration." All of a sudden his face appeared 20 x 30 ft wide on this enormous screen, because they borrowed one of the NASA... 
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Kay: one of the first one of the first video projectors. 
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Kay: On this, and they used this huge situation display, and then they, they used video editing so you could see while he was giving this demonstration what he was doing with his hands, with the mouse on the key set, what was going on, on the screen and so forth. 
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Kay: And that, that is video taped, I mean that is something that you can use for your--
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Interviewer: YOU WERE TALKING ABOUT DOUG, WHAT DID HE DEMONSTRATE, WHAT SORT OF THINGS DID HE SHOW YOU?
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Kay: Douglas, Douglas Engelbart he started off just showing us how you could point to things on the screen and indicate them and started off actually fairly, fairly simply just showing how you could look at information in various ways. 
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Kay: He showed something very much like HyperCard -- so he had a little map of how he was going to go home that night, how he was going to go to the library and the grocery store and the drug store and so forth. 
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Kay: You could click on each one of those things and it would pop up and show him what he had to get there. 
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Kay: And what he demonstrated were the early stages of what we call hypertext today. 
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Kay: Lots of response in the system. 
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Kay: One of the big shockers was midway through the thing he started doing some collaborative work, and all of a sudden you saw the, in an insert on the screen, you saw the picture of Bill Paxton who was 45 miles away down in Menlo Park, live. 
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Kay: Both of them had their mouse pointers on the screen and they were actually doing the kinds of things that people still dream about today. 
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Kay: So this was a complete vision. 
00:20:31.654 --> 00:20:38.295
Kay: And I think of it as the vision of what we today call personal computing or desktop computing. 
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Kay: Except for the fact that the processor was a big time-shared computer, all of the paraphernalia -- Engelbart used a black and white display, 19 inch display, using video to blow up a calligraphic screen and have a mouse. 
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Kay: If you looked at the thing today, you'd see something that looked like somebody's office that you could walk into. 
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Kay: And what remained was to do something about the the problems in response time and, and all that stuff. 
00:21:08.981 --> 00:21:14.223
Kay: And that was something that I had gotten interested in a few years before. 
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Kay: And the first machine that I did was a thing called the FLEX Machine and...
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Interviewer: JUST BEFORE WE GO INTO FLEX, TELL ME WHAT WAS THE REACTION LIKE AMONG THE COMPUTER COMMUNITY?
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Kay: Well, I didn't take a, in fact, I was actual as I recall I actually would rather, I had the flu or something, but I was determined to go see this thing. 
00:21:33.890 --> 00:21:40.855
Kay: ARPA had spent something like $175,000 on this demo and everybody in the ARPA community wanted to show up. 
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Kay: I recall that the, the crowd, you know he got a standing ovation and he won the best paper in the Fall Joint Computing Conference and so forth. 
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Kay: And what was even better is that he had bought up four or five terminals to the system and had them in a room and people could go in and actually learn to interact with the system a bit. 
00:22:02.401 --> 00:22:04.940
Kay: So it was a large scale demonstration. 
00:22:04.940 --> 00:22:15.875
Kay: I don't think that anybody has ever traced what people did in, over the next 15 or 20 years as a result of having been at that demonstration, that would be interesting.
00:22:15.875 --> 00:22:20.637
Interviewer: DOUG THOUGHT IT, HOPED IT WOULD CHANGE THE FACE OF COMPUTING AND IS VERY DISAPPOINTED THAT IT DIDN'T. 
00:22:20.637 --> 00:22:22.692
Interviewer: HE THINKS IT DIDN'T REALLY HAVE MUCH IMPACT.
00:22:22.692 --> 00:22:29.962
Kay: Well, I mean there are a couple of things that Doug, I mean we thought of Doug as Moses opening the Red Sea. 
00:22:29.962 --> 00:22:32.696
Kay: You know he was like a biblical prophet. 
00:22:32.696 --> 00:22:38.032
Kay: And like a biblical prophet he believed very much in his own particular vision. 
00:22:38.032 --> 00:22:41.768
Kay: And that vision was not a one, a 100 percent good idea. 
00:22:41.768 --> 00:22:47.437
Kay: One of the things that they neglected completely was the learnability of the system. 
00:22:47.437 --> 00:22:56.175
Kay: People who used the system were all computer experts who loved it, were willing to memorize hundreds of commands in order to be... 
00:22:56.175 --> 00:23:04.512
Kay: If you memorized hundreds of commands and you learned how to use the key set you could fly through this n-dimensional space. 
00:23:04.512 --> 00:23:10.715
Kay: It was quite exhilarating to watch people doing this and exhilarating to learn how to do it. 
00:23:10.715 --> 00:23:16.185
Kay: The problem with it though was that there were so many barriers towards learning. 
00:23:16.185 --> 00:23:20.520
Kay: And there were many other, many other things that were problems. 
00:23:20.520 --> 00:23:27.190
Kay: It will, it wasn't a particularly good simulation of paper, partly because he didn't want it to be. 
00:23:27.190 --> 00:23:39.730
Kay: And so the idea that there would be a transition period where you would be producing documents, of course, they printed documents out, but there was no notion of desktop publishing there. 
00:23:39.730 --> 00:23:42.598
Kay: The whole system was rather like a violin. 
00:23:42.598 --> 00:23:49.935
Kay: And if you were willing to learn how to become a violinist you could play incredible music through the thing. 
00:23:49.935 --> 00:23:55.805
Kay: And of course all of us were so completely sold on this system in the in the late '60s. 
00:23:55.805 --> 00:24:01.141
Kay: And the first machine that I, that I did, the FLEX Machine, was an echo of this.
00:24:01.141 --> 00:24:02.367
Interviewer: NOW THE FLEX MACHINE. 
00:24:02.367 --> 00:24:10.784
Interviewer: THE OTHER ELEMENT WHICH IS IN THIS, APART FROM THESE FANTASTIC SOFTWARE ACHIEVEMENTS OF SUTHERLAND AND ENGELBART IS OF COURSE THE SIZE OF THE MACHINE. 
00:24:10.784 --> 00:24:13.125
Interviewer: THERE WERE SOME PRECEDENTS, WEREN'T THERE?
00:24:13.125 --> 00:24:18.574
Kay: Oh yes, the first personal computer in my opinion, was the machine called the LINC. 
00:24:18.574 --> 00:24:21.946
Kay: If you include size as one of the important things. 
00:24:21.946 --> 00:24:27.719
Kay: Of course, you could say that the Whirlwind was a personal computer at MIT, or the TX-2. 
00:24:27.719 --> 00:24:40.495
Kay: Some people tried to get Ivan Sutherland to write a paper called "When There Was Only One Personal Computer." And that was him using Sketchpad on the TX-2, which is this thing bigger than a house. 
00:24:40.495 --> 00:24:50.678
Kay: But in 1962 Wes Clark did a machine in which part of the design parameter was it was small enough to look over when you're sitting down at a desk, you know. 
00:24:50.678 --> 00:24:56.580
Kay: So, it was not supposed to loom over you, it was something you could actually see over it. 
00:24:56.580 --> 00:25:00.018
Kay: And many important things were done on that machine. 
00:25:00.018 --> 00:25:07.476
Kay: In fact quite, quite a few hundred, if not a few thousand of them were built and used in the biomedical community. 
00:25:07.476 --> 00:25:17.983
Kay: It was designed for biomedical research, designed to be programmed by its who were not computer scientists, even designed to be built by non-computer scientists. 
00:25:17.983 --> 00:25:27.128
Kay: They used to have gatherings in the summertime where 30 people or so would come and build their own LINCs and then take them back and stuff. 
00:25:27.128 --> 00:25:29.009
Kay: It was great little machine. 
00:25:29.009 --> 00:25:33.095
Kay: It had a little display and display editors and, and so forth. 
00:25:33.095 --> 00:25:39.127
Kay: And so it was something that you could point to when you were trying to think of what to do. 
00:25:39.127 --> 00:25:41.397
Kay: And there were other small things. 
00:25:41.397 --> 00:25:46.845
Kay: There was a machine called the IBM 1130, which was really an abortion of a machine. 
00:25:46.845 --> 00:25:52.488
Kay: It was sort of a keypunch keyboard hooked to a, one of the early removable disc packs. 
00:25:52.488 --> 00:25:58.390
Kay: I mean this was a mess of a machine, but it was the size of a desk and you could sit down. 
00:25:58.390 --> 00:26:07.859
Kay: It wasn't, it wasn't designed really to be programmed except by storing programs on cartridge, very funny, you could only store data on the disc. 
00:26:07.859 --> 00:26:15.901
Kay: IBM forced you to put the programs on punchcards and that was the only way you could feed them in, it was really hilarious. 
00:26:15.901 --> 00:26:19.468
Kay: So there were lots different kinds of things like that.
00:26:19.469 --> 00:26:22.704
Interviewer: WHAT WERE YOU TRYING TO DO WITH FLEX?
00:26:22.704 --> 00:26:34.193
Kay: Well, I worked on this machine with a guy by the name of Ed Cheadle who was, he was trying to do, really trying to invent what today we would call personal computing. 
00:26:34.193 --> 00:26:54.280
Kay: And he had a little machine and he had a little Sony television set, and what he wanted was something for engineers that would allow them to -- he was an engineer -- and he wanted something that allow them to flexibly do calculations beyond the kinds of things that you do with a calculator. 
00:26:54.280 --> 00:26:58.339
Kay: So you should be able to program the machine in something. 
00:26:58.339 --> 00:27:01.572
Kay: You should be able to store the programs away. 
00:27:01.572 --> 00:27:04.530
Kay: You should be able to get it to do things. 
00:27:04.530 --> 00:27:11.547
Kay: And then I sort of came and corrupted the design by wanting it to be for people other than engineers. 
00:27:11.547 --> 00:27:21.315
Kay: I'd seen JOSS, and I'd also recently seen one of the first object-oriented programming languages, and I realized how important that could be. 
00:27:21.315 --> 00:27:33.285
Kay: And then Cheadle and I escalated -- the problem is that he and I got along really well, and so we escalated this design beyond the means of the time to build it practically. 
00:27:33.285 --> 00:27:43.879
Kay: But we did build one, and it had many things that people associate today, it fit on top of a desk -- special desks, because it weighed hundred of pounds. 
00:27:43.879 --> 00:27:52.547
Kay: But it, it had a fan likened to a 747 taking off because the integrated circuits back then had maybe 8 or 16 gates on a chip. 
00:27:52.547 --> 00:27:55.367
Kay: So this thing had about 700 chips in it. 
00:27:55.367 --> 00:27:58.669
Kay: It had a high-resolution, calligraphic display. 
00:27:58.669 --> 00:28:06.305
Kay: It had a tablet on it and it had a user interface that included multiple windows, things like icons and stuff. 
00:28:06.305 --> 00:28:25.842
Kay: But it was, it was rather like trying to assemble a meal, maybe make an apple pie from random things that you find in kitchen -- like no flour, so you grind up Cheerios, you know? You wind up with this thing that looks sort of like an apple pie, but actually it isn't very palatable. 
00:28:25.842 --> 00:28:32.652
Kay: So the result of this, this, this machine was a technological success and a sociological disaster. 
00:28:32.652 --> 00:28:42.833
Kay: And it was the, the magnitude of the rejection by non-computer people we tried it on, that got me thinking about user interface for the first time. 
00:28:42.833 --> 00:28:48.887
Kay: And I realized that what Cliff Shaw had done in JOSS was not a luxury, but a necessity. 
00:28:48.887 --> 00:28:53.015
Kay: And so it, it led to other, other ways of looking at things.
00:28:53.015 --> 00:29:03.987
Interviewer: SO IF WE GO BACK TO ORIGINALLY YOU WERE SAYING PEOPLE THOUGHT OF MAINFRAMES AS LIKE FACTORIES, RIGHT? ...THESE EARLY ATTEMPTS AT PERSONAL COMPUTERS, ARE WHAT, LIKE MODEL T....?
00:29:03.987 --> 00:29:13.921
Kay: Yeah, I think Engelbart -- I think one of the ways that, that we commonly thought about Engelbart's stuff was he was trying to be Henry Ford. 
00:29:13.921 --> 00:29:22.597
Kay: That the, you could think of the computer as a railroad and the liberating thing for a railroad is the personal automobile. 
00:29:22.597 --> 00:29:37.499
Kay: And Engelbart thought of what you were doing on his system as traveling, so you're moving around from link to link in the, in the hyperspace and he used terms like "thought vectors" and "concept space" and stuff. 
00:29:37.499 --> 00:29:45.266
Kay: Nobody knew what it meant, not sure he did either but it, it's, it was that kind of a, that kind of a metaphor.
00:29:45.266 --> 00:29:48.281
Interviewer: WHAT'S WRONG WITH THAT METAPHOR, ULTIMATELY?
00:29:48.281 --> 00:30:00.195
Kay: Well I don't think there is anything particularly wrong with it but it's it, when you're doing things by analogy, you always want to pick the right analogy because there's so many ways of making them. 
00:30:00.195 --> 00:30:10.686
Kay: And, the thing that was limiting about it when you apply it to humanity, as an example, is a car you expect to take a few months to learn how to do it, that was certainly true. 
00:30:10.686 --> 00:30:14.480
Kay: It's something that doesn't extend into the world of the child. 
00:30:14.480 --> 00:30:19.162
Kay: There's a whole bunch of things, but of course we didn't think of it that way. 
00:30:19.162 --> 00:30:25.800
Kay: We thought of the car as one of the great things of the 20th century and it changed our society and everything. 
00:30:25.800 --> 00:30:30.305
Kay: So, we were, we were definitely, definitely using that as a, as a metaphor. 
00:30:30.305 --> 00:30:40.796
Kay: And, in fact the thing that changed my mind had nothing to do with rejecting the car as a metaphor, it was finding a better metaphor that, one that was completely possessed me. 
00:30:40.796 --> 00:30:44.412
Kay: And that came about from seeing a, quite a different system. 
00:30:44.412 --> 00:30:47.435
Kay: I had called the FLEX machine a personal computer. 
00:30:47.435 --> 00:30:50.102
Kay: I think that was the first use of that term. 
00:30:50.102 --> 00:31:04.268
Kay: While I was trying to figure out what was wrong with it I happened to visit RAND Corporation over here in Santa Monica and saw sort of a follow-on system to JOSS that they had done for their end users who were people like RAND economists. 
00:31:04.268 --> 00:31:07.113
Kay: These people loved JOSS but they hated to type. 
00:31:07.113 --> 00:31:13.514
Kay: And so, in the same year the mouse was invented, the RAND people had invented the first really good tablet. 
00:31:13.514 --> 00:31:24.361
Kay: It was a high-resolution thing and they decided that the thing to do was to get rid of keyboards entirely, and so the first really good hand character recognizer was developed there. 
00:31:24.361 --> 00:31:29.458
Kay: And they built an entire system out of it called GRAIL, for GRAphical Input Language. 
00:31:29.458 --> 00:31:31.296
Kay: So there's no keyboard at all. 
00:31:31.296 --> 00:31:34.556
Kay: You interacted directly with the things on the screen. 
00:31:34.556 --> 00:31:36.215
Kay: You could move them around. 
00:31:36.215 --> 00:31:43.802
Kay: If you did a, a square on the machine, if you drew a square, it recognized you were trying to draw a square, it would make one. 
00:31:43.802 --> 00:31:56.842
Kay: If you put in your hand printed characters it would recognize them and straighten them up and the system was designed for building simulations of the kinds that, that economists and other scientists would like to build. 
00:31:56.842 --> 00:32:01.583
Kay: And using this system was completely different from using the Engelbart system. 
00:32:01.583 --> 00:32:10.830
Kay: And this system, it felt like you were sinking your fingers right through the glass of the display and touching the information structures directly inside. 
00:32:10.830 --> 00:32:18.832
Kay: And if what Engelbart was doing was the dawn of personal computing, what the RAND people were doing was the dawn of intimate computing.
00:32:18.832 --> 00:32:24.373
Interviewer: AND IN INTIMATE COMPUTING YOU FORGET THAT IT'S A MACHINE AND YOU THINK OF IT MORE AS A MEDIUM.
00:32:24.373 --> 00:32:41.390
Kay: Yeah, you start...and, one of the things that completely took hold of me in using the GRAIL system was it felt more like a musical instrument than anything because a musical instrument is something that -- most musicians don't think of their instruments as machines. 
00:32:41.390 --> 00:32:51.778
Kay: And it's that closeness of contact, the fitness that you're directly dealing with content more than the form of the content that, that possessed me very strongly. 
00:32:51.778 --> 00:32:56.304
Kay: And I saw, that was in 1968 as well, and I saw another several things. 
00:32:56.304 --> 00:33:09.815
Kay: I saw Seymour Papert's early work with LOGO for, here were children writing programs and that happened because they had taken great care to try and combine the power of the computer with an easy to use language. 
00:33:09.815 --> 00:33:22.753
Kay: In fact they used the RAND JOSS as a model and used the power of LISP which had been developed a few years before as a an artificial intelligence language, put them together and that was the early LOGO. 
00:33:22.753 --> 00:33:29.446
Kay: And to see children, confidently programming, just blew out the whole notion of the automobile metaphor. 
00:33:29.446 --> 00:33:33.142
Kay: And the thing that replaced it was that this is a medium. 
00:33:33.142 --> 00:33:35.118
Kay: This is like pencil and paper. 
00:33:35.118 --> 00:33:46.909
Kay: We can't wait until the kids are seniors in high school to give them driver's ed on the thing, they have to start using it practically from birth the way we, they use pencil and paper. 
00:33:46.909 --> 00:33:55.449
Kay: And it was destined not to be packaged on the desktop, because we don't carry our desks with it- It had to be something much smaller. 
00:33:55.449 --> 00:34:00.548
Kay: And that was when I first started seriously thinking about a notebook computer. 
00:34:00.548 --> 00:34:24.385
Kay: And of course the, the first thing I, I wanted to know after deciding that it had to be no larger than this was when would that be possible, if ever? And, so I started looking at what the integrated circuit people were doing, Gordon Moore and Bob Noyce and stuff and there were these nice projections that they, as confident physicists had made, about where silicon can go. 
00:34:24.385 --> 00:34:31.842
Kay: And what's, what's wonderful is, these projections have only been off by a few percent now more than 20 years later. 
00:34:31.842 --> 00:34:32.670
Kay: And those... 
00:34:32.670 --> 00:34:38.853
Kay: and of course I was very enthusiastic, I would believe anything that was in the right direction. 
00:34:38.853 --> 00:34:54.914
Kay: So I took this hook, line, and sinker and said, - okay, 20 years from now, we'll be able to have notebook size computer that we can not only do all the wonderful things on computers, we can do mundane things to, because that's what paper is all about. 
00:34:54.914 --> 00:35:00.650
Kay: You can write a Shakespearean sonnet on it, but you can also put your grocery list on it. 
00:35:00.650 --> 00:35:20.663
Kay: So one of the questions I asked back in 1968 is, - what kind of a computer would it have it to be for you to do something so mundane as to put your grocery list on it, be willing to carry it into a supermarket and be willing to carry it out with a couple of bags of groceries? There is nothing special about that. 
00:35:20.663 --> 00:35:22.320
Kay: You can do it with paper. 
00:35:22.320 --> 00:35:27.801
Kay: So the, the question is -- see the question is, not whether you replace paper or not. 
00:35:27.801 --> 00:35:32.071
Kay: The question is whether you can cover the old medium with the new. 
00:35:32.071 --> 00:35:39.210
Kay: And then you have all these marvelous things that you can do with the new medium that you can't do with the old.
00:35:39.210 --> 00:35:43.702
Interviewer: MANY PEOPLE FIND THE IDEA OF A MEDIUM A TRICKY CONCEPT. 
00:35:43.702 --> 00:35:50.442
Interviewer: IN THE SENSE YOU WERE TALKING ABOUT WRITING AND SO FORTH OR MUSIC, WHAT DO YOU MEAN?
00:35:50.442 --> 00:36:04.552
Kay: Well, I think most of my thoughts about media were shaped by reading McLuhan which not everybody agrees with but one of his points is that the notion of intermediary is something that is not added on to humans. 
00:36:04.552 --> 00:36:06.291
Kay: It's sort of what we are. 
00:36:06.291 --> 00:36:09.434
Kay: We deal with the world through intermediaries. 
00:36:09.434 --> 00:36:13.246
Kay: We deal with our, we can't fit the world into our brain. 
00:36:13.246 --> 00:36:17.861
Kay: We don't have a one to one representation of the world in our brain. 
00:36:17.861 --> 00:36:28.026
Kay: We have something that is an abstraction from it and so we, the very representations that our mentality uses to deal with the world is an intermediary. 
00:36:28.026 --> 00:36:31.103
Kay: So we kind of live in a waking hallucination. 
00:36:31.103 --> 00:36:33.911
Kay: And, we have language as an intermediary. 
00:36:33.911 --> 00:36:36.319
Kay: We have clothes as an intermediary. 
00:36:36.319 --> 00:36:59.860
Kay: So this, this whole notion of what we think of as technology, could also be replaced by the word "medium." And I think there's a, even though media has this connotation of, you know, the news business and stuff like that, I think it's an awfully good word because it, because it gives us this notion of something being between us and direct experience.
00:36:59.860 --> 00:37:09.364
Interviewer: NOW, OF THOSE MEDIA, WRITING AND PRINTING OBVIOUSLY AS A MEDIA WE CAN ALL THINK ABOUT HAVE GREAT POWER, AND MUSIC AS WELL. 
00:37:09.364 --> 00:37:11.914
Interviewer: WHAT DOES THAT MAINLY CONSIST OF?
00:37:11.914 --> 00:37:24.490
Kay: Well, I think that, you know, the trade off with, with using any kind of intermediary is that any time you put something between you and direct experience you're alienating a bit. 
00:37:24.490 --> 00:37:29.381
Kay: And, what you hope to get back from it is some kind of amplification. 
00:37:29.381 --> 00:37:43.005
Kay: Various people who have studied evolution talk about the difference between the direct experience you get from kinesthetically touching something to the indirect experience you get of seeing it. 
00:37:43.005 --> 00:37:45.939
Kay: And one is less involving than the other. 
00:37:45.939 --> 00:37:52.995
Kay: The seeing is a good one because it means you don't have to test out every cliff by walking over it. 
00:37:52.995 --> 00:37:57.397
Kay: And so there's an enormous survival value about stepping back. 
00:37:57.397 --> 00:38:12.697
Kay: To have a brain that can plan and envision things that might happen, whether as images or even more strongly in terms of symbols, is of tremendous survival value because it allows you to try out many more alternatives. 
00:38:12.697 --> 00:38:23.456
Kay: And so as the existentialists of this century have pointed out that the, we have gained our power over the world by, at the cost of alienating ourselves. 
00:38:23.456 --> 00:38:24.993
Kay: So the thing that we--
00:38:25.211 --> 00:38:29.516
Interviewer: ...A COMPUTER IS ANYTHING BUT A MACHINE IN A CERTAIN WAY. 
00:38:29.516 --> 00:38:31.594
Interviewer: WHY SHOULD THAT BE A MEDIUM?
00:38:31.594 --> 00:38:38.984
Kay: Well, I think, well, I think machine is a word that has a connotation that's unfortunate. 
00:38:38.984 --> 00:38:51.465
Kay: Yeah, maybe what we should do is either elevate what we think of when you say machine, you know mechanism, kind of thing or maybe use a different word. 
00:38:51.465 --> 00:38:55.652
Kay: To most scientists, machines are not a dirty word. 
00:38:55.652 --> 00:39:07.558
Kay: Because we, one of the ways we think about things even in biology these days is that what we are is an immense, immensely complicated mechanism. 
00:39:07.558 --> 00:39:23.159
Kay: That's not to say that it's predictable in the sense of free will because there's this notion now people are familiar with what's called chaotic systems, systems that are somewhat unstable. 
00:39:23.159 --> 00:39:27.182
Kay: There's a lot of instability and stuff built in. 
00:39:27.182 --> 00:39:42.783
Kay: It's a little more stochastic in a way, but the idea that there are things operating against each other and they make larger things and those things are part of larger things, and so forth. 
00:39:42.783 --> 00:39:49.270
Kay: To most scientists it seems like a beautiful thing, it's not a derogatory term.
00:39:49.269 --> 00:40:02.134
Interviewer: I THINK IT'S ALSO THAT MOST MACHINES WERE BUILT TO DO USEFUL WORK, BUT THIS MACHINE IN PROCESSING INFORMATION HAS PROPERTIES WHICH ARE SORT OF LINGUISTIC AS WELL AS...
00:40:02.134 --> 00:40:08.545
Kay: Yeah, well I think the connotation of machine is something that has to do with physical world. 
00:40:08.545 --> 00:40:22.989
Kay: Most people who most people haven't learned mathematics, have never encountered the notion of an of an algorithm, which is a process for producing -- you could of your moving around physical things called symbols. 
00:40:22.989 --> 00:40:29.806
Kay: I mean something physical is always being moved around, that's the way scientists look at the world. 
00:40:29.806 --> 00:40:46.882
Kay: And it's the real question is is this a trivial example of it or is this an unbelievably interesting example of it? So flower is a very interesting example of a machine, and a lever is a somewhat trivial and like more understandable notion of a machine.
00:40:46.882 --> 00:41:00.898
Interviewer: NOW THESE MACHINES CAN MOVE AROUND SYMBOLS PRESUMABLY, LIKE THE ELECTRONIC VOLTAGES OR WHATEVER, SO FAST THAT THEY CAN DYNAMICALLY SIMULATE VIRTUALLY ANYTHING YOU WANT...
00:41:00.898 --> 00:41:02.312
Kay: Lots of things, yeah. 
00:41:02.312 --> 00:41:07.198
Kay: One way to think of it is the, a lot of the what a computer is is markings. 
00:41:07.198 --> 00:41:18.319
Kay: And just as you it doesn't matter whether you make the markings for a book on metal or paper or you make them in clay, all kinds of ways of making the equivalent of a book. 
00:41:18.319 --> 00:41:30.534
Kay: The main thing about a marking is you have to have some way of distinguishing from other markings, and once you've got that then they can act as carriers of different kinds of descriptions. 
00:41:30.534 --> 00:41:38.570
Kay: And the range of the markings that you can have in a book, and the range of markings you can have in a computer are the same.
00:41:38.570 --> 00:41:42.632
Interviewer: SO LIKE IN A COMPUTER IT STARTED WITH PUNCH CARDS.
00:41:42.632 --> 00:41:45.119
Kay: Yeah, it doesn't matter what it is. 
00:41:45.119 --> 00:41:52.094
Kay: You can make, there's a wonderful computer built out of Tinker Toy in the computer museum of Boston. 
00:41:52.094 --> 00:41:54.581
Kay: It was done some MIT grad students. 
00:41:54.581 --> 00:41:56.860
Kay: You can make it out of anything. 
00:41:56.860 --> 00:42:12.399
Kay: And so that's one set of ideas, that is, the representational properties of things are very very much like a book, but then the computer has this even more wonderful thing, is that it's a book that can read and write itself. 
00:42:12.399 --> 00:42:15.161
Kay: And moreover it can do it very quickly. 
00:42:15.161 --> 00:42:20.825
Kay: So it has this self-reflexivity that you usually only find in biological systems. 
00:42:20.825 --> 00:42:25.245
Kay: And it can carry through these descriptions very, very rapidly. 
00:42:25.245 --> 00:42:42.165
Kay: Okay and then you get, then everything that's the big nirvana experience where you suddenly realize "Holy Smokes this thing is a pocket universe." And it has a nice complementary role to the way we deal with our physical universe as scientists. 
00:42:42.165 --> 00:42:53.768
Kay: The physical universe especially in the nineteenth century was thought that it was put there by God and it was the job of scientist to uncover this glorious mechanism. 
00:42:53.768 --> 00:43:09.515
Kay: So in the computer what you do is you start off with a theory, and the computer will bring that theory to life so you can have a theory of the universe that is different than our own, like it has an inverse cube law of gravity. 
00:43:09.515 --> 00:43:20.427
Kay: And you can sit down and in not too much time you can program up a simulation of that and discover right away that you don't get orbits anymore with planets. 
00:43:20.427 --> 00:43:31.201
Kay: And that's curious and a little more thinking and deeper delving will soon make you discover that only the inverse square law will actually give you orbits.
00:43:31.201 --> 00:43:35.833
Interviewer: THAT'S CURIOUS, BUT THE OTHER WAY YOU PUT IT ONCE IS YOU COULD INVENT A UNIVERSE WITH NO GRAVITY, RIGHT?
00:43:35.833 --> 00:43:52.269
Kay: Yes, and in fact, I think, it's again the difference between a physical book which when, you can drop it and it will fall down to the floor, and the story that's in the book that could be about a place that has no gravity, like out in space. 
00:43:52.269 --> 00:44:03.272
Kay: And the computer is at once a physical thing and the stories that it holds don't have to have anything to do with the physical universe its components reside in. 
00:44:03.272 --> 00:44:13.528
Kay: So, in other words you can lie, both with books and with computers -- and it's important because if you couldn't lie you couldn't get into the future. 
00:44:13.528 --> 00:44:18.826
Kay: Because we are living a world of things that were complete lies 500 years ago.
00:44:18.826 --> 00:44:27.906
Interviewer: NOW THE THING ABOUT THE COMPUTER AS WELL, APART FROM BEING DYNAMIC, IT'S ABILITY TO SIMULATE MEANS THAT IT CAN EMBODY ALL OTHER MEDIA. 
00:44:27.906 --> 00:44:30.463
Interviewer: IT IS THE FIRST META-MEDIUM, ISN'T IT?
00:44:30.463 --> 00:44:43.616
Kay: Yes, yes, I called it the first meta-medium in the, in the early '70s when I was trying to explain what it was as being distinct from big mainframes with whirling tape drives, that... 
00:44:43.616 --> 00:44:51.121
Kay: The physical media that we have like paper and the way it takes on markings are fairly easy to simulate. 
00:44:51.121 --> 00:45:00.843
Kay: The higher the resolution display you get, the more you can make things look like a high-resolution television camera looking at paper. 
00:45:00.843 --> 00:45:08.421
Kay: That was one of the things that we were interested in at at Xerox PARC was to do that kind of simulation. 
00:45:08.421 --> 00:45:13.567
Kay: And there are deeper simulations than the simulation of physical media. 
00:45:13.567 --> 00:45:17.427
Kay: There's the simulation of physical processes, as well.
00:45:17.427 --> 00:45:33.917
Interviewer: NOW, IF THEN -- THIS IS A PRETTY MIND-BLOWING, BECAUSE THE COMPUTER THEN IS NOT JUST IMPORTANT AS A VERSATILE TOOL, A NEW MACHINE, WHAT WE'RE TALKING ABOUT IS SOMETHING OF THE OF THE GRAVITY OF THE INVENTION OF WRITING OR PRINTING. 
00:45:33.917 --> 00:45:39.034
Interviewer: IN POPULAR TERMS, WE'RE TALKING ABOUT SOMETHING REALLY PRETTY FANTASTIC.
00:45:39.034 --> 00:45:39.500
Kay: Right. 
00:45:39.500 --> 00:45:43.157
Kay: It's sort of sneaking its way in the way the book did. 
00:45:43.157 --> 00:46:19.063
Kay: The the Catholic Church didn't, I think the Catholic Church thought that the book might be a way of getting more bibles written in Latin, and so at the by the time they started thinking about suppressing it, it was too late because of course, you could print all these other things, and all of a sudden you go from having 300 or 400 books in the Vatican Library that, in the year 1400 to something 100 or 150 years later where there are some 40,000 different books in circulation in Europe and 80 percent of the population could read them. 
00:46:19.063 --> 00:46:27.840
Kay: And so all of a sudden you have something totally at odds with most ways of dealing with religion, which is multiple points of view.
00:46:27.840 --> 00:46:31.722
Interviewer: WHAT CAN WE LEARN, LOOKING AT THE HISTORY OF THE BOOK. 
00:46:31.722 --> 00:46:36.098
Interviewer: CLEARLY IT TOOK A LOT LONGER TO HAPPEN, RIGHT, FOR ONE THING. 
00:46:36.098 --> 00:46:40.969
Interviewer: BUT WHAT WERE THE STAGES IT HAD TO GO THROUGH TO GET TO THAT POINT? .
00:46:40.969 --> 00:46:46.972
Kay: Well, I think in doing in doing these analogies, analogies can be suggestive, you know. 
00:46:46.972 --> 00:46:54.613
Kay: And of course, the the amount that analogy carries through from one place to another depends on lots of things. 
00:46:54.613 --> 00:47:05.938
Kay: I happen to like the analogy to the book, quite a bit because you have several stages, you have the invention of writing, which is a huge idea, incredibly important. 
00:47:05.938 --> 00:47:10.578
Kay: And the difference between having it and not having it is enormous. 
00:47:10.578 --> 00:47:18.423
Kay: The difference between having computers even if they're big, just big mainframes and not having them, is enormous. 
00:47:18.423 --> 00:47:21.766
Kay: There're just things you cannot do without them. 
00:47:21.766 --> 00:47:38.686
Kay: Then the next stage was the Gutenberg stage and Gutenberg just as McLuhan liked to say, "when a new medium comes along it imitates the old." So Gutenberg's books were the same size as these beautiful illuminated manuscripts that were done by hand. 
00:47:38.686 --> 00:47:45.372
Kay: And big like this and in the libraries of the day, back then the books generally weren't shelved. 
00:47:45.372 --> 00:47:51.921
Kay: There were so few books in a given library that they were actually had their own reading table. 
00:47:51.921 --> 00:47:54.650
Kay: And if you look at woodcuts of the day. 
00:47:54.650 --> 00:47:58.471
Kay: It looks for all the world like a time-sharing bullpen. 
00:47:58.471 --> 00:48:04.679
Kay: You know, you go into the library, there's one library in Florence that's set up that way. 
00:48:04.679 --> 00:48:13.548
Kay: You go over to the table that the particular book is at, they are chained in because they were too valuable, they were priceless. 
00:48:13.548 --> 00:48:18.802
Kay: And Gutenberg imitated that, but of course he could produce many more books. 
00:48:18.802 --> 00:48:29.786
Kay: But he didn't know what size they should be, and it was some decades later that, Aldus Manutius was a Venetian publisher decided that books should be this size. 
00:48:29.786 --> 00:48:37.495
Kay: He decided they should be this size because that was the size that saddle bags were in Venice in the late 1400s. 
00:48:37.495 --> 00:48:41.793
Kay: And the key idea that he had was that books could now be lost. 
00:48:41.793 --> 00:48:46.637
Kay: And because books could now be lost, they could now be taken with you. 
00:48:46.637 --> 00:48:52.300
Kay: And they couldn't be like this, they had to be something that was a portable size. 
00:48:52.300 --> 00:48:57.416
Kay: And I think in very important respects where we are today is before Aldus. 
00:48:57.416 --> 00:49:02.670
Kay: Because this notion that a computer can be lost is not one that we like yet. 
00:49:02.670 --> 00:49:05.126
Kay: You know, we protect our computers. 
00:49:05.126 --> 00:49:07.786
Kay: We bolt them to the desk and so forth. 
00:49:07.786 --> 00:49:09.356
Kay: Still quite expensive. 
00:49:09.356 --> 00:49:12.698
Kay: They'll be really valuable when we can lose them.
00:49:12.699 --> 00:49:17.463
Interviewer: THE OTHER POINT ABOUT THE POINT OF LITERACY, IS ALSO WELL TAKEN THERE. 
00:49:17.463 --> 00:49:23.436
Interviewer: WHILE THERE ARE VERY, WHILE THERE ARE NO BOOKS TO READ I ASSUME THERE'S NO POINT IN IT...
00:49:23.436 --> 00:49:30.045
Kay: Right, well if reading and writing is a profession you don't have the notion of literacy and illiteracy. 
00:49:30.045 --> 00:49:40.368
Kay: Like, there's no word in our language that stands for "il-medicine." There is medicine, which is practiced by professionals, and there is no notion of il-medicine. 
00:49:40.368 --> 00:49:54.341
Kay: Now if we all learned medicine, if that were part of, and it may be some day that staying healthy might be something that becomes an important part of everyone's life then there'll be a notion of medicine and il-medicine. 
00:49:54.341 --> 00:50:01.831
Kay: And so it wasn't until there was a potential for the masses to read that we had the notion of literacy and illiteracy. 
00:50:01.831 --> 00:50:06.362
Kay: And to me literacy has three major parts that you have to contend with. 
00:50:06.362 --> 00:50:16.181
Kay: One is you have to have a skill to access material prepared for you by somebody else, regardless of what it is that you're you're trying to be literate in. 
00:50:16.181 --> 00:50:19.769
Kay: In print mediums it's called reading, reading/accessing. 
00:50:19.769 --> 00:50:26.126
Kay: I don't think many people in our society would think that a person who just could read was literate. 
00:50:26.126 --> 00:50:35.756
Kay: Because you have to be able to create ideas and put them into the information stream, so you have creative literacy, which is the equivalent of writing. 
00:50:35.756 --> 00:50:48.470
Kay: And then finally after a medium has been around for awhile you have the problem that there are different genre of these things so that you have to go into a different gear to read a Shakespearian play. 
00:50:48.470 --> 00:50:51.051
Kay: Now there's a different way of doing it. 
00:50:51.051 --> 00:51:02.758
Kay: The way they wrote essays 200 years ago is different than the way they write essays today, and so you have to have some sort of literacy in the different styles for representing things. 
00:51:02.758 --> 00:51:16.479
Kay: And so I think those three things when something new comes along, since we have we're talking about media, we could talk about "mediacy" and "il-mediacy," or "computeracy" and "il-computeracy," or something like that. 
00:51:16.479 --> 00:51:21.074
Kay: And I think each one of those things is a problem that has to be solved. 
00:51:21.074 --> 00:51:30.389
Kay: There's the problem of how can you, when you get something new made for a computer, be able to do the equivalent of read it - of access what it is. 
00:51:30.389 --> 00:51:43.859
Kay: You go to a computer store and get some new wonderful thing, slap it into your computer and if you have to learn a new language in order to use the thing, then things are not set up for you being computer literate.
00:51:43.858 --> 00:51:47.786
Interviewer: SO WRITING IN LATIN WOULD BE ANALOGOUS TO RATHER DIFFICULT...
00:51:47.786 --> 00:52:09.769
Kay: Yeah I think it has a lot to do with that, and again to sort of strain the analogy we're making with with printing my other hero back then was Martin Luther who a few years later had this intense desire to let people have a personal relationship with God without going through the intermediaries of the of the church. 
00:52:09.769 --> 00:52:32.789
Kay: And he wanted people to be able to read the bible in their own language and knew that German which was a bunch of different regional dialects back then, mostly for talking about farming and stuff was not going to be able to carry the weight of the bible, as it was portrayed in Latin which is a much more robust and mature language. 
00:52:32.789 --> 00:52:58.297
Kay: So Martin Luther had to invent the language we today call High German, before he could translate the bible into it and so the language that Germans speak today is is in a very large part the invention of a single person who did it as a user interface, so that he could bring the media much closer to the people, rather trying to get everybody in Germany to learn Latin.
00:52:58.297 --> 00:53:11.811
Interviewer: NOW WITH THAT THAT SORT OF INSIGHT, WE COULD THINK OF THIS WHOLE PROCESS LITERALLY TOOK A LONG TIME TOOK MANY CENTURIES AND WE CAN YOU SAY, THE EARLY PHASES OF THE COMPUTER HAVE GONE QUITE MUCH MORE RAPIDLY HAVEN'T THEY?
00:53:11.811 --> 00:53:17.304
Kay: Right, I think, well I think we're part you know, things are going more rapidly. 
00:53:17.304 --> 00:53:33.376
Kay: But also to the extent that analogies help, you know, certainly that progression, I happen to know, be a big fan of books, and I happen to know that progression of of illuminated manuscripts which I absolutely adored when I was a child. 
00:53:33.376 --> 00:53:42.802
Kay: The Gutenberg story, the Aldus story; he was one of my great heroes, because he was the guy who decided he had to read more than one book. 
00:53:42.802 --> 00:53:44.430
Kay: And then Martin Luther. 
00:53:44.430 --> 00:53:51.076
Kay: Those immediately sprang to mind as soon as I had decided that the computer wasn't a car anymore. 
00:53:51.076 --> 00:53:57.450
Kay: And then, then the thing becomes the two most powerful things that you have to do right away. 
00:53:57.450 --> 00:54:01.045
Kay: You don't have to wait to gradually figure them out. 
00:54:01.045 --> 00:54:12.505
Kay: You have to get the thing small and you have to find a language that will allow people, that will bring what it is closer to the people rather than the other way around.
00:54:12.505 --> 00:54:23.436
Interviewer: NOW AN OPPORTUNITY CAME FOR YOU, I KNOW YOU WERE GOING TO MAKE YOUR DYNABOOK ONE WAY OR ANOTHER, BUT AN OPPORTUNITY CAME FOR YOU TO GET TO A BRAND NEW CENTER WHEN YOU WENT TO XEROX PARC.
00:54:23.436 --> 00:54:41.539
Kay: Yeah, I thought up the Dynabook in 1968 and made a cardboard model of it, and a couple of years later I was about to go to Carnegie Mellon University to do the thing, and I had been consulting a little bit for the newly formed Xerox PARC, and it just got to be too much fun, so I never wound up going to Pittsburgh.
00:54:41.539 --> 00:54:43.634
Interviewer: WHAT WAS XEROX PARC?
00:54:43.634 --> 00:54:56.471
Kay: Xerox PARC was an attempt by Xerox to spend part of its research and development money on really far out stuff that was not going to be particularly controlled by them. 
00:54:56.471 --> 00:55:04.143
Kay: In the late '60s they bought themselves a computer company, they bought a whole bunch of publishers. 
00:55:04.143 --> 00:55:09.536
Kay: They were trying to get into a larger sphere than just office copiers. 
00:55:09.536 --> 00:55:39.161
Kay: The the one of the ringing phrases of the late '60s was "Xerox should be the architects of information." And so they had this expansive feeling about getting into other areas, and they got Jack Goldman in, who was a scientist at Ford and as the chief new chief scientist at Xerox and Jack realized that what we actually had to have at Xerox was something like a long range research center. 
00:55:39.161 --> 00:55:49.947
Kay: Xerox was a big company even then, and what Jack decided to do was to hire George Paik who was the chancellor of Washington University in St. 
00:55:49.947 --> 00:55:59.518
Kay: Louis and George was quite familiar with ARPA and so he hired Bob Taylor who had been one of the funders of ARPA in the '60s. 
00:55:59.518 --> 00:56:07.190
Kay: Taylor was one of the champions of Engelbart, one of the champions of the work at RAND and so forth. 
00:56:07.190 --> 00:56:18.053
Kay: What Taylor did was to, instead of hiring random good scientists, what he did was to decide to set up a miniature concentrated ARPA community. 
00:56:18.053 --> 00:56:40.082
Kay: So he went out after all of the people he thought were the best in the ARPA research community and those people were somewhat interested because the Mansfield Amendment was shutting down, constricting the kinds of far out things that ARPA could do, so it was one of those things where the..
00:56:40.081 --> 00:56:41.025
Interviewer: WHAT WAS THE MANSFIELD AMENDMENT?
00:56:41.025 --> 00:56:45.443
Kay: The Mansfield Amendment was an overreaction to the Vietnam War. 
00:56:45.443 --> 00:56:55.591
Kay: A lot of people were worried about various kinds of government and especially military funding on campus and secret funding and all of this stuff. 
00:56:55.591 --> 00:57:09.811
Kay: And the the ARPA information processing techniques projects got swept up in this even though every single one of them was public domain and had already been spun off into dozens of companies including DEC. 
00:57:09.811 --> 00:57:21.340
Kay: And so this is this is just one of these broad brush things done by Congress that happened to kill off one of the best things that's ever been set up in this country. 
00:57:21.340 --> 00:57:32.938
Kay: And so a lot of smart people in universities who believed more or less the same dream about the destiny of computers were gathered up by Taylor, and I was one of those.
00:57:36.052 --> 00:57:40.717
Interviewer: SO HOW GOOD WERE THEY -- YOU WERE TALKING ABOUT THE PEOPLE THAT WERE GATHERED, HOW GOOD WERE THEY?
00:57:40.717 --> 00:57:42.324
Kay: Well, I thought they were the best.
00:57:42.324 --> 00:57:44.351
Interviewer: OKAY. 
00:57:44.351 --> 00:57:52.798
Interviewer: HOW GOOD WERE THEY, ALAN?
00:57:52.798 --> 00:57:57.463
Kay: I thought the people that were there were among the very best. 
00:57:57.463 --> 00:58:08.567
Kay: In my personal pick, by 1976 which was about six years after the place was started there were 58 out of my personal pick of the top 100 in the world. 
00:58:08.567 --> 00:58:11.159
Kay: And divided into a couple of labs. 
00:58:11.159 --> 00:58:39.513
Kay: People who had very strong opinions who normally would not work with each other at all, in any normal situation, were welded together by having known each other in the past, having come up through the ARPA community believing more or less the same things, of course, when you have that kind of level of people, the disagreements in the in the tenth decimal place become significant. 
00:58:39.513 --> 00:58:52.987
Kay: But it worked out very well because we were able to get together completely on joint hardware projects, so we built all of our own hardware as well as all of our own software there. 
00:58:52.987 --> 00:59:08.090
Kay: And the hardware was shared amongst the many different kinds of groups that were there, so there was one set of hardware, as we moved on from year to year and then many different kinds of software design.
00:59:08.090 --> 00:59:16.146
Interviewer: AS XEROX HAD THIS IDEA OF ARCHITECTURE OF INFORMATION, A RATHER GENERAL CONCEPT, WHAT DID YOU GUYS THINK YOU WERE DOING?
00:59:16.146 --> 00:59:23.618
Kay: Well, the the psychology of that kind of person is, would be thought as being arrogant in most situations. 
00:59:23.618 --> 00:59:33.953
Kay: We we thought we knew we didn't know exactly what we were going to do, but we were quite sure that nobody else could do it better, whatever it was. 
00:59:33.953 --> 00:59:41.495
Kay: And the architecture of information, that was a phrase that sounded good, it didn't actually mean anything. 
00:59:41.495 --> 00:59:50.713
Kay: And there was some mumbling also about if paper goes away in the office in the next 25 years, Xerox should be the company to do it. 
00:59:50.713 --> 00:59:58.394
Kay: Because that was their heartland business, but Taylor had was setting the place up to realize the ARPA dream. 
00:59:58.394 --> 01:00:13.687
Kay: Which was to do man-computer symbiosis in all of the different directions that ARPA had been interested in the past which included interactive computing, which included artificial intelligence and the notion of agents. 
01:00:13.687 --> 01:00:22.276
Kay: So there're projects that range from being intensely practical ones, like Gary Starkweather doing the first laser printer. 
01:00:22.276 --> 01:00:28.351
Kay: Metcalf and other people doing the Ethernet the first packet switching local area net. 
01:00:28.351 --> 01:00:37.290
Kay: Thacker being the main designer of the Alto which was the first work station and the first computer to look like the Macintosh. 
01:00:37.290 --> 01:00:54.957
Kay: I was head of the group that was interested in the Dynabook design and a lot of the things that we came up with for the Dynabook were simulated on the Alto and became part of the first notion of what work stations and personal computers should be like. 
01:00:54.957 --> 01:01:06.619
Kay: And those included things like the icons and the multiple overlapping windows and the whole, the whole paraphernalia that you see on machines like the Macintosh today.
01:01:06.619 --> 01:01:16.092
Interviewer: THE BASIC IDEA WAS, THE SORT OF MACHINE YOU WERE INTERESTED IN WAS ONE WHICH HAD THE CAPACITY TO HANDLE RICH GRAPHICAL INTERFACES, BUT COULD BE NETWORKED TOGETHER. 
01:01:16.092 --> 01:01:20.713
Interviewer: SO IT HAD TO HAVE MORE STAND ALONE POWER THAN NORMAL TIME-SHARING, IS THAT TRUE?
01:01:20.713 --> 01:01:27.429
Kay: Yeah, in fact one of the things we were incredibly interested in was how powerful did it have to be. 
01:01:27.429 --> 01:01:45.447
Kay: We had we used phrases like we didn't know how powerful it had to be, but it had to be able to something like 90 or 95 percent of your, the things that you would generally like to do before you wanted to go to something more -- of course, we didn't know what that meant. 
01:01:45.447 --> 01:01:53.426
Kay: We thought it would be somewhere around ten MIPS (million instructions per second), that was sort of the rule of thumb. 
01:01:53.426 --> 01:02:01.537
Kay: The machine we built was effectively some, it was somewhere between one and three MIPS, depending on how you measured it. 
01:02:01.537 --> 01:02:04.529
Kay: And so it was less powerful than we thought. 
01:02:04.529 --> 01:02:09.848
Kay: On the other hand it was about 50 times as powerful as a time-sharing terminal. 
01:02:09.848 --> 01:02:13.971
Kay: So the magnification of what we could aspire to was enormous. 
01:02:13.971 --> 01:02:16.497
Kay: And the machine was not done blindly. 
01:02:16.497 --> 01:02:36.842
Kay: It was done after about a year of studying things like fonts, and what happens when the eye looks at little dots on screens, and what animation means, and we did a bunch of real time music very early synthesis kinds of stuff and so we knew a lot about what the machine should be and how fast it should run.
01:02:36.842 --> 01:02:43.041
Interviewer: SO TO DESIGN THIS MACHINE AND THE SOFTWARE THAT WENT WITH IT YOU STUDIED HUMAN BEINGS?
01:02:43.041 --> 01:02:43.469
Kay: Yeah. 
01:02:43.469 --> 01:02:44.680
Kay: A lot of us did. 
01:02:44.680 --> 01:02:51.516
Kay: I mean what was nice here is I was one I was one of the drivers on one of these small machines. 
01:02:51.516 --> 01:03:03.908
Kay: There were other groups at this time in 1971 when PARC was forming who were building a large time-sharing system to act as a as a kind of an institutional resource for PARC. 
01:03:03.908 --> 01:03:19.220
Kay: There were lots of different things going on and I wanted to do stuff with children because my feeling after doing the FLEX machine was that we, and I especially, were not very good at designing systems for adults. 
01:03:19.220 --> 01:03:33.250
Kay: And so then I thought, well children have to use this thing, why don't we forget about adults for a while, we'll just design a tool for children, a medium for children, and we'll see what happens. 
01:03:33.250 --> 01:03:37.310
Kay: So I desperately wanted to get a bunch of these systems. 
01:03:37.310 --> 01:03:39.517
Kay: I needed like fifteen of them. 
01:03:39.517 --> 01:03:50.342
Kay: I needed to have them in a school somehow, with children, Because I wanted to see how children reacted to these things, and improve the design that way.
01:03:50.342 --> 01:03:53.339
Interviewer: WE'LL KEEP GOING DON'T WORRY ABOUT IT. 
01:03:53.339 --> 01:04:01.023
Interviewer: SO THE IDEA WAS THAT WHEN YOU USED CHILDREN IT THREW INTO FOCUS MANY OF THE PROBLEMS YOU HAD BEFORE?
01:04:01.023 --> 01:04:01.417
Kay: Yeah. 
01:04:01.417 --> 01:04:07.998
Kay: I don't know that it threw into -- the shock when you go out to real users of any kind is enormous. 
01:04:07.998 --> 01:04:12.340
Kay: Because technical people live in this tiny little world actually. 
01:04:12.340 --> 01:04:17.210
Kay: We like to think it's a big world, but it's actually a tiny little world. 
01:04:17.210 --> 01:04:23.790
Kay: And it's full of phrases that we learned when we were taking math classes, and it's, it's hermetic. 
01:04:23.790 --> 01:04:29.186
Kay: And it's full of people who like to learn complicated things, they delight in it. 
01:04:29.186 --> 01:04:38.793
Kay: And so one of the one of the hardest things is for these kind of people to do any kind of user interface for people who are not like that at all. 
01:04:38.793 --> 01:04:44.452
Kay: That is the number one dictum of user interface design, is the users are not like us. 
01:04:44.452 --> 01:04:52.348
Kay: And so what you need to have is some way of constantly shocking yourself into realizing that the users are not like us. 
01:04:52.348 --> 01:05:09.391
Kay: And children do it really well, because they don't care about the same kinds of things that adults do, you know, they're not like this, they're not like that, they can always go out and play ball if, they haven't learned to feel guilty about not working yet. 
01:05:09.391 --> 01:05:14.260
Kay: And the last thing you want to do is subject the children to more school. 
01:05:14.260 --> 01:05:19.656
Kay: You don't want to put them through a training course to learn a computing system. 
01:05:19.656 --> 01:05:22.090
Kay: So we use the term forcing function. 
01:05:22.090 --> 01:05:31.171
Kay: It was a setup where in many ways it's harder to design a system for children than it is for adults, along a couple of couple of avenues. 
01:05:31.171 --> 01:05:36.041
Kay: And it forced us to start thinking about how human mentalities might work.
01:05:36.041 --> 01:05:40.184
Interviewer: THESE WERE YOUR SMALLTALK KIDS, RIGHT?
01:05:40.184 --> 01:05:43.199
Kay: These eventually became the Smalltalk kids. 
01:05:43.199 --> 01:05:50.738
Kay: And the lead into that was that Seymour Papert had gotten a lot of good ideas from having worked with Piaget. 
01:05:50.738 --> 01:05:59.580
Kay: And Piaget had a notion of the evolution of mentality in early childhood as being sort of like a a caterpillar into a butterfly. 
01:05:59.580 --> 01:06:07.119
Kay: And the most important idea of it was that each stage of development, that the kid was not a deficient adult. 
01:06:07.119 --> 01:06:09.998
Kay: That it was a fully functioning organism. 
01:06:09.998 --> 01:06:14.659
Kay: Just didn't think about the world quite the same way as adults did. 
01:06:14.659 --> 01:06:20.759
Kay: And other psychologists like Jerome Bruner had similar ideas, also inspired by by Piaget.
01:06:20.759 --> 01:06:22.820
Interviewer: WHAT WERE THESE BASIC STAGES?
01:06:22.820 --> 01:06:29.923
Kay: Well, if you break them down into just three stages, one in which a lot of thinking is done just by grabbing. 
01:06:29.923 --> 01:06:32.894
Kay: A hole is to dig it, an object is to grab it. 
01:06:32.894 --> 01:06:54.334
Kay: And then the next stage is very visual, in which many of the judgments that you make about the world are dominated by the way things look, so in this stage you have the Piaget water pouring experiment, you know you pour from a squat glass into a tall thin one and the kid in this stage says there's more water in the tall thin one. 
01:06:54.334 --> 01:07:00.017
Kay: He doesn't have an underlying notion, a symbolic notion, that quantities are conserved. 
01:07:00.017 --> 01:07:05.765
Kay: He doesn't have what Piaget calls "conservation." And conservation is not a visual idea. 
01:07:05.765 --> 01:07:09.252
Kay: Visual is what does it look like when you compare it. 
01:07:09.252 --> 01:07:23.201
Kay: And then later on you get a stage that Piaget called the "symbolic stage" where facts and logic start to dominate the ways thinking, and a child in that stage knows as a fact that water doesn't appear and disappear. 
01:07:23.201 --> 01:07:24.751
Kay: Nor does anything else. 
01:07:24.751 --> 01:07:31.984
Kay: And so it's able to give you judgments or inferences based on these facts rather than by the way things appear. 
01:07:31.984 --> 01:07:38.313
Kay: Now Bruner did a lot of these experiences over again and added some sort of side trips into them. 
01:07:38.313 --> 01:08:16.156
Kay: So one of the things he did in the water pouring experiment was to intersperse a cardboard after the child had said there's more water in the tall thin glass, and the kid immediately changed what he had just said, he said, "Oh no, there can't be more because where would it come from." And Bruner took the card away, and the kid changed back, he said, "No, look, there is more." Bruner put the card back and the kid said, "No, no there can't be more, where would it come from?" And so if you have any six year olds you'd like to torment, you know this is a pretty good way of doing it. 
01:08:16.156 --> 01:08:22.808
Kay: And Bruner the way interpreted this is that we actually have separate ways of knowing about the world. 
01:08:22.808 --> 01:08:30.428
Kay: One of them is kinesthetic, one of them is visual, one of them is symbolic, and of course we have other ways as well. 
01:08:30.428 --> 01:08:32.818
Kay: And that these ways are in parallel. 
01:08:32.818 --> 01:08:35.724
Kay: They really constitute separate mentalities. 
01:08:35.724 --> 01:08:46.896
Kay: And because of their evolutionary history they are both rather distinct in the way that they deal with the world, and they are not terribly well integrated with each other. 
01:08:46.896 --> 01:09:00.005
Kay: So you can get some remarkable results by telling people an English sentence which they'll accept and then showing them the picture that represents the same thing and have an enormous emotional reaction.
01:09:00.006 --> 01:09:02.846
Interviewer: HOW WAS THIS GOING TO HELP YOUR INTERFACE DESIGN?
01:09:02.846 --> 01:09:08.986
Kay: Well, you know we were clutching at straws! You'll do anything, when you don't know what to do. 
01:09:08.986 --> 01:09:23.696
Kay: But it seemed like a reasonable thing to since we're going to be dealing with humans, it seemed like a reasonable thing to try and get something out of the newly formed cognitive of psychology to do it, and the thing that got me. 
01:09:23.696 --> 01:09:26.126
Kay: The Piaget stuff didn't help me much. 
01:09:26.126 --> 01:09:36.999
Kay: Because one of the ways of interpreting it is that for example, you shouldn't probably teach first graders arithmetic because they aren't quite set up to receive it yet. 
01:09:36.999 --> 01:09:43.075
Kay: You'd be better off teaching them something that's more kinesthetic like geometry or topology. 
01:09:43.075 --> 01:09:54.459
Kay: They're just, they're learning, they're tying their shoes and stuff and there are a whole bunch of things you can do with knots and things that are that are, higher mathematics. 
01:09:54.459 --> 01:10:00.406
Kay: But the particular symbolic manipulations of arithmetic are not easy for them at that stage. 
01:10:00.406 --> 01:10:08.401
Kay: Well, that's that's important when you're designing curriculum in schools but it didn't tell us much about a user interface. 
01:10:08.401 --> 01:10:11.279
Kay: The Bruner thing though was really exciting. 
01:10:11.279 --> 01:10:19.401
Kay: Because one of the ways of interpreting it is that at every age in a person's life there are these multiple mentalities there. 
01:10:19.401 --> 01:10:28.419
Kay: Now when your kid is six years old, the symbolic one may not be functioning very much, but there are tricks that you can get it to function. 
01:10:28.419 --> 01:10:42.042
Kay: And Bruner had this notion that you could take an idea that's normally only taken, taught symbolically like some physical principle, and teach it to a six year-old kinesthetically, and to a ten year-old visually. 
01:10:42.042 --> 01:10:46.263
Kay: And later on to a fifteen year-old you can teach it symbolically. 
01:10:46.263 --> 01:10:47.861
Kay: This notion of a spiral. 
01:10:47.861 --> 01:10:49.844
Kay: And Pappert had the same idea. 
01:10:49.844 --> 01:10:56.176
Kay: If you want to learn how a gyroscope works, the last thing you want to do is look at the equation. 
01:10:56.176 --> 01:11:17.921
Kay: What you want to do is do a little bit of visual reasoning about the thing and then have one in your hand in the form of a big bicycle wheel, and when you turn that bicycle wheel and feel what it does, it clicks together with a small amount of reasoning you are doing and all of a sudden you understand why it it has to flop the other way. 
01:11:17.921 --> 01:11:30.136
Kay: But there's nothing that mysterious about it, but from the outside and looking at the equation, you know and thinking about cross products and stuff like that it just doesn't make any sense. 
01:11:30.136 --> 01:11:43.886
Kay: So Bruner's idea was when you don't know what else to do in developing a curriculum, you try recapitulating the Piagetian stages, cast this adult level knowledge down into a kinesthetic form and recast it later on. 
01:11:43.886 --> 01:11:48.172
Kay: Teach it over and over again, recast it later on in a visual form. 
01:11:48.172 --> 01:11:55.718
Kay: And he thought of the these lower mentalities kinesthetically and iconic mentalities as being what we call intuition. 
01:11:55.718 --> 01:12:05.440
Kay: They can't talk much but they have their own figurative ways of knowing about the world that supply a nice warm way of thinking about physical problems.
01:12:05.439 --> 01:12:10.367
Interviewer: ENGLEBART HAD SOMETHING...ALREADY THE MOUSE IS A KINESTHETIC...
01:12:10.367 --> 01:12:12.041
Kay: Yes, but not a good one. 
01:12:12.041 --> 01:12:12.778
Kay: It's okay. 
01:12:12.778 --> 01:12:18.674
Kay: But if you only use it to point on the screen it's not very, it's not very kinesthetic. 
01:12:18.674 --> 01:12:23.765
Kay: Because major operation in kinesthesia is grabbing something and moving it. 
01:12:23.765 --> 01:12:25.976
Kay: And Engelbart did not have that. 
01:12:25.976 --> 01:12:36.360
Kay: And that was one of the first, of course people been moving things around in in computer graphics and most people that had ever done this liked it better. 
01:12:36.360 --> 01:12:44.064
Kay: The first little paper I wrote about the Dynabook talked about moving things around and GRAIL moved things around. 
01:12:44.064 --> 01:12:46.141
Kay: Sketchpad moves things around. 
01:12:46.141 --> 01:12:59.137
Kay: It's a natural thing when you're do when you're thinking about things from a graphic center, which Engiebart wasn't even though he had little bit of graphics he was thinking about it from text. 
01:12:59.137 --> 01:13:01.951
Kay: Think about things from a graphic center. 
01:13:01.951 --> 01:13:05.435
Kay: It's natural to want to just move something around. 
01:13:05.435 --> 01:13:17.024
Kay: And so the connection with what had already been done, with what Bruner was saying got us thinking a little bit more strongly about what the mouse was supposed to be about. 
01:13:17.024 --> 01:13:24.796
Kay: The mouse was not just for indicating things on the screen, it was to give you a kinesthetic entry into this world. 
01:13:24.796 --> 01:13:31.428
Kay: Now the important thing about it is that the I don't know how all scientific discoveries are made. 
01:13:31.428 --> 01:13:47.908
Kay: They usually are connected together with little flashes of insight over long periods of time, but in fact the we're when I started off I was quite sure that Bruner had the key and we got the ingredients rather early for doing the user interface. 
01:13:47.908 --> 01:13:53.402
Kay: But it was remarkable to me how many people we had to try ideas out on for years. 
01:13:53.402 --> 01:14:13.566
Kay: Three or four years we had to not only build the system but in fact the early versions of the system were not as good as later versions of the system, and actually took about five years and hundred, dealing with hundreds of people to come out with the first thing that was sort of looked like the Mac.
01:14:13.567 --> 01:14:15.610
Interviewer: AND THIS IS THE DESKTOP...
01:14:15.610 --> 01:14:20.713
Kay: Yeah, the desktop was actually an idea we didn't like particularly. 
01:14:20.713 --> 01:14:28.443
Kay: That was something that was developed as a -- when Xerox was thinking specifically of going at offices.
01:14:28.443 --> 01:14:34.246
Interviewer: THIS WAS THE ICONS, WINDOWS...
01:14:34.246 --> 01:14:47.039
Kay: Yeah, in the in the Dynabook idea, see when you have a Dynabook and you have simulations and multidimensional things as your major way of storing knowledge, the last thing you want to do is print any of it out. 
01:14:47.039 --> 01:14:51.586
Kay: Because you are destroying the multidimensionality and you can't run them. 
01:14:51.586 --> 01:14:58.740
Kay: So if you have, so one of the rules is if you have anything interesting in your computer, you don't want to print it. 
01:14:58.740 --> 01:15:04.197
Kay: And that's why if your computer is always with you you don't want to, you won't print it. 
01:15:04.197 --> 01:15:11.473
Kay: When you give it to somebody else what you're sending to them is something that was in your Dynabook to their Dynabook. 
01:15:11.473 --> 01:15:21.901
Kay: Okay, and the user interface that we worked on was very much aimed at that, and so it had a different notion than the than the desktop was sort of a smaller version of it. 
01:15:21.901 --> 01:15:36.452
Kay: What we had was this, you can think of it as multiple desks if you want, but we had this notion that people wanted to work on projects, and I especially liked to work on multiple projects and people used to accuse me of abandoning my desk. 
01:15:36.452 --> 01:15:40.515
Kay: You know it got piled up and I'd go to another one and pile it up. 
01:15:40.515 --> 01:15:52.398
Kay: And when I'm working on multiple things I like to have a table full of all the crap that goes there and another table and so forth, so I can everything is in the state it was when I last left it. 
01:15:52.398 --> 01:16:10.042
Kay: And that was user interface that we wound up doing where you could move from one project to another project and you could think of it on, if you did it on the Macintosh you could think of it as having multiple Macintosh desks, each one of which was all the tools for that particular project.
01:16:11.384 --> 01:16:19.385
Interviewer: THE REASON WHY THESE, YOU USED THE TERM INTUITIVE BEFORE, OR WE FEEL THINGS THAT USE OUR KINESTHETIC AND ICONIC MENTALITIES ARE INTUITIVE. 
01:16:19.385 --> 01:16:21.227
Interviewer: ALSO THE TERM LEVERAGE IS USED. 
01:16:21.227 --> 01:16:26.810
Interviewer: CAN YOU TELL ME WHAT YOU MEAN WHEN YOU SAY, WHEN YOU SUCCEED, WHEN YOU CONFER LEVERAGE ON A USER?
01:16:26.810 --> 01:16:34.724
Kay: Yeah, well, I think -- I mean, another part of my background before I was heavily into computer science, was theater. 
01:16:34.724 --> 01:16:50.417
Kay: And if you think about it, theater is kind of an absurd setup, because you have perhaps a balding person in his forties impersonating a teenage in triumph, holding a skull in front of cardboard scenery, right? It can't possibly work. 
01:16:50.417 --> 01:16:53.032
Kay: But in fact it does all, all the time. 
01:16:53.032 --> 01:17:02.153
Kay: And the reason it does is that theater, the theatrical experience is a mirror that blasts the audience's intelligence back out at them. 
01:17:02.153 --> 01:17:12.547
Kay: So it's a as somebody once said, "People don't come to the theater to forget, they come tingling to remember." And so what you -- what it is is an evoker. 
01:17:12.547 --> 01:17:21.064
Kay: And again, having the thing go from an automobile to a medium started me thinking about user interface as a theatrical notion. 
01:17:21.064 --> 01:17:44.670
Kay: And the -- what you do in the theater is to take something that is impossibly complex, like human existence or something, and present it in something that is more like stereotypes, which the user can then resynthesize human existence out of the, the -- I think it was Picasso who said the, that art is not the truth, art is a lie that tells the truth. 
01:17:44.670 --> 01:18:00.430
Kay: And so I started thinking about the user interface as something that was a lie, namely, what it really isn't what's going on inside the computer, but it nonetheless tells the truth because it evokes, it's a different kind of computer. 
01:18:00.430 --> 01:18:06.533
Kay: It evokes what the computer can do in the user's mind and that's what you're trying to do. 
01:18:06.533 --> 01:18:09.484
Kay: So that's the computer, they wind up going. 
01:18:09.484 --> 01:18:12.434
Kay: And, and that's what I think of as leverage.
01:18:27.341 --> 01:18:31.904
Interviewer: SO JUST AS THE TIME-SHARING, YOU SORT OF HAD THE ILLUSION THAT YOU HAD EXCLUSIVE USE OF THE COMPUTER. 
01:18:31.904 --> 01:18:36.556
Interviewer: HERE, YOU HAVE A DIFFERENT ILLUSION THAT YOU'RE MOVING THINGS ON, THAT THERE ARE OBJECTS ON YOUR SCREEN.
01:18:36.556 --> 01:18:36.880
Kay: Yes. 
01:18:36.880 --> 01:18:39.723
Kay: In, in fact, we use the term user illusion. 
01:18:39.723 --> 01:18:45.993
Kay: I don't think we ever used the term user interface, or at least certainly not in the early days. 
01:18:45.993 --> 01:18:50.323
Kay: And we did not use the term metaphor, like as in desktop metaphor. 
01:18:50.323 --> 01:18:53.554
Kay: That was something that I think came along later. 
01:18:53.554 --> 01:19:02.279
Kay: The idea was what, what can you do theatrically that will cover the amount of magic that you want the person to be able to experience. 
01:19:02.279 --> 01:19:24.965
Kay: Because we again the understanding was in the theater, you don't have to present the world as physicists see it, but if you're going to have magic in Act III, you better foreshadow it in Act I, so there's this whole notion of how do you dress the set, in order to set up expectations that will later turn out to be true in the, in the audience's mind.
01:19:24.965 --> 01:19:30.752
Interviewer: NOW WHILE YOU WERE WORKING ON THESE THINGS, OTHER PEOPLE AT PARC WERE BUILDING A MACHINE?
01:19:30.752 --> 01:19:33.658
Kay: They were building various machines. 
01:19:33.658 --> 01:20:02.964
Kay: And it was a -- it's kind of funny, because in the way it worked out is I had come up with a, took Wes Clark's LINC design and came up with a version, sort of a modern version of that in a little handheld, you know, sort of a like a suitcase, that I called MiniCOM, and has done some design of it, how things would run on it, and the problem was it wasn't powerful enough. 
01:20:02.964 --> 01:20:15.456
Kay: But it was something I figured I could get 15 or 20 of for the experiments that we wanted, and I had designed the first version of Smalltalk for this machine. 
01:20:15.456 --> 01:20:21.663
Kay: And much to my amazement I got turned down flat by a nameless Xerox executive. 
01:20:21.663 --> 01:20:26.927
Kay: And I was crushed that, you know, no, we're doing time-sharing ... 
01:20:26.927 --> 01:20:27.399
Kay: sorry.
01:20:27.399 --> 01:20:29.943
Interviewer: WE'LL START AGAIN...JUST GO FROM WHERE YOU SAID YOU WERE TURNED DOWN BY A XEROX EXECUTIVE.
01:20:27.399 --> 01:20:27.416
Kay: Okay, so ... 
01:20:27.416 --> 01:20:27.631
Kay: there was a I couldn't believe that a, this, an unnamed, a nameless Xerox executive turned me down flat as far as the idea of building a bunch of these things. 
01:20:27.631 --> 01:20:27.656
Kay: And I was crushed. 
01:20:27.656 --> 01:20:27.764
Kay: You know, I was only, I was 31 years old then, and, just, ach, it was terrible. 
01:20:27.764 --> 01:20:28.346
Kay: And so then I evolved another scheme of getting a bunch of little minicomputers, like Data General Novas, and I could only afford five of those -- I had something like $230,000 or so, and I figured five of those, and take the system they were experimenting with fonts and bitmap displays on and I'll replicate that, I'll get five of them -- it's an incredibly expensive way to do it, but that would give me five machines to do stuff. 
01:20:28.346 --> 01:20:29.007
Kay: And then this this Xerox executive went away on a, on a task force, and Chuck Thacker and Butler Lampson came over to me in September of 1972 and said to me, "Have you got any money?" And I said, "Well, I've got about $230,000." And they said, "Well, how would you like us to build you your machine?" And I said, "I'd like it fine." And so what I gave them was the results of the experiments I had done in fonts and bitmap graphics, plus we had done some prototyping of animations and music. 
01:20:29.007 --> 01:20:29.083
Kay: So to do all these things that had to be so and so fast. 
01:20:29.083 --> 01:20:29.267
Kay: And what happened there was a combination of my interest in a very small machine and Butler Lampson's interest in a $500 PDP-10 someday. 
01:20:29.267 --> 01:20:29.381
Kay: And Chuck Thacker wanted to build a machine 10 times as fast as a Data General Nova. 
01:20:29.381 --> 01:20:29.650
Kay: And Chuck was the hardware genius, so he got to decide what it was in the end, and he went off and in 3 1/2 months with two technicians completely built the first machine that had the bitmap display. 
01:20:29.650 --> 01:20:29.816
Kay: And he built it not as small as I wanted it, but ten times faster than I had planned, and it was a larger capacity machine. 
01:20:29.816 --> 01:20:29.943
Kay: So it was simultaneously both the first thing that was like a Mac, and the first work station.
01:22:44.037 --> 01:22:44.860
Interviewer: THIS WAS THE ALTO.
01:22:44.860 --> 01:22:45.760
Kay: An absolute triumph. 
01:22:45.760 --> 01:22:46.788
Kay: Yeah, this was the Alto.
01:22:46.788 --> 01:22:50.918
Interviewer: WHAT WAS THE BITMAP DISPLAY? WHY WAS THAT SO . 
01:22:50.918 --> 01:22:51.094
Interviewer: . 
01:22:51.094 --> 01:22:51.270
Interviewer: . 
01:22:51.270 --> 01:22:51.358
Interviewer: ?
01:22:51.358 --> 01:22:59.278
Kay: Well, it was -- I mean that was fairly controversial, because the, the problem is that bits were expensive back then. 
01:22:59.278 --> 01:23:17.066
Kay: And before about 1971, bits were intolerably expensive, because they're, in memory, they're in forms of these little magnetic cores, and just even a modest memory was many cubic feet, and required expensive read sense, amplifiers and power supply -- it was a mess. 
01:23:17.066 --> 01:23:23.711
Kay: And in the early '70s, Intel came out with a chip called the 1103, that had a thousand bits on it. 
01:23:23.711 --> 01:23:32.168
Kay: Right? The chips you buy today have like 4 million bits, and the Japanese are making ones with 16 million -- 64 million bits. 
01:23:32.168 --> 01:23:34.786
Kay: So this was a thousand bits on a chip. 
01:23:34.786 --> 01:23:37.672
Kay: This is the best thing that ever happened. 
01:23:37.672 --> 01:23:40.693
Kay: Because all of a sudden, everything changed. 
01:23:40.693 --> 01:23:50.023
Kay: This is one of these predictions that Bob Noyce and Gordon Moore, that it completely changed the relationship of us to computing hardware. 
01:23:50.023 --> 01:24:01.300
Kay: And the people who wanted to build a big time-sharing machine at PARC, including Chuck Thacker and Butler Lampson, immediately started building one out of this memory. 
01:24:01.300 --> 01:24:05.730
Kay: And it was also the right kind of thing to build the Alto out of. 
01:24:05.730 --> 01:24:08.415
Kay: But we still couldn't have a lot of it. 
01:24:08.415 --> 01:24:11.100
Kay: This was 1972 that we're talking about. 
01:24:11.100 --> 01:24:16.000
Kay: And so this notion -- bitmap display is something that we didn't invent. 
01:24:16.000 --> 01:24:20.430
Kay: People had talked about it, there even were small versions of it. 
01:24:20.430 --> 01:24:21.302
Kay: Television --
01:24:21.302 --> 01:24:22.757
Interviewer: EACH PART --
01:24:22.757 --> 01:24:36.073
Kay: Television is something that is discrete in one dimension and analog in another dimension but you can think of it as being 300,000 separate pixels on a screen, and it's something everybody would like, because it's perfectly general. 
01:24:36.073 --> 01:24:43.503
Kay: The nicest thing about television is that you don't have to determine beforehand what kind of picture you're going to show on it. 
01:24:43.503 --> 01:24:44.817
Kay: You can show anything. 
01:24:44.817 --> 01:24:46.246
Kay: You don't have to worry. 
01:24:46.246 --> 01:24:56.533
Kay: Whereas every other kind of display, you had to have some notion about what you were going to display in order to know what kind, how much power you should build into the display. 
01:24:56.533 --> 01:25:20.021
Kay: So we spent a year and a half or so trying different kinds of displays and making calculations and stuff, and at some point we realized, oh, the heck with it, you know, we just have to go for a bitmap display, and of course, we didn't know that people would settle for tiny little displays like this, you know, so the first display on the Alto actually was about two and a half times the size of the first Mac. 
01:25:20.021 --> 01:25:26.822
Kay: It was about 500,000 pixels and it was an 8 1/2 x 11 page display, the exact size that the Dynabook was supposed to be-
01:25:26.822 --> 01:25:30.238
Interviewer: IS IT TRUE YOU PROGRAMMED THE COOKIE MONSTER? IS THAT TRUE?
01:25:30.238 --> 01:25:55.986
Kay: The Cookie Monster the first I invented the first painting program in the summer of 1972 and it was programmed up by Steve Purcell, who was one of our students, and again the idea was to get away from having just crisp computer graphics, as they had been in the past, because the idea was that people don't design on computers, and one of the reasons they don't design on computers is they can't make things messy enough. 
01:25:55.986 --> 01:26:01.050
Kay: And my friend Nick, Nicholas Negroponte at MIT was also thinking similar thoughts. 
01:26:01.050 --> 01:26:04.711
Kay: He wanted people to be able to sketch as well as to render. 
01:26:04.711 --> 01:26:07.457
Kay: And so I invented the, the painting program. 
01:26:07.457 --> 01:26:12.704
Kay: The painting program was a direct result of thinking seriously about bitmap displays. 
01:26:12.704 --> 01:26:15.450
Kay: It, it's maybe the first thing you think of. 
01:26:15.450 --> 01:26:21.673
Kay: Because you are always painting on it, when you're putting up characters, you're painting characters. 
01:26:21.673 --> 01:26:26.189
Kay: And it was very much like MacPaint, it turned out to be many years later. 
01:26:26.189 --> 01:26:28.812
Kay: I have a nice video showing it being used. 
01:26:28.812 --> 01:26:57.489
Kay: And the second thing I thought of was that having a bitmap display with a, combined with multiple windows like the FLEX machine had would automatically allow us to do this overlapping idea, which we all thought was terribly important, because the, we thought this 8-1/2 x 11 display was impossibly small for all the stuff we wanted to put on, and the overlapping windows would give you a way of having much more effective screen space, as you, as you move things around.
01:26:57.489 --> 01:27:00.997
Interviewer: NOW THIS MACHINE, THE ALTO, THE PROTOTYPE WAS PRODUCED IN 1973. 
01:27:00.997 --> 01:27:06.807
Interviewer: HOW DOES IT COMPARE IN TERMS OF WHAT IT'S GOT, COMPARED WITH THE MACINTOSHES AND THE MACHINES WE HAVE NOW.
01:27:06.807 --> 01:27:20.193
Kay: Well, I think the, the first thing is the Macintosh is, represents an amount of work, even to get the first Mac out, an amount of work equivalent to what we did at Xerox added on to it. 
01:27:20.193 --> 01:27:26.957
Kay: So the screen design in the Macintosh is unique to the Macintosh and much nicer than we used. 
01:27:26.957 --> 01:27:30.771
Kay: I mean there all of these extra, extra things on it. 
01:27:30.771 --> 01:27:42.501
Kay: And of course the number of tools you can buy -- there's something like 9,000 pieces of software rendered in the Macintosh user interface that you can buy for it. 
01:27:42.501 --> 01:27:44.373
Kay: So the scope is enormous. 
01:27:44.373 --> 01:27:48.762
Kay: But in terms of the categories it's about the same you know. 
01:27:48.762 --> 01:28:09.560
Kay: We had both painting with bitmaps, we had a crisp computer, computer graphics, we did the first desktop publishing, the first WYSIWYG editors, and most of the paraphernalia that people work with, with one exception, were part of the original concept of the software that went on the Alto. 
01:28:09.560 --> 01:28:12.150
Kay: And that exception was spreadsheets.
01:28:12.150 --> 01:28:23.991
Interviewer: SO ONE OF THE THINGS THAT IS QUITE INTERESTING FOR AN OUTSIDER, THEY SEE THIS, EARLY, MID-'70S, MOST OF THE KEY IDEAS OF THAT WE NOW REGARD AS SORT OF INTIMATE COMPUTING ARE THERE. 
01:28:23.991 --> 01:28:26.411
Interviewer: YET XEROX IS NOT A COMPUTER COMPANY. 
01:28:26.411 --> 01:28:34.000
Interviewer: DID YOU HAVE HOPE? WHAT WERE YOUR HOPES WHEN THE ALTO WAS BUILT? DID YOU HOPE THAT THE WORLD WOULD SEE THIS PRODUCT?
01:28:34.000 --> 01:28:40.739
Kay: We -- I for one oscillated between -- because I thought of the Alto as just an intermediate stage. 
01:28:40.739 --> 01:28:42.305
Kay: I wanted the Dynabook. 
01:28:42.305 --> 01:28:57.010
Kay: And I thought of that user interface as a stopgap measure for the real thing, which is -- see, I was basically interested not in the access literacy part, which the user interface represents, but in -- [INTERRUPTION]
01:29:12.234 --> 01:29:17.470
Interviewer: DID YOU HOPE THE WORLD WOULD GET TO SEE THIS? BECAUSE THIS WAS NO LONGER A GENERAL RESEARCH PROGRAM...
01:29:17.470 --> 01:29:25.921
Kay: Well, one of the things that we realized early in the game with Xerox and its executives was that we were going to have to do a lot of demonstrations. 
01:29:25.921 --> 01:29:39.634
Kay: Because we originally started out trying to talk to them and we wrote some, a bunch of papers called the Pendery Papers that expressed sort of what we were trying to do and, those did not get received into any worthwhile corners of their minds. 
01:29:39.634 --> 01:29:42.712
Kay: So we thought that we would have to do demonstrations. 
01:29:42.712 --> 01:29:46.686
Kay: So we were set up to do demonstrations, we did lots of demonstrations. 
01:29:46.686 --> 01:29:51.444
Kay: Also we didn't want to be cut off from the research community that we had come from. 
01:29:51.444 --> 01:29:53.627
Kay: So we wanted to be able to give demos. 
01:29:53.627 --> 01:30:01.742
Kay: And the experience with Xerox went from, with the lab being fairly open to periods of paranoia, where the lab was completely closed to visitors. 
01:30:01.742 --> 01:30:09.355
Kay: And we used to say to Xerox, look, you know, we're years ahead of everybody else, you know -- lead time is everything in this business. 
01:30:09.355 --> 01:30:19.038
Kay: And you just carry through on this stuff -- don't worry, you know, you can show everybody in the world this stuff, it doesn't matter, they won't be able to build it in time.
01:30:19.037 --> 01:30:21.452
Interviewer: WERE THEY --
01:30:21.452 --> 01:30:22.527
Kay: It's still true. 
01:30:22.527 --> 01:30:30.309
Kay: I mean, if you look at the Macintosh, which came out years later, look how long it's taken IBM to not quite get there yet. 
01:30:30.309 --> 01:30:34.358
Kay: They're still pushing that idea, Windows 3.0 has just come out. 
01:30:34.358 --> 01:30:36.889
Kay: It takes, this stuff takes years to do. 
01:30:36.889 --> 01:30:42.773
Kay: If you have a few years lead time on anybody and your people are capable, you can sustain it.
01:30:42.773 --> 01:30:46.442
Interviewer: SO XEROX COULD'VE HAD IT ALL? THERE MIGHT NOT BE AN APPLE.
01:30:46.442 --> 01:30:52.442
Kay: Well, I don't know about that, because it's really hard to predict that kind of future. 
01:30:52.442 --> 01:31:00.420
Kay: I was amazed at the number of people, for instance, who bought IBM PCs, considering how useless I thought they were. 
01:31:00.420 --> 01:31:12.967
Kay: And the, the interest of everybody in switching over to the overlapping window interface with icons and mouse, I think shows that what people bought millions of is not what they want. 
01:31:12.967 --> 01:31:15.968
Kay: They want what we wanted early in the '70s. 
01:31:15.968 --> 01:31:21.969
Kay: But I think predicting what people will do under conditions of expediency is impossible.
01:31:21.969 --> 01:31:32.177
Interviewer: IN THOSE DAYS, RIGHT, THERE WERE JUST A FEW ALTOS, YOU COULDN'T BUY THEM RIGHT? THERE WEREN'T THAT MANY, AND XEROX DIDN'T SEEM TO HAVE ANY IMMEDIATE PLANS TO SELL THEM.
01:31:32.177 --> 01:31:32.566
Kay: Yeah. 
01:31:32.566 --> 01:31:49.454
Kay: Well, we actually set up a production line for the things, because I, as I say, I needed quite a few, and they started getting popular, and so we set up a prodcution line and I believe that upwards of 2,000 of them were built in the decade of the, of the '70s. 
01:31:49.454 --> 01:32:07.636
Kay: Certainly by 1975 or '76, almost everybody at PARC including the secretaries had Altos and they were connected together by ethernet and they were page-a-second laser printers nearby that you could go, so it was a very similar model to the offices that you see, that you see today. 
01:32:07.636 --> 01:32:17.406
Kay: There were enough -- when Xerox made its fateful turndown in 1976 there were at least 500 machines operating the way machines do in the, in the 1980s. 
01:32:17.406 --> 01:32:26.270
Kay: So we're not turning down a paper idea or a single prototype, they were turning down something that had been functioning for three years.
01:32:26.270 --> 01:32:32.701
Interviewer: AND THIS WAS TURNING DOWN AN IDEA TO SELL A COMPUTER WITH A WORD PROCESSOR AS OPPOSED TO A --
01:32:32.701 --> 01:32:35.875
Kay: Well, the story, the story is, is complicated. 
01:32:35.875 --> 01:32:38.577
Kay: It has to do with a, a bunch of things. 
01:32:38.577 --> 01:32:59.921
Kay: I think the simplest way of characterizing what happened is that, just as when IBM in the '50s turned down their chance at the Xerox machine, because they ultimately thought they were in the computer business rather than the communications business, Xerox when push came to shove thought they were a copier company. 
01:32:59.921 --> 01:33:09.174
Kay: Thought, you know, so the problem with railroads, right, is they tried to make faster locomotives rather than investing in the airlines. 
01:33:09.174 --> 01:33:10.998
Kay: So there was that problem. 
01:33:10.998 --> 01:33:18.225
Kay: There was a problem of slight, more cost in doing the Alto versus a word processor that they wanted to do. 
01:33:18.225 --> 01:33:20.252
Kay: All these things contributed. 
01:33:20.252 --> 01:33:31.329
Kay: I think one of the main problems is that the executive who made the final decision had no way of personally evaluating what he was being told from different sides. 
01:33:31.329 --> 01:33:33.153
Kay: So, so it was complicated. 
01:33:33.153 --> 01:34:07.195
Kay: I mean, the, the best they could've -- 1976, when they had to make the decision, you figure, under, under best conditions it would take a couple of years to get a machine out, they would've had to charge around $20,000 or so for it, which is not bad that early, because that's what word processors were selling for, but it was right on the, right on the edge, and by the time the Star came out, which was too little too late, it was I guess a $20,000 machine that should've been sold for around $10,000. 
01:34:07.195 --> 01:34:14.558
Kay: The Lisa had some of the same problem, it was a $10,000 machine that should've sold for a couple of thousand.
01:34:16.157 --> 01:34:19.012
Interviewer: ALL RIGHT NOW IF YOU CAN RECOLLECT WHERE WE WERE YESTERDAY. 
01:34:19.012 --> 01:34:20.630
Interviewer: WE WERE TALKING ABOUT XEROX PARC. 
01:34:20.630 --> 01:34:26.198
Interviewer: DO YOU LOOK BACK ON IT AS SORT OF A GOLDEN AGE IN COMPUTING? THAT SO MANY PEOPLE WERE GATHERED FOR A PERIOD TOGETHER.
01:34:26.198 --> 01:34:33.556
Kay: Well I think, I know I sort of feel it would be a little bit presumptuous to declare it a golden age in computing. 
01:34:33.556 --> 01:34:35.987
Kay: It was certainly a golden age for me. 
01:34:35.987 --> 01:34:41.809
Kay: I think the five years between '71 and '76 were the most fun I've ever had doing research. 
01:34:41.809 --> 01:34:53.071
Kay: And I think that there've been five or six critical places in computing over the last forty years that have effected the way people think about things and PARC was one of them.
01:34:53.070 --> 01:35:00.627
Interviewer: NOW YOU WEREN'T THE RUN OF THE MILL XEROX EXECUTIVES, AND STEWART BRAND WROTE AN INTERESTING ARTICLE ABOUT YOU, DIDN'T HE?
01:35:00.627 --> 01:35:04.869
Kay: Oh yes, well that was that was a hilarious little side excursion. 
01:35:04.869 --> 01:35:16.565
Kay: Stewart Brand was the person who put the Whole Earth Catalog together and he got interested in computer people because he lived right across the street from Englebart's work at SRI. 
01:35:16.565 --> 01:35:19.713
Kay: So he decided he'd do a piece about the culture. 
01:35:19.713 --> 01:35:29.803
Kay: And one of the places that was just starting up in 1971 and '72 was Xerox PARC and so we you know we all knew him and he was a friend and we invited him in. 
01:35:29.803 --> 01:35:40.277
Kay: He wrote this great article which was published in the Rolling Stone which was really considered to be a rag back then, especially by the East Coast establishment.
01:35:40.278 --> 01:35:44.730
Interviewer: IT DESCRIBES YOU PEOPLE AS SITTING ON BEAN BAGS AND...
01:35:44.730 --> 01:35:57.677
Kay: Yes, the whole culture and we were photographed, the photographs were all taken by Annie Leibowitz and you know it was it was a very Hollywood, California type scene, and the Xerox people did not like it at all. 
01:35:57.677 --> 01:36:13.371
Kay: They had an enormous reaction, so, so large a reaction to it that when Stewart republished the article in his book, they forced him to not use the name Xerox, and so he, he referred constantly in this article to "Shy Corporation" which is what he called it.
01:36:13.371 --> 01:36:27.952
Interviewer: NOW YOU WERE TALKING YESTERDAY ABOUT, ABOUT HAVING DONE ALL THIS WORK ON THE ALTO, THE QUESTIONS OF WHETHER YOU REALLY WANTED TO GET IT OUT THERE AND SO FORTH, AND YOU MADE LOTS OF DEMOS YOU SAID, NOW ONE IN PARTICULAR, BIG EFFORT WAS MADE OF A SALES MEETING IN BOCA RATON WASN'T IT?
01:36:27.952 --> 01:36:31.083
Kay: Yes, that was rather late in the game, though. 
01:36:31.083 --> 01:36:46.208
Kay: That was quite a few years after the Alto had been around, but there were constantly recirclings, of try...this wasn't so much trying to get the Alto out as a product, although there were people who were very interested in it. 
01:36:46.208 --> 01:37:00.466
Kay: A lot of these meetings particularly the Boca Raton one had to do with just getting Xerox at the top and its major executives to have some sense of how the world was changing and what their future was likely to be.
01:37:00.466 --> 01:37:10.706
Interviewer: DID YOU FEEL KIND OF DISAPPOINTED NOT SO MUCH AS YOU SAY, THAT THEY MIGHT ___ HAVE COMMERCIAL REASONS FOR NOT BACKING IT, BUT DID YOU FEEL THAT THEY REALLY UNDERSTOOD WHAT YOU'VE DONE, THAT THEY GOT IT?
01:37:10.706 --> 01:37:12.895
Kay: No, I don't think they got it. 
01:37:12.895 --> 01:37:23.985
Kay: But I think the important thing about the Xerox deal is what they did promise to do is to give us relatively unsupervised support for a period of ten years. 
01:37:23.985 --> 01:37:25.892
Kay: And that is what they did. 
01:37:25.892 --> 01:37:39.808
Kay: We had our skirmishes with them, but and there were some people who had to sacrifice their body and soul to keep the umbrella over the group, but in fact Xerox turned out to be a very good funder. 
01:37:39.808 --> 01:37:48.920
Kay: And there was no promise or even any intent that I ever heard in the beginning that Xerox was going to turn these into products. 
01:37:48.920 --> 01:37:57.890
Kay: Most large corporations use their long range research more as a hedge against future disaster than as pure product development.
01:37:57.890 --> 01:38:01.770
Interviewer: SO IN A SENSE YOU WERE PARTICULARLY SURPRISED THEN.
01:38:01.770 --> 01:38:03.337
Kay: Yeah, I was surprised. 
01:38:03.337 --> 01:38:17.363
Kay: Sure, I mean it it's one thing for them not to make any representations about doing it as a product, but the whole setup was so obviously the way it was going to be that I was surprised, sure, I was amazed.
01:38:17.363 --> 01:38:26.110
Interviewer: NOW WHILE THIS HAD BEING GOING ON, TED HOFFMAN HAD DONE THE WORK ON MICROCHIP, AND SO FORTH, AND HOBBYIST MACHINES STARTED TO APPEAR. 
01:38:26.110 --> 01:38:29.243
Interviewer: WHAT DID YOU GUYS MAKE OF THE HOBBYIST MACHINES?
01:38:29.243 --> 01:38:40.975
Kay: Well you know there was something that, with for instance a 4-bit wide chip and then a 8-bit chip, and so forth and they were sort of inevitable that they would appear. 
01:38:40.975 --> 01:38:45.696
Kay: For me I was surprised that so many people were interested in them. 
01:38:45.696 --> 01:38:58.122
Kay: I realized that an enormous number of people felt disenfranchised from computers completely and these were a way of getting in, I could can touch the new technology and so forth. 
01:38:58.122 --> 01:39:03.259
Kay: But they, the kinds of software you could run on them was really limited. 
01:39:03.259 --> 01:39:06.175
Kay: And so there're various opinions at PARC. 
01:39:06.175 --> 01:39:12.145
Kay: Larry Tesler was much more interested in the 8-bit machines than I was as an example. 
01:39:12.145 --> 01:39:24.224
Kay: My feeling was is that you had to have at least a 16-bit machine that went so and so fast in order to do all of this stuff, and in fact that's exactly the way it worked out. 
01:39:24.224 --> 01:39:34.498
Kay: The Macintosh was a 16-bit machine that went thus and so fast and you had to go that fast in order to do all the things that we were doing at PARC. 
01:39:34.498 --> 01:39:42.412
Kay: And so from my standpoint I would have just been just as happy if no machines had been built up until 1984 or so. 
01:39:42.412 --> 01:39:53.241
Kay: Just from the standpoint, you think of all of the unfortunate standards that were set, like MS-DOS and so forth that are holding back the world even today. 
01:39:53.241 --> 01:39:55.324
Kay: I think it would have been... 
01:39:55.324 --> 01:39:56.642
Kay: but you never know.
01:39:56.643 --> 01:40:02.231
Interviewer: YES, BUT ON THE OTHER HAND AS YOU SAY THEY RELEASED THIS, THIS PENT UP SORT OF MASS OF DISENFRANCHISED PEOPLE. 
01:40:02.231 --> 01:40:06.712
Interviewer: I MEAN THAT WAS WHAT WAS SURPRISING EVEN THOUGH AS YOU SAID THERE WERE TOYS IN ONE SENSE.
01:40:06.712 --> 01:40:16.494
Kay: Yes, yes, and I think that depending on how you look at it certainly one great thing was done on an 8-bit micro and that was VisiCalc. 
01:40:16.494 --> 01:40:22.943
Kay: That was one of the best things that's ever been done on a personal computer as an idea. 
01:40:22.943 --> 01:40:27.291
Kay: The reaction to that at PARC was both admiration and shock. 
01:40:27.291 --> 01:40:31.204
Kay: You know, we couldn't believe that we hadn't seen it. 
01:40:31.204 --> 01:40:33.596
Kay: That's how arrogant we, we were. 
01:40:33.596 --> 01:40:45.480
Kay: But I think that the, aside from that almost everything else done on the 8-bit micro was a sort of a reversion back to the early '60s when machines were very weak. 
01:40:45.480 --> 01:40:51.784
Kay: Most of the 8-bit micros had either no operating system or terrible operating systems. 
01:40:51.784 --> 01:40:54.030
Kay: It's not clear which is worse. 
01:40:54.030 --> 01:40:58.886
Kay: And many of those operating systems are still hanging around today.
01:40:58.886 --> 01:41:13.732
Interviewer: NOW WHAT YOU SAW HAPPEN AFTER THIS WORK WAS DONE AT PARC, IN THE NEXT YEARS AHEAD, THIS WAS GOING TO BE EXPORTED FROM A COMPANY LIKE XEROX, THAT WASN'T REALLY A COMPUTER COMPANY INTO ONE OF THESE NEW FLEDGLING POPULIST HOBBYIST COMPANIES. 
01:41:13.732 --> 01:41:16.652
Interviewer: AND THAT WAS A REMARKABLE TRANSITION WASN'T IT?
01:41:16.652 --> 01:41:23.233
Kay: Yeah, I actually thought that Xerox was the right place to launch from since it wasn't in the computer business. 
01:41:23.233 --> 01:41:26.087
Kay: It really didn't have any history to give there. 
01:41:26.087 --> 01:41:37.735
Kay: Whereas, I think it was more remarkable for a company that was deeply wedded to a certain kind of 8-bit computing, like Apple was, to be willing to throw it all out and start in a completely new way. 
01:41:37.735 --> 01:41:41.520
Kay: But that, this is very much one of Steve Jobs' biggest strengths.
01:41:41.520 --> 01:41:47.677
Interviewer: DO YOU HAVE ANY RECOLLECTION OF THE EVENTS LEADING UP TO JOBS' VISIT? WERE YOU INVOLVED AT ALL IN THAT?
01:41:47.677 --> 01:41:55.935
Kay: No, no, I was at the the famous demo that Larry Tesler gave Steve Jobs and some of the other people from, from Apple, but...
01:41:55.935 --> 01:42:00.301
Interviewer: WHAT HAD YOU HEARD? HAD YOU HEARD THAT XEROX WAS INTERESTED IN BUYING A STAKE IN APPLE, WAS THAT KNOWN?
01:42:00.301 --> 01:42:02.973
Kay: No Xerox, Xerox had a stake in Apple by then. 
01:42:02.973 --> 01:42:08.606
Kay: There's a company called Xerox Development Corporation and they had stakes in various companies. 
01:42:08.606 --> 01:42:12.497
Kay: I forget how much it was, 10 or 20 percent or something like that. 
01:42:12.497 --> 01:42:21.441
Kay: But I don't think, you know, of course we, we thought the, at PARC we thought the Apple was the better of the 8-bit micros that were around and so forth. 
01:42:21.441 --> 01:42:24.809
Kay: But it was not unusual to have, we gave many, many demos. 
01:42:24.809 --> 01:42:29.571
Kay: So it was not unusual to have somebody like Steve Jobs and other people come over.
01:42:29.572 --> 01:42:32.899
Interviewer: DO YOU REMEMBER TALKING TO JOBS THAT DAY?
01:42:32.899 --> 01:42:34.788
Kay: Sure, sure-
01:42:34.788 --> 01:42:36.100
Interviewer: DID HE GET IT THEN?
01:42:36.100 --> 01:42:37.272
Kay: He got it right away. 
01:42:37.272 --> 01:42:39.242
Kay: I mean there are two kinds of demos. 
01:42:39.242 --> 01:42:43.607
Kay: There are ones where you are struggling to get the person to see what's going on. 
01:42:43.607 --> 01:42:56.651
Kay: We found for many people we had to put our -- they weren't used to looking at a computer screen so we had to put our finger on the screen and get them to watch our finger and then see if they could focus in another quarter of an inch and stuff. 
01:42:56.651 --> 01:43:00.644
Kay: And then there are other people who tell you what is going to happen next. 
01:43:00.644 --> 01:43:03.519
Kay: I mean they are so on top of the demo that they know. 
01:43:03.519 --> 01:43:06.820
Kay: And now you're going to show me, - yes, here it is, you know. 
01:43:06.820 --> 01:43:08.045
Kay: Those are great demos. 
01:43:08.045 --> 01:43:15.871
Kay: I had the great pleasure of showing Smalltalk to Kristen Nygaard who is the inventor of Simula, which is one of the major influences on Smalltalk. 
01:43:15.871 --> 01:43:20.077
Kay: And it was that kind of demo, he just knew everything I was going to show him. 
01:43:20.077 --> 01:43:23.910
Kay: It was stuff that he had been dreaming about for years and here it was. 
01:43:23.910 --> 01:43:25.720
Kay: And we've been friends ever since.
01:43:25.720 --> 01:43:31.846
Interviewer: NOW, WHAT DO YOU THINK STEVE JOBS GREATEST ACHIEVEMENT IS THEN? HE TOOK THIS, HE GOT IT AND HE TOOK IT BACK.
01:43:31.846 --> 01:43:39.497
Kay: Well, I think his, I mean what he, what he took back was an idea that things could be done a different way. 
01:43:39.497 --> 01:43:47.218
Kay: And, particularly Steve who is such a visual person, very sensitive to how things look and appear and stuff. 
01:43:47.218 --> 01:43:54.230
Kay: And the whole notion of the graphics interface was something that really captured his imagination. 
01:43:54.230 --> 01:43:54.797
Kay: But ... 
01:43:54.797 --> 01:44:00.960
Kay: and eventually some people from PARC went over to Apple, Larry Tesler was one of them. 
01:44:00.960 --> 01:44:09.885
Kay: But what happened there was that they pretty much took what we had done as a departure point and did a completely new design. 
01:44:09.885 --> 01:44:14.985
Kay: And I remember, I didn't see any of it until the Lisa came out in 1983. 
01:44:14.985 --> 01:44:20.085
Kay: And when I saw it I thought it was just the best thing I had ever seen. 
01:44:20.085 --> 01:44:22.281
Kay: It was just incredible what... 
01:44:22.281 --> 01:44:23.911
Kay: the Lisa was beautiful.
01:44:38.646 --> 01:44:41.327
Interviewer: OKAY, BUT THE LISA WAS STILL TOO EXPENSIVE. 
01:44:41.327 --> 01:44:45.775
Interviewer: SO REALLY THE MACINTOSH WAS THE THRESHOLD MACHINE WHICH REALLY CHANGED...
01:44:45.775 --> 01:44:55.150
Kay: Yeah, their, I mean and the Macintosh in many ways is not a good a design as the Lisa, but it was a severe compromise. 
01:44:55.150 --> 01:45:04.289
Kay: And the thing that was great about it is that it used the weak power of the then 16-bit, 68,000 to great advantage. 
01:45:04.289 --> 01:45:10.512
Kay: Where the Lisa couldn't quite make it with all the things it was trying to do. 
01:45:10.512 --> 01:45:17.602
Kay: And, so in many ways the, you can think of the Macintosh II as Apple's return to the Lisa.
01:45:17.603 --> 01:45:40.729
Interviewer: NOW WHEN THE MACINTOSH CAME OUT, AND CERTAINLY THE HISTORY OF THE COMPUTER SINCE THEN HAS BEEN VERY MUCH A SORT OF A VINDICATION OF EVERYTHING YOU DID AT PARC, ISN'T IT? IN A SENSE, HADN'T THE MAIN VICTORY BEEN WON BY THAT POINT? PEOPLE HAD REALIZED AT LEAST COMPUTERS COULD BE DIFFERENT FROM WHAT THEY WERE...
01:45:40.729 --> 01:45:49.787
Kay: Well I don't, well, I wasn't I don't think any of us at PARC were fighting a war so it wasn't clear who we were victorious against. 
01:45:49.787 --> 01:46:02.550
Kay: But if it, if it meant getting lots of people convinced, I don't think that it was won because the majority of people who compute today still don't interact with a computer in that way. 
01:46:02.550 --> 01:46:10.167
Kay: We're still, you know, there's this big urgency for -- (hang on one second I can hear a, my Macintosh dinging. 
01:46:10.167 --> 01:46:11.952
Kay: It needs, it needs paper).
01:46:30.637 --> 01:46:35.605
Interviewer: SO YOU WERE SAYING THAT WHILE IT INTRODUCED A LOT OF PEOPLE TO THIS TECHNIQUE, IT HADN'T...
01:46:35.605 --> 01:46:45.323
Kay: Yeah, I think that the, I think the important thing is that the, what we did at PARC was not an ultimate answer to the, the problem of interacting with computers. 
01:46:45.323 --> 01:47:00.645
Kay: So, it's, I think that a lot of people are going to be interested in it more than the millions that are now and what will inevitably happen is that people will continue to be interested in it long after it is worthwhile interacting with computers that way. 
01:47:00.645 --> 01:47:10.780
Kay: So you have this thing where people have this tendency to, once they like something, they get religious about it and it hangs on and hangs on long beyond it's actual use.
01:47:10.780 --> 01:47:22.763
Interviewer: NOW, AT THE TIME MACINTOSH CAME OUT, APPLE ESSENTIALLY WAS BETTING THE COMPANY ON IT, RIGHT? AND THERE WAS THIS VERY POPULAR STANDARD MS-DOS IN EXISTENCE ON MILLIONS OF COMPUTERS. 
01:47:22.763 --> 01:47:33.280
Interviewer: WHAT ARE THE REASONS WHY MOST PEOPLE FIND ONE MORE INTUITIVE AND EASIER THAN THE OTHER? AND I WANT YOU TO TALK ABOUT SOME OF THE THINGS YOU TOLD ME YESTERDAY.
01:47:33.280 --> 01:47:37.558
Kay: Yeah, well I don't think we ultimately know. 
01:47:37.558 --> 01:47:38.509
Kay: But the --
01:47:43.091 --> 01:47:56.736
Kay: I, I don't think we ultimately know what, what the reasons are, but we certainly were guided by some theories that we have different ways of knowing about the world and only one of them is through language. 
01:47:56.736 --> 01:48:01.219
Kay: We have a kinesthetic way of knowing about the world through touch. 
01:48:01.219 --> 01:48:04.449
Kay: We have a visual way of knowing about the world. 
01:48:04.449 --> 01:48:09.063
Kay: The kinesthetic and visual ways seem to be more intuitive for people. 
01:48:09.063 --> 01:48:10.381
Kay: They're less crisp. 
01:48:10.381 --> 01:48:15.193
Kay: They deal more with analogy, and the touch thing makes you feel at home. 
01:48:15.193 --> 01:48:20.664
Kay: You're not isolated from things when you're in contact with them, you're grounded. 
01:48:20.664 --> 01:48:34.507
Kay: And so, I think that for me the, the major reason the Macintosh works is because the mouse gives you just the tiniest way of putting your hand in through the screen to touch the objects that you're working on. 
01:48:34.507 --> 01:48:51.712
Kay: The screen gives you a theatrical representation of something much more complex, something that computer designers don't even want to think about as a computer executing two million instructions per second with thousands and thousands of instructions in there. 
01:48:51.712 --> 01:49:04.500
Kay: And then finally the least successful thing that we did, that we're still working on, is a symbolic underpinning for all of this that allows you to express back into this little pocket universe.
01:49:04.500 --> 01:49:13.350
Interviewer: CERTAINLY THE IMAGE YOU HAVE -- YOU HAVE A FILM WHERE YOU SHOW A TWO YEAR-OLD CHILD -- THE IMAGE OF THE COMPUTER UNDERWENT QUITE A TRANSFORMATION.
01:49:13.350 --> 01:49:14.538
Kay: Yes, I think so. 
01:49:14.538 --> 01:49:27.533
Kay: That film of the little girl, 22 months old, using a Mac very confidently -- she'd already been using it for about six months or so -- strikes a lot of people in a way that words don't. 
01:49:27.533 --> 01:49:35.987
Kay: Because they see here's this little child, about 70 percent literate in the access part of the Macintosh user interface. 
01:49:35.987 --> 01:49:42.624
Kay: She can start up applications, and do things in them, save them away, and all of those things. 
01:49:42.624 --> 01:49:57.016
Kay: That's what we were trying to do, to extend this thing from being something like a specialized tool or a car to something that is more like media that extends down into childhood and up through the elderly.
01:49:57.016 --> 01:50:08.796
Interviewer: I WANT TO TURN A BIT NOW TO THE PRACTICE OF WRITING BOTH INTERFACES AND APPLICATION SOFTWARE ITSELF, AND SOME OF THE PROBLEMS WITH THE DIFFERENCES BETWEEN SOFTWARE AND HARDWARE. 
01:50:08.796 --> 01:50:21.833
Interviewer: BASICALLY, HOW WOULD YOU CHARACTERIZE THE DIFFERENCE BETWEEN SOFTWARE AND HARDWARE? BECAUSE THE WORD SOFTWARE, AS FAR AS I CAN SEE, ONLY GREW UP ABOUT 1960, IT'S NOT, IT WAS SOMETHING NEW IN A WAY.
01:50:21.833 --> 01:50:27.522
Kay: That's true although the notion, the notion of the stored program goes back a long way. 
01:50:27.522 --> 01:50:34.892
Kay: But I think the, for me there isn't any real difference, that hardware is just software that's crystalized early. 
01:50:34.892 --> 01:50:42.973
Kay: Because basically what you always have is something that you can remember in terms of some medium that can take on markings. 
01:50:42.973 --> 01:50:45.752
Kay: And there are different kinds of markings. 
01:50:45.752 --> 01:50:52.476
Kay: Then you have to have something that allows you to change those markings and read them and change them. 
01:50:52.476 --> 01:50:59.910
Kay: And the simplest kind of computer you can build is one that only has a couple of states in it and it's all memory. 
01:50:59.910 --> 01:51:03.918
Kay: It's practically a clock and everything is out on the memory. 
01:51:03.918 --> 01:51:06.762
Kay: So there's almost no hardware there at all. 
01:51:06.762 --> 01:51:23.700
Kay: And the main reason there's a fair amount of bits in the, the hardware of today's computers is there are a lot of functions you would like to compute rapidly and so there are special purpose little pieces of logic in there for doing fast arithmetic and so forth.
01:51:23.699 --> 01:51:31.526
Interviewer: AND THAT GREW OUT OF THIS HISTORICAL ACCIDENT THAT THE FIRST FUNCTIONS PEOPLE WANTED TO COMPUTE WERE COMPUTATIONAL. 
01:51:31.526 --> 01:51:35.034
Interviewer: SO IT MADE SENSE TO PUT IN SPECIAL CIRCUITS TO DO...
01:51:35.034 --> 01:51:36.883
Kay: To do arithmetic and stuff. 
01:51:36.883 --> 01:51:59.791
Kay: Yeah, I think, I think it definitely is true and there, there have been computer designs and computers built that look at their memory in a completely different way, of doing content-addressed storage and having many thousands of processors looking at storage at the same time where hardly anything resembling arithmetic is done most of the time. 
01:51:59.791 --> 01:52:09.100
Kay: But in fact, it doesn't matter, because arithmetic itself is just a manifestation of a particular way of putting the logic elements together.
01:52:09.100 --> 01:52:16.770
Interviewer: SO AT ITS VERY BASIC LEVEL -- THE WAY TURING MIGHT HAVE THOUGHT ABOUT THIS -- THIS IS A GENERAL PURPOSE MANIPULATOR OF SYMBOLS. 
01:52:16.770 --> 01:52:20.904
Interviewer: IT TAKES SOME MARKINGS, TRANSFORMS THEM, AND PUTS OUT OTHER MARKINGS.
01:52:20.904 --> 01:52:34.360
Kay: Right, right and there's a trade-off between the number of different kinds of markings that you want to have the memory store, and the amount of logic that you need to be able to carry out computing functions.
01:52:34.730 --> 01:52:42.395
Interviewer: IF WE TAKE AN AVERAGE COMPUTER IT'S HARDWARE CAN CARRY OUT, WHAT, JUST ABOUT A HUNDRED BASIC FUNCTIONS?
01:52:42.395 --> 01:52:47.454
Kay: Sometimes, yeah, these days they're usually up in the range of 300 or so. 
01:52:47.454 --> 01:53:00.648
Kay: I think for, for most people trying to understand how a computer works down inside, it's actually mostly memory, a vast amount of very undifferentiated stuff that is just for holding markings. 
01:53:00.648 --> 01:53:06.459
Kay: Then there's a very small amount of logic that carries out a few basic instructions. 
01:53:06.459 --> 01:53:17.807
Kay: And you can think of all of the rest of the hundreds of instructions as things that the basic instructions could carry out but have been encoded especially for speed.
01:53:17.807 --> 01:53:25.682
Interviewer: AND THEN WHAT THE PROGRAMMER HAS TO DO, IS USING THESE AVAILABLE FACILITIES IT HAS TO INSTRUCT IT TO DO OTHER THINGS...
01:53:25.682 --> 01:53:35.672
Kay: Yeah, well most good programmers are relatively lazy, so the last thing they want to do is spend a lot of time grubbing around down in the machine code of the computer. 
01:53:35.672 --> 01:53:44.833
Kay: So, usually what they do is, they write a couple of pieces of software, one is called an operating system, another one is called the programming language. 
01:53:44.833 --> 01:53:47.907
Kay: And often they are both the same, as Smalltalk was. 
01:53:47.907 --> 01:53:54.113
Kay: And what, what that piece of software does is to create a virtual machine which is much more hospitable. 
01:53:54.113 --> 01:54:00.142
Kay: And so it's a, the machine simulating a much nicer machine and all of a sudden life is much more fun. 
01:54:00.142 --> 01:54:04.339
Kay: And often you will use that machine to simulate an even nicer machine. 
01:54:04.339 --> 01:54:19.353
Kay: Eventually things slow down so that the, the most wonderful machine you could have might run too slowly to be interesting, but some people still like to program in terms of these highly idealized machines because maybe they'll be built one of these days.
01:54:19.353 --> 01:54:25.416
Interviewer: SO IN A SENSE ARE YOU TELLING US THAT WHAT WE SEE ON OUR MACINTOSHES IS A MUCH MORE PLEASANT MACHINE...?
01:54:25.416 --> 01:54:36.469
Kay: Yes, in fact the user interface you can think of as the last layer that is designed to further sweeten the realities of all these different layerings that are going on. 
01:54:36.469 --> 01:54:58.577
Kay: Most important thing is it's, it's, when your doing when you're cooking a cake, baking a cake in the kitchen, you don't have to worry about the details of organic chemistry, because they're already subsumed by the ingredients that you have and the recipes are there to make sure that what you have converges on a cake rather than a mess. 
01:54:58.577 --> 01:55:14.340
Kay: And for exactly the same reason people like to confine where they're working into an area where they know what roughly is going to happen and if they, that area doesn't work out well, then they'll go to a deeper lever and make a few changes.
01:55:14.340 --> 01:55:19.884
Interviewer: NOW ALL OF THIS OF COURSE DEPENDS ON THE COMPUTER BEING ABLE TO CARRY OUT INSTRUCTIONS FAST? OTHERWISE WE WOULDN'T BE HAVING THIS CONVERSATION...
01:55:19.884 --> 01:55:24.152
Kay: Simulation would not be that much fun if it were really slow. 
01:55:24.152 --> 01:55:38.678
Kay: Right, as it was when people, when they had to just calculate simple trajectories of, of shells in World War II, they'd have 300 or 400 people on desk calculators just calculating a simple ballistic trajectory. 
01:55:38.678 --> 01:55:47.490
Kay: That was a simulation and in wartime in was deemed important enough to put these 400 people to work for days doing these things.
01:55:47.489 --> 01:55:59.131
Interviewer: NOW, BEFORE THE COMPUTER WAS BUILT, ALAN TURING, APPROACHING THE SUBJECT FROM A DIFFERENT POINT OF VIEW SPOKE OF A VERY SIMPLE MACHINE WHICH COULD IMITATE ALL OTHER MACHINES. 
01:55:59.131 --> 01:56:08.578
Interviewer: THE DIGITAL COMPUTER IS AN EXAMPLE OF ONE SUCH SORT OF MACHINE, ISN'T IT? WHAT DOES IT MEAN THEN IN THAT SENSE TO CALL IT A UNIVERSAL MACHINE?
01:56:08.578 --> 01:56:13.693
Kay: Well I think it's one of the niftiest things to wrap your head around. 
01:56:13.693 --> 01:56:29.182
Kay: And that is that regardless of what kind of thing you have, if it has a few basic properties like a memory and the ability to put symbols into memory and take them out and make changes and make a few tests on them. 
01:56:29.182 --> 01:56:38.115
Kay: That is enough machinery to enable you to simulate any computer that has ever existed or any computer that will ever exist. 
01:56:38.115 --> 01:56:43.303
Kay: How interesting the result will be depends on fast the simulation runs. 
01:56:43.303 --> 01:56:55.694
Kay: But in fact it's, people sometimes think that a little machine on a desk or even a Wizard, a Sharp Wizard calculator is a different kind of thing than a big Cray computer. 
01:56:55.694 --> 01:56:59.008
Kay: But in fact, they are the same kind of thing. 
01:56:59.008 --> 01:57:11.328
Kay: You could calculate one of the greatest pieces of 3D graphics on a Sharp Wizard given enough centuries to do it and enough external memory to put parts of the calculation.
01:57:11.328 --> 01:57:22.007
Interviewer: SO THIS MACHINE, EVEN THOUGH IT WAS BUILT MAINLY TO DO SCIENTIFIC CALCULATIONS, SOME PEOPLE REALIZED RIGHT FROM THE BEGINNING THAT IT HAD JUST ENORMOUS POTENTIAL.
01:57:22.007 --> 01:57:33.169
Kay: Yes, in fact the, the first person who seemed to realize it was Ada Augusta Lovelace who was the side-kick of Babbage and, and maybe history's first programmer. 
01:57:33.169 --> 01:57:55.632
Kay: And she wrote in one of her papers that, she said that "the analytic engine weaves algebraic patterns just as the Jacquard loom weaves patterns in silk." And she understood that the generality of representation was the same kind as you can represent in books which is namely the, the kinds of things that we can talk about. 
01:57:55.632 --> 01:58:04.090
Kay: It wasn't restricted to just numeric calculations but it extended into the realm of general symbolisation of -- of models.
01:58:04.090 --> 01:58:09.627
Interviewer: THIS AMAZING CAPACITY HAS A VERY SEDUCTIVE QUALITY ABOUT IT.
01:58:09.627 --> 01:58:11.224
Kay: It is to us. 
01:58:11.224 --> 01:58:11.962
Kay: Right.
01:58:11.962 --> 01:58:27.845
Interviewer: I'M THINKING OF SAY IN THE LATE '50S AT MIT, SOME OF THE EARLY HACKERS -- ONCE PEOPLE WHO REALIZED THE POTENTIAL THAT THEY COULD MAKE THIS MACHINE DO THIS, THAT, AND THE OTHER -- OR IVAN SUTHERLAND OR WHOMEVER YOU MENTIONED...
01:58:27.845 --> 01:58:39.400
Kay: Yeah, I think two, two things happened, the, the Turing thing was there and most of the early computer people either were mathematicians or had a lot of math in their background. 
01:58:39.400 --> 01:58:42.950
Kay: And there were other formulations like that of Turing. 
01:58:42.950 --> 01:58:47.081
Kay: Godel's theorem also was a way of building a universal machine. 
01:58:47.081 --> 01:58:57.861
Kay: And there is a thing called Post's production system which is a similar -- they're all studying mathematical problems, but they translated well to computer machinery. 
01:58:57.861 --> 01:59:00.765
Kay: And most computer people were aware of them. 
01:59:00.765 --> 01:59:14.256
Kay: Then the second thing that had to happen was that, there had to be some way of believing that the computer could get big enough and fast enough so that any, anything that Turing said made any practical sense. 
01:59:14.256 --> 01:59:17.613
Kay: You know, so you have to have both of those things. 
01:59:17.613 --> 01:59:34.460
Kay: And what's happened is that very early on in the -- even in the '60s but especially in the '70s -- people regularly would build very simple computers and then use those simple computers that ran very quickly to simulate the kind of hardware they really wanted. 
01:59:34.460 --> 01:59:36.655
Kay: That's what we did at Xerox PARC. 
01:59:36.655 --> 01:59:42.722
Kay: Chuck Thacker who did the Alto, built a machine with almost no logic for that period of time. 
01:59:42.722 --> 01:59:47.563
Kay: I mean 1972 it had two, it had about 160 chips, two boards worth of chips. 
01:59:47.563 --> 01:59:49.823
Kay: So, that was very, very few gates. 
01:59:49.823 --> 01:59:51.565
Kay: But it ran extremely fast. 
01:59:51.565 --> 01:59:55.955
Kay: And it ran about five times faster than it's, than its main memory. 
01:59:55.955 --> 02:00:00.021
Kay: And because of that the Alto could be many different machines. 
02:00:00.021 --> 02:00:03.636
Kay: It was a Smalltalk machine when we ran Smalltalk on it. 
02:00:03.636 --> 02:00:06.734
Kay: It was a Mesa machine when they ran Mesa on it. 
02:00:06.734 --> 02:00:09.704
Kay: And it could take on different personalities. 
02:00:09.704 --> 02:00:27.455
Kay: And I've always thought that was a really good way to go until you actually know what the, the biblical truth is on what your computer architecture should be, why not have a computer that you can mold into the kind of virtual machine that you want, right at the lowest level.
02:00:27.454 --> 02:00:34.813
Interviewer: THIS TRACTABILITY, THIS MOULDABILITY GIVES THE COMPUTER A ROMANTICISM THAT OTHER MACHINES LACK, DOESN'T IT?
02:00:34.813 --> 02:00:44.675
Kay: Yeah, well I don't -- I agree on the romantic part but of course, I'm fairly romantic about musical instruments so that, you know, most musicians are. 
02:00:44.675 --> 02:00:47.287
Kay: Most musicians adore their instruments. 
02:00:47.287 --> 02:01:05.640
Kay: And, so, I think that the, from, from my standpoint my romance is very much connected to the same way I think about other marvelous contraptions that we've made, including musical instruments but sail planes, the kind of marvelous inventions that Paul McCready makes, and so forth.
02:01:05.640 --> 02:01:08.207
Interviewer: BUT THEY DON'T HAVE THIS CAPACITY OF BUILDING A PRVATE UNIVERSE DO THEY?
02:01:08.207 --> 02:01:09.251
Kay: No.
02:01:09.251 --> 02:01:10.176
Interviewer: THIS IS SPECIAL TO THE COMPUTER...
02:01:10.176 --> 02:01:16.109
Kay: No, in the, with a musical instrument you can build a private universe for somebody else. 
02:01:16.109 --> 02:01:22.109
Kay: That is, you can make one, but it doesn't have the tangibility that that the computer has. 
02:01:22.109 --> 02:01:37.208
Kay: On the other hand, it's worthwhile remembering though that no matter what we build on the computer and no matter what appears on the screen, it doesn't have any particular sense to it unless some human is there comprehending it. 
02:01:37.208 --> 02:01:54.416
Kay: So, it does have something in common with, with building a beautiful piece of music, that there has to, ultimately there is a listener, it might be just the composer, but what comes out, has to, in some way, come back into the human sensorium and be understood.
02:01:54.417 --> 02:01:59.817
Interviewer: NOW, YOU USE A METAPHOR WHICH IS QUITE HELPFUL IN UNDERSTANDING PROGRAMMING OF A PUPPET THEATRE. 
02:01:59.817 --> 02:02:01.765
Interviewer: I WONDER IF YOU COULD GIVE US THAT.
02:02:01.765 --> 02:02:05.513
Kay: Yeah, I think I got talked into that by some, some magazine. 
02:02:05.513 --> 02:02:14.113
Kay: One of the traditional ways of programming on a computer is to think of the memory part of it as being inert like ingredients in a kitchen. 
02:02:14.113 --> 02:02:30.823
Kay: And to think of the programs that you write as being like the recipes and then the central processor is kind of like the cook whose looking at the recipe book and then goes over and stirs the ingredients and, if you're lucky, you wind up with, with something good to eat. 
02:02:30.823 --> 02:02:40.222
Kay: And, another way of thinking about that is, is that's like a puppet theatre because the puppets are all inert and there are puppet masters going around. 
02:02:40.222 --> 02:02:53.061
Kay: In the computer it's a very energetic puppet master because there's one, generally, goes around twitching all of the strings of all of the puppets fast enough so that it seems like something real is going on. 
02:02:53.061 --> 02:03:00.064
Kay: And, but another way of looking at programming is to say, - well, why not let the puppets pull their own strings. 
02:03:00.064 --> 02:03:12.227
Kay: So, we'll let each puppet, have, in effect, its own little computer within this larger computer and we'll let them be much more self contained, there won't be puppet masters from, from the outside. 
02:03:12.227 --> 02:03:15.237
Kay: And that's called - object-oriented programming. 
02:03:15.237 --> 02:03:19.660
Kay: And the benefits of it are: simplicity and ease of writing the programs.
02:03:19.661 --> 02:03:32.064
Interviewer: IN A PROCEDURAL PROGRAMMING, IF I WANT TO TELL MY PUPPET MASTER WHAT TO DO, I HAVE TO LIST EVERYTHING ABSOLUTELY IN THE RIGHT ORDER. 
02:03:32.064 --> 02:03:38.127
Interviewer: IN OBJECT-ORIENTED, I BUILD MY OBJECTS, GIVE THEM BEHAVIOR AND...
02:03:38.127 --> 02:04:03.180
Kay: Yeah, well there's, I think there's a continuum from totally lock-step proceduralism to trying to deal with multiple processes, to having objects which have many of their processes inside of them and act much less sequential and so forth to what's coming in the future which is something called agent-oriented programming or modular control programming -- it hasn't got a good name yet. 
02:04:03.180 --> 02:04:10.625
Kay: But of something where, where the elements are much more like biological cells, that they're quite self contained. 
02:04:10.625 --> 02:04:21.047
Kay: They may spend 90 percent of their energies just maintaining their own equilibrium and maybe only 10 percent of them contributes to the larger system as a whole.
02:04:21.047 --> 02:04:25.328
Interviewer: AND THESE ARE PRESUMABLY EVEN HIGHER LEVELS OF VIRTUAL MACHINE, AS IT WERE?
02:04:25.328 --> 02:04:26.990
Kay: Yes, that's a very good way of thinking about them.
02:04:26.990 --> 02:04:36.518
Interviewer: EVERY TIME WE GO FURTHER UP TO A HIGHER LEVEL OF VIRTUALITY THAT SUITS US, IT GENERALLY MEANS THAT THE COMPUTER HAS TO WORK EVEN HARDER.
02:04:36.518 --> 02:04:42.310
Kay: Yeah, oh, I don't think it's, the computer is, is only working at one level, any given computer. 
02:04:42.310 --> 02:04:45.834
Kay: It's always executing two million instructions per second. 
02:04:45.834 --> 02:04:47.864
Kay: So you can't make it work harder. 
02:04:47.864 --> 02:04:57.539
Kay: But it's like a, if you have a, a 5 horsepower go-cart and you put it up various grades of hills, there will be a hill eventually that it won't be able to climb. 
02:04:57.539 --> 02:05:02.794
Kay: It's always putting out at 5 horsepower and it needs 10 to get up that particular hill. 
02:05:02.794 --> 02:05:09.900
Kay: And that's what happens, you just, things start slowing down as you put more and more burden on an old-style processor.
02:05:09.900 --> 02:05:19.006
Interviewer: CAN YOU GIVE ME AN IDEA OF WHAT'S GOING ON IF I'M LOOKING AT A SCREEN AND I WANT TO DO SOMETHING LIKE ON OPEN A FILE ON THE MAC DESKTOP... 
02:05:19.006 --> 02:05:22.478
Interviewer: SOME NOTION OF HOW MANY OPERATIONS MIGHT BE INVOLVED?
02:05:22.478 --> 02:05:30.375
Kay: Well, it's, you can figure it out because the typical Mac these days executes about two million instructions per second. 
02:05:30.375 --> 02:05:41.601
Kay: And if it takes, well say opening a file it has to go out to the disc so it's complicated because you, now it depends on the speed of the desk moving stuff back and forth. 
02:05:41.601 --> 02:06:06.469
Kay: But, suppose you're just in the Multi-Finder and you go, you're in this window doing something and you put the mouse in another window and the window comes up to the top of the screen and you can easily, you just get out a stopwatch, if it takes us, if it's a big, lumbering thing and it takes about a second to rebuild the screen then two million instructions have been executed. 
02:06:06.469 --> 02:06:11.364
Kay: If it takes two seconds then four million instructions have been executed. 
02:06:11.364 --> 02:06:17.108
Kay: And, it's always executing that many instructions per second even when it's just idling.
02:06:17.108 --> 02:06:21.676
Interviewer: THERE'S IMMENSE, MONUMENTAL COMPLEXITY GOING ON UNDERNEATH THESE SIMPLE THINGS...
02:06:21.676 --> 02:06:29.734
Kay: Yeah, and often the complexity is something that is a by-product of the way the system was programmed rather than being intrinsic.
02:06:29.734 --> 02:06:40.350
Interviewer: I WANT TO MOVE ON NOW -- I'M GOING TO MOVE ON TO YOUR CURRENT WORK WITH THE SCHOOLS, BUT I WANT FIRST FOR YOU TO TALK ABOUT THE IDEA OF TOOLS AND AGENTS, HISTORICALLY, AND SO FORTH.
02:06:40.350 --> 02:06:47.942
Kay: Okay, well the way, the way I think about tools and agents is, you need some sort of perspective to think about them. 
02:06:47.942 --> 02:06:55.277
Kay: And I think about them in terms of the way we've extended ourselves over the last several hundred thousand years. 
02:06:55.277 --> 02:07:10.011
Kay: And when you, when you say extension to somebody they almost always come back and say "tools." And indeed there have been levers and wheels and physical tools, but there have also been mental tools like language and mathematics. 
02:07:10.011 --> 02:07:15.802
Kay: And I think of tools as being extensions of the gesture, as a way of manipulating things. 
02:07:15.802 --> 02:07:19.855
Kay: You're manipulating symbols when you're dealing with language. 
02:07:19.855 --> 02:07:26.868
Kay: You're bringing things that are hard to deal with into your power via your hand or something like your hand. 
02:07:26.868 --> 02:07:30.150
Kay: So the 'M-word,' to me, for tools is manipulation. 
02:07:30.150 --> 02:07:34.203
Kay: And tools are things that you watch while you manipulate them. 
02:07:34.203 --> 02:07:41.345
Kay: And then the other main way people have extended themselves is by getting other people to take on their goals. 
02:07:41.345 --> 02:07:51.318
Kay: Mumford called this making "mega-machines." He said that for most of human history most machinery made by humans has had other humans as its moving parts. 
02:07:51.318 --> 02:07:57.817
Kay: So we make cities and cultures, and there are groups trying to do this and groups trying to do that. 
02:07:57.817 --> 02:08:02.642
Kay: And, there are fewer goals in those kinds of groups than there are people. 
02:08:02.642 --> 02:08:09.141
Kay: They've taken on each other's goals, traded off, in one way or the other and they are communicating. 
02:08:09.141 --> 02:08:15.124
Kay: And the kind of entity that can take on your goals and act in your behalf, we call an agent. 
02:08:15.124 --> 02:08:19.049
Kay: So an agent is something that watches you and you manage it. 
02:08:19.049 --> 02:08:23.489
Kay: So the 'M-word' is management for agent, and manipulation for tools. 
02:08:23.489 --> 02:08:24.390
Kay: And in the ...
02:08:24.390 --> 02:08:28.957
Interviewer: YOU'RE SAYING THAT AGENTS HAVE BEEN PEOPLE UP TO NOW, WHEREAS TOOLS HAVE BEEN ....
02:08:28.957 --> 02:08:42.702
Kay: Yeah, you could, you could say that that a shepherd dog, or maybe a horse, maybe a thermostat is something you have to work fairly hard with to build a thermostat to get it to take on the goal of what temperature that you, that you want. 
02:08:42.702 --> 02:08:45.589
Kay: But, by and large, they've been people up to now. 
02:08:45.589 --> 02:08:57.660
Kay: And the interesting thing about computers, when you're building agents on them, is the agents don't have to be as smart as people, just like a thermostat does not have to be as smart as a person to be useful. 
02:08:57.660 --> 02:09:06.149
Kay: The main thing you want it to do is to be able to take on some collection of goals and to be able to deal with those goals while you're not around.
02:09:06.149 --> 02:09:09.766
Interviewer: SO AN AGENT HAS TO HAVE SOME ARTIFICIAL INTELLIGENCE IN IT?
02:09:09.766 --> 02:09:11.999
Kay: Yeah, if you like to use that, that term. 
02:09:11.999 --> 02:09:16.198
Kay: You could call it "flexible competence" and make it sound a little less loaded.
02:09:16.198 --> 02:09:29.605
Interviewer: SO HOW WOULD THIS WORK? YOU FEEL THAT THE COMPUTERS OF THE NEXT 10, 20 YEARS IN ADDITION TO HAVING THE RICH INTERFACES WE HAVE, WILL HAVE PERSONAL AGENTS AS WELL?
02:09:29.605 --> 02:09:41.460
Kay: Yeah, one of the ways I think about looking ahead into future is to try and find analogies that might actually make some sense, and also to look for driving forces. 
02:09:41.460 --> 02:09:51.805
Kay: So the, one of the driving forces for the PARC-type user interface came out just from there being inexpensive ICs...integrated circuits around. 
02:09:51.805 --> 02:10:10.126
Kay: You start getting a proliferation of computers that are inexpensive enough for people to buy, and all of a sudden the kinds of people who might want to use computers changes completely, and so all of a sudden you need a much easier to use user interface. 
02:10:10.126 --> 02:10:17.238
Kay: There is a driving force now to do something because it, it isn't just graduate students any more. 
02:10:17.238 --> 02:10:31.463
Kay: To me the driving force for agents is pervasive networking, because the techniques used on the Macintosh don't work well when you're connected up to a trillion objects scattered all over the world. 
02:10:31.463 --> 02:10:37.426
Kay: You need something looking for potential objects that will further your own goals. 
02:10:37.426 --> 02:10:41.593
Kay: And you need that something to be looking 24 hours a day. 
02:10:41.593 --> 02:11:03.865
Kay: So we think that what, what we'll have is, you know, 10, 15, 20 or more little agents -- many of them not particularly intelligent but able to flexibly take on a goal that we have like, an example of one is an agent that goes out and finds you the newspaper you'd most like to read at breakfast every morning. 
02:11:03.865 --> 02:11:05.948
Kay: So, all night long it works. 
02:11:05.948 --> 02:11:16.222
Kay: It can touch dozens of different news sources, the Associated Press, New York Times and so forth, looking for things that are relevant to you. 
02:11:16.222 --> 02:11:20.892
Kay: It can go to other sources for getting photographs and so forth. 
02:11:20.892 --> 02:11:29.873
Kay: It can do the news gathering with a particular interest in the kinds of things that you're...that you have been involved in. 
02:11:29.873 --> 02:11:42.302
Kay: A headline could say, "New fighting in Afghanistan," or it might say, "Your 3 o'clock meeting was cancelled today," because news now could involve your own electronic mail. 
02:11:42.302 --> 02:11:53.940
Kay: The sidebar might say, "Your children slept well last night." And this is an interesting example of an agent because it's one that was built about ten years ago. 
02:11:53.940 --> 02:11:58.826
Kay: It did not require a large amount of intelligence in order to work. 
02:11:58.826 --> 02:12:15.996
Kay: It's major strength was its ability to work 24 hours a day while you weren't there and with limited ability of doing matching against what you said you wanted and what it thought you wanted, it could do a great deal of useful work for you.
02:12:16.251 --> 02:12:35.203
Interviewer: SO WE THINK OF -- THERE HAVE BEEN A NUMBER OF REVOLUTIONS IN THE HISTORY OF COMPUTERS SO FAR, BUT WE'RE THINKING NOW -- MOST PEOPLE THINK OF THE COMPUTER AS A STAND ALONE, DESKTOP OBJECT, RIGHT? WHERE DO YOU SEE -- TYING THIS IN WITH YOUR DYNABOOK CONCEPT, WHAT YOU'VE BEEN SAYING ABOUT NETWORKING AND AGENTS -- WHERE DO YOU SEE THE NEXT THING TAKING US?
02:12:35.203 --> 02:12:45.526
Kay: Yeah, but I think the way I think about that is the, these three very different ways of relating the, the human to the computer. 
02:12:45.526 --> 02:13:07.450
Kay: One is this institutional way of the time-sharing mainframe, one is the desk top way where you control all the stuff and then the, the third way is the intimate way, which is the, is the Dynabook way which is continuously connected into the worldwide informational network. 
02:13:07.450 --> 02:13:08.650
Kay: So, it's part--
02:13:08.650 --> 02:13:08.537
Interviewer: WHAT IS A DYNABOOK EXACTLY?
02:13:08.537 --> 02:13:12.120
Kay: Well a Dynabook is sort of a figment of imagination. 
02:13:12.120 --> 02:13:15.297
Kay: It's a, it was a Holy Grail that got us going. 
02:13:15.297 --> 02:13:21.990
Kay: It was a cardboard model that allowed us to avoid having meetings about what we were trying to do. 
02:13:21.990 --> 02:13:28.142
Kay: It was a lot of different things but it was basically a service concept not a box concept. 
02:13:28.142 --> 02:14:03.365
Kay: So, there were actually three physical renderings of the Dynabook we thought about: one was the notebook, one was something that went in your pocket that had a head-mounted display and glasses, as I had worked with Ivan Sutherland's head-mounted display in the '60s, and then one was, Nicholas Negroponte's idea of the sensitive wrist watch that in the 20 years future or so when there is a network wherever there is an electric plug in the wall, then your user interface will follow you from room to room as, as you go. 
02:14:03.365 --> 02:14:11.884
Kay: Everything has become pervasive you don't have, need to carry a big computer or even a tiny computer around, around with you. 
02:14:11.884 --> 02:14:21.349
Kay: So, the, the whole idea behind the Dynabook was the kinds of service and your relationship to it which should be intimate, casual, mundane. 
02:14:21.349 --> 02:14:36.087
Kay: You should be able to aspire to the heights on it just as you can when you learn English, you can aspire to the heights of Shakespeare, but you're not forced to do what Shakespeare did every time you use the language. 
02:14:36.087 --> 02:14:46.296
Kay: So, this idea of having a nice, connected ramp without lots of bumps and so forth in it -- as Seymour Papert likes to say, "low threshold, no ceiling."
02:14:56.881 --> 02:15:11.393
Interviewer: NOW GIVEN YOU HAVE THAT CONCEPT OF THE FUTURE, YOUR CURRENT WORK AT THE MOMENT AT THE OPEN SCHOOL HERE IN LOS ANGELES WITH CHILDREN WHO MAY INHERIT SUCH A MARVELOUS COMPUTER, WHAT ARE THE OBJECTIVES OF THIS WORK?
02:15:11.393 --> 02:15:31.198
Kay: Well, it's several, several one is that Apple traditionally has been a company very interested in the educational process and helping children in, in schools and, so we do a lot of things in this school that have to do with thinking about how schooling might be in the future. 
02:15:31.198 --> 02:15:50.073
Kay: Then, specifically, one of the things that we do is a project that's been going on for about four years now to try and help find ways that will allow children to be able to write in the computer as fluently as they can now read using the Macintosh user interface. 
02:15:50.073 --> 02:16:11.738
Kay: And what we do, since artificial intelligence is coming along, we're trying to find ways to both understand artificial intelligence and understand how to program it by putting together a set of tools that allow children to do the kind of artificial intelligence programming normally only done by adults.
02:16:11.738 --> 02:16:17.697
Interviewer: NOW THIS IS DONE THROUGH A RATHER AMBITIOUS SIMULATION.
02:16:17.697 --> 02:16:25.018
Kay: Yeah, well our, our, I, we're trying to, I mean you think of adults try and simulate humans and, and so forth. 
02:16:25.018 --> 02:16:28.777
Kay: Humans are pretty tough, nobody has done simulation yet. 
02:16:28.777 --> 02:16:39.529
Kay: I've always felt it would be a good idea to work our way up through the food chain and start off with fairly simple animals, see how they interact with the world. 
02:16:39.529 --> 02:16:42.827
Kay: That's something that children are interested in. 
02:16:42.827 --> 02:17:04.131
Kay: And so quite a few years ago we got the idea that it would be really great if we could give children an environment where they could create ecologies to study animals and plants and then build those models into the computer and see if those models reflected what they thought they understood from the, from the real world. 
02:17:04.131 --> 02:17:10.001
Kay: So, there's a constant comparison between the real world and the and the computer model. 
02:17:10.001 --> 02:17:17.587
Kay: The, the school has torn up part of its playground to make a, a life lab, which has both animals and plants in it. 
02:17:17.587 --> 02:17:21.610
Kay: The classrooms have animal cages and aquariums and so forth. 
02:17:21.610 --> 02:17:24.710
Kay: And so there's a lot of real animals to study. 
02:17:24.710 --> 02:17:38.165
Kay: And then we also have Macintoshes with a new system we've designed called Playground, that tries to bring some of the techniques of artificial intelligence programming to 8, 9, and 10 year-olds right now.
02:17:38.165 --> 02:17:43.061
Interviewer: ARE YOU TRYING TO LITERACY -- COMPUTER LITERACY -- IN CHILDREN? ARE YOU THINKING ABOUT THAT?
02:17:43.061 --> 02:17:45.349
Kay: Well...
02:17:45.349 --> 02:17:45.747
Interviewer: IS THAT WHAT YOU MEAN BY IT, OR...?
02:17:45.747 --> 02:17:58.642
Kay: Yeah, I've never...you know, in one sense I think so, in the sense that I've always wanted to close the loop at least with something that was like reading and something that was like writing. 
02:17:58.642 --> 02:18:09.253
Kay: And right now, the something that's like reading is using the Macintosh user interface language to deal with 9,000 or 10,000 applications that are out there. 
02:18:09.253 --> 02:18:12.879
Kay: That seems to work reasonably successfully right now. 
02:18:12.879 --> 02:18:22.013
Kay: And the equivalent of writing should be something that allows children to aspire to the same kinds of things that are built on the Mac. 
02:18:22.013 --> 02:18:30.743
Kay: Now they may not sit down and do Aldus PageMaker or something like that, because that's something like a large play or something. 
02:18:30.743 --> 02:18:38.399
Kay: But they should be able to see a continuity between what they're doing and these tools that adults make for them. 
02:18:38.399 --> 02:18:53.174
Kay: We want to do something like what Dewey was talking about in the last century, which is, he pointed out that in most of the ages of mankind the games that children played were serious simulations of what the adults did. 
02:18:53.174 --> 02:19:08.688
Kay: So the African child practicing with a spear, or the Eskimo child learning how to kill birds because he's eventually going to have to go and kill seals for food, is doing something that is content-rich relative to the adult world. 
02:19:08.688 --> 02:19:20.507
Kay: But, the 20th century child dressed up in a nurse's suit and playing nursie with her doll has been cut off from the content part of that adult activity, only the form is left. 
02:19:20.507 --> 02:19:26.149
Kay: So the kids are very disenfranchised from most things that are happening to adults. 
02:19:26.149 --> 02:19:45.625
Kay: And one of the things that was noticed right away with computers is that when you put a child on a computer they know they're doing the real thing, that this is, they can see instinctively the continuity between it and the other things that are going -- actually much better than adults do.
02:19:45.625 --> 02:19:53.007
Interviewer: THE COMPUTER, MANY PEOPLE CLAIM, IS GOING TO HAVE A BIG ROLE IN SAVING AMERICAN EDUCATION, AND SO FORTH. 
02:19:53.007 --> 02:20:02.358
Interviewer: AND THIS IS A WORRYING THING, BECAUSE YOU SAID YESTERDAY THAT THE COMPUTER WAS A META-MEDIUM, SO IT CAN BE WHAT WE CHOOSE IT TO BE...
02:20:02.358 --> 02:20:26.974
Kay: Yeah, well, I mean, the story I always tell is - imagine the parents were afraid that their children wouldn't make it in life unless they were musicians, and the State legislature said, "Well, okay, we'll put a piano in every classroom but we don't have enough money to hire musicians, so we'll give the existing teachers two week refresher courses," and music doesn't get into the classroom. 
02:20:26.974 --> 02:20:33.990
Kay: And I think we have a very similar problem when we want to think of the technology as being the magic ointment. 
02:20:33.990 --> 02:20:37.435
Kay: Musicians will tell you, the music isn't in the piano. 
02:20:37.435 --> 02:20:40.066
Kay: If it were, we would have to let it vote. 
02:20:40.066 --> 02:20:47.081
Kay: So, at best what we have is an amplifier and often these things that could be amplifiers will turn people away. 
02:20:47.081 --> 02:20:51.779
Kay: Pianos often turn people away from music rather than turn them towards it. 
02:20:51.779 --> 02:21:11.385
Kay: So, I think the most important thing is to have for people who want healthy schools is to have parental involvement, because down deep it's the value system that the children pick up about what's important in life, that they mainly get from their parents, that is going to condition what they do with their time. 
02:21:11.385 --> 02:21:13.703
Kay: It's hard to learn things in school. 
02:21:13.703 --> 02:21:15.895
Kay: There are lots of things going on. 
02:21:15.895 --> 02:21:23.411
Kay: School, to me, is basically about a resource for finding out that various things existed that you didn't think existed. 
02:21:23.411 --> 02:21:28.798
Kay: But as far as learning them, most of the learning, I think is done outside of school. 
02:21:28.798 --> 02:21:35.375
Kay: And what the child decides to do outside of school with his time is going to depend on the value system. 
02:21:35.375 --> 02:21:46.963
Kay: Once you have that going really well then it's fairly easy to use all kinds of technology because then you will simply amplify out from this interest in getting stuff happening in here-
02:21:46.963 --> 02:21:58.042
Interviewer: INTERESTING THAT THIS MEDIUM SHOULD COME ALONG AT A TIME WHEN THE PREVIOUS IMPORTANT MEDIUM LIKE WRITING, EVERYONE IS SO CONCERNED ABOUT LITERACY IN THE SCHOOLS. 
02:21:58.042 --> 02:22:01.940
Interviewer: DO YOU SEE IT AS A SOLUTION, OR POSSIBLY A WORSE PROBLEM?
02:22:01.940 --> 02:22:24.512
Kay: Well, I think that was one of McLuhan's tongue-in-cheek jokes -- that we've had all these great inventions like the book and they've hardly affected education at all because if you go into most schools in the northern hemisphere you find 30 humans writing down what another human is saying and that's what was going on in Oxford in the 12th century. 
02:22:24.512 --> 02:22:29.091
Kay: So, you know, where is the book in all of this? So I think that the... 
02:22:29.091 --> 02:22:41.087
Kay: the kinds of social whirlpools that exist when you get different kinds of humans together, like teachers and children, are going to have a lot to do whether technology gets used at all. 
02:22:41.087 --> 02:22:54.888
Kay: I think the most important aspects of are, have to do with areas of control and other kinds of things which are, theoretically outside the domain of the education, but a lot of school is about controlling the kids.
02:22:54.888 --> 02:23:04.721
Interviewer: NOW, IF WE'RE LOOKING INTO THIS FUTURE, SOME OF THE THINGS THAT MIGHT BE IMPORTANT, CAN WE COUNT ON THE HARDWARE CONTINUING TO IMPROVE FOR ANOTHER DECADE?
02:23:04.721 --> 02:23:12.659
Kay: Yeah, yeah, we can definitely count on the hardware continuing to improve another decade and probably more. 
02:23:12.659 --> 02:23:23.683
Kay: But I mean just, this is just extrapolation, the current kinds of hardware that we know how to build has a very stable outlook for the next ten years.
02:23:23.683 --> 02:23:32.505
Interviewer: WHAT ABOUT KEY INGREDIENTS FROM SOFTWARE FROM ARTIFICIAL INTELLIGENCE, DO YOU THINK PROJECTS LIKE THE CYC PROJECT ARE GOING TO BE VITALLY IMPORTANT?
02:23:32.505 --> 02:23:40.555
Kay: Well, Cyc Project is one of my favorite projects partly because it's done by one of the smartest guys in the U.S. 
02:23:40.555 --> 02:23:48.534
Kay: in computer science, and partly because it's one of the hardest projects that anybody is trying to do right now. 
02:23:48.534 --> 02:23:57.855
Kay: There are not a lot of researchers working on, what I would call, really frontier difficult projects, and, but this is one of them. 
02:23:57.855 --> 02:24:04.351
Kay: And, it, his success will be and is, is about turning up new ideas for representing things. 
02:24:04.351 --> 02:24:18.050
Kay: Whether the system is actually able to turn into what its design goals say it is, which is a model of human common sense, I don't think is nearly as important as the wake that it's throwing up. 
02:24:18.050 --> 02:24:28.289
Kay: When you got a smart guy working on something really hard and a bunch of people being ingenious about it, you're always going to get good things.
02:24:28.289 --> 02:24:35.394
Interviewer: WHY WOULD IT BE IMPORTANT TO INCORPORATE COMMON SENSE -- A REPRESENTATION OF COMMON SENSE IN FUTURE COMPUTERS?
02:24:35.394 --> 02:24:40.516
Kay: Yeah, it's, that's a good question because common sense is frequently wrong. 
02:24:40.516 --> 02:24:45.638
Kay: Scientific discoveries of the last 300 years have been against common sense. 
02:24:45.638 --> 02:24:54.086
Kay: But, whatever common sense is, it's a kind of underlying fabric for getting between things that we know in much higher detail. 
02:24:54.086 --> 02:25:06.460
Kay: So, one way of thinking about it is there are things, little things that we're expert in are like islands and then there's this ocean that we can paddle around in from island to island. 
02:25:06.460 --> 02:25:09.719
Kay: There's a way to get from one island to another. 
02:25:09.719 --> 02:25:17.103
Kay: And the problem with most expert systems up to now is that they're an island completely surrounded by a cliff. 
02:25:17.103 --> 02:25:21.893
Kay: If you go anywhere off what it's good at, it just drops you completely. 
02:25:21.893 --> 02:25:31.206
Kay: There's no way of paddling to the next thing and, and I think as I said yesterday, somebody, Picasso, I think, said, "Art is not the truth. 
02:25:31.206 --> 02:25:35.929
Kay: Art is a lie that tells the truth." And common sense is not the truth. 
02:25:35.929 --> 02:25:42.781
Kay: But it's a lie that provides a continuous fabric to work around in that we can then delve deeper into. 
02:25:42.781 --> 02:26:03.203
Kay: Another thing about common sense that's kind of interesting is that it might be possible to use the computer to enlarge what we think of as common sense by giving us sensory contact with things we've never been able to have sensory contact with before, like things that are a million times smaller than us. 
02:26:03.203 --> 02:26:11.053
Kay: Because common sense I think has a lot to do with the sensory domain and reasoning from things that are on our scale. 
02:26:11.053 --> 02:26:17.107
Kay: Science, in a very literal sense, is non-sense because it's outside of the sensory domain. 
02:26:17.107 --> 02:26:27.085
Kay: Almost everything that happens in science is very far, you know, just common sense this is solid, (should hit here), common sense says this is solid. 
02:26:27.085 --> 02:26:28.881
Kay: But science says it isn't. 
02:26:28.881 --> 02:26:35.933
Kay: Common sense says the sun is going to come up tomorrow morning and science says no, the earth is turning. 
02:26:35.933 --> 02:26:58.950
Kay: And, yet we still say what time is sunrise tomorrow? So I think the importance of Cyc using common sense has a lot to do with that regardless of whether we are scientists or not, we have this one way of knowing the world, rightly or wrongly that is very comprehensive and gives a sort of universal way of weakly getting from one topic to another.
02:26:58.950 --> 02:27:11.020
Interviewer: WHAT DO YOU THINK THE MAIN LEGACY OF ARTIFICIAL INTELLIGENCE IS?
02:27:11.020 --> 02:27:15.480
Kay: I think, you know, some of my favorite crazy people are AI people. 
02:27:15.480 --> 02:27:20.740
Kay: AI in the '60s was once defined as all that stuff we don't know how to do yet. 
02:27:20.740 --> 02:27:24.136
Kay: And the, to some extent it's been a moving target. 
02:27:24.136 --> 02:27:31.726
Kay: Things, things that were AI problems in the '50s and '60s are now taught as part of computer engineering courses. 
02:27:31.726 --> 02:27:39.382
Kay: And but as far as the AI as something mimicking, in a strong way, human intelligence, we're very far away from it. 
02:27:39.382 --> 02:27:41.313
Kay: And so it, it's a good goal. 
02:27:41.313 --> 02:27:44.043
Kay: It gives you something to, to reach for. 
02:27:44.043 --> 02:28:22.592
Kay: And I think for people in the field who have some biological motivation to their interest, it's a good goal because it has partly to do with understanding more how we do it, wonder if there are alternate ways to do it, can you only do it the way we do it, at what level do we do it? Do we have to do it at the absolutely neuronal level? Do we have to simulate every neuron in a human brain to get artificial intelligence or is there a higher level that we can do it? And those are good questions to ask because if you look at the way for instance biochemistry is done by nature. 
02:28:22.592 --> 02:28:33.378
Kay: It is appallingly inefficient, very low energy transfer the absence of some watcher from the outside saying, oh, yeah it would be much simpler to do it this way. 
02:28:33.378 --> 02:28:41.234
Kay: So that, for instance, the way we do chemistry in a lab and the way nature does biochemistry is completely different. 
02:28:41.234 --> 02:28:43.365
Kay: We do it much more efficiently. 
02:28:43.365 --> 02:28:48.158
Kay: Nature does it much more ingeniously because of the way it's contrived. 
02:28:48.158 --> 02:28:52.952
Kay: And you can learn a lot from looking at the comparison between the two. 
02:28:52.952 --> 02:29:02.672
Kay: And so there, there is a lot of reason to expect that you don't have to go to the neuronal level to be able to do the kinds of things that we do. 
02:29:02.672 --> 02:29:06.934
Kay: But nobody knows whether, what level you actually have to go to.
02:29:06.933 --> 02:29:12.506
Interviewer: YOU MENTIONED YOU WORKED WITH IVAN SUTHERLAND ON THE HEADS-UP DISPLAY. 
02:29:12.506 --> 02:29:21.925
Interviewer: ONE GROUP OF PEOPLE ARGUE THAT STAGE WE'VE GOT TO WITH THE HUMAN COMPUTER INTERFACE, 2D, 2.5D IS JUST A STEPPING-STONE. 
02:29:21.925 --> 02:29:25.692
Interviewer: THAT BEYOND THAT THERE IS THIS VIRTUAL REALITY. 
02:29:25.692 --> 02:29:27.655
Interviewer: WHAT'S YOUR VIEW ON THAT?
02:29:27.655 --> 02:29:37.124
Kay: Well I think, I think people many people will enjoy virtual reality, since many people don't enjoy the current reality. 
02:29:37.124 --> 02:29:40.360
Kay: Television is a kind of virtual reality. 
02:29:40.360 --> 02:29:47.936
Kay: And I think things that go further in that direction will be very popular with a lot of people. 
02:29:47.936 --> 02:29:56.933
Kay: I think the best thing about virtual reality is that you can deal with these things outside of the normal senses. 
02:29:56.933 --> 02:30:05.456
Kay: You can take a trip down into a cell and see how incredibly agitated the thermal properties are down there. 
02:30:05.456 --> 02:30:19.108
Kay: I think all the things that you only can read about now in terms of symbols, you can actually go there and get a much more kinesthetic and visual hit on doing those things. 
02:30:19.108 --> 02:30:24.395
Kay: I think the use of it in fantasy will certainly, certainly happen. 
02:30:24.395 --> 02:30:41.599
Kay: But if you look at what you actually have to do to get good dramatic situations in the theatre, then it's going to be a while before something good can happen in a movie that's partly being generated by your presence. 
02:30:41.599 --> 02:30:50.280
Kay: On the other hand, if you look at a typical Arnold Schwarzenegger shoot-em-up, then those will be easy to do. 
02:30:50.280 --> 02:31:00.303
Kay: Right, because so, I forget what was, what was the name of that movie? I can't remember the name of that movie that he just ...
02:31:00.302 --> 02:31:01.111
Interviewer: TOTAL RECALL.
02:31:01.111 --> 02:31:06.631
Kay: Total Recall, you know Total Recall, somebody said, if you like road accidents, you'll love this picture. 
02:31:06.631 --> 02:31:14.964
Kay: And the, that kind of stuff, you know, where you have, you know, five people you have to kill every 30 seconds or so is very easy to set up in virtual reality. 
02:31:14.964 --> 02:31:18.350
Kay: I'm sure that a large percentage of the population will enjoy it.
02:31:18.925 --> 02:31:19.317
Kay: ... 
02:31:19.317 --> 02:31:26.748
Kay: computer, do a computer simulation that kids could understand from that one.
02:31:28.549 --> 02:31:39.163
Interviewer: THAT'S THE INTERESTING THING, CLEARLY THE FACT THAT YOU CAN MAKE REAL THOUGHT EXPERIMENTS, SO YOU PUT MANY OF THE CLASSIC THOUGHT EXPERIMENTS OF EINSTEIN AND BOHR, YOU COULD DO.
02:31:39.163 --> 02:31:50.618
Kay: Yeah, and of course you have to be careful because because simulations are lies, in a sense, then there is nothing that says the simulation has to be like real life. 
02:31:50.618 --> 02:31:56.345
Kay: I mean you can make, there have been plenty of thought experiments that are wrong. 
02:31:56.345 --> 02:32:00.347
Kay: And most of the great scientists have been good guessers. 
02:32:00.347 --> 02:32:08.697
Kay: And, so you can, you can also set up simulations of situations that don't have anything to do with the physical world... 
02:32:08.697 --> 02:32:12.699
Kay: So you can delude yourself as well as help yourself along.
02:32:12.700 --> 02:32:15.364
Interviewer: AND YOU THINK THAT MIGHT BE ONE OF THE DANGERS?
02:32:15.364 --> 02:32:17.315
Kay: No, I don't think that's a danger. 
02:32:17.315 --> 02:32:26.287
Kay: I think that anytime people try and make models, try and look at their beliefs from different points of view rather than just one point of view, I think is good.
02:32:26.287 --> 02:32:42.579
Interviewer: IF WE LOOK BACK -- I KNOW YOU'VE THOUGHT A LOT ABOUT THE PROBLEMS OF PREDICTING WHAT IS GOING HAPPEN -- IF WE LOOK BACK AT THE HISTORY OF THE COMPUTER, IT SEEMS THAT ALMOST EVERYBODY HAS BEEN QUITE SERIOUSLY WRONG AT EVERY STAGE WITHOUT VERY FEW EXECPTIONS. 
02:32:42.579 --> 02:32:44.727
Interviewer: WHAT LESSONS CAN WE LEARN, IF ANY?
02:32:44.727 --> 02:32:53.892
Kay: Well, I think prediction, there are lots of different ways of doing prediction but the, the worst one in the 20th century has been extrapolation. 
02:32:53.892 --> 02:33:01.739
Kay: So just because something is X and 10 percent in some other direction of X gets you here and so forth, doesn't mean a thing. 
02:33:01.739 --> 02:33:08.080
Kay: It's like, if a computer could do so and so, it would have to be the size the Empire State Building. 
02:33:08.080 --> 02:33:12.600
Kay: Well, that was when people's imaginations were limited by vacuum tubes. 
02:33:12.600 --> 02:33:15.300
Kay: So the extrapolative way, I think, is out. 
02:33:15.300 --> 02:33:39.093
Kay: But the reason the predictions that we made in the late '60s were so good, and the reason Bush's predictions in the '40s were so good, had to do with a completely different way of predicting which had to do with thinking about things that amplify human endeavor and the amount of horsepower available that is interested in making human endeavor be amplified is very, very large. 
02:33:39.093 --> 02:33:53.155
Kay: So, as you can hook into something like say, if you can say, "Oh, the computer is a medium." Then all of a sudden you start seeing what the powers of amplification are and you also start getting ideas about what to do next. 
02:33:53.155 --> 02:33:59.370
Kay: You look at say, Freud's model of human mentality, which is a good one, but it's all about drives. 
02:33:59.370 --> 02:34:02.635
Kay: That doesn't help you much in doing user interface. 
02:34:02.635 --> 02:34:10.607
Kay: You look at Bruner's mental model which is about different ways we have of knowing the world and all of a sudden you get ideas.
02:34:10.608 --> 02:34:19.302
Interviewer: IT'S INTERESTING ISN'T IT THAT ONE OF THE ARGUMENTS THAT SAID THERE WOULD NEVER BE MANY COMPUTERS WAS THE ONE THAT WE WOULD NEVER BE ABLE TO FIND ENOUGH THINGS FOR THEM TO DO.
02:34:19.302 --> 02:34:27.195
Kay: Yes and that's another one of those things is the, again it was looking at the kinds of things that computers are doing now. 
02:34:27.195 --> 02:34:35.088
Kay: And as, as people used to say, "That's right, you, you numbskull," you know, but it was all the new things that they can do. 
02:34:35.088 --> 02:34:47.716
Kay: It's not, we can do we can do payroll on the mainframe when the personal computer came along, it's all those things we can't do on the mainframe like spreadsheets and desktop publishing, and so forth.
02:34:47.717 --> 02:34:52.273
Interviewer: YOU SEE THE FUTURE OF THE COMPUTER IS BECOMING TOTALLY UNREMARKABLE.
02:34:52.273 --> 02:34:53.559
Kay: Well, I would hope so. 
02:34:53.559 --> 02:35:00.656
Kay: Nowadays, well, ten years ago, if you went into somebody's office and you didn't see a phone, that would have been remarkable. 
02:35:00.656 --> 02:35:04.288
Kay: It was the absence of the thing that would have been remarkable. 
02:35:04.288 --> 02:35:16.918
Kay: Nowadays if you go into somebody's office and you don't see a phone, you assume they're wearing one but you do not assume that there is no phone in a person's office because it's something that is noticeable when it's absent. 
02:35:16.918 --> 02:35:21.724
Kay: And the computer right now is still more noticeable by its presence than its absence. 
02:35:21.724 --> 02:35:27.535
Kay: When you go somewhere and somebody doesn't have a computer on them and that becomes a remarkable thing. 
02:35:27.535 --> 02:35:30.050
Kay: Then I think the computer will have made it. 
02:35:30.050 --> 02:35:42.121
Kay: It's destiny is to disappear into our lives like all of our really important technology, the things that we don't think of as technology like wristwatches, and paper and pencil, and clothing and all of those things. 
02:35:42.121 --> 02:35:45.083
Kay: I think the computer's destiny is to be one of those.
02:35:45.083 --> 02:35:52.242
Interviewer: AND IT WILL DISAPPEAR INTO OUR LIVES, EMBODYING ALL PREVIOUS MEDIA, OR MANY PREVIOUS MEDIA AS IT GOES?
02:35:52.242 --> 02:35:53.070
Kay: I think so. 
02:35:53.070 --> 02:36:00.523
Kay: I think we have to be careful because when you simulate one thing by another you usually give up something. 
02:36:00.523 --> 02:36:27.230
Kay: And anybody who has ever seen the Book of Kells in the, for real realizes what you don't get from photographs, realizes what you don't get from printed books, and also realizes what you do get from printed books that...compelling charisma, the transcription of the oral event that was a book like the Book of Kells is completely different from the alienating regularity of machine type. 
02:36:27.230 --> 02:36:30.888
Kay: And both those things have their place in the world. 
02:36:30.888 --> 02:36:39.929
Kay: You'd hate to get rid of one completely and say, "Well, we're replacing it with the new," because I don't think it works that way. 
02:36:39.929 --> 02:36:52.489
Kay: I mean I'm building a rather large baroque pipe organ even though you can, quote, unquote, simulate them on synthesizers and stuff today, and the answer is: you can't simulate them. 
02:36:52.489 --> 02:37:06.774
Kay: You can't get all of the stuff yet, and even if you could, even if you could prove beyond the shadow of a doubt that the waveforms from it [were identical], you still don't get something that looks as neat. 
02:37:06.774 --> 02:37:37.346
Kay: And so, I think if you include all of our senses into an experience that when you simulate something as you always do in science, what you're saying is, "I am going to give up this in order to get that and that's my trade-off right now." But a person who says, "I'm going to use this, and I'm not going to give up any of that stuff," is just fooling themselves because there isn't a complete interconvertability between one medium and another.
02:37:37.346 --> 02:37:52.194
Interviewer: HOW WOULD YOU RATE THE COMPUTER? YOU'VE STUDIED A LOT OF HUMAN HISTORY, IS THIS SOMETHING WE'VE BEEN PRIVILEGED TO LIVE THROUGH? IS THIS REALLY A VERY REMARKABLE DEVELOPMENT?
02:37:52.194 --> 02:37:54.228
Kay: Yeah, well I don't think it... 
02:37:54.228 --> 02:38:00.527
Kay: I think one way of rating the computer is to say it's definitely a thing like the printed book. 
02:38:00.527 --> 02:38:29.987
Kay: It is definitely in an unremarkable stage -- like 30 years after Gutenberg -- and almost certainly if its promise is realized, and it's not just turned into television -- because that's one of the things it can simulate as well -- but if it can deal with all of the range of things it can deal with, and people use it to express all of those things, then it very likely will have the same kind of effect on our civilization as the printed book did. 
02:38:29.987 --> 02:38:35.958
Kay: Whether it has that affect on any given person though, is a completely different question. 
02:38:35.958 --> 02:38:55.313
Kay: Because, as people have noted, the Renaissance has come and gone and we have what we are pleased to call civilization now, and a large percentage of the population, not just in Third World countries but in our own country, have never touched the 20th century as far as it's ideas are concerned. 
02:38:55.313 --> 02:39:07.189
Kay: And in spite of all the libraries with all the books, and all the things, and what books have done to us, a very large percentage of people have never been carried along with them. 
02:39:07.189 --> 02:39:10.601
Kay: And that is very likely to happen with the computer.
02:39:10.601 --> 02:39:15.816
Interviewer: SO WE HAVEN'T REALLY SUCCEEDED WITH THE LAST MAJOR MEDIUM?
02:39:15.816 --> 02:39:30.527
Kay: Yeah, I doubt, it's probably the case that we never succeed with those things, that civilization gets transformed and a certain critical mass of people get transformed by it and they are the ones who transform the civilization. 
02:39:30.527 --> 02:39:36.398
Kay: And then, for one reason or another, a large number of people don't get transformed by it. 
02:39:36.398 --> 02:39:55.368
Kay: But if you -- another way of thinking about is, if you take a look at what the average person who has not been transformed by it, but has gone to college today thinks about the world, it is a little bit better, a little bit richer, I think, than what people thought about the world in 1000 A.D.
02:39:55.368 --> 02:39:55.319
Interviewer: BUT THERE IS A PROBLEM WITH THIS LITERACY THING, YOU SAID, BECAUSE I KNOW YOU THINK OF TELEVISION AS LIKE A MEDIEVAL STAINED GLASS WINDOW IN SOME WAYS... 
02:39:55.319 --> 02:39:55.291
Interviewer: THAT ACTUALLY YOU CAN -- YOU DON'T NEED TO LEARN ANYTHING TO DO IT, IS THAT THE POINT...?
02:39:55.291 --> 02:40:00.597
Kay: Well, you have to learn something because we know that when D.W. 
02:40:00.597 --> 02:40:18.474
Kay: Griffith first invented close-ups, and moving cameras, and montages and stuff, that the audience was a little bit startled, but it didn't take long, once, one pass through it and they got the idea of what was going on. 
02:40:18.474 --> 02:40:28.840
Kay: And so the amount of learning in the visual domain is pretty low compared to what you have to do in doing reading and writing. 
02:40:28.840 --> 02:40:31.044
Kay: And that is a big barrier. 
02:40:31.044 --> 02:40:45.492
Kay: The biggest problem though, I think, is that many people believe that there is an equilibrium between the two media, that what you can say in a book, you can say on television. 
02:40:45.492 --> 02:40:48.839
Kay: And all of the evidence is against that. 
02:40:48.839 --> 02:41:06.552
Kay: What you can do with television are some very important things, you can get people interested, you can give them an emotional hit, you can get them to know somebody in a way they didn't think they could do it before. 
02:41:06.552 --> 02:41:15.612
Kay: You can maybe get them to look, be interested enough to look deeper, but it's very strength is its weaknesses. 
02:41:15.612 --> 02:41:21.081
Kay: Its strength is its involvement, it's weakness is its involvement. 
02:41:21.081 --> 02:41:35.529
Kay: Because in order to think scientifically about the world, you have to be romantic, it's true, but you also have to be able to step back and say, "Gee, I wonder what else it is. 
02:41:35.529 --> 02:41:39.529
Kay: It looks this way, but I wonder what else it is. 
02:41:39.529 --> 02:41:51.692
Kay: I wonder what else is going on." And I don't think television gets people to do that kind of connected thought away from the dominance of the senses.
02:41:51.691 --> 02:42:07.751
Interviewer: THERE'S ALSO A THING YOU WRITE ABOUT CALLED "THE AMPLITUDE PROBLEM," THAT SOME MEDIA REQUIRE MORE CONCENTRATION THAN OTHERS, DON'T THEY? WRITTEN MEDIA DO, AND SOME FORMS OF TELEVISION, SOME FORMS OF GAMES AND SUCH DON'T. 
02:42:07.751 --> 02:42:14.291
Interviewer: THE QUESTION IS, WILL THE COMPUTER DISAPPEAR INTO THE TELEVISION, OR THE OTHER WAY AROUND?
02:42:14.291 --> 02:42:25.205
Kay: I'm not sure whether it requires more concentration, but it may very well be that like you know, some people read well and it's nothing for them to read a book a day. 
02:42:25.205 --> 02:42:27.623
Kay: And other people this is a big deal. 
02:42:27.623 --> 02:42:34.485
Kay: I mean it's a struggle, and what's likely is going on is that most people never learn to read very well. 
02:42:34.485 --> 02:42:43.896
Kay: And so, the amount of concentration they have to put into the mechanics is what's defeats them with the amount of material that has to be read. 
02:42:43.896 --> 02:43:01.345
Kay: And I think it's much more like that because it's remarkable how much concentration you have to put into something like tennis until you learn to play it, or how much concentration you have to put into music on the mechanics until you actually get fluent at playing. 
02:43:01.345 --> 02:43:11.867
Kay: But then, then the hour, once you've gotten to that place then the hours go by without even realizing because you're deep into what the content of the medium is.
02:43:11.867 --> 02:43:19.083
Interviewer: LAST QUESTION, WHAT HAS SURPRISED YOU MOST ABOUT THE HISTORY OF COMPUTING?
02:43:19.083 --> 02:43:45.463
Kay: What surprised me most? Well I think that, I think the thing that surprised me the most is how long it has taken to get ideas out of laboratories into the commercial world, of how many different kinds of inertia there are, both for good reason and for bad reason, but just the sheer amount of time where a decade after an idea is a very short period to see it emerging in the commercial world. 
02:43:45.463 --> 02:43:54.234
Kay: That is certainly surprising to me because most of the scientists who work on these things work on them because they were obvious. 
02:43:54.234 --> 02:43:57.916
Kay: They were so obvious that they just want to make them. 
02:43:57.916 --> 02:44:11.106
Kay: And to have them not be obvious, and to have them have, go, something that was revolutionarily obvious, to have to go through an evolutionary stage that may take 10 or 20 years is quite surprising.
02:44:11.106 --> 02:44:14.763
Interviewer: DO YOU THINK THERE IS ANY WAY OF CUTTING DOWN THAT PERIOD?
02:44:14.763 --> 02:44:33.120
Kay: I don't see it right now, because it's, I think it's I think it's a question of having people grow up being interested in multiple points of view rather than being disturbed when they're shown something outside of their single way of looking at the world. 
02:44:33.120 --> 02:44:39.359
Kay: And our civilization is very prone towards single-minded ways of looking at the world. 
02:44:39.359 --> 02:44:49.757
Kay: We come from a monotheistic religious background, which says there's a right and a wrong, and you're either for God or against God and so forth. 
02:44:49.757 --> 02:44:54.562
Kay: And these attitudes trickle over into our reactions to everything. 
02:44:54.562 --> 02:45:02.594
Kay: If we're doing, what we're doing now is right, then something that's different from it can't possibly be right. 
02:45:02.594 --> 02:45:07.757
Kay: The Japanese seem to be a little more flexible in some of those scores. 
02:45:07.757 --> 02:45:16.219
Kay: They have several religions existing side by side in Japan, and many of the people adhere to several of them at once. 
02:45:16.219 --> 02:45:18.585
Kay: They don't see any big conflict. 
02:45:18.585 --> 02:45:29.915
Kay: And I think any civilization that can treat ideas as interesting, as more interesting in an array than as treated singly, is going to make it into the future.