# How to invent the future (part 2)

**Author:** Alan Kay
**Type:** Video
**URL:** https://www.ycombinator.com/library/76-how-to-invent-the-future-part-2
**YouTube ID:** 1e8VZlPBx_0

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Alan Kay, one of the pioneers of personal computing, speaks about the history of the technology we know today.

## Transcript

So I kept on rewriting the title. This is not a bad title for this class. Another way of looking at it is instead
of trying to move forward from here, where everything is confusing, and
the present looks like reality. We want to go out to the future and
bring it back.

And we talked about some process and
methods, today we're going to talk about
a few of the gazillion things. Of course I didn't get done last
week which made this week even more. And finally, I decided **** it
I'm going to do both of these talks again without an audience to
do them to their natural length. Because the destiny for
this is being online and online people are not
confined to 50 minute hours. I'm sure Sam was all for that, great.

So again, here's my email address. Now, of all the people who are tuned
into this talk and in the classroom, I got three emails. One of which was interesting. That means that either or both of my talk isn't interesting,
or you're not interesting, or both. So try and, at least,
disabuse me of the latter. Okay, to start off with,
here's Leonardo, pretty smart guy.

Imagine if you were born
with twice Leonardo's IQ. Think of how easy it would
be to get into Stanford. Maybe you do have twice Leonardo's IQ. But suppose you were born with
twice Leonardo's IQ in 10,000 BC. How far are you going to get? Zero, zip, right? Before they burn you at the stake,
or whatever they did back then. Yeah, so here's a guy with nowhere
near Leonardo's IQ, Henry Ford.

And whereas Leonardo could
not invent a single motor for any of his vehicles, think about that. So he was smart, but he wasn't that smart. Henry Ford was able to put together
processes that allowed him to make millions and millions of cars for
about, sell them for $800 a piece. And the difference between the two was
that Ford was born into the right century, and Leonardo was born
into the wrong century. And so the knowledge that had
accumulated in the 19th century made

much more difference than
any level of smartness. And where did that knowledge come from, it came might as well pick Newton
if you're going to pick anybody. It came because the context was
changed from the Middle Ages and the Renaissance to something completely
different in the 17th century. And Newton made the biggest
change of anybody. And so we can call that
change a change in outlook. We can call it a change in context, world
view, point of view, whatever you want.

So when I'm numbering rules for you I
decided to go back and start with zero. So the zeroth rule here,
probably the most important one is to make progress here,
let me move this guy off. Context or
point of view is worth 80 IQ points. If you've got the context of science and
math, you're a gazillion of times smarter, effectively, than the smartest
people of antiquity like Archimedes.

A person who learns calculus
with an IQ of 110 or 120 can do things that the greatest
geniuses of the past can't do. Okay, so we can sum that up by saying knowledge is silver, context is gold. And, IQ is just lead. It's a lead weight on you. Biggest problem with most people
who are at your level and going to the next level is you're always

the smartest people in your classroom or
room at home. But that only means you're the smartest
person amongst 30 or a 100. And if you happened to be in a room that
had the 100 smartest people in the world. And you were the smartest
person in that room, you're still not as smart as
the other 99 working together. So being clever doesn't do it. And this is the simplest
snare is the IQ snare.

Tony Hoare, really great guy,
was here at Stanford for awhile Turing winner, said debugging
is harder than programming so don't use all your cleverness
to write the program. Anybody recognize this? Anybody write programs here? Let me see hands. Yeah, so people are so clever writing the program
they forget that debugging is harder. And that's true about anything. So that's principle number one,
we had zero. And then here's a summary
of what I showed you.

And the number 2 one at the top there
is that the goodness of the results correlates most strongly with
the goodness of the funders. This is the simplest way
of summing up the past. because you have to realize the difference
in the past wasn't that the people were smarter back then, we weren't
smarter than the smart people today. Every generation has really smart people. The difference in whether
you get enormous results or not, is in this context idea and
the funders that support it.

One of the ways of thinking about them is, as opposed to getting gold medals like a
bunch of us have gotten in our sixties and seventies, 40 years
after you did the deeds. Good funders give out the gold
models ahead of time. Knowing that 70% of them
are going to turn to lead, because the funders give it out
before you've gotten the results. So this will be a slide
that you can use later on, it's basically what I said last time. Now last time we looked at four systems.

Sketchpad, we didn't really look
at the Engelbart system, but it's easy to find out about online. We looked at the first really
good gesture system, GRAIL. And we saw that Ivan Sutherland, again, invented VR a long,
long before it ever came to use. And I really rushed past
personal computers. The first thing that was kind
of like a personal computer, it was kind of cute, was
Henry Husky's Bend XG 15 in the mid-50s.

So this was really early. Harry just left us a few
years over the age of 100. Really wonderful guy. Here's my vote for the first real personal
computer called the LINC by Wes Clark. Wes Clark also did the building size
computer that Sketchpad was done on. So he liked to work both large and small. Here's one I did with Ed Cheadle. Looks kind of modern. And an idea I had in 1968,

which struck me really deeply,
not because it was a tablet, but because it was a thing
that children needed. And I'd learned from Seymour Papert what
children could actually do with computers. And that seized me in a romantic fashion. And we looked at this idea of better and perfect are the enemy Of
what is actually needed. In other words, you have to draw
thresholds in order to know where you are or else you're just
measuring local variations.

You don't know whether they're good or
bad. And the last thing we did on Tuesday
was looking at this process of taking a glimmer of an idea out 30 or
more years, to see if it makes more sense 30
years from now than it seems to now. And if it does, you bring it back. Simulate it by making super computers
that allow you to do the software. And then five or eight years later, you've got something that
will revolutionize the world.

This is where the trillions
rather than billions comes in because you create an industry. And last time, I didn't get a chance to show you kind of
just one of the examples of what PARC did. So I thought I'd do it today. And this is a self-portrait, because
now I have extracted stuff from a demo. But this is a system we brought back
to life from 1978, so you get a chance.

And this is a self-portrait. So this is the successor to
the Alto called the Dorado. So it had now bigger than XVGA screen
rather than the portrait model. And this dithering technique was
invented at the same time in the 70s by Bob Floyd and Steinberg,
and partly done at PARC. So this is what a typical image on only
a few computers in the world looked like,

back then, one bit per point. And where do we get this system from? Well, here's the Xerox dump. And if you closely there, there's a disk
pack, actually we got Xerox through out. Most of the disk packs of the work
that was done at Xerox PARC, few of them got rescued. Here it is, few hundred files on there. One of them happened to be most
of a system that we did in 1978.

And it's of partial interest
because the next year, it was the stuff that Steve Jobs got
shown doing his famous visit to. So you have a little flavor here. Now what we did is we
brought this back to life. And it was relatively easy because
the system is called Smalltalk. Smalltalk-78 is a pure object system,
and so it resembles the internet. This is an internet self-portrait and it's
just as a good a self-portrait, Smalltalk.

Because the idea was to have one-to-one correspondence between the idea
of little logical computers. Which is what we called objects
that could send messages around and make an entire system. And so it's a little different than from
what you think object-oriented programming is today. One of the consequences is that there
are no actual applications because

you can mix and
match objects as you choose. Here we see something
that is vaguely familiar. I thought I turned that off. Okay, so
this is a typical screen back then, and it ran on the Alto there,
the portable note taker, and the Dorado. Here's a bitmap painting I did 45 years
ago that we found and stuck in here. See the user interface is with the object
itself, and here I'm marking it up.

And it has a character recognizer,
gesture recognizer like GRAIL did. There it's recognizing I want an arrow and
making one. The overlapping windows, the icons. What would be called Rich Text today. And you can see the gesture recognizer
is being used to tell it how to justify. And this system is organized
in terms of projects. So each project you can think of in
today's terms as a separate desktop,

they persist over time. Now think about this compared
to the user interface today, where you use an application that doesn't
have every feature that you want. And you start and stop applications,
and try and cut and paste between them. Here what you have is just working spaces,
an unlimited desk for every project that you have. You can have as many, they persist over
time because this is a workflow idea. We couldn't get Apple to adopt this idea.

And so these are kind of
thumbnails of each one of them. We can go into one of them. Here's a little thing done
by a 13-year old girl, writing an article for
Creative Computing back in 1975. And so you can see it's sort
of like desktop publishing. But in fact,
any object can be used in here. And so for example, if we look here,
she's telling about how she

used the program and
how she's typing in there. She's typing in code, and it's being
executed to with the box and turn the box, and so forth. All right, get the idea? So, it'd be nice if Wikipedia had
even thought about this, right? Because imagine,
you go to the article on logo, guess what? You can't execute logo code in there. Why?
It's on a computer. What didn't they get about computing? Well, pretty much everything.

If you look at it closely,
you'll see the web design and the web browser are two of the worst
things ever done in computing. Because they failed to take account of the
fact that you're actually on a computer. Okay, another example here
is an animation system. You notice that ball is
not squashing there. And it would look better if
the ball squashed when it hit.

So if this were normal system and
it didn't have that feature, we'd be done. But we can relate objects to each other. So here we're single stepping to get
to that frame that we'd like to change. We're looking at the interface
of this bouncing guy, and we're seeing, yeah,
there's a thing called current frame. That's what this thing is. And here's our painting window. And let's look at its interface. And here's something that allows
me to set the picture in there.

And I want to connect
the two windows together, so I use the gesture recognizer
to draw a line between them. It gives me a little place to
explain how I'd like to relate them. And I save all the painter's picture, wants to be the bouncing
animation's current frame. Okay, everybody get what's going on here? So I say, okay, go ahead and do that, and now it's latched onto
that thing that's there. Now we can start the animation going
again, but while it's going, I can paint.

Look carefully and you'll see that the
thing is being painted while it's running. Won't you like to be
able to do that today? And just think about, why not? This is like sketch pad, right? Except a few years later. Yeah, this is completely natural. It's what you get very, very easily
if you just have unlimited objects. So in this Particular thing gives you
automatically something much more powerful in PowerPoint,
because all you have to do is sequence

these things called projects for
the desktops. That's what I'm doing here. I'm just moving from one to another. So that's an example of
what happened at Parc, and if we go back to the screen
of the various inventions there. We can look at this now I'm
answering Sam's question. Well how much of the alto idea
actually made it out of Xerox parc. Well about half. We'll see that see what
the other half is in a second.

How about the GUI? Well about 70%,
because you notice the GUI didn't come out as something that has
this unlimited desktop idea. Even today, 30 some odd years after
this nobody has put it in there. It's ridiculous. But it has to do with people wanting to
have application and sell applications. Even though most applications won't
do all the things that you need. How about desktop publishing about 70% for
the same reason.

The way we did programming,
only about 10% has come out. And I won't go into all the differences,
but I think you've seen some of them. Laser printer about 90%. Postscript 100%, and
that's partly because the guys who did this at Parc formed Adobe,
Geschke and Warnock. And so they sold, in their company, how they thought you should
be able to do printing. A 100% of the Ethernet,
there was no competitor.

About 50% of peer to peer and
client server, we'll see why in a second. 100% of the Internet. Again, there was no competitor for
it, there was no. And so one way of looking at this is,
what came out? Most successfully were the things for which people already out there didn't
think they already knew how to do it. So everybody knew how to program, and so the biggest resistance was
on how we did programming. That just didn't make it. Now here's three things I've mentioned
before, because none of them made it.

But one of them was, hey the architecture
of the Alto was revolutionary and it allowed you to run very high
level languages very efficiently. And to make changes on the fly. And we tried with Intel and
Motorola to get them to adopt these architectures for
the chip and zero. Intel especially at the time,
didn't know anything about computing, didn't know anything about programming and
didn't want to learn. They had to be dragged kicking and
screaming even to do CPUs.

Andy Grove for instance was against
the first CPU on a chip that Intel did. The idea of the Dynabook
didn't make it out. Think about it, when did the iPad decide to put
the styles in the keyboard in the iPad? Right the iPad Pro. Why couldn't they do it? What was their problem? So 10% of that idea came out.

Now here's an interesting
idea to think about. Here we've got the Internet of machines connected together and
if your programming language happens to be a software Internet like small talk was,
then you can map the objects into the network and
you can migrate the objects around. Each object is self contained,
they do messaging. The messaging is either done internally or
it goes out on the Internet.

And so you have a solution for all the
different scalings of computing that you have, whether it's a small device. Yes? >> So why do you say only 10%
of the Dynabook, what's so important about the stylus and keyboard? >> Well so here's the thing,
2 year old use this and 92 year old use this, and everybody
else uses tools for dealing with media. So Steve decided not to do styluses. He completely went away.

All he was doing was selling
sugar water to babies. He was not selling something, for
instance that any artist can draw on. And when I first, and he sent me the first
iPad for my comments on the thing, and the first thing I did was to go
out and get a capacitive stylus and draw lines with a rule on
I guess it was Autodesk, one of the Autodesk software
that was pretty good. And I determined that the touch
sensitivity on the iPad was fabulous despite the fact
that it's done in a very,

very complex way because it has to
find centroids from wide things on it, but it was done extremely well and
I got very linear results on it. And so it was there to do, but there was
no place to put the stylus on the iPad. And long, long ago,
remember I showed you a tablet system from the mid 60s, 50 years ago. So we had a perfect chance to decide by experiment whether a purely stylus
driven system was actually enough to do

the work that you want to do and
the answer is no. Similarly with angle bar,
you could do every piece of text entry without using the
keyboard but they have the keyboard there. Because you just can't
do it fast enough for being able to put in large amount of text,
you need to have a keyboard. This is-
>> [INAUDIBLE] >> Well, so here's the thing that Engelbart said. Well, why do you have
to learn your system? Back then he said, well people
are going to use their computers for

6 to 8 hours a day and
they laughed at him. So what you guys are doing,
[SOUND] is using your computers for 6 to 8 hours a day and
using interfaces that are made for a couple of seconds a day. That if that is the most
ridiculous thing you've ever, it's a bout ridiculous as this building. >> [LAUGH]
>> You think about it as a user interface, right? Come in the door and
there's a stairway and there's no map. And where am I, where can I go?

And Jesus, this looks like a dungeon. >> [LAUGH]
>> And remember, computer-human interface is part of
what you're supposed to learn about and you can't do it in a dump like this. >> [LAUGH]
>> You have to have some sense of design around. And I'm not sure you can do software without having some
sense of design around. So how could,
I won't make any really rude remarks. But-
>> [LAUGH]

>> And just to use up time I don't have, I should point out that some of this
migrating object idea was done at Parc, a really great follow up was
done by a visitor to Parc Jerry. Who was at UCLA, went back to UCLA,
and did a fabulous system, using Unix as the base,
called LOCUS, L-O-C-U-S. And if you're interested in
looking at a future that will

at some point actually happen,
you can get that book from MIT Press. And particularly the first
couple of chapters of that book outline what the issues are for
dealing with real scaling on the Internet. I won't go further than that, so zero. So the principle 21 reality
is a low pass filter. You have to have enormous ideas in order,
so that people not understanding
them will retain something.

You don't want to have the low pass
filter give you back a dial tone. That happens, because most
ideas are mediocre down to bad, even by people who have good ideas. Those are the ones that
you don't want to work on. Because if you're successful on them,
they're still going to get peeled at. So here's a book, I put this slide up
here for Sam, because Sam reads books. >> [LAUGH]
>> You people probably don't.

But this is not a book about Xerox PARC,
Sam. This is a book by an executive
at Xerox written in the 60s, before PARC, about trying to
get the Xerox machine adopted. And this was after Xerox had
been the fastest growing, but one of the companies that turned
down the complete rights for a licensing fee to
the Xerox machine was IBM. That story is in this book.

And IBM's consultant said,
well this isn't going to work, because there's no market for
plain paper copying. Because people are not copying. Well of course,
it wasn't good copier back then. And so I could write a book, Our Years
with Xerox, the Trillions Nobody Wanted. I didn't have time to make a picture
that looks like John Dessauer. So it doesn't matter, and I'm going to
try and explain to you in the time I

have left, why the goodness of
an idea is almost irrelevant. Now, for the reality kit. Get out your reality kit. And we're going to deal with the top. So just break the seal,
and just open up the, Thing and this will work best if you put
it down on your thing like this, but, And look at the instructions for

people online, Did you get a reality kit? Okay, everybody got one? What happened? Where were you? Hey, you know what? You guys must've been late. >> [INAUDIBLE]
>> Take them, hand them out to. Anybody else?

Okay, you're killing me guys. Okay, so cover your right eye. Look at the + with your left eye and
then slowly move the thing in. Keeping focused on the plus
until something happens. Slowly moves, slow. Slow as in the word slow. Who's seeing something? What do you see? >> Disappears on the blind spot.

>> Disappears on the blind,
is everybody seeing that? Don't say yes if you're not. >> [COUGH]
>> This is a good thing for everybody, particularly in computing
to do once a day. All right. Okay, so now let me ask you. What do you see, where the dot was? Nothing? >> [INAUDIBLE]
>> You see text?

How can that be? >> [CROSSTALK] >> Black. >> That's what I expect. >> Okay, so here's what's happening here. You see something like this, right? So what's happening is inside your eye
there is, I wonder if I go to laser.

Over here is where the blood
vessels come through. So we have a very badly designed eye. If you're arguing with a creationist this
is a good argument against God here. >> [LAUGH]
>> Because if there was a God, he gave squids a great eye and
he gave us a bad one. Our eye happens to have the blood vessels
in front of the light detecting cells. And so our brain has to
filter out all of those also. And over here is where most of your
acuity is in an area called the fovea.

And, So when the thing is further away,
you get something like this. And when you move in at some point the dot gets over where there are no
light sensitive cells at all. And you can't see it anymore. And as my friend over here said,
somehow the brain fills it in and
we'll look at that in a second. So principle number 22, is we have a blind spot in our eyes that
our brain makes up stuff to fill in.

It's just making it up. Think about this, because what's the other case where your brain
makes up stuff that you think is real? A dream? Most people think they
only dream at night, but in fact human brains are set up so
that we actually dream. Did you get one of these? So in the old days we'd throw chalk
at you but there is no chalk. >> [LAUGH]
>> Okay.

And a powerful idea about that
is number 23 is that we can't learn to see until we realize and
admit that we are blind. And the biggest problem with
most human beings is they don't understand that they are blind,
because they think they can see. This leads to much of
the trouble in the world. And the powerful idea about that
is the 0th one again is it makes huge difference if ideas are experienced
in as many ways as possible. In other words, perspective point
of view is worth 80 IQ points.

Just because something seems to be right,
and this is why math is
a danger about thinking. Okay, let's go to the poker chips now. Pry them loose. Okay, and what you're going to
do is hold them up like this, so one is about twice as
far away as the other. Like that.

Okay, you'll see something like this,
right? On your retina is actually
something like this. Think about it, if it's twice as far
away it's subtending half the angle and therefore it should show up as half size. But it doesn't show up as half size,
and we can stick these guys on a ruler. Since these poker chips are now yours,
you can take it back and really, science the **** out of it. >> [LAUGH]
>> Here's what we should see,

that's what's on our retina. Descartes by the way, got an axis and
peel the back of it off to see whether a biological lenses actually active
like glass lenses and they do. And here's what's going on. So the stuff that's on your
retina gets mapped into about 12 different places in your brain. Your brain is active. If you think about this in computer terms,

[INAUDIBLE]. In computer terms, the cells in your
brain are like the hardware and there are processes going on. And one set of processes are all the ones
that have to do with our belief system. And before we recognize something, it
goes through our belief system, and then it goes into the real-time version of our
belief system, which is called The Dream.

So we have beliefs in the dream and our beliefs are, damn it,
these things are the same size. By the way you can do this with oranges,
with quarters, Anything where you know they're
the same size, do the same thing and. So the result of Information
from the actual world combined with your beliefs, you wind up with this. And anybody here who's
an artist who can draw?

Okay, you must know this illusion then,
right? It's called size constancy. And it's why, One of the things that you
learned, I mean, can you actually draw? >> [INAUDIBLE]
>> Yeah. Don't you erase here? You can draw, right? So if you can actually draw,
first thing you realize is you can't see what's going on,
and so you start measuring. Hold your arm rigid,
you measure it off, so I can measure.

Sam's head is that high and wow, it's only half size compared to
this guy who's closer to me. It doesn't look like it to me, it looks like it's almost the same
size because heads are the same. Got it? So the principle 24. The mind's eye is different
than our sensory eye. And we do things according
to the mind's eye. And most people who have
ever lived on this planet don't know that there
are two different eyes.

Because they take the world as it seems. They build up a common sense
from the world as it seems. This is why human beings
generally cannot think. You can't think if
you're doing this stuff. So another term for
beliefs is a private universe. We each have one of our very own. If you've ever argued with somebody you
thought was reasonable up to that point, what's happening is your beliefs
are conflicting with their beliefs. Our waking dreams are private.

I love this phrase, this is a new phrase,
Alternate Truths, Kelly Ann Conway. That's what is going on. So you can see why being
a scientist is tough. A scientist has to get around all of
this crap that our brain is throwing up. Okay, so
a quick easy model is how random this is, is a little bit of rain water on dirt,
dislodges a few crumbs of dirt, and a little gully happens and the gully
is more efficient at routing water,

so things start happening just
where things start happening. Originally, you get something like this,
completely random, it could've gone any way. And you can make a whole world out of it. Here's a world that's completely pink, if you've ever been in the Grand Canyon,
it is just almost overwhelming. If you look up,
you have to remember to look up. There's a little bit of blue sky up above. And the problem with human beings
was we don't look up, we look out.

So, here's an example. That's pretty washed out,
but that's a pink plain, and our thoughts are like
ants crawling over it. We can think about things. We can make progress. We can run into an obstacle. We can get around the obstacle,
and so forth. But everything we're doing here is pink,
except we don't know it's pink because we've never been
in anything else but pink. So this is like a fish not
knowing it's in water. It's always been in water. Every once in a while,
you might have little outlaw thought,

little blue thought. But you've been to school,
you're going to Stanford. You go to church, temple,
synagogue, mosque, whatever it is. Because our beliefs project out. And when we see something
that isn't normal, normal is actually the same as crazy. Smash. But maybe you're out for a run,
you're just waking up in the morning,

you're taking a shower, and
all of a sudden, you get a holy ****. Holy ****. There's a blue world. Blue world that orthogonal
to the one I'm in. Once you're in that blue world, you
realize, there's probably a lot of them. Can you see each one
of these as a context? Can you see that what happened
from the renaissance by Newton to our modern age was going from
a pink plane to a blue plane, right?

This is what ARPA did with computing. It went from mainframes, a completely
different way of thinking about things, to the world we have today despite the
fact that nobody had thought of it at all. It was considered literally
crazy by our colleagues in computing when we were doing it, okay? So you just leave the compass on there. It's for you to remember that some
people get to this really early. Einstein was five, he was recovering
from having the measles I think.

His father brought him a little
compass for him to play with, and Einstein remembered later in life,
he said, this made the most impression of
me of anything in my childhood. Because the way he looked at it, there must be something
deeply hidden behind things. He didn't take it as it came, because he was worrying about how
does the needle know where to go. There's nothing visible about it,
and yet it is doing this. And that changed Einstein's complete
way of thinking about things.

Okay, so when a baby is born, when we
are born, we're not born into nothing. We're born into a culture. Most cultures over the last hundred plus thousands of years were traditional
cultures, hunting and gathering cultures. And traditional cultures don't know that
they are inside a particular outlook. Traditional cultures
think they're in reality. And so they react incredibly strongly to other people's versions of
reality to the point of war.

And may people, this is what our genes give rise to in
many people today including in our country are born into this pretty natural
way of looking at things. We had to invent the idea of outlook,
and well, here's another one. So if you happen to be born here,
you can have the same baby and bring it up here, the baby will grow into
being French, French in its outlook, French in language, and so forth. Here's a big idea. What happens when books got invented?

So a guy by the name of Asher Mccluen
asked the question, what are books? What is writing as an environment? If you thought of writing as
being brought up in France, what would that actually
mean to the human race? Turns out its profound. Take a look at it if you're interested. You also ask,
what is media as an environment? So for example,
what is this is an environment 24/7?

Think about it. Not that the kids are being
told to shoot people. But the problem is,
they're seeing shooting people as normal. Because what environments do is to
take things and normalize them, they make them into part of reality and
make things thinkable. They don't say what to do, and
of course, media that we have today is doing exactly the same thing,
and most people don't realize.

Okay, so unhook the last flap here. There's a little Desktop here, tabletop. So look at the picture there first,
and before you start experimenting, let me make an assertion that the tops of
the tables are exactly the same shapes. I've been doing this hundreds of times and
I can't see it,

but if I take my plastic thing and
move it over there. No, it isn't crazy, we are crazy. >> [LAUGH]
>> If you remember nothing else from this course, remember that the natural
state of humanity is to be crazy. Because crazy is not having good models in
our mind for what's going on out there.

We just draw the line at certain kinds
of crazy, but we are actually crazy. So this is a really good one, isn't it? Happens to have been first done here at
Stanford, this guy is Roger Sheppard. And that his book, it's full of these. Okay so, Good, last couple of, got a, yeah, I think I'll get through. So anthropologists over
the last 120 years or

so, studied several thousand
traditional cultures and wrote down properties of these
cultures that were never absent. So, if a single culture out of
several thousand did not have a trait, Then that trait was removed. So all of these traits are thought
of as human universals. Virtually all of them are genetic. And, Here's a book.

You know books are actually useful. This is another good one to read. >> This is a great book. >> This is, yeah. I became very friendly with Sam, and I
noticed that I could not mention a book to him that he would not have
read the next time I saw him. That's how you know he's a good guy. >> [LAUGH]
>> Okay, so the basic idea here is
genetics drives culture. Genetics has the precursors, the desires,
and culture fills in the parameters.

So you can think of these,
they're all category names. And once that list was made,
people got interested in things that were not in every culture,
and this is a partial list of those. So agriculture had to be invented. It was a pretty easy invention but, it
was only invented about 12,000 years ago, out of several hundred thousand
years of us being on the planet.

So initially,
it was a hard thing for hunting and gathering people to think about. Like every animal we have zillions of
genes to help us cope with things. We can deal with hardship
like every animal incredibly. But the idea of progress
had to be invented. It's really an invention
of the 18th century. And the reason is, is that for
almost all of human existence, people died in the same world
that they were born into.

Almost nothing happened. And so, what you had to do,
to get from birth to death was to cope. It's only been recently that the idea of,
no, we could shape the world to be better. That's a new idea,
these are all powerful ideas. Oral language versus writing and reading, the differences are profound,
stories, superstition, religion, and magic versus the representation
systems of science, News.

Remember news,
never introduces a new category, right? What you hear about is,
it's this forest fire, it's that war, it's this murder, it's this kind deed. This is why news can happen so quickly. And that's what our mind craves, what we
hate is categories because it can take us a couple of year to learn a category. That's why you never hear
any news about calculus, takes a couple of years to learn it,
and there aren't enough people.

Fast thinking verses slow thinking. Differences over similarities, this is one of the reasons why
most programming languages go bad. Web browser went bad. Whereas, a modern way of thinking about
things is similarities over differences. Emphasizes similarities. It has many things to do also
with equal rights and democracy. Vendetta and revenge. Those are the favorite movies, and the
favorite video games are revenge games.

Personal revenge games,
where the system has gone bad, and somebody has to break
the law to put things right. We just love that trope. But in fact,
the whole legal system was setup and we're doing avoid thousand
year feuds in Vendettas. Okay, so we can think of this side,
we have things that human beings want. And simple way of thinking about them is, every single one of them on
this side is illegal drug. And for people in this class who
are trying to make money by being

entrepreneurs, just make
a technological amplifier for any of these things that we crave,
genetically. Look at the things that are there, hunting and gathering, social, language. Like the telephone. Stories, news, theater,
all of those things. That's your list. Just get this book, right, Sam? And, make something that will make people
worse, and they'll buy the hell out of it.

Because we don't have any natural, all of
these things are in shortage in the world that human beings have been into
except for a couple hundred years ago. Over here, we have things a human beings
need and you can't really see, but these are terribly difficult to learn. Because they're not particularly
genetically prepared for. They had to be They had to be invented,
okay.

So last shot here, 21st century
going on into the 22nd century. Hey, we're not born into France,
or traditional society anymore. We're born into a universe
that is unbelievably large. A planet that most people don't
even realize we're on yet. Not just our social system of a few
hundred people that we know, but millions of social systems,
and billions of people.

A technological system that is
starting to touch everybody in many, many different ways. For instance, modern medicine really
dates from only World War II. That's a long time ago for you folks,
but it's within my lifetime. I was born before World War II. And before World War II, you simply did not get antibiotics
when you had an infection. Was that soon,
doctoring was almost quackery.

Much of scientific medicine has
happened in the last 50 or 60 years. And then we have the system of our mind. There's not just social, but
psychological, cognitive, and so forth. So we can sum up this world that
we're born into in this century as the systems we live in and
the systems we are. Think about that,
the difference between that and what most people think that they want. These are the systems we have
to learn about and deal with.

And these systems are not separate,
I've mentioned them separately but they're all intertwined with each other,
they're all invisible. Okay, and
I'll just leave you with this last slide. So we found out about
all of these systems. They were invisible until
a few hundred years ago, and some of them invisible
until a few years ago. And the human tragedy is in two parts. Part of it is just finding out
something in our civilization,

doesn't automatically transmit it to
people born into the civilization, right? The educational system has to be
changed in order to reflect this stuff. And the composite picture here
is that part of our brain, the genetic part of our brain,
even overlaid with this stuff, still has these reactions, and
ways of thinking about things or not thinking about things that go
back a hundred thousand years. So I think with things like
television to look at,

things like video games to look at,
things like Facebook to look at, if you're going to go out and make a company that is
going to appeal to people, try to do it without appealing to the parts of their
nature, that they're helpless in front of. Because one of the things that those of
us who helped invent the technologies of today are quite worried about now,
is that the technology is so

much easier to invent than it is
to change the educational system. And so what we've got is
the informational equivalent of cave people with nuclear weapons, but
now they're informational weapons. And in many ways, I think these
weapons are more dangerous because by renormalizing human attitudes and
human beliefs could very easily bring down our civilization and
put us back into the Stone Age.

The talk on Tuesday, maybe a little
thicker today, but the whole impetus behind the ARPA research and
inventions of these things. And particularly,
people like Engelbart was to try to invent new tools and new media for humanity to get
itself out of its problems. And Engelbart, for example,
said almost everything important

that has consequence in the adult world
is done by adults working together. And so this is why his system
was collaborative from the, so here's an interesting thing. So here's a Mac, some people have Linux,
some people have Windows on it. Here's the interesting thing. Not a single one of the main operating
systems today has built into it the thing that Englebart showed in 1968,
which is the intrinsic ability to share any content that
you're looking at with anybody else,

to the point of allowing them to interact
with it and to talk back and forth, right? Skype, it doesn't do it. So this a thing that is at
an operating system level. It's not a trivial thing to do. It is possible to do, but not a single
operating system use today does it. And so the ability to actually work
collaboratively on content is been held back by notions of operating
systems that go back pre-1965.

All three operating systems we have today
that are the main ones are old, old ideas. They don't even get to where Park was, the notion of how processes can
coordinate with each other. And there are many, many other of
these things, because these operating systems are rather similar to each other,
and because they're pervasive. Unless you use your reality kit, you're
going to think that they're normal and, therefore, that's the way
things should be. Many people, in computing,
have a misplaced notion of

Darwinian process, Like most people. Most people think Darwinian
processes optimize. That is absolutely not the truth. One of my degrees in molecular biology,
and I can tell you, any biologist would say,
they're absolutely not optimized. The whole point of Darwinian processes is to fit into some niche
in some environment. And if that environment isn't the right
kind of environment, the processes of

evolution is not going to give you
something that's very interesting. That is the way it works. And as computing gets less and
less interesting, its way of accepting and rejecting things gets more and
more mundane. So this is why some of these early
systems, like Sam looks at sketchpads and said, why aren't they doing it today? Well, because nobody even thinks
about that that's important. Nobody even thinks of doing
Wiziwig on the web, on web media.

I just typed in some answers to Cora, and I was in a regime that was pre-70s. I was typing into a little window. I couldn't see what it was going to
look like until I clicked the button. Come on, this is ****. >> [LAUGH]
>> But nobody is protesting except old fogies
like me, because I know it can be better. You need to find out that it can
be better, that is your job. Your job is not to agree with me,
your job is to wake up.

Find ways of criticizing
the stuff that seems normal. That is the only way out of the soup. You have to go against your
genetic impulses to try and learn the environment around you,
it's the most natural thing we have. But it's not going to help,
because the environment is weak. And if you learn the environment,
you're going to be weak. >> All right, thank you very much. >> [APPLAUSE]
