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WILLIAM BONVILLIAN: So
today, we really kind of talk

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more about the system, the
kind of third direct innovation

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factor, and then about
these indirect factors that

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are important and significant,
but not as powerful, I'd argue,

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as the direct factors.

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But first, let me just
recap last week just really

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in a few seconds,
and then give us

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a glimpse of what
we're getting into.

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So last week, Robert Solow,
the great growth economist,

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developed-- really
created growth economics--

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developed the theory that
the dominant causative

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factor in economic
growth was, quote,

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technological and
related innovation,

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a phrase that you'll
hear all the time here.

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And then we followed up
that discussion with talk

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about Paul Romer and his
work on human capital

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engaged in research as a kind
of second key direct innovation

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factor.

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That's the talent base that has
to be behind the R&D system.

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We read Dale Jorgenson who
told us that, yes, in fact,

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this innovation based
economic growth model

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is in fact correct.

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That's what happened
in the IT wave

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and he showed us, in
effect, how that occurred.

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The model was you do an
invention or a core group

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of inventions, they
begin to scale up,

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applications pile on them,
they enter into the economy

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and really begin to
scale up in the economy.

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And eventually, over time,
become a true innovation wave.

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And we'll talk more today, as
you know, about innovation wave

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theory.

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We also read a piece by
some Merrill Lynch analysts,

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and the fundamental
point in that piece

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was that industry is very
interested in innovation,

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but they're only prepared to
fund the very short late stage

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of it.

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So somehow, even though
the evolution to innovation

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is a very long-term process,
the financial sector

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is only going to
dive in as close

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as they can to certainty--
in other words,

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at a very late stage.

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So those were kind of
our four core readings.

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And one other idea in
that Merrill Lynch piece

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was this notion that
innovation needs

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to move through a series of
stages to kind of get there.

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There needs to be
an early vision--

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kind of a visionary who will
set out what could happen.

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And then enabling
technologies evolve

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that become technical
enablers for the evolution

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to an innovation wave.

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And then there's going to be
substantial talent on task.

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In other words, people have
got to be-- researchers

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have got to be working on this
in significant depth in order

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for this thing to evolve.

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So it's going to take a
community scale kind of effort.

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So the first class
left us with two

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direct or explicit
innovation factors.

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And we could in a--

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oversimplify them and
put them in shorthand,

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but we could say
you've got to do R&D

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and you've got to have a talent
base staffing that R&D system.

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And we worked on a definition
of innovation as a system

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for introducing
technical advance,

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and we talked briefly about
innovation waves, which

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we'll spend more time on today.

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So that's a quick recap
of last week's discussion.

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And Chris, you and
I can follow up

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so you catch up on some of
the issues that came up there.

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And I've posted the slides
to the STELLAR site which

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will help as well, but I'd be
happy to talk to you further

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about it.

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So let me just do
a quick snapshot

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to open up today's discussion.

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So that's Thomas Edison.

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That's his idea factory
and that's the group

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that does the light bulb.

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It's the light bulb
and you can see

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the idea factory-- this building
in that scheme at the top.

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And then you can
see the farmhouse

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back behind which
is where Edison

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lived with his wife except that
he never spent any time there.

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He was in the idea
factory pretty much 24/7.

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I just want to give
you a feel for what

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innovation is like when
it starts to take off.

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And this is a good--

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Edison is a classic example.

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So he-- very limited education.

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He was homeschooled
by his mother.

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He's probably pretty dyslexic.

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We don't quite know that,
but it's probably the case.

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As a kid, he understands
the early evolution

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of the telegraph and he develops
kind of a newspaper sales

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scheme during the
Civil War where

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he gets the newspapers
ahead of time in Cleveland,

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gets them out to the trains
coming into Cleveland,

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and then sells
them on the trains.

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And he's kind of kept--

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in other words, he kind
of beats the news cycle

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and then unloads newspapers on
these early commuting efforts

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as people are coming
into the city.

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He gets his big
break by scooping up

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the child of the
telegraph operator.

00:06:06.250 --> 00:06:08.890
So trains had to operate
by telegraph systems--

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they were a crucial technology
to enable trains to work.

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And the telegraph operator for a
train system is very important,

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but also obviously serves a
larger community communications

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purpose.

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So the kid of the
telegraph operator

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is down on the tracks--

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train is coming down the tracks.

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Edison, as a boy,
sees what's happening,

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rushes, scoops the child up,
barely escapes the train.

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Needless to say, the
telegraph operator

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is appreciative, so he
trains Edison in Morse code

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and how telegraph
operations work.

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So he becomes an expert on
telegraph, which is obviously

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early electrical technology.

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And he becomes a master
at it, and then he

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becomes very interested
in technology itself.

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So over time, he
goes to New York--

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he develops what
becomes, in effect,

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an early stock
ticker, which can--

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what we would call multiplex.

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In other words, you could
receive multiple telegraphing

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signals and communications
over the same line, which

00:07:10.050 --> 00:07:13.500
obviously was a key enabler
for keeping track of stocks.

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So he becomes very close to
the scions of Wall Street,

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including JP Morgan.

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He gets to know them all
because he's like their enabler.

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And then he sees this thing
in Ansonia Connecticut.

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It's not-- it's a much
bigger version of this,

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but there's this
kind of gimmick--

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these nine foot tall
polls with a spark,

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because they're
positive and negative

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a spark travels across--

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looks really cool.

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People are wondering
around-- they

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don't know what to do
with it, but they're

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awestruck by this kind of
electric movement of lightning

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going across the two poles.

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Edison has the idea-- oh, light.

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So he takes the-- he makes
his money on Wall Street,

00:08:05.020 --> 00:08:06.750
he takes all his money out.

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He goes off into a farm
in Menlo Park, New Jersey

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out into this rural area.

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He hires this team which
consists of an interesting mix

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of artisans--

00:08:20.080 --> 00:08:24.910
like, there's an incredibly
important glass blower here,

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which heralds back to the
MIT glass lab which I always

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buy stuff from.

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And there's also
scientists and engineers

00:08:32.620 --> 00:08:34.750
in here, but a lot
of people who just

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know how to do things
who are very good at sort

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of mechanical tinkering.

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And it's an interesting
team, and he

00:08:42.580 --> 00:08:45.190
has to take this idea
of this weird arc

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that he saw-- these nine
foot tall couple of poles

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that he saw in
Ansonia Connecticut

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and turn it into a light bulb.

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It's not an easy job
and it's very intense.

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There's only a certain
amount of money--

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the money is going to run out.

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He's gotta get this thing done
before he runs out of cash.

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And they work
literally all the time.

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They're always on it but they're
having the time of their lives.

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So there's a wood
stove in here over in--

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I'm not sure-- maybe
it's in another corner.

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But around midnight, they all
gather around the wood stove

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and they're--

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rap music has not
been invented yet,

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so they do doggerel verses which
they throw at one another--

00:09:33.360 --> 00:09:36.450
insulting and funny and
this incredible doggerel

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verse back and forth going on.

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And they all have big cherry
pies and apple pies at midnight

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and gather around the stove.

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It's a very intense effort.

00:09:47.670 --> 00:09:50.880
And actually, Edison
is away for so long

00:09:50.880 --> 00:09:54.127
from the farmhouse which is
further back on the property

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that at one point, when he
comes in at like 2:00 o'clock

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in the morning, his wife
pulls a revolver on him

00:09:58.440 --> 00:10:00.065
thinking he's an
intruder because she's

00:10:00.065 --> 00:10:01.850
seen him so rarely.

00:10:01.850 --> 00:10:04.080
Fortunately, she doesn't shoot.

00:10:04.080 --> 00:10:06.840
But there they are gathered
on the idea factory,

00:10:06.840 --> 00:10:12.330
and eventually they come
up with the core concepts.

00:10:12.330 --> 00:10:14.550
The vacuum tube
obviously is core here

00:10:14.550 --> 00:10:16.380
and the right
filament is core here.

00:10:16.380 --> 00:10:19.860
They come up with a working
model of the electric light.

00:10:19.860 --> 00:10:21.420
There's only one problem--

00:10:21.420 --> 00:10:23.910
there's no electrical system.

00:10:23.910 --> 00:10:25.717
There's no nothing.

00:10:25.717 --> 00:10:27.300
So they've got a
wonderful application

00:10:27.300 --> 00:10:29.220
for a nonexistent system.

00:10:29.220 --> 00:10:35.510
So the real innovation here
is not simply the invention,

00:10:35.510 --> 00:10:38.570
it's creating the whole system.

00:10:38.570 --> 00:10:40.850
So they have to envision--

00:10:40.850 --> 00:10:43.880
they have to think of what
an electric utility might be.

00:10:43.880 --> 00:10:46.970
They envision the
utility, they envision

00:10:46.970 --> 00:10:48.620
what a generator would be.

00:10:48.620 --> 00:10:50.690
They have to think through
all these early safety

00:10:50.690 --> 00:10:52.610
requirements.

00:10:52.610 --> 00:10:56.660
So it's an incredibly big
thing that they're launching.

00:10:56.660 --> 00:10:59.120
They're launching the
electrical system, not simply

00:10:59.120 --> 00:11:00.380
the light bulb.

00:11:00.380 --> 00:11:01.880
But the light bulb
is the enabler

00:11:01.880 --> 00:11:04.760
that's going to enable
them to sell the system.

00:11:04.760 --> 00:11:06.440
Eventually, they do
a big demonstration

00:11:06.440 --> 00:11:10.160
on a couple of city blocks in
New York-- everybody loves it.

00:11:10.160 --> 00:11:11.630
Gas lighting is
not what you call

00:11:11.630 --> 00:11:14.690
optimal since you have a good
chance of blowing yourself up.

00:11:14.690 --> 00:11:17.950
And the nation
eventually switches over,

00:11:17.950 --> 00:11:21.380
but I just wanted you to
see what that innovation

00:11:21.380 --> 00:11:23.313
moment looks like.

00:11:23.313 --> 00:11:24.980
And we'll talk about
great group theory,

00:11:24.980 --> 00:11:27.230
and this is certainly
a great group.

00:11:27.230 --> 00:11:32.313
But that's the moment
we're after in this class.

00:11:32.313 --> 00:11:33.980
That's the moment we
want to understand.

00:11:33.980 --> 00:11:38.420
We want to understand how
that innovation emerges

00:11:38.420 --> 00:11:42.410
from the group, but
importantly, how it scales--

00:11:42.410 --> 00:11:43.940
what happens to it.

00:11:43.940 --> 00:11:45.510
So that's kind of a little--

00:11:45.510 --> 00:11:47.310
that's story time
for today's class.

00:11:47.310 --> 00:11:51.080
Now we'll do serious work.

00:11:51.080 --> 00:11:53.100
I want to get some
other basic ideas down.

00:11:53.100 --> 00:11:55.430
So we talked about some
basic concepts last time.

00:11:55.430 --> 00:11:57.290
I want to put a few
more on the table.

00:11:59.900 --> 00:12:04.180
Steps in the technology
development process.

00:12:04.180 --> 00:12:07.060
So we talked a
little bit last week

00:12:07.060 --> 00:12:11.690
about three of those
steps, but let me put them

00:12:11.690 --> 00:12:13.030
into a larger context.

00:12:13.030 --> 00:12:15.370
So typically,
you're going to have

00:12:15.370 --> 00:12:18.760
to go through a
series of steps here

00:12:18.760 --> 00:12:22.930
to actually get to really
scaling a technology up.

00:12:22.930 --> 00:12:26.140
We talked last week
about having a vision.

00:12:26.140 --> 00:12:28.990
We talked last week
about supporting

00:12:28.990 --> 00:12:31.960
enabling technologies.

00:12:31.960 --> 00:12:34.930
Then you're going to do
your particular invention.

00:12:34.930 --> 00:12:37.720
Idea-- you're going to need to
do some research to perfect it.

00:12:37.720 --> 00:12:40.305
You're going to need to
develop a prototype of it.

00:12:40.305 --> 00:12:42.430
Then you're going to need
to go through engineering

00:12:42.430 --> 00:12:44.200
development.

00:12:44.200 --> 00:12:46.360
Then you can start to
think about production,

00:12:46.360 --> 00:12:48.430
and manufacturing that
prototype, and then

00:12:48.430 --> 00:12:51.260
eventually scaling up to
commercial production.

00:12:51.260 --> 00:12:54.730
You've got to have a supporting
infrastructure system

00:12:54.730 --> 00:12:57.640
and there may be additional
applications that you

00:12:57.640 --> 00:12:59.795
can use and pile on here.

00:12:59.795 --> 00:13:02.170
And then you've got to go
through a series of generations

00:13:02.170 --> 00:13:03.420
of the product.

00:13:03.420 --> 00:13:07.590
So that's a lot of
stuff to get through.

00:13:07.590 --> 00:13:14.050
So the US typically thinks
about innovation as, like,

00:13:14.050 --> 00:13:17.790
in the vision idea
research realm,

00:13:17.790 --> 00:13:20.850
but it's a much
more complex process

00:13:20.850 --> 00:13:25.290
that has to be mastered to
actually get from the discovery

00:13:25.290 --> 00:13:28.480
to the innovation.

00:13:28.480 --> 00:13:30.810
So there's models for
technology change,

00:13:30.810 --> 00:13:32.940
and we'll talk more about
those in a later class,

00:13:32.940 --> 00:13:37.890
but just a couple of core ideas
to put on the table right now.

00:13:37.890 --> 00:13:43.560
Technology push-- so we talked
a bit about the innovation

00:13:43.560 --> 00:13:46.650
pipeline last week.

00:13:46.650 --> 00:13:51.990
Technology push is typically
where you support research,

00:13:51.990 --> 00:13:55.200
something emerges from
that research in effect,

00:13:55.200 --> 00:13:59.670
and then enters into
widespread use--

00:13:59.670 --> 00:14:01.890
typically a
commercializable product.

00:14:01.890 --> 00:14:04.680
So in effect, you're nurturing
and developing a technology,

00:14:04.680 --> 00:14:09.120
and you're pushing it
towards the economy.

00:14:09.120 --> 00:14:12.390
Technology pull, or
sometimes called demand pull,

00:14:12.390 --> 00:14:14.410
is a different model.

00:14:14.410 --> 00:14:19.530
So in this case, the market
will create an opportunity.

00:14:19.530 --> 00:14:22.260
The market may create
a niche or someone

00:14:22.260 --> 00:14:24.690
may spot the opportunity
or the niche.

00:14:24.690 --> 00:14:27.390
And in effect, the
market is going

00:14:27.390 --> 00:14:29.510
to pull that technology out--

00:14:29.510 --> 00:14:32.310
is going to be, in
a way, the enabler

00:14:32.310 --> 00:14:34.320
for that technology to evolve.

00:14:34.320 --> 00:14:37.310
So these are two very
different processes,

00:14:37.310 --> 00:14:40.090
and we'll talk more
about who does which.

00:14:40.090 --> 00:14:43.670
There's incremental innovation
and there's radical innovation.

00:14:43.670 --> 00:14:47.790
So incremental innovation--
as a definition here,

00:14:47.790 --> 00:14:50.070
it improves function,
aesthetics, performance,

00:14:50.070 --> 00:14:53.350
efficiency, manufacturability
and so forth.

00:14:53.350 --> 00:14:57.540
In other words, modest
incremental steps.

00:14:57.540 --> 00:15:00.030
It's very important.

00:15:00.030 --> 00:15:03.000
We all kind of love
radical innovation,

00:15:03.000 --> 00:15:06.420
and there's actually
good evidence

00:15:06.420 --> 00:15:10.080
that radical innovation
will lead to a really

00:15:10.080 --> 00:15:13.440
disproportionate profit impact.

00:15:13.440 --> 00:15:16.620
In other words, if you can
launch a radical innovation,

00:15:16.620 --> 00:15:19.297
the gains can really
be big, and that

00:15:19.297 --> 00:15:21.630
will become an important idea
when we talk about venture

00:15:21.630 --> 00:15:23.270
capital later in the class.

00:15:23.270 --> 00:15:24.812
AUDIENCE: From what
year to what year

00:15:24.812 --> 00:15:26.877
is that-- is the
scale of that graph?

00:15:26.877 --> 00:15:28.710
WILLIAM BONVILLIAN: Now
you're calling on me

00:15:28.710 --> 00:15:31.080
to really look closely.

00:15:31.080 --> 00:15:32.250
I don't know how many years.

00:15:32.250 --> 00:15:34.890
This is a '97 study out of
the Harvard Business School,

00:15:34.890 --> 00:15:36.920
and I just don't
remember, Martine,

00:15:36.920 --> 00:15:38.072
how many years this covers.

00:15:38.072 --> 00:15:39.780
But I'll be happy to
look that up for you

00:15:39.780 --> 00:15:42.090
because I don't see it on here.

00:15:42.090 --> 00:15:45.180
But it's gotta be at
least a 10 year look,

00:15:45.180 --> 00:15:48.330
I think, to be meaningful.

00:15:48.330 --> 00:15:51.473
So I don't want you
to get the idea though

00:15:51.473 --> 00:15:52.890
that one is better
than the other.

00:15:52.890 --> 00:15:56.130
That incremental or radical
are better than one another.

00:15:56.130 --> 00:16:00.510
I just think-- the Wright
Brothers aircraft would

00:16:00.510 --> 00:16:04.327
be a good example of
a radical innovation,

00:16:04.327 --> 00:16:06.660
but you and I would not want
to take the Wright Brothers

00:16:06.660 --> 00:16:08.370
aircraft across
the Atlantic Ocean.

00:16:08.370 --> 00:16:11.370
We would rather do the 787.

00:16:11.370 --> 00:16:15.020
So incremental can be
extremely important.

00:16:15.020 --> 00:16:19.620
Historically, industry
does the incremental.

00:16:19.620 --> 00:16:24.960
That's more of a technology
demand kind of model--

00:16:24.960 --> 00:16:27.990
a technology pull
kind of model--

00:16:27.990 --> 00:16:31.500
as opposed to the
radical, which tends

00:16:31.500 --> 00:16:36.678
to be more out of a
technology push research base.

00:16:36.678 --> 00:16:38.970
And we'll talk more about
those things as time goes by,

00:16:38.970 --> 00:16:42.840
but I wanted to get
those out on the table.

00:16:42.840 --> 00:16:45.090
So although radical
may be more profitable,

00:16:45.090 --> 00:16:47.230
incremental is easier,
and obviously, there

00:16:47.230 --> 00:16:48.860
is much more
incremental advance.

00:16:48.860 --> 00:16:50.040
Max?

00:16:50.040 --> 00:16:52.170
AUDIENCE: Regarding
the technology push,

00:16:52.170 --> 00:16:54.310
is that more funded
by governments

00:16:54.310 --> 00:16:57.130
and big institutions,
universities, or?

00:16:57.130 --> 00:16:58.380
WILLIAM BONVILLIAN: Yes.

00:16:58.380 --> 00:17:03.930
Because in our system, as we
talked a bit about last week,

00:17:03.930 --> 00:17:07.589
research is predominantly
funded by government

00:17:07.589 --> 00:17:12.930
and the actors are
universities, and development

00:17:12.930 --> 00:17:15.330
is predominantly
funded by industry,

00:17:15.330 --> 00:17:17.205
which tends to be a more
incremental advance.

00:17:22.550 --> 00:17:24.859
And there's something also
that you just kind of need

00:17:24.859 --> 00:17:26.276
to keep in the
back of your minds,

00:17:26.276 --> 00:17:29.060
which is product cycle theory.

00:17:29.060 --> 00:17:31.310
That products go
through cycles--

00:17:31.310 --> 00:17:33.600
go through evolutionary stages.

00:17:33.600 --> 00:17:37.400
So a firm defines a product,
it develops a market for it,

00:17:37.400 --> 00:17:39.890
then it standardizes
the product.

00:17:39.890 --> 00:17:43.100
And then typically
over time, one design

00:17:43.100 --> 00:17:45.950
will tend to dominate.

00:17:45.950 --> 00:17:49.580
And then the number of competing
companies with varying designs

00:17:49.580 --> 00:17:52.430
will tend to shrink.

00:17:52.430 --> 00:17:55.430
And over time, the
product will sometimes

00:17:55.430 --> 00:17:58.940
become a true commodity product.

00:17:58.940 --> 00:18:01.970
High volume, the price
goes significantly down,

00:18:01.970 --> 00:18:05.570
and the profit margin
is much lower, so

00:18:05.570 --> 00:18:10.370
the uniqueness of the
product kind of ebbs.

00:18:10.370 --> 00:18:13.910
At that stage in the US
system, the production

00:18:13.910 --> 00:18:15.362
often goes offshore.

00:18:15.362 --> 00:18:17.570
That's the moment where it
occurs where the commodity

00:18:17.570 --> 00:18:19.910
production begins.

00:18:19.910 --> 00:18:22.400
Barriers to entry
increase at this point

00:18:22.400 --> 00:18:25.760
because only a modest number of
firms on a standardized product

00:18:25.760 --> 00:18:27.530
tend to dominate.

00:18:27.530 --> 00:18:31.802
And the surviving firms
have to have the capacity

00:18:31.802 --> 00:18:33.260
to keep advancing
their technology,

00:18:33.260 --> 00:18:35.210
keep making
incremental advances.

00:18:35.210 --> 00:18:37.993
They've gotta be able to
master large scale production,

00:18:37.993 --> 00:18:40.160
they've gotta have strong
distribution and marketing

00:18:40.160 --> 00:18:41.952
arms, and they've gotta
have the management

00:18:41.952 --> 00:18:45.050
talent to kind of work
across all those pieces.

00:18:45.050 --> 00:18:45.663
Matt?

00:18:45.663 --> 00:18:47.330
AUDIENCE: Could you
explain just briefly

00:18:47.330 --> 00:18:50.980
how you go from the number of
competing companies reducing

00:18:50.980 --> 00:18:53.938
[INAUDIBLE] commodity
[INAUDIBLE]??

00:18:53.938 --> 00:18:54.980
WILLIAM BONVILLIAN: Yeah.

00:18:54.980 --> 00:18:57.530
I mean, think about things
you see all the time,

00:18:57.530 --> 00:18:58.640
like search engines.

00:18:58.640 --> 00:19:02.390
How was it that Google really
came to dominate the search

00:19:02.390 --> 00:19:03.290
engine business?

00:19:03.290 --> 00:19:05.480
Or think about
operating systems--

00:19:05.480 --> 00:19:10.040
how was it that Microsoft really
came to dominate the operating

00:19:10.040 --> 00:19:12.320
system world?

00:19:12.320 --> 00:19:16.640
So that's just--
consumers tend to lock

00:19:16.640 --> 00:19:18.950
into the dominant product.

00:19:18.950 --> 00:19:21.860
How was it that apple
came to dominate iPhones--

00:19:21.860 --> 00:19:26.300
Although that's obviously up
for grabs every few years.

00:19:26.300 --> 00:19:29.240
It's not to say there
can't be entry of others

00:19:29.240 --> 00:19:32.930
into these fields, but
the barriers to entry

00:19:32.930 --> 00:19:35.150
tend to get higher because
how many firms can really

00:19:35.150 --> 00:19:38.390
master all these skill sets?

00:19:38.390 --> 00:19:41.200
That's pretty sophisticated.

00:19:41.200 --> 00:19:42.195
Does that help?

00:19:42.195 --> 00:19:42.820
AUDIENCE: Yeah.

00:19:42.820 --> 00:19:44.465
I was just thinking
about, like, I

00:19:44.465 --> 00:19:47.620
would expect stiffer competition
to lead to that commodity

00:19:47.620 --> 00:19:50.100
market where you have
a lower profit margin.

00:19:50.100 --> 00:19:52.630
WILLIAM BONVILLIAN: Yeah.

00:19:52.630 --> 00:19:56.650
So you really have to
systematize the operation

00:19:56.650 --> 00:20:01.990
to be able to continue to make
strong gains out of that more

00:20:01.990 --> 00:20:03.467
commodity product line.

00:20:03.467 --> 00:20:05.050
And then typically,
you've got to keep

00:20:05.050 --> 00:20:06.342
driving the costs down as well.

00:20:09.340 --> 00:20:11.140
Now this is not
eternally true, and you

00:20:11.140 --> 00:20:14.170
began to poke at some of
the problems in this model.

00:20:14.170 --> 00:20:17.950
You can think about ways
of disrupting this pattern.

00:20:17.950 --> 00:20:20.710
So for example,
some companies are

00:20:20.710 --> 00:20:25.570
learning how to do continuing
radical innovations.

00:20:25.570 --> 00:20:28.270
That was-- Apple is a
good example of that.

00:20:28.270 --> 00:20:30.610
That was Apple's magic.

00:20:30.610 --> 00:20:32.870
It does the Mac, and
then it does the iPod,

00:20:32.870 --> 00:20:35.008
and then it does the
iPhone and so forth.

00:20:35.008 --> 00:20:36.550
In other words, it's
able to continue

00:20:36.550 --> 00:20:40.630
to do pretty radical innovations
on a continuing basis.

00:20:40.630 --> 00:20:43.360
What enables a company to keep--

00:20:43.360 --> 00:20:46.390
that ability to keep innovating.

00:20:46.390 --> 00:20:49.540
Because it's not--
there are only

00:20:49.540 --> 00:20:52.180
a handful of companies in the
world that are over 100 years

00:20:52.180 --> 00:20:54.220
old.

00:20:54.220 --> 00:20:57.970
They burn themselves out.

00:20:57.970 --> 00:21:00.310
Globalization obviously
spurs competitiveness,

00:21:00.310 --> 00:21:04.210
and it spurs entry and
increased competition.

00:21:04.210 --> 00:21:07.150
It speeds the
product cycle, so it

00:21:07.150 --> 00:21:11.650
can be disruptive of this
traditional product cycle.

00:21:11.650 --> 00:21:14.920
There may be-- and we'll talk
about it more in our next

00:21:14.920 --> 00:21:15.530
class--

00:21:15.530 --> 00:21:19.660
but a kind of rebirth
of manufacturing process

00:21:19.660 --> 00:21:24.880
improvements that could disrupt
this cycle and change it.

00:21:24.880 --> 00:21:29.150
And there's now a very
interesting service sector

00:21:29.150 --> 00:21:32.030
that's not hard-product
based that's emerging,

00:21:32.030 --> 00:21:36.940
and the possibility of
tying services to hardware.

00:21:36.940 --> 00:21:41.650
So an Apple iPhone
is a classic example

00:21:41.650 --> 00:21:46.252
of a hard technology that is
also a service delivery model.

00:21:46.252 --> 00:21:47.710
So we're getting
these combinations

00:21:47.710 --> 00:21:50.260
in interesting new ways.

00:21:50.260 --> 00:21:53.990
That will change this
product cycle as well.

00:21:53.990 --> 00:21:57.700
So it's not a eternal, but I
want you to get an idea product

00:21:57.700 --> 00:21:59.790
cycle theory.

00:21:59.790 --> 00:22:04.290
And then our final idea before
we dig in on the readings--

00:22:04.290 --> 00:22:08.260
dynamic versus static
competitive advantage.

00:22:08.260 --> 00:22:13.230
So David Ricardo, great
economist in the 19th century,

00:22:13.230 --> 00:22:18.660
develops essentially a theory
of static comparative advantage.

00:22:18.660 --> 00:22:21.240
That advantage would be
intrinsic to a country

00:22:21.240 --> 00:22:23.520
typically based on
natural resources,

00:22:23.520 --> 00:22:28.620
and his famous
economic example was--

00:22:28.620 --> 00:22:33.120
and we talked about it
a little bit last week--

00:22:33.120 --> 00:22:37.320
but England has a lot of
rain, has a lot of grass--

00:22:37.320 --> 00:22:41.730
it can have sheep, it
can do wool very well.

00:22:41.730 --> 00:22:44.130
And Portugal doesn't have
that much rain, doesn't

00:22:44.130 --> 00:22:47.880
have that much grass, but
it's great for growing grapes,

00:22:47.880 --> 00:22:51.810
so it's going to do
wine, England will wool.

00:22:51.810 --> 00:22:54.120
Each has a natural
comparative advantage

00:22:54.120 --> 00:23:01.140
based on a resource advantage
and it benefits both to trade.

00:23:01.140 --> 00:23:03.180
Portugal expands
its market for wine

00:23:03.180 --> 00:23:04.920
by growing outside
its own borders.

00:23:04.920 --> 00:23:06.720
England expands
its market for wool

00:23:06.720 --> 00:23:08.340
by growing outside its borders.

00:23:08.340 --> 00:23:10.060
There's a benefit to each.

00:23:10.060 --> 00:23:13.530
So that's the kind of 19th
century concept that's

00:23:13.530 --> 00:23:17.370
the heart of free trade theory.

00:23:17.370 --> 00:23:20.340
That's a static
comparative advantage.

00:23:20.340 --> 00:23:22.500
Starting around the middle
of the 20th century,

00:23:22.500 --> 00:23:25.200
something very different
began to evolve.

00:23:25.200 --> 00:23:30.240
A dynamic comparative
advantage, and this

00:23:30.240 --> 00:23:31.930
is based on growth theory.

00:23:31.930 --> 00:23:35.160
In other words, if
you can be innovative

00:23:35.160 --> 00:23:36.930
and you can lead
innovation waves,

00:23:36.930 --> 00:23:39.660
you can capture a lot of the
early gains of that innovation

00:23:39.660 --> 00:23:41.010
wave.

00:23:41.010 --> 00:23:44.550
It's Solow innovation
based growth theory.

00:23:44.550 --> 00:23:49.140
So that is a dynamic
advantage created by--

00:23:49.140 --> 00:23:52.050
and we have to understand the
menu-- but investments in R&D,

00:23:52.050 --> 00:23:54.360
and education, and
efficient governance,

00:23:54.360 --> 00:23:56.930
those could all be inputs--

00:23:56.930 --> 00:23:59.400
and we'll talk more about
the system later today--

00:23:59.400 --> 00:24:03.930
into a dynamic
comparative advantage.

00:24:03.930 --> 00:24:08.130
Now a dynamic comparative
advantage is not eternal--

00:24:08.130 --> 00:24:08.970
it may get lost.

00:24:08.970 --> 00:24:10.595
And we're going to
talk about some work

00:24:10.595 --> 00:24:15.410
by Paul Samuelson who laid
a lot of that thinking out

00:24:15.410 --> 00:24:20.710
in a famous 2004 article in one
of the next couple of classes.

00:24:20.710 --> 00:24:26.070
So the US created, in many
ways, the biggest innovating

00:24:26.070 --> 00:24:30.840
economy in the world coming out
of that World War II period.

00:24:30.840 --> 00:24:34.860
So it built a
competitive advantage

00:24:34.860 --> 00:24:42.237
based on innovation, which
had been evolving in Europe.

00:24:42.237 --> 00:24:43.820
And countries like
Britain and Germany

00:24:43.820 --> 00:24:46.700
had been doing something
similar starting

00:24:46.700 --> 00:24:48.920
in the second half
of the 19th century,

00:24:48.920 --> 00:24:51.860
but the US really scaled that
model up and really built

00:24:51.860 --> 00:24:55.850
a very strong early
stage innovation system.

00:24:55.850 --> 00:24:58.700
It became the richest
nation on earth.

00:24:58.700 --> 00:25:01.610
That was its model, that was
its comparative advantage.

00:25:01.610 --> 00:25:06.200
Now the problem with a
comparative advantage

00:25:06.200 --> 00:25:09.410
based on innovation
is that others

00:25:09.410 --> 00:25:10.950
can figure out how to innovate.

00:25:14.420 --> 00:25:17.090
England is always going to
have rain, and sheep, and wool,

00:25:17.090 --> 00:25:21.980
and Portugal is always going to
have sun, and grapes, and wine.

00:25:21.980 --> 00:25:24.860
Those are inherent, static
comparative advantages--

00:25:24.860 --> 00:25:26.190
they are not going to change.

00:25:26.190 --> 00:25:29.570
An innovation
advantage can change.

00:25:29.570 --> 00:25:33.050
So the US had an incredible mass
production system coming out

00:25:33.050 --> 00:25:34.820
of the end of World War II.

00:25:34.820 --> 00:25:37.700
Japan figures out a
better innovation model

00:25:37.700 --> 00:25:42.710
based on quality production
and takes consumer electronics

00:25:42.710 --> 00:25:44.960
and large parts of
the auto sector.

00:25:44.960 --> 00:25:50.990
So that's how a comparative
innovation advantage can erode.

00:25:50.990 --> 00:25:55.430
So it's powerful-- you can
get very rich as a nation

00:25:55.430 --> 00:25:57.330
and as a society--

00:25:57.330 --> 00:26:01.010
but it's also up for grabs.

00:26:01.010 --> 00:26:05.350
Anything so far on this?

00:26:05.350 --> 00:26:08.510
Any questions so far?

00:26:08.510 --> 00:26:09.010
All right.

00:26:09.010 --> 00:26:12.490
And these slides will be
parked on the STELLAR site

00:26:12.490 --> 00:26:13.420
and accessible to you.

00:26:13.420 --> 00:26:15.962
So these underlying foundational
ideas will be around for you

00:26:15.962 --> 00:26:17.740
to glance at.

00:26:17.740 --> 00:26:21.460
So today, we move to our
discussion leader system,

00:26:21.460 --> 00:26:23.120
and so here's how
it's going to work.

00:26:23.120 --> 00:26:25.310
I'm going to talk for
10 minutes or so--

00:26:25.310 --> 00:26:26.890
12 minutes,
something like that--

00:26:26.890 --> 00:26:29.080
about the readings.

00:26:29.080 --> 00:26:34.690
And then each of our
able discussion leaders

00:26:34.690 --> 00:26:39.760
is going to in turn
take that reading.

00:26:39.760 --> 00:26:45.310
So Beth has got Nelson
and did you have Atkinson?

00:26:45.310 --> 00:26:46.037
AUDIENCE: Yes.

00:26:46.037 --> 00:26:48.370
WILLIAM BONVILLIAN: Beth
somehow got the really two hard

00:26:48.370 --> 00:26:48.870
readings.

00:26:48.870 --> 00:26:51.270
I don't know how she
lost in the jump ball.

00:26:51.270 --> 00:26:57.520
But lily will take the
next couple of readings,

00:26:57.520 --> 00:27:01.390
and then Martine will follow
up with actually the really fun

00:27:01.390 --> 00:27:03.700
stuff as we get towards
the end of the class.

00:27:03.700 --> 00:27:06.520
So we'll have to make sure
we find full time for it.

00:27:06.520 --> 00:27:07.780
But let me start with Nelson.

00:27:07.780 --> 00:27:13.420
And he's our third grade
growth economist-- a Columbia

00:27:13.420 --> 00:27:15.610
professor of economics.

00:27:15.610 --> 00:27:21.700
And he writes in 1993 this
really interesting book

00:27:21.700 --> 00:27:24.230
about national
innovation systems--

00:27:24.230 --> 00:27:26.590
a comparative analysis.

00:27:26.590 --> 00:27:32.910
And he essentially
puts out another--

00:27:32.910 --> 00:27:34.570
a third innovation factor.

00:27:34.570 --> 00:27:36.960
So we've got Solow's and
Romer's, and Nelson really adds

00:27:36.960 --> 00:27:39.720
a third.

00:27:39.720 --> 00:27:42.480
He develops this term
national innovation system.

00:27:42.480 --> 00:27:43.940
He's not the first
one to use it.

00:27:43.940 --> 00:27:46.440
An economist named Chris Freeman
at the University of Sussex

00:27:46.440 --> 00:27:49.490
in Britain actually is probably
the first to use that term

00:27:49.490 --> 00:27:52.540
in looking at the
Japanese economy.

00:27:52.540 --> 00:27:58.830
But he in this book really
kind of spells that out.

00:27:58.830 --> 00:28:01.620
So he talks about how the
technological capabilities

00:28:01.620 --> 00:28:04.860
of a nation's firms and
other innovation actors

00:28:04.860 --> 00:28:07.965
are a key source of the
nation's competitive palace.

00:28:10.720 --> 00:28:13.240
Does the term
national innovation

00:28:13.240 --> 00:28:16.930
system still make
sense in what is

00:28:16.930 --> 00:28:19.940
a much more globalized world?

00:28:19.940 --> 00:28:22.350
This is, after all, being
written back in 1993.

00:28:22.350 --> 00:28:24.050
A lot has changed.

00:28:24.050 --> 00:28:26.490
It is a much more
integrated, globalized world.

00:28:26.490 --> 00:28:29.970
Is it still a term
that you can look at?

00:28:29.970 --> 00:28:33.090
If Nelson was sitting here,
I think he would argue, yes.

00:28:33.090 --> 00:28:38.640
He would say that enough
of the factors that

00:28:38.640 --> 00:28:40.620
go into an innovation
system are still

00:28:40.620 --> 00:28:44.520
tied to national investments.

00:28:44.520 --> 00:28:49.600
That you can still do a national
analysis, but it's harder.

00:28:49.600 --> 00:28:52.150
And we'll talk about what
some of those national factors

00:28:52.150 --> 00:28:53.890
are in a bit.

00:28:53.890 --> 00:28:57.250
And Nelson here uses the same
broad definition of innovation

00:28:57.250 --> 00:29:01.000
that we've been using so far
in our first two classes.

00:29:01.000 --> 00:29:03.880
And he refers to it as the
process by which firms master

00:29:03.880 --> 00:29:07.510
and get into practice product
designs and new manufacturing

00:29:07.510 --> 00:29:08.330
processes.

00:29:08.330 --> 00:29:13.280
So it's not the invention,
it's something much larger.

00:29:13.280 --> 00:29:16.270
So let's do some background--

00:29:16.270 --> 00:29:19.060
some of his background points.

00:29:19.060 --> 00:29:26.060
He argues that capitalism is
destructive and disruptive.

00:29:26.060 --> 00:29:31.760
That's a term from a great
economist named Schumpeter.

00:29:31.760 --> 00:29:34.490
Destructive capitalism
occurs via innovation.

00:29:34.490 --> 00:29:37.670
It's not necessarily
the first innovator

00:29:37.670 --> 00:29:40.670
that gets all of the rewards
or even most of the rewards.

00:29:40.670 --> 00:29:43.550
Sometimes, the second
follow-on innovator

00:29:43.550 --> 00:29:46.610
captures a lot of the
rewards because they

00:29:46.610 --> 00:29:50.120
pick up from what the first
innovator's mistakes were

00:29:50.120 --> 00:29:51.530
and improve them.

00:29:51.530 --> 00:29:56.760
But a nation's
concern, therefore,

00:29:56.760 --> 00:30:01.470
shouldn't be necessarily with
sponsoring the first innovator.

00:30:01.470 --> 00:30:04.500
It's got to have
a broader concern

00:30:04.500 --> 00:30:07.120
about innovative capability.

00:30:07.120 --> 00:30:08.970
So again, if the
dominant causative factor

00:30:08.970 --> 00:30:11.790
of economic growth is
technological and related

00:30:11.790 --> 00:30:15.500
innovation as Solow
taught all of us,

00:30:15.500 --> 00:30:17.870
Nelson goes on to
start to think about

00:30:17.870 --> 00:30:22.490
what do you do to make sure
you're getting a lot of that?

00:30:22.490 --> 00:30:28.610
And his point is that you need
a system to be able to do that.

00:30:28.610 --> 00:30:34.280
A system of actors that can
be connected and influence,

00:30:34.280 --> 00:30:38.120
and affect, and drive
your innovative outcomes.

00:30:38.120 --> 00:30:40.020
So who are these
institutional actors?

00:30:40.020 --> 00:30:43.040
Universities, firms,
government agencies,

00:30:43.040 --> 00:30:45.680
and the policies around them.

00:30:45.680 --> 00:30:47.540
And he argues that,
yes, there can

00:30:47.540 --> 00:30:53.060
be a common analytical
framework across nations

00:30:53.060 --> 00:30:54.770
by looking at these actors.

00:30:54.770 --> 00:30:56.900
So this is a really
important idea that's

00:30:56.900 --> 00:30:58.970
at the heart of today's class.

00:30:58.970 --> 00:31:01.280
Here it is.

00:31:01.280 --> 00:31:03.620
Innovation is a
system and you can

00:31:03.620 --> 00:31:05.480
look at the strength
of that system

00:31:05.480 --> 00:31:07.880
based on the strength
and connectedness

00:31:07.880 --> 00:31:11.070
of the actors in that system.

00:31:11.070 --> 00:31:16.520
So you can now go to
any nation region area

00:31:16.520 --> 00:31:20.990
and you can start doing
an analysis of just how

00:31:20.990 --> 00:31:23.060
strong that innovation
system is by looking

00:31:23.060 --> 00:31:25.460
at the strength of the actors.

00:31:25.460 --> 00:31:28.880
Things like the firms,
government agencies,

00:31:28.880 --> 00:31:32.120
universities, related policies.

00:31:32.120 --> 00:31:36.500
You can do an assessment
on innovation strengths,

00:31:36.500 --> 00:31:39.680
so this is a key tool.

00:31:39.680 --> 00:31:42.330
And a lot of your-- a lot
of the paper in this class

00:31:42.330 --> 00:31:47.840
is going to be built around
this Nelson system idea.

00:31:47.840 --> 00:31:50.030
He goes off and makes
some interesting points

00:31:50.030 --> 00:31:52.460
about the relationship between
science and technology,

00:31:52.460 --> 00:31:55.070
which is also really a
point about the relationship

00:31:55.070 --> 00:31:57.590
between basic research,
and applied research,

00:31:57.590 --> 00:32:02.120
and development, and
between university research,

00:32:02.120 --> 00:32:05.900
government sponsored
research, and firms.

00:32:05.900 --> 00:32:08.360
And his point is
that new science

00:32:08.360 --> 00:32:13.580
can give rise to new
technology and vise versa.

00:32:16.510 --> 00:32:21.180
So he cites an example
of science leading

00:32:21.180 --> 00:32:24.060
to a technology
such as electricity,

00:32:24.060 --> 00:32:26.010
and he cites Faraday
and so forth.

00:32:26.010 --> 00:32:30.710
He cites chemistry as
science as a follower.

00:32:30.710 --> 00:32:33.370
That it really came
out of a whole series

00:32:33.370 --> 00:32:35.980
of pretty practical professions.

00:32:35.980 --> 00:32:38.410
Some other examples.

00:32:38.410 --> 00:32:41.530
Gibbs creates the whole
science of thermodynamics

00:32:41.530 --> 00:32:45.370
because he's analyzing
steam engines.

00:32:45.370 --> 00:32:49.540
That's where he
develops his thesis.

00:32:49.540 --> 00:32:51.250
Edison is the other way around.

00:32:51.250 --> 00:32:55.030
Edison is trying to do a
very practical electrical

00:32:55.030 --> 00:32:56.920
technology-- the light bulb--

00:32:56.920 --> 00:32:59.890
but he stumbles into science,
something called the Edison

00:32:59.890 --> 00:33:02.590
effect, which actually is kind
of an early way of looking

00:33:02.590 --> 00:33:06.250
at electron theory,
as part of that.

00:33:06.250 --> 00:33:07.780
But this development
of electricity

00:33:07.780 --> 00:33:12.040
yields all kinds of follow-on
scientific advances.

00:33:12.040 --> 00:33:15.130
Aircraft technology starts with
the Wright Brothers who are--

00:33:15.130 --> 00:33:17.770
these are mechanics,
these are tinkerers--

00:33:17.770 --> 00:33:24.640
but then leads to very
deep aerospace engineering.

00:33:24.640 --> 00:33:29.320
The transistor is an attempt
to solve a practical problem--

00:33:29.320 --> 00:33:35.860
high speed switching-- and yet
that leads directly to solid

00:33:35.860 --> 00:33:36.760
state physics--

00:33:36.760 --> 00:33:39.460
a whole new field in physics.

00:33:39.460 --> 00:33:42.610
Computing yields
computing science.

00:33:42.610 --> 00:33:44.980
So it's a two-way street here.

00:33:44.980 --> 00:33:48.970
Science can yield technology,
but technology can also

00:33:48.970 --> 00:33:50.470
yield science.

00:33:50.470 --> 00:33:55.585
So you've got to have that
two-way street operating, which

00:33:55.585 --> 00:33:57.460
means that you've got
to have some connection

00:33:57.460 --> 00:33:58.978
between the forces
in your society

00:33:58.978 --> 00:34:01.270
that are more focused on
technology, which is typically

00:34:01.270 --> 00:34:05.440
firms, and the research
side and vise versa.

00:34:09.738 --> 00:34:10.655
The limits of science.

00:34:14.000 --> 00:34:16.400
Again, innovation is not
simply the invention.

00:34:16.400 --> 00:34:19.790
It's bigger and it
includes design.

00:34:19.790 --> 00:34:21.500
So you engineers
in the room will

00:34:21.500 --> 00:34:23.840
know what we're
talking about here,

00:34:23.840 --> 00:34:26.780
but that really means choosing
the right, quote, "mix

00:34:26.780 --> 00:34:29.969
of performance
characteristics," for example

00:34:29.969 --> 00:34:33.380
in designing a
modern aircraft wing.

00:34:33.380 --> 00:34:36.440
It's not enough to get
the discovery right.

00:34:36.440 --> 00:34:38.210
You've gotta get the
design right too.

00:34:38.210 --> 00:34:42.199
In other words, you need
to select the right mix

00:34:42.199 --> 00:34:44.138
of performance characteristics.

00:34:48.130 --> 00:34:51.040
Who are these innovation actors?

00:34:51.040 --> 00:34:56.710
First and foremost-- and
this was written in 1993--

00:34:56.710 --> 00:34:58.510
is the industry lab.

00:34:58.510 --> 00:35:02.740
So in 1993, something like Bell
Labs, or the great GE labs,

00:35:02.740 --> 00:35:05.440
or the great IBM labs.

00:35:05.440 --> 00:35:09.370
These dominated, in many ways,
the industrial innovation

00:35:09.370 --> 00:35:10.910
landscape.

00:35:10.910 --> 00:35:12.700
They are by and large gone.

00:35:12.700 --> 00:35:16.600
That has dramatically
changed since 1993.

00:35:16.600 --> 00:35:19.600
Now it's not that
large firms don't

00:35:19.600 --> 00:35:26.800
do R&D. They do a lot of it
and that number is growing,

00:35:26.800 --> 00:35:33.320
but it's increasingly
D and less R.

00:35:33.320 --> 00:35:37.850
Also there's a reminder
here that R&D is only part

00:35:37.850 --> 00:35:39.350
of a larger innovation picture.

00:35:39.350 --> 00:35:43.370
So things like management
and management organization--

00:35:43.370 --> 00:35:46.130
organization of R&D can
have major roles here too.

00:35:46.130 --> 00:35:48.410
So actor number one is industry.

00:35:48.410 --> 00:35:51.290
And at the time he writes,
it's industry labs.

00:35:51.290 --> 00:35:53.810
Now that's a much more
dispersed model now,

00:35:53.810 --> 00:35:57.065
because industries have largely
abandoned their old labs

00:35:57.065 --> 00:36:00.050
that used to a lot more
fundamental work to really

00:36:00.050 --> 00:36:03.560
development processes and
rounding up innovators,

00:36:03.560 --> 00:36:05.420
and in some cases,
acquiring them

00:36:05.420 --> 00:36:08.090
like in the biotech sector.

00:36:08.090 --> 00:36:11.190
But industry is still a
central player obviously.

00:36:11.190 --> 00:36:12.830
There are also
university laboratories.

00:36:12.830 --> 00:36:14.163
You all are familiar with those.

00:36:14.163 --> 00:36:16.640
The government laboratories
like the great labs

00:36:16.640 --> 00:36:20.000
for the Department of Energy
or the Department of Defense.

00:36:20.000 --> 00:36:21.770
Then there's a whole
public sector support

00:36:21.770 --> 00:36:27.030
system that's an actor
here as well for R&D,

00:36:27.030 --> 00:36:29.420
and there is an
element historically

00:36:29.420 --> 00:36:33.050
that has supported
industry R&D, particularly

00:36:33.050 --> 00:36:36.710
through the Defense Department.

00:36:36.710 --> 00:36:41.340
So one way to look at
this is the actors.

00:36:41.340 --> 00:36:44.430
The actors will be different in
different industrial sectors.

00:36:44.430 --> 00:36:47.462
They're going to look different,
and they'll be a different mix,

00:36:47.462 --> 00:36:49.170
and they're going to
organize differently

00:36:49.170 --> 00:36:51.480
in different industrial sectors.

00:36:51.480 --> 00:36:58.170
So steel is really
different than aviation.

00:36:58.170 --> 00:37:00.870
These are differently organized
things, but you can see--

00:37:00.870 --> 00:37:04.980
you can nonetheless look at the
innovation actors in a system

00:37:04.980 --> 00:37:08.370
and look at their
strengths and weaknesses.

00:37:08.370 --> 00:37:11.340
Complex technologies
require supply chains,

00:37:11.340 --> 00:37:13.710
and therefore
customers and users

00:37:13.710 --> 00:37:16.740
play a role in the
innovation system

00:37:16.740 --> 00:37:22.500
because there's a whole
feedback system that comes in.

00:37:22.500 --> 00:37:25.780
So the customers play a role
for complex technologies

00:37:25.780 --> 00:37:27.300
particularly.

00:37:27.300 --> 00:37:29.610
So it's not only the actors
I've gone through so far.

00:37:29.610 --> 00:37:33.360
Customers can be brought in
and users can be brought in.

00:37:33.360 --> 00:37:36.690
So you've got much closer to an
idea of an innovation network

00:37:36.690 --> 00:37:39.680
here, and we'll talk a
bit about Rycroft and Kash

00:37:39.680 --> 00:37:41.280
to kind of spell that out.

00:37:41.280 --> 00:37:43.860
So he does a comparison.

00:37:43.860 --> 00:37:48.150
He compares the US
innovation system in the 1945

00:37:48.150 --> 00:37:50.210
the 1975 time frame--

00:37:50.210 --> 00:37:52.530
he compares that to
the Japanese innovation

00:37:52.530 --> 00:37:55.260
system in the '70s and '80s.

00:37:55.260 --> 00:38:01.190
It's a very different
innovation systems,

00:38:01.190 --> 00:38:04.620
hence, help driving the theory
of national innovation systems.

00:38:04.620 --> 00:38:07.730
So in that time
period, the US firms

00:38:07.730 --> 00:38:09.290
tended to be larger in scale.

00:38:09.290 --> 00:38:11.990
They served a
continent-sized market.

00:38:11.990 --> 00:38:16.430
The firms spent more in the US
on R&D. The government spends

00:38:16.430 --> 00:38:19.672
a lot more on R&D at the
time, particularly because

00:38:19.672 --> 00:38:20.630
of the defense mission.

00:38:20.630 --> 00:38:24.410
US university
research was stronger

00:38:24.410 --> 00:38:26.600
as a result of some
post-war decision making

00:38:26.600 --> 00:38:28.040
that the US made.

00:38:28.040 --> 00:38:31.110
And most US goods were
sold into US markets.

00:38:31.110 --> 00:38:35.510
So that's some framing
ideas around the US model.

00:38:35.510 --> 00:38:36.770
Japan is really different.

00:38:36.770 --> 00:38:39.830
Japan is very
resource poor, so it

00:38:39.830 --> 00:38:44.480
has to have strong exports to
be able to get the resources.

00:38:44.480 --> 00:38:47.510
So it's got to be an
export led economy.

00:38:47.510 --> 00:38:49.610
Whereas the US can
organize essentially

00:38:49.610 --> 00:38:51.710
on national consumer
markets, Japan

00:38:51.710 --> 00:38:54.560
has got to expand globally.

00:38:54.560 --> 00:38:56.762
R&D in Japan in
this time period--

00:38:56.762 --> 00:38:58.220
and still pretty
much to this day--

00:38:58.220 --> 00:39:02.840
is more tied to industry
than is the case with the US.

00:39:02.840 --> 00:39:04.338
There's less
fundamental research.

00:39:04.338 --> 00:39:06.380
There's much more applied
and development support

00:39:06.380 --> 00:39:08.630
from government.

00:39:08.630 --> 00:39:12.740
And there are, from government,
very explicit technology

00:39:12.740 --> 00:39:17.070
development policies
at this time.

00:39:17.070 --> 00:39:20.348
So that's just a way of looking
at two different countries

00:39:20.348 --> 00:39:22.640
and beginning to think about
their different innovation

00:39:22.640 --> 00:39:24.410
systems and some of
the underlying factors

00:39:24.410 --> 00:39:26.600
that will drive them.

00:39:26.600 --> 00:39:30.470
He argues that there's several
basic categories of countries.

00:39:30.470 --> 00:39:34.100
Large high income, small
high income, and then

00:39:34.100 --> 00:39:36.860
lower income countries.

00:39:36.860 --> 00:39:40.220
Countries without resources have
to have an export orientation,

00:39:40.220 --> 00:39:43.970
and he cites Germany,
Japan, Korea.

00:39:43.970 --> 00:39:46.910
The US, and to some
extent the UK and France,

00:39:46.910 --> 00:39:49.130
have a national
security orientation

00:39:49.130 --> 00:39:50.900
for their innovation systems.

00:39:50.900 --> 00:39:53.690
We justify a lot
of R&D investment

00:39:53.690 --> 00:39:55.760
for national security
reasons in the US.

00:39:55.760 --> 00:39:58.940
Other countries don't do that.

00:39:58.940 --> 00:40:01.940
There's differences in
the governmental role.

00:40:01.940 --> 00:40:06.085
The US government tends to
be a lot less interventionist

00:40:06.085 --> 00:40:08.210
in the innovation system,
in the economy in general

00:40:08.210 --> 00:40:12.030
than, for example, Japan
was in this time period.

00:40:12.030 --> 00:40:14.060
So there are
country differences.

00:40:14.060 --> 00:40:16.850
What's innovation's success?

00:40:16.850 --> 00:40:20.450
Strong firms, in Nelson's
mind, is the critical factor.

00:40:20.450 --> 00:40:22.970
They have got to do
all the translation,

00:40:22.970 --> 00:40:28.340
moving from discovery, to
fit a whole raft of tasks

00:40:28.340 --> 00:40:30.980
that they've got to perform
in this translation task.

00:40:30.980 --> 00:40:33.110
So without strong firms,
you got a serious problem

00:40:33.110 --> 00:40:35.213
in your innovation system.

00:40:35.213 --> 00:40:36.380
But there are other factors.

00:40:36.380 --> 00:40:40.400
Education and training,
trade policy, fiscal policy,

00:40:40.400 --> 00:40:43.110
public support of
university research.

00:40:43.110 --> 00:40:45.680
These are all elements,
again, in the system.

00:40:45.680 --> 00:40:48.680
But he places the firm
kind of front and center.

00:40:48.680 --> 00:40:52.340
And given what firms
look like in 1993,

00:40:52.340 --> 00:40:53.420
you can kind of see why.

00:40:53.420 --> 00:40:55.500
It's a more complicated,
complex story now.

00:40:58.670 --> 00:41:02.420
How about an explicit
governmental role

00:41:02.420 --> 00:41:05.620
in innovation?

00:41:05.620 --> 00:41:08.830
How direct should that
governmental role be?

00:41:08.830 --> 00:41:10.900
So he's fine with
the earlier stages.

00:41:10.900 --> 00:41:13.960
He notes that there's a whole
ongoing debate about how far

00:41:13.960 --> 00:41:17.200
down the innovation pipeline
the government should intervene.

00:41:17.200 --> 00:41:18.820
That's been a
longstanding US debate,

00:41:18.820 --> 00:41:21.790
and we'll get more into
that as the class goes on.

00:41:21.790 --> 00:41:26.510
So that's our Nelson story.

00:41:26.510 --> 00:41:28.250
And Beth, why don't
I turn it over to you

00:41:28.250 --> 00:41:31.910
to raise some ideas about
Nelson that you saw,

00:41:31.910 --> 00:41:36.735
and to lead us in some and Q&A?

00:41:36.735 --> 00:41:37.860
AUDIENCE: OK.

00:41:37.860 --> 00:41:41.306
So based on the questions that
I got from people in the class,

00:41:41.306 --> 00:41:43.434
I kind of saw four
trends emerge in things

00:41:43.434 --> 00:41:45.090
that we were curious about.

00:41:45.090 --> 00:41:49.170
One being the stuff we
brought up in the beginning--

00:41:49.170 --> 00:41:52.542
is considering a national
innovation system as a better

00:41:52.542 --> 00:41:59.238
way to promote innovation, or
do we look at a more granular

00:41:59.238 --> 00:42:02.710
level by looking at industries,
or at a less granular--

00:42:02.710 --> 00:42:05.730
[AUDIO OUT]

00:42:05.730 --> 00:42:08.910
The second main topic
area that came up a lot

00:42:08.910 --> 00:42:11.130
was just what are the best
policies for innovation

00:42:11.130 --> 00:42:15.420
now, given that this paper
is a little bit older.

00:42:15.420 --> 00:42:17.710
As the world has
changed, what do

00:42:17.710 --> 00:42:21.180
we see as the best
ways to move forward.

00:42:21.180 --> 00:42:24.840
Third theme that came up
was technology spillover

00:42:24.840 --> 00:42:28.740
and how that can be
used as an advantage.

00:42:28.740 --> 00:42:31.680
And last was balancing
these national interests

00:42:31.680 --> 00:42:33.630
versus the international
relationships that

00:42:33.630 --> 00:42:36.180
have emerged in firms.

00:42:36.180 --> 00:42:39.985
So just a few summary points
before we go into those.

00:42:39.985 --> 00:42:41.610
I'll read through
some of the questions

00:42:41.610 --> 00:42:45.960
that I thought were
especially enlightening.

00:42:45.960 --> 00:42:50.460
Just the basis of using
national innovation systems

00:42:50.460 --> 00:42:53.040
from Nelson's point of
view is that countries

00:42:53.040 --> 00:42:55.650
have some similarities, but
because of their differences

00:42:55.650 --> 00:42:58.890
in history, culture, their
infrastructure, laws,

00:42:58.890 --> 00:43:01.980
financial institutions,
policies, and investing,

00:43:01.980 --> 00:43:05.430
we see that there are inherent
differences to innovation

00:43:05.430 --> 00:43:08.370
systems in different countries.

00:43:08.370 --> 00:43:11.160
And that for these
countries to be successful,

00:43:11.160 --> 00:43:13.995
it's not just enough
to have manufacturing--

00:43:13.995 --> 00:43:17.670
that's not a substitute for
technological innovation.

00:43:17.670 --> 00:43:21.965
So you need these strong firms
that are constantly innovating.

00:43:21.965 --> 00:43:23.340
And so he comes
to the conclusion

00:43:23.340 --> 00:43:25.860
that national innovation
systems, while they

00:43:25.860 --> 00:43:29.760
may seem somewhat contradictory
term considering policies are

00:43:29.760 --> 00:43:32.220
different for different
industries within a nation,

00:43:32.220 --> 00:43:37.120
are still useful for comparing
how nations foster innovation.

00:43:37.120 --> 00:43:38.670
And so first I
just think it'd be

00:43:38.670 --> 00:43:41.970
interesting to hear what people
see as the appropriate way

00:43:41.970 --> 00:43:43.290
to treat innovation systems.

00:43:43.290 --> 00:43:46.380
Is it at this national level,
is it at industry level,

00:43:46.380 --> 00:43:50.480
should it just be international
interactions with each other?

00:43:50.480 --> 00:43:52.690
So I'd like to open it up
to some thoughts on that.

00:43:56.563 --> 00:43:58.730
AUDIENCE: I think there was
one point that was made.

00:43:58.730 --> 00:44:00.188
I think it was
[INAUDIBLE] reading.

00:44:00.188 --> 00:44:02.320
It said, like, it
sort of depends

00:44:02.320 --> 00:44:06.400
on the industry as to whether
an innovation system takes

00:44:06.400 --> 00:44:10.090
place on a national level
or, like a firm level.

00:44:10.090 --> 00:44:13.010
Certain things, like
aerospace, were often--

00:44:13.010 --> 00:44:16.630
or defense oriented
things were very isolated

00:44:16.630 --> 00:44:18.220
to the nation in question.

00:44:18.220 --> 00:44:20.590
But other-- like
biotech type stuff

00:44:20.590 --> 00:44:25.230
could be more group effort
between multiple things.

00:44:25.230 --> 00:44:29.120
So it kind of
depends on the field.

00:44:29.120 --> 00:44:31.120
AUDIENCE: I think it
depends on what time period

00:44:31.120 --> 00:44:33.900
your analyzing it, because
a lot of the readings

00:44:33.900 --> 00:44:36.250
spoke about past economic
trends and, like,

00:44:36.250 --> 00:44:38.420
these big, long-term waves.

00:44:38.420 --> 00:44:40.510
But I forget which
one of the readings

00:44:40.510 --> 00:44:45.040
stated that [INAUDIBLE] a lot
of more global connection being

00:44:45.040 --> 00:44:46.780
impossible.

00:44:46.780 --> 00:44:50.000
The idea of a national
level doesn't make sense

00:44:50.000 --> 00:44:52.665
as much as a global scale does.

00:44:52.665 --> 00:44:54.040
But I guess that's
yet to be seen

00:44:54.040 --> 00:44:58.844
because we're still sort of
in the same wave, I guess.

00:45:02.412 --> 00:45:04.120
AUDIENCE: So you think
it might be more--

00:45:04.120 --> 00:45:06.460
rather than trying to make
a generalization for how

00:45:06.460 --> 00:45:07.960
innovation has
always happened, it's

00:45:07.960 --> 00:45:10.125
kind of depending on
what kind of innovation

00:45:10.125 --> 00:45:11.500
we're seeing that
might be how we

00:45:11.500 --> 00:45:14.830
want to describe the innovation
systems going forward.

00:45:17.370 --> 00:45:20.860
And then thinking about
policies for innovation,

00:45:20.860 --> 00:45:22.450
one interesting
question that came up

00:45:22.450 --> 00:45:25.960
was how does national
technology policy shape

00:45:25.960 --> 00:45:28.960
the focus of research being
conducted and company pursuits?

00:45:28.960 --> 00:45:32.080
And then going off that, how
should national technology

00:45:32.080 --> 00:45:35.770
policy shape the
focus of research?

00:45:35.770 --> 00:45:37.360
So that kind of comes
into that debate

00:45:37.360 --> 00:45:40.960
of how far in the pipeline
should the government

00:45:40.960 --> 00:45:43.390
be intervening, or
should it be kind

00:45:43.390 --> 00:45:46.087
of a societal call for action--

00:45:46.087 --> 00:45:47.170
where should this come up?

00:45:50.710 --> 00:45:53.240
AUDIENCE: Well, in general,
the history of innovation,

00:45:53.240 --> 00:45:55.493
like, early on, usually
it's not an expert

00:45:55.493 --> 00:45:56.410
anything that does it.

00:45:56.410 --> 00:46:00.730
Like the Wright Brothers weren't
really experts in flight,

00:46:00.730 --> 00:46:01.805
and the reason that--

00:46:01.805 --> 00:46:03.180
because they
weren't experts that

00:46:03.180 --> 00:46:06.440
were able to figure out a
different way of doing it.

00:46:06.440 --> 00:46:08.590
So probably the right
area for government

00:46:08.590 --> 00:46:12.923
is right after the initial
is then figured out.

00:46:12.923 --> 00:46:14.840
When you kind of know
there's something there,

00:46:14.840 --> 00:46:17.490
and now you can start
pulling in resources.

00:46:17.490 --> 00:46:19.252
But innovation in
general, it could

00:46:19.252 --> 00:46:20.710
be like making a
sculpture or maybe

00:46:20.710 --> 00:46:21.972
that you need to make a house.

00:46:21.972 --> 00:46:23.680
So when it's time to
kind of make a house

00:46:23.680 --> 00:46:25.300
and you need a lot
of hammers, I think

00:46:25.300 --> 00:46:27.245
that's a good time
for government policy.

00:46:27.245 --> 00:46:28.870
Before when it's like
chiseling, that's

00:46:28.870 --> 00:46:31.570
better for individuals or firms.

00:46:31.570 --> 00:46:35.470
Back to the idea of
industry being incentivized

00:46:35.470 --> 00:46:38.400
through government funds,
in general, an industry

00:46:38.400 --> 00:46:41.950
they'll do their own research
when they have a monopoly.

00:46:41.950 --> 00:46:45.370
I guess if-- what used
to happen which was--

00:46:45.370 --> 00:46:49.620
I forget what company Apple
took the graphic user interface

00:46:49.620 --> 00:46:51.640
from, but that was all--

00:46:51.640 --> 00:46:53.590
AUDIENCE: Xerox?

00:46:53.590 --> 00:46:54.890
AUDIENCE: Yeah, Xerox PARC.

00:46:54.890 --> 00:46:56.890
They were famous for
having a lot of innovations

00:46:56.890 --> 00:46:59.140
that they could never take
to the product stage, which

00:46:59.140 --> 00:47:00.622
is back to the
point that you made

00:47:00.622 --> 00:47:02.080
on being able to
take an innovation

00:47:02.080 --> 00:47:03.700
and also make it
a product and put

00:47:03.700 --> 00:47:06.340
in some kind of
industrial cycle.

00:47:06.340 --> 00:47:08.080
But government grants,
like SBIR grants,

00:47:08.080 --> 00:47:12.610
are pretty good too for
creating that kind of industry

00:47:12.610 --> 00:47:16.000
innovation, and I guess
with better incentives.

00:47:19.400 --> 00:47:21.442
WILLIAM BONVILLIAN:
So Martine, you

00:47:21.442 --> 00:47:22.900
make a series of
interesting points

00:47:22.900 --> 00:47:25.510
there, and let me back to
the first one which you made.

00:47:25.510 --> 00:47:28.090
And you made this interesting
distinction between a sculpture

00:47:28.090 --> 00:47:29.860
and a building.

00:47:29.860 --> 00:47:34.030
And I think historically in
the US, the attitude has--

00:47:34.030 --> 00:47:37.690
even though logic would
say let's think about

00:47:37.690 --> 00:47:40.420
the building-- that might be the
moment for government support--

00:47:40.420 --> 00:47:43.690
historically, the
government support

00:47:43.690 --> 00:47:46.930
has been at the earlier stage,
at that sculpture moment

00:47:46.930 --> 00:47:49.240
before it turns into a building.

00:47:49.240 --> 00:47:51.260
And that's pretty
deep in our system.

00:47:51.260 --> 00:47:52.810
So in other words,
it's historically

00:47:52.810 --> 00:47:55.450
been OK for government to
support basic research,

00:47:55.450 --> 00:47:58.930
but when it gets within
range of commercialisation,

00:47:58.930 --> 00:48:01.720
that would be a
governmental interference

00:48:01.720 --> 00:48:03.340
into the marketplace.

00:48:03.340 --> 00:48:08.015
So most countries don't do
that, but that historically

00:48:08.015 --> 00:48:09.640
has been a limit on
the way in which we

00:48:09.640 --> 00:48:10.598
think about this stuff.

00:48:10.598 --> 00:48:15.260
So when Nelson talks about
whether there should be

00:48:15.260 --> 00:48:20.562
an explicit role for government,
what he calls high tech

00:48:20.562 --> 00:48:22.520
innovation-- in other
words, later stage work--

00:48:22.520 --> 00:48:25.670
that's a controversial
topic for him to take on.

00:48:25.670 --> 00:48:29.180
And when we talk about
Charles Schulz later,

00:48:29.180 --> 00:48:34.173
we'll see kind of the dimensions
of this debate come further.

00:48:34.173 --> 00:48:35.090
But what do you think?

00:48:35.090 --> 00:48:36.810
Is that--

00:48:36.810 --> 00:48:38.600
AUDIENCE: What I'm curious is--

00:48:38.600 --> 00:48:40.610
so there's two
kinds of, I guess,

00:48:40.610 --> 00:48:42.410
kind of sculpture innovation.

00:48:42.410 --> 00:48:45.133
The only one I can think of that
was successful with government

00:48:45.133 --> 00:48:46.550
intervention was
kind of like when

00:48:46.550 --> 00:48:48.967
they're making the atomic bomb,
because that was very much

00:48:48.967 --> 00:48:50.450
that we need a technology push.

00:48:50.450 --> 00:48:53.330
But in other cases, especially
for the Wright Brothers--

00:48:53.330 --> 00:48:54.830
I forget what the
name of the person

00:48:54.830 --> 00:48:56.163
that the government was funding.

00:48:56.163 --> 00:49:00.440
He was the expert in
aerodynamics at the time,

00:49:00.440 --> 00:49:04.510
but because his equations didn't
work out, he didn't do it.

00:49:04.510 --> 00:49:06.260
WILLIAM BONVILLIAN:
Yeah, all his aircraft

00:49:06.260 --> 00:49:08.120
landed in the Anacostia
River in big flames.

00:49:08.120 --> 00:49:08.745
AUDIENCE: Yeah.

00:49:08.745 --> 00:49:10.850
Well, the way I think about it--

00:49:10.850 --> 00:49:12.980
they say an expert is an
expert in a field that's

00:49:12.980 --> 00:49:14.035
already been created.

00:49:14.035 --> 00:49:15.410
And a lot of time,
this innovator

00:49:15.410 --> 00:49:17.160
is not going to look
like an expert at all

00:49:17.160 --> 00:49:18.680
because the field
has not been made.

00:49:18.680 --> 00:49:23.493
Like Edison, you really wouldn't
say use a genius in any field,

00:49:23.493 --> 00:49:25.160
but he did figure out
something and then

00:49:25.160 --> 00:49:26.908
he took it as far
as he could go.

00:49:26.908 --> 00:49:28.700
But another distinction
too is that there's

00:49:28.700 --> 00:49:30.830
going to be that are going
to team up with them.

00:49:30.830 --> 00:49:35.498
Example with Edison is
that GE had a lot of issues

00:49:35.498 --> 00:49:37.040
with their transmission
lines, and it

00:49:37.040 --> 00:49:40.120
wasn't until they got this one
Hungarian immigrant called--

00:49:40.120 --> 00:49:42.500
I forget his first name, but
his last name was Steinmetz.

00:49:42.500 --> 00:49:44.750
He's like this very hunchback--

00:49:44.750 --> 00:49:46.760
he's famous for never
being in pictures

00:49:46.760 --> 00:49:50.000
because he was just very
hunchback and short.

00:49:50.000 --> 00:49:52.250
But he came up with these
equations and he figured out

00:49:52.250 --> 00:49:52.780
all the--

00:49:52.780 --> 00:49:56.500
he solved all the main
problems with the technology.

00:49:56.500 --> 00:49:59.280
So I definitely think there
should probably more study,

00:49:59.280 --> 00:50:02.652
I guess, on that-- on when was
the government most successful

00:50:02.652 --> 00:50:03.610
with their investments.

00:50:03.610 --> 00:50:04.897
I don't know if they do that.

00:50:04.897 --> 00:50:06.480
I don't really know
how the government

00:50:06.480 --> 00:50:09.780
works with innovation
as much as you do.

00:50:09.780 --> 00:50:10.935
But in general, VCs--

00:50:10.935 --> 00:50:11.430
WILLIAM BONVILLIAN:
Don't worry, you'll

00:50:11.430 --> 00:50:13.597
be an expert by the time
the class has [INAUDIBLE]..

00:50:13.597 --> 00:50:16.200
AUDIENCE: Well, in general VCs
will look at their investments

00:50:16.200 --> 00:50:18.570
and then figure out why they
won with their investment.

00:50:18.570 --> 00:50:20.820
So that might be a good way
of looking into it-- like,

00:50:20.820 --> 00:50:22.680
in the history of the US,
when do we make investments

00:50:22.680 --> 00:50:23.910
and how do they payoff?

00:50:23.910 --> 00:50:25.965
And also, like, what do
we measure the success,

00:50:25.965 --> 00:50:27.840
because it probably
won't be economic returns

00:50:27.840 --> 00:50:29.520
because the nature
of the problem.

00:50:29.520 --> 00:50:32.505
But if you look at in
terms of development,

00:50:32.505 --> 00:50:34.380
there's going to be a
lot of hidden variables

00:50:34.380 --> 00:50:36.330
that we don't account
for that probably

00:50:36.330 --> 00:50:40.410
need to account for when
we measure that success.

00:50:40.410 --> 00:50:42.745
AUDIENCE: I think
Martine hit on something,

00:50:42.745 --> 00:50:44.370
which is how does
the government choose

00:50:44.370 --> 00:50:47.290
sort of when to get involved?

00:50:47.290 --> 00:50:51.030
The only example I
might have is SpaceX,

00:50:51.030 --> 00:50:54.850
because they get a lot of
support because of just the way

00:50:54.850 --> 00:50:56.850
they transitioned sort
of out of the space race.

00:50:56.850 --> 00:50:59.240
We have a lot of
infrastructure at NASA

00:50:59.240 --> 00:51:02.220
who, like, no longer wants
to focus specifically

00:51:02.220 --> 00:51:05.630
sort of on space exploration
in a way that might be private

00:51:05.630 --> 00:51:07.230
or commercially available.

00:51:07.230 --> 00:51:09.500
But you have this sort
of technology spillover

00:51:09.500 --> 00:51:11.448
and all these resources
that exist at NASA.

00:51:11.448 --> 00:51:12.990
They have a whole
bunch of launchpads

00:51:12.990 --> 00:51:15.840
everywhere that
they can't really

00:51:15.840 --> 00:51:17.340
take advantage of
because that's not

00:51:17.340 --> 00:51:18.630
what they're geared
towards, and they're

00:51:18.630 --> 00:51:19.880
trying to move somewhere else.

00:51:19.880 --> 00:51:22.700
But you have this
infrastructure leftover,

00:51:22.700 --> 00:51:26.403
and we started sort of leasing
it out to companies like SpaceX

00:51:26.403 --> 00:51:28.320
to sort of do launch
demonstrations and things

00:51:28.320 --> 00:51:29.620
like that.

00:51:29.620 --> 00:51:30.480
And so I think--

00:51:30.480 --> 00:51:31.740
but that only comes--

00:51:31.740 --> 00:51:33.960
and I don't know exactly
how that came about,

00:51:33.960 --> 00:51:36.293
but I think you might be able
to facilitate those roles,

00:51:36.293 --> 00:51:39.120
where the government sort
of has resources built up

00:51:39.120 --> 00:51:40.350
from things previously.

00:51:40.350 --> 00:51:42.767
And the industry might be
moving in a different direction,

00:51:42.767 --> 00:51:45.040
and it might see
more advantaged ways

00:51:45.040 --> 00:51:49.325
to pass off use of facilities
and things like that.

00:51:49.325 --> 00:51:50.857
And sort of we have--

00:51:50.857 --> 00:51:53.190
these launchpads at NASA we're
trying to get away from--

00:51:53.190 --> 00:51:54.840
I guess we have
national labs now

00:51:54.840 --> 00:51:57.000
which are traditionally
more basic research,

00:51:57.000 --> 00:52:01.770
but could be used to sort of
bring in companies as sort

00:52:01.770 --> 00:52:04.320
of testing grounds for a lot
of different technologies.

00:52:04.320 --> 00:52:06.180
So I think energy might
be a little bit more

00:52:06.180 --> 00:52:09.900
useful, and even biotech
because we have supercomputers

00:52:09.900 --> 00:52:11.590
that are shown.

00:52:11.590 --> 00:52:14.790
But it's important
to kind of identify

00:52:14.790 --> 00:52:16.860
that point which
technologies might

00:52:16.860 --> 00:52:20.860
be a little bit more receptive
to sort of that branching out.

00:52:20.860 --> 00:52:23.700
And I think it comes from maybe
one of the latter readings,

00:52:23.700 --> 00:52:27.960
where it's, like you have to
identify who's in the market

00:52:27.960 --> 00:52:29.820
and what are their needs.

00:52:29.820 --> 00:52:31.620
And that conversation
doesn't really

00:52:31.620 --> 00:52:35.250
happen because the government
doesn't get to choose winners.

00:52:35.250 --> 00:52:36.810
But I think at some
point, it's going

00:52:36.810 --> 00:52:41.605
to be necessary to kind
of consult the necessary--

00:52:41.605 --> 00:52:43.230
I'm going to use the
word experts here.

00:52:43.230 --> 00:52:44.647
And then you don't
really know who

00:52:44.647 --> 00:52:47.255
the experts are until you kind
of bring the Wright Brothers in

00:52:47.255 --> 00:52:49.380
if they make a jump or a leap.

00:52:49.380 --> 00:52:51.450
But I think it could
have been facilitated

00:52:51.450 --> 00:52:55.020
if they had brought
this guy in and found

00:52:55.020 --> 00:52:56.395
that maybe all of
his experiments

00:52:56.395 --> 00:52:57.937
were crashing in
the Anacostia river.

00:52:57.937 --> 00:53:00.180
So the government would
have initially-- like, OK,

00:53:00.180 --> 00:53:01.950
his experiments are crashing--
we need to look somewhere else

00:53:01.950 --> 00:53:03.610
and we found the
Wright Brothers.

00:53:03.610 --> 00:53:06.770
And so I think it's this--

00:53:06.770 --> 00:53:10.340
the emphasis has to be on these
public-private partnerships

00:53:10.340 --> 00:53:12.720
and facilitate those maybe
a little bit earlier.

00:53:12.720 --> 00:53:15.150
And bringing in sort of
these industry experts who

00:53:15.150 --> 00:53:17.600
are shifting gears to new
directions to kind of figure

00:53:17.600 --> 00:53:20.000
out what is the best
role, because it's

00:53:20.000 --> 00:53:22.000
going to vary sector by sector.

00:53:22.000 --> 00:53:25.770
Because obviously, it wouldn't
do maybe the Wright Brothers

00:53:25.770 --> 00:53:28.550
as much good if they had
access to a supercomputer,

00:53:28.550 --> 00:53:29.240
for example.

00:53:29.240 --> 00:53:31.850
But it might do them
good if they had access

00:53:31.850 --> 00:53:35.040
to sort of these landing
zones or large areas of space

00:53:35.040 --> 00:53:38.140
[INAUDIBLE] to test
flight developments

00:53:38.140 --> 00:53:39.773
and things like that.

00:53:39.773 --> 00:53:41.940
AUDIENCE: Yeah, but kind
of going back to your point

00:53:41.940 --> 00:53:45.530
and playing devil's
advocate there,

00:53:45.530 --> 00:53:48.470
if we're not funding the
sculptors originally,

00:53:48.470 --> 00:53:52.040
do we have concerns that there
won't be enough that are taking

00:53:52.040 --> 00:53:54.470
the risk on their own
to make the first steps

00:53:54.470 --> 00:53:56.410
before commercialization?

00:53:56.410 --> 00:53:58.845
Like, do we need to consider
that balance a little bit?

00:53:58.845 --> 00:54:01.220
AUDIENCE: I think that's an
interesting question in terms

00:54:01.220 --> 00:54:03.920
of if the Wright Brothers
were alive today,

00:54:03.920 --> 00:54:06.370
would they be able to get any
kind of government support.

00:54:06.370 --> 00:54:08.970
And then you can think about,
well, what kind of support,

00:54:08.970 --> 00:54:11.178
or how should the government
be structured to support

00:54:11.178 --> 00:54:12.912
that kind of innovator?

00:54:12.912 --> 00:54:14.870
AUDIENCE: I don't think
it's necessarily fair--

00:54:14.870 --> 00:54:15.880
I think you make very--

00:54:15.880 --> 00:54:16.760
WILLIAM BONVILLIAN: So
I'm going to ask everybody

00:54:16.760 --> 00:54:18.935
to identify themselves
because we're all in film.

00:54:18.935 --> 00:54:20.800
We're all part of a movie.

00:54:20.800 --> 00:54:22.253
So just throw out
your first name

00:54:22.253 --> 00:54:24.545
before you start so we all
get to know each other well.

00:54:24.545 --> 00:54:26.110
AUDIENCE: Chloe.

00:54:26.110 --> 00:54:28.420
I think you make a great
point about the interaction

00:54:28.420 --> 00:54:30.920
between-- in commercial space,
like between NASA and SpaceX,

00:54:30.920 --> 00:54:34.148
and NASA optimizing
their resources

00:54:34.148 --> 00:54:36.440
when it's not really in their
best interest to use them

00:54:36.440 --> 00:54:38.027
all the time, but
leasing them out

00:54:38.027 --> 00:54:39.410
to private companies that can.

00:54:39.410 --> 00:54:44.100
But I think they do still
sort of choose winners.

00:54:44.100 --> 00:54:47.450
Like the Wright Brothers in
the world of spaceflight,

00:54:47.450 --> 00:54:49.220
there's a lot of--

00:54:49.220 --> 00:54:52.502
NASA would put out a bid for
maybe a certain spacecraft

00:54:52.502 --> 00:54:53.210
bus or something.

00:54:53.210 --> 00:54:55.340
And then Lockheed and--

00:54:55.340 --> 00:54:57.590
not so much SpaceX, but a
bunch of different companies

00:54:57.590 --> 00:55:03.050
could submit proposals for how
they might fulfill those design

00:55:03.050 --> 00:55:06.290
requirements cheapest and
the most technologically

00:55:06.290 --> 00:55:06.790
successful.

00:55:06.790 --> 00:55:08.870
So I think that might
not be choosing winners,

00:55:08.870 --> 00:55:11.090
but that is sort of one
way that the government can

00:55:11.090 --> 00:55:13.880
support some innovation
in the early stage

00:55:13.880 --> 00:55:19.578
and maybe encourage
newcomers to take some risks.

00:55:19.578 --> 00:55:20.745
AUDIENCE: Chris, by the way.

00:55:20.745 --> 00:55:24.790
I think where government
has a really important role

00:55:24.790 --> 00:55:28.990
is probably galvanizing support,
and especially initial funding,

00:55:28.990 --> 00:55:33.370
for potentially riskier kind
of ventures at earlier stages.

00:55:33.370 --> 00:55:36.280
For example, I know
in like biotech--

00:55:36.280 --> 00:55:38.020
for example cystic
fibrosis, that

00:55:38.020 --> 00:55:40.660
was a huge push by the
government and some pretty

00:55:40.660 --> 00:55:45.220
national groups to get research
on the ground and really focus.

00:55:45.220 --> 00:55:47.830
And it took like 10 or
12 years and hundreds

00:55:47.830 --> 00:55:49.900
of millions of dollars,
but they finally

00:55:49.900 --> 00:55:53.860
came up with a drug, Kalydeco
which was produced by Vertex.

00:55:53.860 --> 00:55:57.050
So that kind of initiative
I think is really useful.

00:55:57.050 --> 00:56:01.060
And national policies, like
for example cancer [INAUDIBLE]

00:56:01.060 --> 00:56:04.480
or something like that, that
set a precedence and places

00:56:04.480 --> 00:56:07.930
importance on development
of these kind of drugs

00:56:07.930 --> 00:56:12.070
and creates some sort of
importance and path for them

00:56:12.070 --> 00:56:17.290
to incentivize development
throughout expedited patent

00:56:17.290 --> 00:56:20.590
approval and kind
of maybe tax breaks

00:56:20.590 --> 00:56:22.970
or support for that R&D process.

00:56:22.970 --> 00:56:27.190
I think those can really help
guide technology development as

00:56:27.190 --> 00:56:30.460
well as innovation,
especially as firms

00:56:30.460 --> 00:56:33.100
are looking what
to do next-- what

00:56:33.100 --> 00:56:34.450
to kind of put their money in.

00:56:37.370 --> 00:56:38.865
AUDIENCE: [INAUDIBLE].

00:56:38.865 --> 00:56:41.237
I think a really interesting
undercurrent and something

00:56:41.237 --> 00:56:43.570
that I haven't really seen
any of the economics readings

00:56:43.570 --> 00:56:45.500
talk about is game
theory and the importance

00:56:45.500 --> 00:56:46.580
of potential cooperation.

00:56:46.580 --> 00:56:48.360
And I really see that
as a potential role

00:56:48.360 --> 00:56:49.902
for the government
as we move forward

00:56:49.902 --> 00:56:52.735
in technological development,
because I think cooperation

00:56:52.735 --> 00:56:54.860
and particularly from a
design-research standpoint,

00:56:54.860 --> 00:56:57.260
is incredibly important
in identifying

00:56:57.260 --> 00:57:01.740
the competitive and dynamic and
static advantages of the firm.

00:57:01.740 --> 00:57:05.200
And I see it as particularly
being an issue in manufacturing

00:57:05.200 --> 00:57:06.690
with robotics.

00:57:06.690 --> 00:57:09.110
The United States is
not invested as much

00:57:09.110 --> 00:57:11.120
in our robotics infrastructure
and now China is,

00:57:11.120 --> 00:57:12.953
and they're poised to
become a global leader

00:57:12.953 --> 00:57:15.650
in the next decade or so.

00:57:15.650 --> 00:57:17.720
And it's really
fascinating to think

00:57:17.720 --> 00:57:20.510
about the ways in which the
United States is not really

00:57:20.510 --> 00:57:21.875
cooperating--

00:57:21.875 --> 00:57:23.750
firms within the United
States are not really

00:57:23.750 --> 00:57:25.970
cooperating with one another
to align their interests

00:57:25.970 --> 00:57:28.850
to sort of dominate
international markets as well

00:57:28.850 --> 00:57:30.270
as domestic markets.

00:57:30.270 --> 00:57:32.770
So that cooperation can be
really important and it's not

00:57:32.770 --> 00:57:35.020
really something that I saw
in either the Solow, Romer

00:57:35.020 --> 00:57:37.525
or Nelson reading, is that
game theory component.

00:57:37.525 --> 00:57:41.900
And so game theory could be
quite valuable when applied.

00:57:41.900 --> 00:57:44.300
WILLIAM BONVILLIAN: So
great discussion so far.

00:57:44.300 --> 00:57:47.620
You're really driving, I think,
to get at Beth's underlying

00:57:47.620 --> 00:57:52.110
point which is what is the
governmental role going

00:57:52.110 --> 00:57:53.330
to be in this mix.

00:57:53.330 --> 00:57:55.010
Where do you draw
the lines, how far

00:57:55.010 --> 00:57:58.003
should it extend down the
innovation pipeline, what are

00:57:58.003 --> 00:57:59.170
the different controversies?

00:57:59.170 --> 00:58:01.160
So you all have laid
out, I think, really

00:58:01.160 --> 00:58:06.750
nicely a whole set of examples
about how we start that debate.

00:58:06.750 --> 00:58:10.550
But that'll be a central
kind of issue in the class

00:58:10.550 --> 00:58:12.270
as we go along.

00:58:12.270 --> 00:58:15.000
So Beth, do you want to give
us some closing thoughts here?

00:58:17.432 --> 00:58:19.140
AUDIENCE: So I guess
we have been viewing

00:58:19.140 --> 00:58:22.410
this in a very much US
context, and that's obviously

00:58:22.410 --> 00:58:25.020
what we're most familiar with.

00:58:25.020 --> 00:58:26.460
But it is very
important to think

00:58:26.460 --> 00:58:28.650
about what actions
other countries

00:58:28.650 --> 00:58:30.600
are taking compared
to what we're doing,

00:58:30.600 --> 00:58:34.870
and how we can learn from them
and best compete with them.

00:58:34.870 --> 00:58:38.220
I guess the American system
tends to lean a little bit more

00:58:38.220 --> 00:58:41.460
towards the kind of
capitalist free market.

00:58:41.460 --> 00:58:45.690
Once these companies emerge,
it is seen as kind of unfair

00:58:45.690 --> 00:58:48.090
to support certain industries
and certain companies,

00:58:48.090 --> 00:58:50.670
while in other countries
that's more acceptable.

00:58:50.670 --> 00:58:52.170
And it is worthwhile
to think about,

00:58:52.170 --> 00:58:54.210
is that something
that we would want

00:58:54.210 --> 00:58:57.300
to move towards or is it better
to kind of let these firms

00:58:57.300 --> 00:58:58.470
fight it out on their own?

00:59:02.060 --> 00:59:05.480
And as far as the relationship
between national interests

00:59:05.480 --> 00:59:10.130
and international partnerships,
kind of one closing question

00:59:10.130 --> 00:59:12.380
to consider is, how much
should the governments

00:59:12.380 --> 00:59:17.780
be intervening and protecting
their companies versus if that

00:59:17.780 --> 00:59:21.260
limits them from being
able to kind of function

00:59:21.260 --> 00:59:25.100
on the international
market, such as tariffs

00:59:25.100 --> 00:59:27.382
and other things that are
protecting industries.

00:59:27.382 --> 00:59:29.090
Is that something that
governments should

00:59:29.090 --> 00:59:32.180
be able to do, is that fair
if other countries don't have

00:59:32.180 --> 00:59:33.890
those policies in
place, and are we

00:59:33.890 --> 00:59:36.410
limiting which technologies
are successful on the market

00:59:36.410 --> 00:59:40.910
by protecting ones that
might not be as productive?

00:59:40.910 --> 00:59:44.150
WILLIAM BONVILLIAN:
Great closing thoughts,

00:59:44.150 --> 00:59:48.830
and the discussion
leader system is working.

00:59:48.830 --> 00:59:52.220
Thank you for getting
us off to a good start.

00:59:52.220 --> 00:59:55.820
Let me do some quick
summaries and then lead

00:59:55.820 --> 00:59:57.725
into the Atkinson material.

00:59:57.725 --> 00:59:59.600
And Beth, we'll come
back to you in a minute.

01:00:02.370 --> 01:00:04.550
So in last week's
class, we talked

01:00:04.550 --> 01:00:06.350
about these direct
innovation factors.

01:00:06.350 --> 01:00:09.590
In other words, these factors
that you really can't do

01:00:09.590 --> 01:00:12.440
without if you want to have
a strong innovation system.

01:00:12.440 --> 01:00:14.930
And the purpose of that would
be to drive economic growth,

01:00:14.930 --> 01:00:19.310
to grow economic well-being in
your society in your economy.

01:00:19.310 --> 01:00:27.620
So government plays a role in
some of these direct factors.

01:00:27.620 --> 01:00:32.230
It supports almost
all of university R&D,

01:00:32.230 --> 01:00:34.310
it supports governmental
laboratories,

01:00:34.310 --> 01:00:38.270
it provides lots of support
for the education system.

01:00:38.270 --> 01:00:43.950
And then it provides support
for industry R&D in some areas--

01:00:43.950 --> 01:00:47.310
particularly defense, but to
some extent in agriculture.

01:00:47.310 --> 01:00:48.770
So those are kind of--

01:00:48.770 --> 01:00:58.170
if the Solow factor of
doing R&D is a core factor,

01:00:58.170 --> 01:01:00.080
then you can see the
governmental role here.

01:01:00.080 --> 01:01:02.180
But there's also a private
sector and industry

01:01:02.180 --> 01:01:05.990
role on that initial factor.

01:01:05.990 --> 01:01:08.600
Of course, there's industry
R&D which, as we discussed,

01:01:08.600 --> 01:01:12.530
is predominantly D, but
that's what takes you

01:01:12.530 --> 01:01:15.590
through the prototyping, and
engineering, and production

01:01:15.590 --> 01:01:16.670
stages.

01:01:16.670 --> 01:01:19.160
And then industry provides
the dominant role in training.

01:01:22.320 --> 01:01:28.280
So those are direct
Solow-Romer factors

01:01:28.280 --> 01:01:32.000
that are tied to industry and
tied to the private sector.

01:01:32.000 --> 01:01:37.520
But then there is
a raft of indirect,

01:01:37.520 --> 01:01:42.180
or we could call them
implicit, innovation factors.

01:01:42.180 --> 01:01:47.030
So if Nelson is right that there
is an innovation ecosystem,

01:01:47.030 --> 01:01:51.440
then there's a lot of pieces
in that complex system.

01:01:51.440 --> 01:01:55.220
And government is supplying
some of those pieces that

01:01:55.220 --> 01:01:57.980
have a role in the
innovation process,

01:01:57.980 --> 01:02:01.430
but are not as direct as the
first thing we talked about.

01:02:01.430 --> 01:02:06.735
So government is providing
fiscal tax monetary policy,

01:02:06.735 --> 01:02:09.530
it's providing trade policy,
technology standards,

01:02:09.530 --> 01:02:12.307
technology transfer policies.

01:02:12.307 --> 01:02:13.890
It's providing
government procurement,

01:02:13.890 --> 01:02:17.030
which buys a lot of technology,
particularly in defense.

01:02:17.030 --> 01:02:19.220
It sets up the intellectual
property system,

01:02:19.220 --> 01:02:23.570
the whole legal contracting
liability system,

01:02:23.570 --> 01:02:27.110
the regulatory system
in many, many areas,

01:02:27.110 --> 01:02:30.420
accounting standards,
export controls.

01:02:30.420 --> 01:02:34.430
These all will have an effect
on the innovation system

01:02:34.430 --> 01:02:38.240
and your ability to innovate.

01:02:38.240 --> 01:02:41.150
But then there are
these indirect factors

01:02:41.150 --> 01:02:45.020
that are is less critical than
the two we've talked about,

01:02:45.020 --> 01:02:47.420
but nonetheless
part of that system.

01:02:47.420 --> 01:02:50.090
So the private sector sets
some really important ones.

01:02:50.090 --> 01:02:52.790
That includes investment
capital which can be angel,

01:02:52.790 --> 01:02:58.240
or venture, or IPO, or
equity, or lending markets--

01:02:58.240 --> 01:03:00.560
is a private sector
function obviously.

01:03:00.560 --> 01:03:02.390
Management and
management organization

01:03:02.390 --> 01:03:05.030
is really a private sector
function in our system.

01:03:05.030 --> 01:03:06.640
The whole reward system--

01:03:06.640 --> 01:03:09.590
the compensation
system for talent

01:03:09.590 --> 01:03:11.630
is largely private sector set.

01:03:11.630 --> 01:03:14.440
So the private sector
plays a huge role too

01:03:14.440 --> 01:03:17.120
in this complex ecosystem mix.

01:03:17.120 --> 01:03:23.250
So the picture I want you to
have is of a complex innovation

01:03:23.250 --> 01:03:24.690
system.

01:03:24.690 --> 01:03:28.090
There's direct factors,
and if we include Nelson,

01:03:28.090 --> 01:03:30.990
we've talked about three.

01:03:30.990 --> 01:03:33.060
But there's a whole mix
of other stuff there,

01:03:33.060 --> 01:03:35.820
and you want to get as many of
those right in your innovation

01:03:35.820 --> 01:03:39.030
system as you can to have a
strong functioning innovation

01:03:39.030 --> 01:03:40.210
system.

01:03:40.210 --> 01:03:42.810
So it's not only the actors.

01:03:42.810 --> 01:03:46.290
You've also got to take into
account this larger system

01:03:46.290 --> 01:03:47.580
as well.

01:03:47.580 --> 01:03:52.560
And we'll get, in a
few minutes, into some

01:03:52.560 --> 01:03:55.355
of the indirect factors
and how to look at those.

01:03:55.355 --> 01:03:57.480
But first we're going to
do innovation wave theory.

01:03:57.480 --> 01:04:00.490
That's Rob Atkinson
who's head of ITIF,

01:04:00.490 --> 01:04:04.290
a thinktank in Washington.

01:04:04.290 --> 01:04:07.530
We talked about-- and I
drew a scribble last week

01:04:07.530 --> 01:04:11.550
on the blackboard, but this
is a better rendition--

01:04:11.550 --> 01:04:13.420
what does an innovation
wave look like?

01:04:13.420 --> 01:04:17.110
And just to recap from
our discussion last week,

01:04:17.110 --> 01:04:20.580
there's a long build up
and that can be 15, 20

01:04:20.580 --> 01:04:22.973
years-- it can be longer.

01:04:22.973 --> 01:04:24.640
And then at some
point, it hits a moment

01:04:24.640 --> 01:04:26.790
where it can start to
scale up pretty quickly

01:04:26.790 --> 01:04:29.620
and spread into the
society and economy.

01:04:29.620 --> 01:04:32.430
So there is a fast
growth period here--

01:04:32.430 --> 01:04:35.177
maybe that's a decade.

01:04:35.177 --> 01:04:36.760
Then there's a period
of more stable--

01:04:36.760 --> 01:04:39.990
there's always a
bubble and then there's

01:04:39.990 --> 01:04:42.930
a period of more stable growth.

01:04:42.930 --> 01:04:45.420
And maybe that's 20
years, maybe that's more.

01:04:45.420 --> 01:04:50.070
And then eventually, you reach
kind of technological maturity.

01:04:50.070 --> 01:04:55.050
So the IT wave, the one you all
are most familiar with that's

01:04:55.050 --> 01:04:58.680
still ongoing, long build up.

01:04:58.680 --> 01:05:00.160
When do we start it from?

01:05:00.160 --> 01:05:03.330
Do we start it from
Babbage, do we start it

01:05:03.330 --> 01:05:04.890
from Vannevar
Bush's differential

01:05:04.890 --> 01:05:09.210
analyzer in the 1930s, do
we start it from ENIAC--

01:05:09.210 --> 01:05:14.790
1946, the first functioning
mainframe computer.

01:05:14.790 --> 01:05:16.290
We can start it
at various points,

01:05:16.290 --> 01:05:18.660
but you get a sense for
how long that buildup is.

01:05:18.660 --> 01:05:21.540
And then finally,
we hit the 1990s

01:05:21.540 --> 01:05:24.140
and that incredible decade
of growth in the 1990s.

01:05:24.140 --> 01:05:26.560
This very rapid scale up.

01:05:26.560 --> 01:05:27.060
Max?

01:05:27.060 --> 01:05:28.440
AUDIENCE: Why is it in this
diagram the buildup is not

01:05:28.440 --> 01:05:30.605
as long as what you
pointed out last week?

01:05:30.605 --> 01:05:33.447
Like, last week, you had said it
was 40 or 50 years [INAUDIBLE]..

01:05:33.447 --> 01:05:34.530
WILLIAM BONVILLIAN: Right.

01:05:34.530 --> 01:05:37.380
It depends on when
you date it from,

01:05:37.380 --> 01:05:40.320
because everybody stands on
everybody else's shoulders

01:05:40.320 --> 01:05:41.490
in the innovation process.

01:05:41.490 --> 01:05:43.740
Maybe we ought to date it
Newtonian physics, right?

01:05:43.740 --> 01:05:46.170
[LAUGHS]

01:05:46.170 --> 01:05:48.990
I think ENIAC is a pretty
reasonable start date,

01:05:48.990 --> 01:05:52.320
but there's a long time
between 1946 and 1990--

01:05:52.320 --> 01:05:53.980
it's a very long period of time.

01:05:53.980 --> 01:05:56.740
So it's a longer
period, frankly,

01:05:56.740 --> 01:06:00.480
than this in many, many cases.

01:06:00.480 --> 01:06:03.750
But then after the bubble--
and in the IT world,

01:06:03.750 --> 01:06:06.870
that's the Dot-com bust of 2001.

01:06:06.870 --> 01:06:09.720
Then all kinds of dot-coms fail.

01:06:09.720 --> 01:06:12.360
And then the surviving
firms are stronger

01:06:12.360 --> 01:06:15.120
and they go on a period of
stable continued growth.

01:06:15.120 --> 01:06:17.290
I would argue that
that's where we're on now

01:06:17.290 --> 01:06:20.070
in the IT innovation wave.

01:06:20.070 --> 01:06:23.100
Eventually, we'll reach
technology maturity.

01:06:23.100 --> 01:06:27.330
The IT wave is complicated
because information

01:06:27.330 --> 01:06:31.770
is a core organizing
principle of the universe.

01:06:31.770 --> 01:06:33.340
It's like mass and energy--

01:06:33.340 --> 01:06:35.020
it's one of those big things.

01:06:35.020 --> 01:06:37.590
And if you're tying your
innovation wave to something

01:06:37.590 --> 01:06:41.190
as fundamental and powerful as
that, maybe it's more enduring.

01:06:41.190 --> 01:06:43.920
And we haven't begun to touch
artificial intelligence yet.

01:06:43.920 --> 01:06:48.270
So maybe we'll get a
lot longer run, Max,

01:06:48.270 --> 01:06:50.230
in our stable growth period--

01:06:50.230 --> 01:06:52.080
maybe we have a lot more to go.

01:06:52.080 --> 01:06:53.670
But think about railroads.

01:06:53.670 --> 01:06:56.760
You can think about
somewhere in the first half

01:06:56.760 --> 01:06:58.680
of the 20th century, we
reached a fair amount

01:06:58.680 --> 01:07:00.972
of technological maturity,
particularly with the advent

01:07:00.972 --> 01:07:03.480
of the diesel-electric engine.

01:07:03.480 --> 01:07:05.750
So there are incremental
advances in railroads,

01:07:05.750 --> 01:07:08.880
but the real challenging
period is probably

01:07:08.880 --> 01:07:11.412
over for the time being.

01:07:11.412 --> 01:07:12.340
Beth?

01:07:12.340 --> 01:07:15.180
AUDIENCE: So when we're looking
at the stable growth here,

01:07:15.180 --> 01:07:17.300
it doesn't seem to account
for, like, other things

01:07:17.300 --> 01:07:18.300
going on in the economy.

01:07:18.300 --> 01:07:22.110
So if we're using recent
years for an example,

01:07:22.110 --> 01:07:24.510
you don't think about
the financial crisis

01:07:24.510 --> 01:07:26.860
and how that's affected
the economy as a whole.

01:07:26.860 --> 01:07:29.790
So is this just kind of a
general upward trend where

01:07:29.790 --> 01:07:32.820
we expect to see some ups
and downs from other causes,

01:07:32.820 --> 01:07:35.168
or have you captured
those effects?

01:07:35.168 --> 01:07:36.210
WILLIAM BONVILLIAN: Yeah.

01:07:36.210 --> 01:07:39.450
I mean, there's-- we could call
them black swan elements that

01:07:39.450 --> 01:07:42.105
pop up periodically that
disrupt everything like crazy.

01:07:44.610 --> 01:07:46.650
I'd argue that
you could actually

01:07:46.650 --> 01:07:54.140
treat the growth in financial
services as an innovation wave.

01:07:54.140 --> 01:07:57.480
That there were a whole
series of technological areas

01:07:57.480 --> 01:07:58.620
of advance--

01:07:58.620 --> 01:08:02.370
in areas like mathematics
in particular.

01:08:02.370 --> 01:08:04.470
But IT revolution
accompanies that.

01:08:04.470 --> 01:08:06.540
You could actually add
the technology foundation

01:08:06.540 --> 01:08:09.390
and the processes
to really create

01:08:09.390 --> 01:08:13.050
global financial
services system.

01:08:13.050 --> 01:08:17.010
And you can plot that
growth, and sure enough, they

01:08:17.010 --> 01:08:18.710
have a bubble.

01:08:18.710 --> 01:08:22.290
The problem with the bubble
in the financial services bust

01:08:22.290 --> 01:08:25.290
is that it just doesn't bring
down a bunch of dot-coms,

01:08:25.290 --> 01:08:26.819
it brings down the
entire economy.

01:08:26.819 --> 01:08:30.660
So be careful about innovation
waves in the financial services

01:08:30.660 --> 01:08:33.960
sector-- be very careful
because it messes everything up.

01:08:33.960 --> 01:08:35.540
But I think you can actually--

01:08:35.540 --> 01:08:37.290
I think that one
actually works as a wave.

01:08:37.290 --> 01:08:39.109
Biotech for sure
works as a wave.

01:08:39.109 --> 01:08:42.010
It's not nearly as big as IT,
but nonetheless is significant.

01:08:42.010 --> 01:08:42.510
Matt?

01:08:42.510 --> 01:08:46.540
AUDIENCE: I think my impression
of that, reading Atkinson,

01:08:46.540 --> 01:08:49.350
was that because the
timescale of the innovation

01:08:49.350 --> 01:08:53.140
is so much longer than
the business cycle,

01:08:53.140 --> 01:08:55.680
the business cycles are, like,
flips that are superimposed

01:08:55.680 --> 01:08:56.180
[INAUDIBLE].

01:08:56.180 --> 01:08:57.788
WILLIAM BONVILLIAN:
Very good point.

01:08:57.788 --> 01:08:59.205
They modulate
through the process.

01:09:01.710 --> 01:09:03.990
Atkinson argues
that in US history,

01:09:03.990 --> 01:09:06.270
there were essentially
four phases--

01:09:06.270 --> 01:09:10.740
for long waves in
the US economy.

01:09:10.740 --> 01:09:12.257
So he argues that--

01:09:12.257 --> 01:09:14.340
and different people can
look at this differently.

01:09:14.340 --> 01:09:16.548
And look, there's big waves,
and there's small waves,

01:09:16.548 --> 01:09:18.540
and there's wavelets
within a wave,

01:09:18.540 --> 01:09:21.000
so it's not absolutely
straightforward.

01:09:21.000 --> 01:09:23.640
But he argues that in the
1840s, the development

01:09:23.640 --> 01:09:26.910
of small local manufacturing
industries in New

01:09:26.910 --> 01:09:31.319
England around textiles
and early machines,

01:09:31.319 --> 01:09:33.359
that's one wave.

01:09:33.359 --> 01:09:37.859
By the 1880s and '90s, that's
regional factory based systems.

01:09:37.859 --> 01:09:40.830
And you know what those
19th century cities look

01:09:40.830 --> 01:09:44.310
like-- think about Pittsburgh.

01:09:44.310 --> 01:09:46.500
By the 1940s, we're
moving towards

01:09:46.500 --> 01:09:49.140
corporate mass
production in areas

01:09:49.140 --> 01:09:51.660
like automobiles and aircraft.

01:09:51.660 --> 01:09:55.530
Then in the 1990s, he
argues the new economy

01:09:55.530 --> 01:10:01.570
which is an IT based
innovation wave emerges--

01:10:01.570 --> 01:10:04.410
that's global, that's
entrepreneurial,

01:10:04.410 --> 01:10:05.380
that's knowledge based.

01:10:05.380 --> 01:10:11.680
But that's his way of looking
at innovation waves in the US

01:10:11.680 --> 01:10:12.624
economy.

01:10:15.220 --> 01:10:18.940
We're familiar with the 1990s--
we just discussed that one,

01:10:18.940 --> 01:10:21.610
so I won't dwell on it here.

01:10:21.610 --> 01:10:23.290
The political
system typically is

01:10:23.290 --> 01:10:25.630
slow to react to these
innovation waves.

01:10:25.630 --> 01:10:28.630
It does not see them.

01:10:28.630 --> 01:10:31.420
John Maynard Keynes,
the great economist

01:10:31.420 --> 01:10:35.190
who created Keynesian
theory, once

01:10:35.190 --> 01:10:37.260
said, "practical men
who believe themselves

01:10:37.260 --> 01:10:40.530
to be quite exempt from
any intellectual influences

01:10:40.530 --> 01:10:44.310
are usually slaves of
some defunct economist."

01:10:44.310 --> 01:10:46.830
In other words, they're
operating off old economics

01:10:46.830 --> 01:10:50.310
and tend to perpetrate them.

01:10:50.310 --> 01:10:54.330
Atkinson argues that
the American old left

01:10:54.330 --> 01:10:56.370
was focused essentially
on a mass production

01:10:56.370 --> 01:11:00.300
economy, which had been
eclipsed by the time the IT

01:11:00.300 --> 01:11:02.020
wave emerges.

01:11:02.020 --> 01:11:05.430
The conservative
political elements--

01:11:05.430 --> 01:11:08.640
the Republican Party at the
time and he's writing in--

01:11:08.640 --> 01:11:13.090
was very supply side,
classical economics based.

01:11:13.090 --> 01:11:14.790
They were worried
about capital supply,

01:11:14.790 --> 01:11:16.207
and they were
worried particularly

01:11:16.207 --> 01:11:19.740
about marginal tax rates
affecting that capital supply.

01:11:19.740 --> 01:11:22.680
So that wasn't organized
around an innovation wave.

01:11:22.680 --> 01:11:26.370
That was organized around
old classical economics.

01:11:26.370 --> 01:11:30.210
So in a way, both
parties got organized

01:11:30.210 --> 01:11:34.580
around the two fundamental bases
in classical economic theory.

01:11:34.580 --> 01:11:36.930
The Democratic Party around
a broad definition of labor

01:11:36.930 --> 01:11:39.180
supply that includes education,
and health, and things

01:11:39.180 --> 01:11:41.070
like that, and the
Republican Party

01:11:41.070 --> 01:11:43.240
around a theory
of capital supply,

01:11:43.240 --> 01:11:45.390
which was translated
into tax policy.

01:11:45.390 --> 01:11:47.430
It's largely where
those parties are today.

01:11:47.430 --> 01:11:50.520
They missed innovation
based growth theory.

01:11:50.520 --> 01:11:52.800
AUDIENCE: When did that start?

01:11:52.800 --> 01:11:57.063
When did that
happen [INAUDIBLE]??

01:11:57.063 --> 01:11:59.230
WILLIAM BONVILLIAN: I would
say that the parties had

01:11:59.230 --> 01:12:03.430
locked into this by pretty
early on in the 20th century.

01:12:03.430 --> 01:12:05.395
By the time of
Franklin Roosevelt

01:12:05.395 --> 01:12:07.985
is when the Democratic
Party locks into--

01:12:07.985 --> 01:12:10.360
look, there's nothing wrong
with capitalist [INAUDIBLE]..

01:12:10.360 --> 01:12:12.683
There's nothing wrong
with labor supply.

01:12:12.683 --> 01:12:15.100
They're important elements and
they need to be considered,

01:12:15.100 --> 01:12:16.720
and they're contributors.

01:12:16.720 --> 01:12:20.920
We just know, however, that
innovation based growth

01:12:20.920 --> 01:12:25.930
is the larger factor in growth,
and the political parties

01:12:25.930 --> 01:12:27.950
haven't gotten there yet.

01:12:27.950 --> 01:12:32.320
So a real structural
problem in the US system.

01:12:32.320 --> 01:12:37.470
Neither then embrace
growth economics

01:12:37.470 --> 01:12:41.440
and spurring innovation,
and that leads us

01:12:41.440 --> 01:12:46.240
to some interesting ideas
about social organization.

01:12:46.240 --> 01:12:51.110
So technology and
technological organization

01:12:51.110 --> 01:12:56.330
is going to drive social
and economic structures.

01:12:56.330 --> 01:12:59.420
So it's a really important
point that he raises here,

01:12:59.420 --> 01:13:01.760
and it's I think
one of the reasons

01:13:01.760 --> 01:13:06.680
why the subject of this class
is actually really important.

01:13:06.680 --> 01:13:09.800
It's bigger than standing
up cool technologies.

01:13:09.800 --> 01:13:14.990
It's a lot bigger than that
because this class is not only

01:13:14.990 --> 01:13:17.930
about technology
development, it is

01:13:17.930 --> 01:13:20.840
about the way society
organizes itself

01:13:20.840 --> 01:13:23.970
around those technologies.

01:13:23.970 --> 01:13:29.030
So Hagel, great German
philosopher-- "western society

01:13:29.030 --> 01:13:32.150
is driven by the
competition of ideas."

01:13:32.150 --> 01:13:35.270
Thesis, antithesis--
you all know the story.

01:13:35.270 --> 01:13:41.270
Marx introduces a very different
concept into that conversation.

01:13:41.270 --> 01:13:45.170
He argues that in acquiring
new productive forces,

01:13:45.170 --> 01:13:47.300
people change their
mode of production,

01:13:47.300 --> 01:13:49.340
and in changing their
mode of production,

01:13:49.340 --> 01:13:51.620
they change their way
of living and they

01:13:51.620 --> 01:13:54.830
change their social relations.

01:13:54.830 --> 01:13:58.010
So that's fundamental Marx
philosophical perspective.

01:13:58.010 --> 01:14:01.700
That is called
determinism in philosophy.

01:14:01.700 --> 01:14:05.060
In other words, the
technological order

01:14:05.060 --> 01:14:08.360
of your society will be
determinative of the kind

01:14:08.360 --> 01:14:10.580
of society you have.

01:14:10.580 --> 01:14:12.290
And that's how Marxism evolves.

01:14:12.290 --> 01:14:14.840
That's the fundamental
philosophical underpinning.

01:14:14.840 --> 01:14:17.270
And he is seeing the
Industrial Revolution drive

01:14:17.270 --> 01:14:23.000
systematic change in
society in the late 18th

01:14:23.000 --> 01:14:24.110
through the 19th century.

01:14:24.110 --> 01:14:25.550
That's what he's seeing.

01:14:25.550 --> 01:14:27.470
He's seeing this
incredible class order

01:14:27.470 --> 01:14:32.420
evolve to match the very
hierarchical structure

01:14:32.420 --> 01:14:35.450
that industrial organization,
driven by the Industrial

01:14:35.450 --> 01:14:37.625
Revolution, requires
at that time.

01:14:37.625 --> 01:14:39.535
Now, Stephanie,
you had a question?

01:14:39.535 --> 01:14:40.970
AUDIENCE: Yeah, [INAUDIBLE].

01:14:40.970 --> 01:14:42.600
I was wondering [INAUDIBLE]--

01:14:42.600 --> 01:14:44.132
WILLIAM BONVILLIAN: I'll get it.

01:14:44.132 --> 01:14:46.090
AUDIENCE: --when I was
looking at the syllabus,

01:14:46.090 --> 01:14:48.396
was are we going to
talk about it some more?

01:14:48.396 --> 01:14:51.110
Because I guess I was
curious if you were operating

01:14:51.110 --> 01:14:53.690
under the presumption, at least
in the lecture and the ways

01:14:53.690 --> 01:14:55.460
in which we were supposed
to be perceiving readings

01:14:55.460 --> 01:14:56.085
were giving us.

01:14:56.085 --> 01:14:59.402
Like, capitalism is good, or
that capitalism is natural,

01:14:59.402 --> 01:15:03.194
or that capitalism is something
that technology sort of--

01:15:03.194 --> 01:15:06.350
or rather that capitalism
perpetuates technology,

01:15:06.350 --> 01:15:08.485
technology works to
perpetuate capitalism.

01:15:08.485 --> 01:15:10.610
When I think there's really
a lot of conversations,

01:15:10.610 --> 01:15:12.420
particularly arising
in the last maybe

01:15:12.420 --> 01:15:14.780
two or three years, about
the basic income guarantee

01:15:14.780 --> 01:15:17.090
and the potential for
technology really eliminating

01:15:17.090 --> 01:15:19.310
the necessity for labor
in [INAUDIBLE] economies.

01:15:19.310 --> 01:15:22.280
So I figured I would
ask at this point

01:15:22.280 --> 01:15:25.310
when it became relevant
because you had brought it up--

01:15:25.310 --> 01:15:26.150
WILLIAM BONVILLIAN: [LAUGHS]
I gave you an opening.

01:15:26.150 --> 01:15:27.310
AUDIENCE: --there you go, yeah--

01:15:27.310 --> 01:15:28.950
whether or not we're operating
under the presumption

01:15:28.950 --> 01:15:31.550
that the free markets are good
or desirable in the long run.

01:15:33.337 --> 01:15:35.420
WILLIAM BONVILLIAN: That
is really a big question.

01:15:35.420 --> 01:15:36.770
[LAUGHING]

01:15:36.770 --> 01:15:38.450
I guess I opened
myself up to that

01:15:38.450 --> 01:15:40.640
by bringing determinism in--

01:15:40.640 --> 01:15:44.750
using the excuse that
Atkinson raised the subject.

01:15:44.750 --> 01:15:47.150
Look, that's not a
dialogue that the US

01:15:47.150 --> 01:15:48.860
has had for some decades.

01:15:48.860 --> 01:15:53.180
We thought the Cold War was over
and we thought capitalism won.

01:15:53.180 --> 01:15:55.580
It's only in fairly recent
years that we're actually

01:15:55.580 --> 01:15:58.340
starting to think, hmm, maybe
there's some more elements here

01:15:58.340 --> 01:16:00.597
that we need to consider.

01:16:00.597 --> 01:16:02.180
Look, I think that's
an open question.

01:16:02.180 --> 01:16:04.160
Obviously, this class
is about innovation

01:16:04.160 --> 01:16:07.817
and it's about innovation in
largely capitalistic systems,

01:16:07.817 --> 01:16:10.400
which obviously is the direction
that the world economies have

01:16:10.400 --> 01:16:13.040
gone in worldwide.

01:16:13.040 --> 01:16:14.930
So I think that's the reality.

01:16:14.930 --> 01:16:18.570
That's the reality we have.

01:16:18.570 --> 01:16:23.390
My personal view is that
that's essentially a positive,

01:16:23.390 --> 01:16:25.490
but there are
different views here.

01:16:25.490 --> 01:16:30.380
And we have to keep in mind how
powerful the technologies that

01:16:30.380 --> 01:16:32.510
are coming out of these
innovation systems

01:16:32.510 --> 01:16:36.830
can be for how we relate
to one another as people--

01:16:36.830 --> 01:16:38.510
how we organize
our social lives.

01:16:42.230 --> 01:16:44.440
So the prevailing
technology system

01:16:44.440 --> 01:16:46.870
really sets parameters
on the fundamentals

01:16:46.870 --> 01:16:49.642
of social organization.

01:16:49.642 --> 01:16:51.640
A few other thoughts
along those lines--

01:16:51.640 --> 01:16:55.240
Kondratieff who developed the
fundamentals of wave theory

01:16:55.240 --> 01:16:57.010
back at the beginning
of the 20th century.

01:16:59.950 --> 01:17:07.870
He viewed depression as a
trough in a 50 year wave cycle.

01:17:07.870 --> 01:17:10.150
Classical economists'
view of depression

01:17:10.150 --> 01:17:13.120
was that they were waiting
for wages and prices

01:17:13.120 --> 01:17:17.980
to fall far enough
to enable a rebound.

01:17:17.980 --> 01:17:21.640
Eventually, everything is cheap
enough-- somebody will buy it.

01:17:21.640 --> 01:17:26.200
Keynes took on that attitude.

01:17:26.200 --> 01:17:29.170
This is to point back to
what you raised, Matt,

01:17:29.170 --> 01:17:33.310
about how does economic cycle
theory interact with innovation

01:17:33.310 --> 01:17:33.990
wave theories.

01:17:33.990 --> 01:17:37.720
So we're right exactly at
that point that you raised.

01:17:37.720 --> 01:17:39.970
So Keynes agreed,
but in the end he

01:17:39.970 --> 01:17:42.130
argued better intervene
because in the long range,

01:17:42.130 --> 01:17:43.390
we're all dead.

01:17:43.390 --> 01:17:45.400
So don't wait that long--

01:17:45.400 --> 01:17:47.950
better get on with it.

01:17:47.950 --> 01:17:52.570
Schumpeter definitely saw--
who's an advocate in economics

01:17:52.570 --> 01:17:56.230
of disruptive capitalism,
destructive capitalism--

01:17:56.230 --> 01:17:59.260
he saw Kondratieff's
long waves theory,

01:17:59.260 --> 01:18:01.990
but he saw them as driven
by innovation, not just

01:18:01.990 --> 01:18:04.568
in technology, but in
the accompanying aspects.

01:18:04.568 --> 01:18:05.860
So production and distribution.

01:18:05.860 --> 01:18:08.560
So it's not only the
technology, but it's

01:18:08.560 --> 01:18:10.420
the production and
distribution system too

01:18:10.420 --> 01:18:13.030
that he would add to that mix.

01:18:13.030 --> 01:18:15.760
So destructive
capitalism, in the end,

01:18:15.760 --> 01:18:19.180
is based on radical
innovation as opposed

01:18:19.180 --> 01:18:23.050
to incremental innovation,
which means that if you really

01:18:23.050 --> 01:18:26.410
want disruptive capitalism
and the potential gains

01:18:26.410 --> 01:18:28.600
of innovation that
can derive from it,

01:18:28.600 --> 01:18:31.120
you've got to think hard about
radical innovation, not just

01:18:31.120 --> 01:18:33.690
incremental advance.

01:18:33.690 --> 01:18:37.130
So in our system,
that means in turn,

01:18:37.130 --> 01:18:39.430
you gotta think about
that early stage R&D

01:18:39.430 --> 01:18:43.500
too, because that's the real
contributor to radical advance

01:18:43.500 --> 01:18:45.540
as opposed to industries
development, which

01:18:45.540 --> 01:18:47.316
is largely incremental.

01:18:47.316 --> 01:18:48.070
You with me?

01:18:51.280 --> 01:18:53.800
So Atkinson argues
that technology

01:18:53.800 --> 01:18:57.040
is the skeleton on which
an economy is formed,

01:18:57.040 --> 01:19:01.810
and every half century or
so, the skeleton changes

01:19:01.810 --> 01:19:04.600
as these waves come about.

01:19:04.600 --> 01:19:06.910
The changes are not steady.

01:19:06.910 --> 01:19:09.490
They can be very clustered.

01:19:09.490 --> 01:19:11.830
This is not a smooth wave.

01:19:11.830 --> 01:19:14.710
There should have been
lots of erratic lines

01:19:14.710 --> 01:19:16.720
in the wave theory
diagram I showed you.

01:19:19.380 --> 01:19:22.450
Now Carlotta Perez is a
great growth economist

01:19:22.450 --> 01:19:24.460
who taught at the
University of Sussex

01:19:24.460 --> 01:19:27.850
and worked with
Chris Freeman there,

01:19:27.850 --> 01:19:33.800
and she argues that it's
not just the economy

01:19:33.800 --> 01:19:36.650
changes, but the politics,
social relations, and the how

01:19:36.650 --> 01:19:38.930
and where we live that changes.

01:19:38.930 --> 01:19:42.440
And it's also how we organize
our education system,

01:19:42.440 --> 01:19:44.508
and how our culture
in turn, which

01:19:44.508 --> 01:19:46.800
is driven by some of these
factors, shapes our beliefs.

01:19:46.800 --> 01:19:50.780
So, quote, "the logic of
the techno-economic paradigm

01:19:50.780 --> 01:19:53.810
reaches well beyond the economic
sphere to become a general

01:19:53.810 --> 01:19:57.830
and shared organization
common sense of the period."

01:19:57.830 --> 01:19:59.620
So here's an idea here--

01:19:59.620 --> 01:20:01.100
a techno-economic paradigm.

01:20:04.090 --> 01:20:06.980
A paradigm that includes
technology, but therefore

01:20:06.980 --> 01:20:08.870
reaches deep into economics.

01:20:08.870 --> 01:20:12.830
So there's a driving
paradigm in a society

01:20:12.830 --> 01:20:14.610
that connects these two.

01:20:14.610 --> 01:20:17.270
I'll argue later in
class that the paradigm

01:20:17.270 --> 01:20:18.430
is even bigger than this.

01:20:21.230 --> 01:20:24.270
And that becomes, in a
way, the order of things.

01:20:24.270 --> 01:20:29.240
So I think we'll kind
of wrap it up here

01:20:29.240 --> 01:20:32.570
in terms of talking
about Atkinson because we

01:20:32.570 --> 01:20:34.010
need to move on.

01:20:34.010 --> 01:20:39.960
But Beth, you've got
Atkinson as well, right?

01:20:39.960 --> 01:20:41.450
And I think,
actually, if you speak

01:20:41.450 --> 01:20:43.250
into the mic in the center--

01:20:43.250 --> 01:20:47.660
and I'll move this
laptop slightly

01:20:47.660 --> 01:20:49.430
so you've got a
direct line there.

01:20:53.890 --> 01:20:55.960
Thanks, Alberto.

01:20:55.960 --> 01:20:58.168
AUDIENCE: So again,
looking at the questions

01:20:58.168 --> 01:20:59.710
that people submitted,
there are kind

01:20:59.710 --> 01:21:03.700
of four themes that came about.

01:21:03.700 --> 01:21:06.700
The first being, do we
believe this is a new economy?

01:21:06.700 --> 01:21:08.797
This whole concept
of the new economy

01:21:08.797 --> 01:21:10.630
that Atkinson talks
about, is that something

01:21:10.630 --> 01:21:12.280
that we're on board with?

01:21:12.280 --> 01:21:14.890
What is the applicability
of long wave theory?

01:21:14.890 --> 01:21:16.900
Is it something that's
unique to the US

01:21:16.900 --> 01:21:19.450
and to more developed
countries, or can we

01:21:19.450 --> 01:21:23.140
apply it anywhere in the world?

01:21:23.140 --> 01:21:24.850
Are there actions
that can be taken

01:21:24.850 --> 01:21:29.490
to minimize these troughs to
shorten how long depressions

01:21:29.490 --> 01:21:30.730
may be?

01:21:30.730 --> 01:21:33.190
And then a lot of
just about what

01:21:33.190 --> 01:21:35.110
is technology's
effect on society,

01:21:35.110 --> 01:21:36.430
and what it should we--

01:21:36.430 --> 01:21:38.440
should the government
be doing things

01:21:38.440 --> 01:21:42.910
to counteract technology's
effect on society

01:21:42.910 --> 01:21:48.164
or is it a good thing that
we're seeing these effects?

01:21:48.164 --> 01:21:50.950
So just a few points
before we go into that

01:21:50.950 --> 01:21:53.820
that I found interesting.

01:21:53.820 --> 01:21:56.220
So Atkinson writes
with the belief

01:21:56.220 --> 01:21:58.290
that this new
economy is something

01:21:58.290 --> 01:22:00.780
that is permanent--
it's not just a blip.

01:22:00.780 --> 01:22:02.280
And I think that's
something that we

01:22:02.280 --> 01:22:04.980
can kind of work with
as an assumption when

01:22:04.980 --> 01:22:06.660
we discuss this.

01:22:06.660 --> 01:22:09.020
But if you have specific
things that you can point out

01:22:09.020 --> 01:22:14.490
that it is just a blip, I'd be
interested to hear this too.

01:22:14.490 --> 01:22:16.380
And so the concept
of this new economy

01:22:16.380 --> 01:22:19.170
forms new businesses,
labor organizations,

01:22:19.170 --> 01:22:22.710
educational systems,
cultural beliefs

01:22:22.710 --> 01:22:24.720
I think is especially
relevant today

01:22:24.720 --> 01:22:28.650
as we're kind of seeing a lot
of interesting political things

01:22:28.650 --> 01:22:29.830
arise.

01:22:29.830 --> 01:22:33.480
And it says with
every disruption,

01:22:33.480 --> 01:22:36.200
entrenched interests will push
back and may resist the change,

01:22:36.200 --> 01:22:37.950
and so I think that's
something that would

01:22:37.950 --> 01:22:39.033
be interesting to discuss.

01:22:41.940 --> 01:22:44.107
So before we go into the
social aspects, I want to--

01:22:44.107 --> 01:22:45.732
WILLIAM BONVILLIAN:
I just want to say,

01:22:45.732 --> 01:22:47.600
Beth, I really like that--

01:22:47.600 --> 01:22:48.530
your last point here.

01:22:48.530 --> 01:22:50.810
In other words, we are
seeing very significant

01:22:50.810 --> 01:22:52.940
social disruption today.

01:22:52.940 --> 01:22:58.370
And we may be able to connect it
back to the IT innovation wave

01:22:58.370 --> 01:23:01.310
which, frankly, the
upper middle class has

01:23:01.310 --> 01:23:05.330
ridden to unparalleled success,
but left a lot of people

01:23:05.330 --> 01:23:06.500
behind--

01:23:06.500 --> 01:23:07.578
maybe.

01:23:07.578 --> 01:23:08.870
Is that what you're driving at?

01:23:08.870 --> 01:23:11.655
AUDIENCE: That's kind of what
I was going to talk about.

01:23:11.655 --> 01:23:14.450
So I guess you can jump
into that actually.

01:23:14.450 --> 01:23:17.510
So we talk about how
these long waves increase

01:23:17.510 --> 01:23:21.020
overall quality of life
perhaps at the national scale,

01:23:21.020 --> 01:23:24.080
but they do tend to be unequal.

01:23:24.080 --> 01:23:26.450
So should the government
have responsibility

01:23:26.450 --> 01:23:29.300
for correcting this
inequity, should it just

01:23:29.300 --> 01:23:33.070
be focusing on total efficiency
for the nation as a whole,

01:23:33.070 --> 01:23:37.730
and how can it balance the idea
that some parts of the country

01:23:37.730 --> 01:23:40.850
may be worse off while
others are better off?

01:23:40.850 --> 01:23:42.320
So it's very broad and open.

01:23:42.320 --> 01:23:44.570
AUDIENCE: Could you repeat
the question one more time?

01:23:44.570 --> 01:23:46.820
AUDIENCE: Yeah.

01:23:46.820 --> 01:23:49.730
So the paper claims
that these long waves

01:23:49.730 --> 01:23:53.000
increase the general quality
of life, maybe at, like,

01:23:53.000 --> 01:23:54.410
a national scale.

01:23:54.410 --> 01:23:59.670
But the benefits are likely
to be uneven based on maybe

01:23:59.670 --> 01:24:03.650
who's most prepared to take
on the technological changes.

01:24:03.650 --> 01:24:05.720
So should the government
have a responsibility

01:24:05.720 --> 01:24:08.480
to increase the equity?

01:24:08.480 --> 01:24:11.510
Should they be more focused
on just total efficiency?

01:24:11.510 --> 01:24:14.060
How do we handle this
and the societal changes

01:24:14.060 --> 01:24:15.300
that arise from it?

01:24:15.300 --> 01:24:18.380
I think there is some
talk that that's kind of--

01:24:18.380 --> 01:24:21.500
that wave of populism
has been very

01:24:21.500 --> 01:24:24.320
evident in recent elections,
so is that something

01:24:24.320 --> 01:24:26.495
that the government
should be intervening with

01:24:26.495 --> 01:24:28.120
or should it be up
to the free markets?

01:24:33.488 --> 01:24:35.440
AUDIENCE: I guess I'll jump in.

01:24:35.440 --> 01:24:37.790
I think the major implications
of innovation wave theory

01:24:37.790 --> 01:24:39.507
is just that we should
always be nervous

01:24:39.507 --> 01:24:41.090
because if we don't
get the next wave,

01:24:41.090 --> 01:24:42.632
then our economy is
kind of screwed--

01:24:42.632 --> 01:24:44.480
we won't be number one anymore.

01:24:44.480 --> 01:24:46.580
And so, like, some key
technologies-- or also

01:24:46.580 --> 01:24:48.890
some examples of what could
happen in the future is,

01:24:48.890 --> 01:24:52.230
like, there's certain
asteroid belts that are

01:24:52.230 --> 01:24:54.950
worth quintillion's of dollars.

01:24:54.950 --> 01:24:57.270
So if we happen to
say, oh, you know

01:24:57.270 --> 01:24:59.720
what, we're just going to
not really focus on having

01:24:59.720 --> 01:25:01.190
rapid innovation in Japan.

01:25:01.190 --> 01:25:03.380
Or China says, oh,
actually, we're not really

01:25:03.380 --> 01:25:05.930
focusing on this at all--

01:25:05.930 --> 01:25:09.050
let's do a Manhattan
Project for going into space

01:25:09.050 --> 01:25:10.328
and being able to mine.

01:25:10.328 --> 01:25:12.620
And they can go in and they
can get quintillion dollars

01:25:12.620 --> 01:25:17.210
into their economy, then their
GDP is looking pretty good.

01:25:17.210 --> 01:25:18.930
Other implications
are say somebody

01:25:18.930 --> 01:25:21.590
focuses a lot on biotech
to the point where

01:25:21.590 --> 01:25:25.700
they can engineer diseases
that only they can counter.

01:25:25.700 --> 01:25:28.460
And then they start doing
biological warfare because they

01:25:28.460 --> 01:25:30.650
know the US has nuclear arms.

01:25:30.650 --> 01:25:33.496
So that's a different
way they can branch out.

01:25:33.496 --> 01:25:37.518
So I guess it's kind
of this idea of we're

01:25:37.518 --> 01:25:39.310
never really on top,
or when you're on top,

01:25:39.310 --> 01:25:41.150
everyone is shooting
for you, I guess.

01:25:41.150 --> 01:25:43.700
Where we could say, yeah,
we're number one, but also

01:25:43.700 --> 01:25:47.450
say we really need to
keep innovating and think

01:25:47.450 --> 01:25:49.160
about how we're structuring it.

01:25:49.160 --> 01:25:51.290
Because the future is
always going to be-- well,

01:25:51.290 --> 01:25:54.150
time is pretty much just
indicating that change

01:25:54.150 --> 01:25:55.670
is happening all the time.

01:25:55.670 --> 01:25:59.170
So we probably won't be where
we're at, and we probably--

01:25:59.170 --> 01:26:01.320
I'm thinking we don't
want to go down,

01:26:01.320 --> 01:26:04.730
but that's really up to
the US and its citizens

01:26:04.730 --> 01:26:07.850
to decide every
single generation.

01:26:07.850 --> 01:26:10.153
AUDIENCE: I might come
at it from a little bit

01:26:10.153 --> 01:26:10.820
different angle.

01:26:10.820 --> 01:26:14.480
I think we've been talking a lot
about sort of a capital based

01:26:14.480 --> 01:26:16.700
innovation and how that might--

01:26:16.700 --> 01:26:19.790
the IT boom and how things
might be a little different

01:26:19.790 --> 01:26:22.610
structured on, like,
a capital side.

01:26:22.610 --> 01:26:25.362
We might have--
just kind of look

01:26:25.362 --> 01:26:27.445
at the effect of human
capital and in the universe

01:26:27.445 --> 01:26:28.410
of innovation.

01:26:28.410 --> 01:26:31.460
But I think there's an
important piece here

01:26:31.460 --> 01:26:34.730
where we see a lot of growth
in the upper middle class

01:26:34.730 --> 01:26:38.330
because they're prepared
to handle [INAUDIBLE]

01:26:38.330 --> 01:26:42.480
a lot of the sort of more human
aspects of where we're going.

01:26:42.480 --> 01:26:45.350
But you see sort
of this transition

01:26:45.350 --> 01:26:48.782
as we look forward into
sort of management styles

01:26:48.782 --> 01:26:50.990
and kind of structuring
things, which is a little bit

01:26:50.990 --> 01:26:52.698
more high level, which
again lends itself

01:26:52.698 --> 01:26:53.790
to the middle class.

01:26:53.790 --> 01:26:55.880
Which I think if
we were looking to,

01:26:55.880 --> 01:26:59.570
as a corrective
measure for government

01:26:59.570 --> 01:27:01.610
widespread involvement,
there is this sort

01:27:01.610 --> 01:27:04.160
of public need for the
smoothing and transition.

01:27:04.160 --> 01:27:07.410
So that, like, you see the
highs for those that are high,

01:27:07.410 --> 01:27:08.980
but you don't see
the aggressive lows

01:27:08.980 --> 01:27:11.870
for those that are low sort
of passed over and made

01:27:11.870 --> 01:27:14.170
obsolete structurally
by this innovation.

01:27:14.170 --> 01:27:17.360
And I think there's
a greater need

01:27:17.360 --> 01:27:22.640
for kind of renewed investment
in sort of this human capital.

01:27:22.640 --> 01:27:24.710
I guess at the end
of the '60s, you

01:27:24.710 --> 01:27:28.360
had the GI Bill which helped
kind of a lot of folks

01:27:28.360 --> 01:27:32.750
get reintegrated in
sort of public education

01:27:32.750 --> 01:27:35.330
and greater institutional
or secondary education

01:27:35.330 --> 01:27:38.267
at postgraduate increased
sort of en masse.

01:27:38.267 --> 01:27:40.100
For a lot of different
reasons, that sort of

01:27:40.100 --> 01:27:43.270
helped ride the wave into
the 1990s because of that.

01:27:43.270 --> 01:27:48.575
But these sort of things
now, it's [INAUDIBLE]..

01:27:53.313 --> 01:27:54.730
There's a lot of
different changes

01:27:54.730 --> 01:27:56.600
that may happen a lot of more
frequently now and a lot more

01:27:56.600 --> 01:27:57.100
connected.

01:27:57.100 --> 01:28:00.550
So there's less room for
error because we can't really

01:28:00.550 --> 01:28:05.520
isolate ourselves in sort
of this US national system.

01:28:05.520 --> 01:28:07.310
But as a general
[INAUDIBLE] summary,

01:28:07.310 --> 01:28:10.310
I think you get a lot of these
interesting events happening

01:28:10.310 --> 01:28:14.200
a lot more quickly, so the highs
can get higher a lot faster

01:28:14.200 --> 01:28:16.003
and the lows can get
lower a lot faster.

01:28:16.003 --> 01:28:18.420
And so if we were sort of to
look for a governmental role,

01:28:18.420 --> 01:28:20.840
it'd be sort of probably
smoothing out these lows

01:28:20.840 --> 01:28:22.340
rather than focusing--

01:28:22.340 --> 01:28:23.590
AUDIENCE: Or insurance.

01:28:23.590 --> 01:28:25.250
AUDIENCE: Insurance-- yeah.

01:28:25.250 --> 01:28:28.910
Investment backing and
equity capital so you have--

01:28:28.910 --> 01:28:30.893
you're more able to kind
of take these shots.

01:28:30.893 --> 01:28:33.310
WILLIAM BONVILLIAN: So Rasheed,
that's really interesting,

01:28:33.310 --> 01:28:35.420
and you're driving
us to a perspective

01:28:35.420 --> 01:28:38.550
here that innovation
waves may be

01:28:38.550 --> 01:28:42.050
a way, at least in the shorter
term, for the rich to get

01:28:42.050 --> 01:28:47.630
richer and to create a
larger underclass, right?

01:28:47.630 --> 01:28:51.360
If we look at the Industrial
Revolution, the workout

01:28:51.360 --> 01:28:54.075
period of doing the
adjustments for the workforce--

01:28:54.075 --> 01:28:55.700
I mean, that's a 100
year long project.

01:28:59.150 --> 01:29:01.250
I think that recent
election results may tell us

01:29:01.250 --> 01:29:04.790
that we don't have the kind
time to play with as we work out

01:29:04.790 --> 01:29:07.220
the latest innovation waves.

01:29:07.220 --> 01:29:10.940
Now is an alternative to
bring on another wave?

01:29:13.580 --> 01:29:15.980
And then maybe all
waves are not the same

01:29:15.980 --> 01:29:18.020
in terms of their class,
and structural effects,

01:29:18.020 --> 01:29:20.240
and deterministic effects.

01:29:20.240 --> 01:29:23.900
So if Martha's innovation wave
around new energy technology

01:29:23.900 --> 01:29:27.560
that she spends her
life on comes about,

01:29:27.560 --> 01:29:30.590
that may be a big net
generator of employment

01:29:30.590 --> 01:29:34.410
overall as opposed to an
IT software wave which

01:29:34.410 --> 01:29:36.410
appears to be less so.

01:29:36.410 --> 01:29:38.480
So different waves may
have different kind

01:29:38.480 --> 01:29:41.900
of underlying structural
features for the society.

01:29:41.900 --> 01:29:44.741
AUDIENCE: [INAUDIBLE]

01:29:44.741 --> 01:29:48.460
WILLIAM BONVILLIAN: [LAUGHS]
Right, unless we get on it.

01:29:48.460 --> 01:29:49.940
Martha, you better hurry up.

01:29:49.940 --> 01:29:50.900
That's all I can say.

01:29:50.900 --> 01:29:52.900
AUDIENCE: [INAUDIBLE]

01:29:52.900 --> 01:29:55.192
WILLIAM BONVILLIAN: What are
you saying this class was?

01:29:55.192 --> 01:29:57.466
AUDIENCE: I wanted to
come back to a point

01:29:57.466 --> 01:29:59.247
that Beth made right
at the beginning

01:29:59.247 --> 01:30:01.580
when she said that we're going
to work on the assumption

01:30:01.580 --> 01:30:06.045
that our economy is an
innovation driven economy.

01:30:06.045 --> 01:30:07.670
And I think that all
of us in this room

01:30:07.670 --> 01:30:09.620
are probably on board with that.

01:30:09.620 --> 01:30:12.630
A lot of economists
are on board with that,

01:30:12.630 --> 01:30:15.890
but then Bill made the point
that our two-party system

01:30:15.890 --> 01:30:21.200
is arranged mostly around
these older views of economics.

01:30:21.200 --> 01:30:25.930
So why haven't one or
both of the parties sort

01:30:25.930 --> 01:30:28.160
of switched over into the
more innovation driven

01:30:28.160 --> 01:30:29.990
economic theory?

01:30:29.990 --> 01:30:31.740
And if they did,
couldn't we solve a lot

01:30:31.740 --> 01:30:33.083
of these problems a lot better?

01:30:33.083 --> 01:30:34.010
[LAUGHS] [INAUDIBLE].

01:30:34.010 --> 01:30:34.940
WILLIAM BONVILLIAN:
Well, Lilly, I'm

01:30:34.940 --> 01:30:37.250
happy to tell you I worked
in the Senate for 15 years.

01:30:37.250 --> 01:30:38.710
I wasn't able to persuade them--

01:30:38.710 --> 01:30:41.248
I just wasn't able
to bring it about.

01:30:41.248 --> 01:30:43.040
AUDIENCE: So just to
play devil's advocate,

01:30:43.040 --> 01:30:44.617
what would that look like?

01:30:44.617 --> 01:30:46.700
How would it be different
than what we have today?

01:30:50.690 --> 01:30:54.500
AUDIENCE: I would say
probably the supply side

01:30:54.500 --> 01:30:59.640
economic theory would take more
of a hit than maybe the labor

01:30:59.640 --> 01:31:01.190
supply economic theory.

01:31:01.190 --> 01:31:03.380
AUDIENCE: Well, if
I make a comment--

01:31:03.380 --> 01:31:07.053
Alberto, for those
watching at home--

01:31:07.053 --> 01:31:08.720
the thing that's been
really jumping out

01:31:08.720 --> 01:31:10.345
at me when we talked
about it earlier--

01:31:10.345 --> 01:31:14.030
sort of like the big old beast
of the military industrial

01:31:14.030 --> 01:31:16.400
complex, which from
my understanding

01:31:16.400 --> 01:31:18.470
thrives not on
radical innovation.

01:31:18.470 --> 01:31:20.540
They really love the
incremental thing

01:31:20.540 --> 01:31:22.580
because it can suck
out as much money

01:31:22.580 --> 01:31:24.420
as they can from the government.

01:31:24.420 --> 01:31:26.762
And if they can
just stay like that,

01:31:26.762 --> 01:31:28.970
if they can convince all
the politicians to give them

01:31:28.970 --> 01:31:31.420
money in funding of
that whole business,

01:31:31.420 --> 01:31:33.320
that's why we're
stuck in the 1950s

01:31:33.320 --> 01:31:36.015
because that's the system
that works best for them.

01:31:36.015 --> 01:31:38.000
But to go back to what
Rasheed said, I think--

01:31:38.000 --> 01:31:38.720
WILLIAM BONVILLIAN:
So Alberto, I'd

01:31:38.720 --> 01:31:40.532
contest with you
because I think it's

01:31:40.532 --> 01:31:42.740
fair to say that the military
has brought on actually

01:31:42.740 --> 01:31:44.600
most of the big
radical innovation

01:31:44.600 --> 01:31:47.385
waves of the second
half of the 19th.

01:31:47.385 --> 01:31:48.260
AUDIENCE: [INAUDIBLE]

01:31:48.260 --> 01:31:50.010
WILLIAM BONVILLIAN:
Well, radar turned out

01:31:50.010 --> 01:31:51.920
to be consumer electronics.

01:31:51.920 --> 01:31:52.855
And so--

01:31:52.855 --> 01:31:54.980
AUDIENCE: What's coming
out the F-35, I don't know.

01:31:54.980 --> 01:31:55.600
WILLIAM BONVILLIAN:
Yeah, what's coming--

01:31:55.600 --> 01:31:57.225
I don't know what's
coming out of that.

01:31:57.225 --> 01:31:58.740
AUDIENCE: [INAUDIBLE]

01:31:58.740 --> 01:32:02.210
AUDIENCE: [INAUDIBLE] Also
Intel is funded originally

01:32:02.210 --> 01:32:03.440
by government.

01:32:03.440 --> 01:32:05.020
AUDIENCE: Yeah.

01:32:05.020 --> 01:32:06.260
AUDIENCE: Maybe I'm wrong.

01:32:06.260 --> 01:32:08.385
WILLIAM BONVILLIAN: No,
but it's a very good point.

01:32:08.385 --> 01:32:09.980
And I think the
answer is that there's

01:32:09.980 --> 01:32:12.140
different forces in the
military and there's

01:32:12.140 --> 01:32:13.700
huge conservative
forces that want

01:32:13.700 --> 01:32:18.590
to perpetuate their
existing operating systems.

01:32:18.590 --> 01:32:22.460
And it's actually hard to
do disruptive innovation

01:32:22.460 --> 01:32:25.440
in the military because it
really is a legacy sector.

01:32:25.440 --> 01:32:29.060
So I think this play out
between how you bring innovation

01:32:29.060 --> 01:32:32.540
into a legacy sector-- which
the military has actually solved

01:32:32.540 --> 01:32:34.550
a few times--

01:32:34.550 --> 01:32:37.693
is kind of an interesting
idea, and we'll

01:32:37.693 --> 01:32:39.360
keep playing with
this idea as we go on.

01:32:39.360 --> 01:32:43.990
So yes, the military has been
able to launch disruptive

01:32:43.990 --> 01:32:48.010
innovation, but overall it's a
legacy sector and a lot of it

01:32:48.010 --> 01:32:51.130
is resistant to innovation
just as you suggest.

01:32:51.130 --> 01:32:54.225
So it's a very
interesting balance.

01:32:54.225 --> 01:32:56.100
AUDIENCE: Well, I wanted
to go back something

01:32:56.100 --> 01:32:57.225
she'd said about education.

01:32:57.225 --> 01:32:59.860
That innovation waves
don't have to, like,

01:32:59.860 --> 01:33:02.510
cause the destruction
of classes of people

01:33:02.510 --> 01:33:05.925
as long as people are educated
with the new skills that

01:33:05.925 --> 01:33:07.550
are associated with
an innovation wave.

01:33:07.550 --> 01:33:11.840
Like you brought the story up
about someone teaching someone

01:33:11.840 --> 01:33:14.930
else Morse code and how people
would not be left behind

01:33:14.930 --> 01:33:16.970
by railroads if
many of them learned

01:33:16.970 --> 01:33:19.940
to Morse code operators.

01:33:19.940 --> 01:33:22.220
And then in the future, I've
just read a lot of things

01:33:22.220 --> 01:33:27.200
about what if coding and
computational IT things become

01:33:27.200 --> 01:33:30.230
the new blue collar
jobs [INAUDIBLE]..

01:33:30.230 --> 01:33:34.400
All you need to do is
change the education system.

01:33:34.400 --> 01:33:37.280
AUDIENCE: And then going
to your point, [INAUDIBLE],,

01:33:37.280 --> 01:33:39.230
I think that it's
a little bit harder

01:33:39.230 --> 01:33:43.820
to sell growth theory to
voters because it is long-term

01:33:43.820 --> 01:33:44.480
oriented.

01:33:44.480 --> 01:33:45.980
So if you give them
the option, I'll

01:33:45.980 --> 01:33:50.010
protect your job today
versus in 10 years,

01:33:50.010 --> 01:33:51.840
you might be a
little bit better off

01:33:51.840 --> 01:33:54.803
because you have an agent
that's just not going to sell.

01:33:54.803 --> 01:33:56.220
AUDIENCE: It's
also kind of hard--

01:33:56.220 --> 01:33:56.770
I don't know.

01:33:56.770 --> 01:34:03.200
No, actually, to your
point, [INAUDIBLE]

01:34:03.200 --> 01:34:06.920
about connecting the legacy
sector innovation or the lack

01:34:06.920 --> 01:34:08.472
thereof to two-party interests.

01:34:08.472 --> 01:34:10.430
Because I think in
particular, you don't really

01:34:10.430 --> 01:34:13.070
see modern companies
that drive innovation

01:34:13.070 --> 01:34:16.220
sponsoring political activities
and particulary lobbying,

01:34:16.220 --> 01:34:16.720
right?

01:34:16.720 --> 01:34:19.012
You don't see them sponsoring
congressional candidates.

01:34:19.012 --> 01:34:21.215
You don't see them developing
political candidate.

01:34:21.215 --> 01:34:23.590
And you don't see them launching
political candidates out

01:34:23.590 --> 01:34:24.950
of their own [INAUDIBLE], right?

01:34:24.950 --> 01:34:26.783
So I think it would be
really curious to see

01:34:26.783 --> 01:34:30.310
the ways in which this election
is now encouraging legions

01:34:30.310 --> 01:34:33.145
of scientists, innovators,
technologists to run for office

01:34:33.145 --> 01:34:34.770
and to see the ways
in which they align

01:34:34.770 --> 01:34:37.400
or don't align themselves
to our two-party system.

01:34:37.400 --> 01:34:41.727
Because if they're-- the most
important thing I think of more

01:34:41.727 --> 01:34:44.060
in political science is that
if you're not at the table,

01:34:44.060 --> 01:34:45.710
you're on the menu.

01:34:45.710 --> 01:34:47.220
And so we're at
the table right now

01:34:47.220 --> 01:34:49.160
and we all have this sort of
vested interest in the ways

01:34:49.160 --> 01:34:50.610
in which the waves
of technology are

01:34:50.610 --> 01:34:52.070
going to impact
not only ourselves,

01:34:52.070 --> 01:34:54.160
individual stakeholders,
but the communities

01:34:54.160 --> 01:34:55.910
that we're a part of
and also the nations.

01:34:55.910 --> 01:34:58.202
Because spheres of influence
matter a lot [INAUDIBLE]..

01:35:03.473 --> 01:35:05.390
So I think it would be
really curious to think

01:35:05.390 --> 01:35:08.510
about the ways in which
precisely legacy sector

01:35:08.510 --> 01:35:14.720
innovation is pushing--

01:35:14.720 --> 01:35:17.990
almost preventing
the development

01:35:17.990 --> 01:35:20.300
of political involvement
between innovative firms

01:35:20.300 --> 01:35:23.460
and the two-party system.

01:35:23.460 --> 01:35:25.940
AUDIENCE: I actually wanted
to mention one of your points.

01:35:25.940 --> 01:35:29.963
You had said that it would
be difficult to have people

01:35:29.963 --> 01:35:31.880
decide, OK, do you want
to save your job today

01:35:31.880 --> 01:35:32.990
versus in the future.

01:35:32.990 --> 01:35:36.110
Well, maybe that's-- isn't
that the purpose of government

01:35:36.110 --> 01:35:38.240
in the first place is to
sometimes make unpopular

01:35:38.240 --> 01:35:43.547
decisions that will in the long
run actually benefit a greater

01:35:43.547 --> 01:35:44.255
number of people?

01:35:48.930 --> 01:35:51.740
I mean, yeah, it's
definitely a tricky subject.

01:35:51.740 --> 01:35:54.180
And it's not-- there's
no easy answer,

01:35:54.180 --> 01:35:57.420
but I at least think that--

01:36:00.360 --> 01:36:02.610
that's why we're a
representative democracy rather

01:36:02.610 --> 01:36:04.027
than just a straight
up democracy.

01:36:04.027 --> 01:36:07.975
It's because then we want these
people to actually represent us

01:36:07.975 --> 01:36:09.350
and to act in our
best interests,

01:36:09.350 --> 01:36:11.940
even if it's not
in the short-term.

01:36:11.940 --> 01:36:14.760
Ideally, we would say
that, OK, we actually

01:36:14.760 --> 01:36:19.881
trust these people to see
what our best interests are.

01:36:19.881 --> 01:36:22.960
AUDIENCE: Yeah, I agree that's
what I would want to happen.

01:36:22.960 --> 01:36:25.598
[INAUDIBLE]

01:36:25.598 --> 01:36:28.140
WILLIAM BONVILLIAN: So I'm going
to curtail this conversation

01:36:28.140 --> 01:36:30.900
because we have five readings to
go and we're more than halfway

01:36:30.900 --> 01:36:32.882
through the class.

01:36:32.882 --> 01:36:34.590
So this is going to
be a standard problem

01:36:34.590 --> 01:36:36.930
we're going to have all year,
so we can get used to it.

01:36:36.930 --> 01:36:40.110
But why don't we take
a quick five minute

01:36:40.110 --> 01:36:45.360
break now and come
back, and then we'll

01:36:45.360 --> 01:36:48.950
tackle the next round.