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  • SHANE GREENSTEIN: Thank you for having me.

  • Look, we're small enough that we can have a conversation.

  • I do have a presentation, but you can also

  • interrupt me if you want.

  • It's really quite OK.

  • I wrote this book, OK?

  • Took a lot of years.

  • And I hope to share a little bit with you.

  • I can't share the whole thing with you now, but perhaps

  • get you to motivate a little bit.

  • And I really appreciate you taking the time.

  • So let me just say what the book's aspirations were

  • and then give you some flavor for it.

  • The big question is why did the commercialization

  • of the internet have such a large economic impact?

  • That's a big question.

  • It's the big question in this area.

  • What the book does, it accomplishes three things.

  • It puts everything into one place

  • I like to say there's nothing in this book that wasn't already

  • known by somebody.

  • It just had never been all together.

  • Second, it focuses on innovation and commercialisation.

  • There's lots of very good writing on invention,

  • a lot less on commercialization.

  • And then third, it offers a big picture,

  • this phrase "innovation from the edges," which

  • we can get to if you want.

  • You might reasonably ask, who cares?

  • And Jonathan gave the answer, because it

  • changed everyday life.

  • If you have children and you talk to them,

  • I don't know if you've had this experience of showing them

  • "Leave It to Beaver on TV" and then you say, look, look,

  • there's no internet there.

  • And it really did change life.

  • It's changed it as we know it.

  • It changed business as we know it.

  • It's changed an enormous number of industries, how they behave.

  • It changed the identities of the leaders in many industries.

  • It's the kind of thing that it was

  • responsible for a boom in investment

  • for about five years in the US.

  • These are sort of things you don't see happening together

  • very often in the 200-year history of capitalism,

  • if I can make an overstatement.

  • It's the sort of thing you only see with electricity,

  • automobiles, the big things.

  • Indoor plumbing.

  • I put a list there.

  • Television, telephones.

  • There aren't many examples like this,

  • and so that, in and of itself it's of interest.

  • But I thought it's also interesting just

  • to understand what happened and why,

  • and why we had a big impact.

  • You can also see some of the symptoms in other things

  • like all the households that were

  • online-- you had half the households online

  • by the beginning of 2001, which is extraordinarily fast,

  • and the number of businesses online 90% of US businesses

  • were online by 2001, which is also extraordinarily fast.

  • The other place to start is to start

  • with misleading metaphors.

  • The other reason to write this book-- many people, when they

  • look at the internet, want to look

  • for an Edison or a Manhattan Project,

  • look for something that the government did,

  • as if the US government orchestrated this, or somebody

  • invented the whole thing.

  • And that's just wrong.

  • That's actually a very misleading metaphor.

  • There are some very, very smart people

  • who were involved in inventing the internet.

  • But if you want to understand why

  • it had the economic impact it had,

  • that's not the place to start.

  • That's the other reason to write a book like this.

  • So I'm going to focus on commercialization.

  • This is the best picture I could find of tubes.

  • And commercialization, in particular,

  • is taking technology and finding value in it.

  • And that's where the focus of the book is.

  • That's typically not something people write about,

  • although you're all living it at the moment.

  • The reason you want to focus on innovation

  • and commercialization, it is a much better focus

  • for understanding creative destruction

  • and the kinds of processes we saw

  • in the latter part of the 90s.

  • And it's also a much better way to understand

  • why some government policies succeeded and others failed.

  • So the big question that shows up in the middle of the book

  • is, how do major technologies deploy?

  • And what are the processes that we observe

  • and what are the patterns we observe?

  • And by the way, these are very durable patterns,

  • the kinds of commercial patterns you find, again,

  • over 100 years, the sort of things you see in electricity,

  • major agricultural inventions, telephones, and so on.

  • So if you start from that question

  • and you look at what happened in the middle of the 1990s,

  • you actually look at computing as in sort of its 2.0 phase.

  • We're presently, by the way, in about a 3.0 phase of big data.

  • Actually, you're at the center of the present phase.

  • I'd say historically, in about the mid-90s, we were at 2.0.

  • 1.0 was pushing out the processors into the frontier

  • and finding value in that.

  • And the typical uses were just the first times anybody'd

  • ever done databases for airlines, hotel

  • reservations, simple logistics.

  • And 2.0, a lot of people knew that it was coming,

  • was to do internetworking, that is,

  • to connect computers over large geographies

  • and do a lot of automated processes.

  • And a lot of prototypes had been built. So the value

  • was identified in advance.

  • What wasn't understood was what form it would

  • take in commercial markets.

  • That was where a lot of the mystery was.

  • In this case, what happened is a very good identification

  • of processes you find in lots of major technologies

  • when they diffuse.

  • And I would call them the two conundrums in order

  • to just identify for a general audience what a lot of research

  • sees over and over again.

  • So the two conundrums are, I call

  • them the circular conundrum and the adaptation conundrum.

  • So when major technologies diffuse,

  • the big problem they face is you have

  • to coordinate multiple suppliers all simultaneously

  • around the same effort.

  • And typically those suppliers are competing with one another

  • or they're not even talking to one another.

  • And so getting them to coordinate

  • can be very challenging.

  • The second conundrum, adaptation conundrum,

  • is when you have major technologies diffusing,

  • typically they have to be adapted

  • into a variety of circumstances in order to be valuable,

  • and that's actually where most of the investment takes place.

  • And nobody wants to make that investment

  • unless they're sure the darn thing is going to pay off.

  • And so then everybody holds back.

  • So you typically get these two conundrums

  • holding back major technologies from deploying.

  • And the question that emerges if you

  • look at any major technology is, how do you

  • resolve these two problems?

  • So I'll just do both of these in this case.

  • And I actually think it helps people understand

  • what we're going through today in a couple other major

  • technologies.

  • OK?

  • That was the plan.

  • So the circular conundrum is often

  • called the chicken-egg problem.

  • If you've not heard this, that's a joke.

  • I'm trying, all right?

  • So the theory is, you have to coordinate multiple firms.

  • So how do you do that?

  • The classic chicken-egg problem has the characteristic

  • that multiple firms need to get their stuff to work together

  • in order to create value.

  • But all of them hold back, and so they all sit on the fence,

  • and so you get long, long delays.

  • Typically what you need is either a focal point,

  • a mandate, a platform that coordinates,

  • a standard that's voluntary that all can participate in.

  • You need a mechanism like that to generate

  • an overcoming the circular conundrum.

  • I put a picture of Google Maps up here

  • because, in fact, that is the function it serves.

  • Just to give you an example, this is still

  • something we see today.

  • So what happened historically in '95?

  • Well, a metaphor that's often used is that what we got

  • was a gold rush as the catalyst.

  • That metaphor is a bit misleading,

  • but there's a grain of truth to it.

  • And so I think walking through the story actually

  • really helps.

  • Any of you ever been to the place for the 1848 gold rush?

  • Anybody?

  • OK.

  • So just to give you a feel for what it is,

  • that's a picture of Sutter's Mill

  • to give you an idea of what gold rush economics is about.

  • Gold rush economics is actually an information problem.

  • So what happened in 1848 is a good illustration.

  • If you look at the Sierra Mountains,

  • they come up at an angle.

  • They have the substrates underneath the surface,

  • and then the glacier cut off a whole bunch of rock

  • and exposed one seam of gold.

  • Most of the seams of gold that sit in the Sierras

  • are not covered by rivers.

  • But they are covered by rivers in one place, which

  • is the South Fork of the American River, which

  • Sutter built his mill on.

  • And so what the river does is, it

  • took off a little bit of gold and put it in the water.

  • But nobody had ever gotten up that high into the Sierras.

  • Once Sutter put his mill that high into the Sierras,

  • the gold dust, which doesn't travel very far, became found.

  • And what that did is, very quickly

  • information about that discovery went out,

  • and then we had a standard economic behavior,

  • which is it was thought that getting to that gold

  • quickly was going to get high returns.

  • So you have the information goes out.

  • Until then nothing is known.

  • Then the information spreads, and then there's

  • a behavioral reason for everyone to rush in.

  • That's a gold rush.

  • So the question is, did we have a gold rush here?

  • Was there something unknown that then

  • became known and then generated a bunch

  • of ideas that wasn't known?

  • And then what were the behavioral reasons to rush in?

  • That's the sort of questions you ask about the situation.

  • So on the one hand, if I was being

  • very pedantic I'd tell you this wasn't a gold rush.

  • There were plenty of firms who were investing prior to 1995.

  • And so you couldn't argue, necessarily, there

  • was something that was unknown.

  • On the other hand, if you're being a little more charitable

  • and you look at historically what happened,

  • the coordinating mechanism is pretty obvious.

  • It was Netscape's founding.

  • And it wasn't Netscape's founding per se.

  • It was the demonstration of a commercial browser

  • as a commercial prototype.

  • It was more than a prototype.

  • It was actually for sale.

  • And that was in February of 1995.

  • And essentially what happened is,

  • many participants in industry, in the computing industry,

  • at the same time saw the same commercial prototype

  • within several months of one another.

  • So you got the equivalent of a gold rush

  • because they were all informed at roughly the same time,

  • and then they all make their investment decisions

  • at roughly the same time.

  • That's actually what happens here.

  • We could talk about Microsoft in a little bit if you want to.

  • Microsoft has a slightly different history

  • at this moment.

  • And Google might take a lesson from that going forward.

  • We'll go to that in a little bit.

  • The other thing that happened at the time, absolutely the one

  • thing about this history that's essentially very interesting

  • is that the governance of the situation

  • was unique relative to anything that had come before it.

  • Again, I think anybody in computer science

  • now takes this for granted, but it was quite novel at the time.

  • There was a governance structure both in the IETF-- sorry,

  • in the Internet Engineering Task Force--

  • and in the World Wide Web Consortium that

  • had two characteristics that had not previously ever shown up

  • in a major platform.

  • The two characteristics were, anybody

  • could come and gain information about the technology.

  • And second, there were no what a lawyer

  • would call restricted rights.

  • There were no reach through rights.

  • The organizations giving out the information

  • did not tell you what to do with it.

  • So those two things.

  • Anyone could come in, and there was

  • no constraint on what could be done with the information.

  • The internet platform had no restraint

  • on what was done with the information.

  • And that was just a new characteristic.

  • Any firm who had ever done a major platform until that

  • had always restricted information flow in and out,

  • and use afterwards.

  • And what that did is it generated

  • what I think most people in computing

  • take for granted, which is you get lots of specialists

  • within platforms.

  • So once you have a well-designed modular platform,

  • you can get a specialist who takes

  • for granted the rest of the platform

  • and then does a commercial product that's offered.

  • In this era, this is the first time

  • we ever saw a major growth across the entire economy

  • in a whole bunch of specialists taking

  • advantage of the platform.

  • I like to use this example from Hotmail since it was so simple.

  • Hotmail, the first web-based email, and it

  • had viral marketing.

  • It had the little footer that said,

  • get your new email at Hotmail.

  • And the people who programmed this

  • didn't have to do an enormous amount of work.

  • They could take for granted the rest of the network

  • was going to work.

  • TCP/IP was going to work, the World Wide Web

  • was going to work, and everybody else was going to be just fine.

  • And if they got a wrong email address,

  • it wasn't going to bring down the network.

  • They could take for granted they could

  • do something very narrow and specialized,

  • and take for granted everything else.

  • And this is a great example of what

  • a modular platform with unrestricted information

  • can do, and did do in this case.

  • So this was the other source of the gold rush.

  • So that's the circular conundrum.

  • Ready for the adaptation conundrum?

  • The adaptation conundrum.

  • I put up a picture here of-- I don't

  • know if anyone knows this one.

  • It looks obscure, but it's fun.

  • Any Midwesterners in the room?

  • This is corn.

  • Particularly, this is taken from hybrid corn.

  • I'll explain the association in a minute.

  • Again, here's the theory.

  • The theory is when you get a new major technology deploying,

  • it has to be adapted in multiple circumstances.

  • That's something, again, we've seen multiple times any time

  • major technology shows up.

  • What happened here, same thing.

  • You would expect the internet not to be used right away,

  • but that it would need a lot of co-investment

  • in a bunch of locations and a bunch of businesses

  • to turn it into something valuable.

  • And then the open question is, how does that co-invention

  • organize itself?

  • There's no natural one answer to that question

  • in any major technology.

  • And what happened here-- I sort of already

  • gave you the answers-- we got a bunch

  • of innovative specialists, unlike what we had seen

  • historically in some major technology pushes,

  • where one firm had dominated the technology,

  • say, for example as in telephony, or in automobiles,

  • the Ford Motor Company dominated it.

  • Here we had enormous numbers of innovative specialists each

  • doing their own thing.

  • And that ended up getting the investment

  • in adaptation specialized across multiple players.

  • And it was also done very quickly as a consequence.

  • It meant all these people and could act independently.

  • So to give you an example, why do specialists

  • do adaptation really well?

  • This is of my favorite stories from this era.

  • Did anybody ever use this product?

  • Any of you old enough to remember this product?

  • Internet in a box.

  • It's totally, you know, cute.

  • So what they did-- this is a 1994 product.

  • So what they did is they took basically a browser.

  • It was a Mosaic browser.

  • It wasn't even a Netscape browser.

  • They put it on a disk, they stuck it in a box

  • to make it look like packaged software,

  • because that was the motif of the time.

  • You would go to, you remember Egghead

  • or one of these retail outlets, and then

  • you would buy packaged software.

  • And then people went and bought it,

  • and then they would put the internet in their PC.

  • I think it's sort of cute.

  • And you go, really?

  • Come on.

  • But this worked.

  • This was extremely popular.

  • And the point is that innovative specialists all

  • find different little niche ways of adapting

  • the technology to the sub-market that they perceive.

  • So they perceived this sub-market

  • for a bunch of new users that nobody else had perceived.

  • They got a huge amount of attention.

  • And so they were a hit, and they eventually ended up

  • selling to someone else.

  • The key to an example like this is the specialist

  • is trying to learn something you don't otherwise see,

  • you can't learn in a lab.

  • They're typically trying to understand something

  • about the mix between demand and costs

  • that's not otherwise learnable through a simple experiment

  • inside of a laboratory.

  • Here's another example from the time.

  • ISPs.

  • Do you remember dial-up ISPs?

  • Why did the US get the internet earlier than any other country?

  • This is the answer.

  • Because we had the fastest deployment

  • of the dial-up network anywhere in the developed world.

  • And that arose, again, because these dial-up companies

  • were specialists in all these different locations.

  • And many of them had previously been bulletin board systems.

  • And so you found them all over the place,

  • and then becoming an internet service provider

  • was a very easy thing for them to do.

  • And so then this is my favorite quote of the book.

  • Let's see if I can-- yeah, I can do this.

  • "A good predictor of not finding an ISP

  • is the presence of a lot of hybrid corn seed,"

  • which comes from Zvi Grill, used to be a professor at Harvard

  • who studied hybrid corn.

  • And this is his 1957 dissertation,

  • one of the more famous studies of major technology deployment.

  • And he observed that ISPs looked an awful lot like what

  • he had studied years ago.

  • You might ask a slightly deeper question,

  • which is where did all these bulletin board systems

  • come from?

  • Where did all the specialists come from?

  • It's one of the characteristics of the US.

  • It's not unique to the United States

  • to have large communities of what are known as wild ducks.

  • Do you use that phrase inside Google as well?

  • This is a perhaps archaic phrase now,

  • a phrase about computing about wild ducks,

  • that people who look at things in a different way

  • or have a different perception of what

  • the innovative value is.

  • The United States is not entirely

  • unique in having communities of wild ducks,

  • but had a fairly large community even at this time.

  • And there were a bunch of regulations

  • to protect them and mandate that telephone companies should

  • work with them.

  • And then there was also the First Amendment turned out

  • to also support them, because many bulletin board systems

  • were doing some unsavory activities.

  • We'll just leave it there.

  • So I'll finish up here pretty quick.

  • One other place that's interesting to find adaptation

  • is in business use.

  • There were two things going in business that often are really

  • under appreciated.

  • One was on the browser side, which looked a lot like home.

  • The other was on enhancement of business services

  • to support electronic commerce.

  • That was really expensive, that kind of investment.

  • As it turned out, after the fact--

  • we shouldn't be surprised by this,

  • but many people at the time were surprised

  • after the fact-- there was a large incentive by users

  • to retrofit existing processes with something that saved

  • the capital they already had.

  • Users did not want to go into a green field situation,

  • typically.

  • They typically wanted to preserve a lot

  • of the things they already had.

  • And as a consequence, many of the dot coms

  • who came into these businesses failed precisely

  • because they didn't respect their end customer wanting

  • to preserve what they were doing.

  • And if you look in retrospect, the reason IBM

  • succeeded in this era was precisely

  • because they respected the existing

  • processes of their client base.

  • That's just one of the big lessons

  • you have to walk away with from looking

  • at this era, for what it's worth.

  • We could talk about the boom if you like.

  • There was a boom.

  • The boom had a gold rush.

  • It was caused by the gold rush.

  • There was a second thing going on,

  • and that was a network effect where

  • investment by firms in processes made browsing more valuable.

  • That made more firms go online with electronic commerce, which

  • then induced more browsing adoption, and so on, and more

  • investment in the network.

  • And so you had these interplays which

  • made it more valuable for each player to do more investment.

  • That was the second thing going on, and that caused the boom

  • in the '90-2000 era.

  • And then, as an economy, we overshot, without question.

  • So that's, in a nutshell, chapters nine, 10, 11 and 12.

  • Just explained how that overshooting happened.

  • So I'm doing the whole thing quickly just

  • because it's more fun.

  • Let me end with two things.

  • Renewal.

  • So after the overshooting there were two forms of renewal

  • that I talk about in the book.

  • One of them is Wi-Fi.

  • And where did Wi-Fi come from?

  • Wi-Fi is a wonderful example because the spectrum was

  • allocated initially for things that the engineers in the FCC

  • regarded as garbage, and many engineers regarded as garbage.

  • So baby monitors, mobile handsets.

  • You remember these kinds of things inside your home?

  • Garage door openers.

  • And the trick, the thing that happened

  • was, the unlicensed spectrum allowed equipment firms

  • to embed the use of that spectrum

  • inside of their wireless antennas and their wireless

  • servers.

  • And users found that very valuable.

  • And so the spectrum ended up migrating

  • from garage door openers.

  • You still find it in some garage door openers,

  • but it ended up migrating mostly into the area of Wi-Fi.

  • And so the unlicensed spectrum ended up

  • being the vehicle for movement of value

  • from a low value use to a high value use.

  • And that's a pretty interesting piece of renewal.

  • And then I had to do this example in this room,

  • just because it's well-known.

  • The book also has a chapter on internet advertising

  • and Google's approach to renewing that market, which

  • was on its way down at the time that Google starts

  • to figure out how to do an ad auction for keywords, which

  • renews the market for advertising at the time.

  • And I suspect this story is known in here,

  • so I won't go over.

  • It's just I had to bring it up because it's in the book.

  • Want to do big lessons, or are we good?

  • Big lessons?

  • OK, big lessons.

  • That's my favorite big picture.

  • Sorry.

  • That's also a bad joke.

  • OK, what movie?

  • Yeah.

  • Ferris Bueller.

  • So the big picture.

  • Innovation from the edges is the major framing.

  • That's about outsiders bringing new perception and new assets

  • to bear on an opportunity that insiders were not investing in.

  • The big lesson from this experience

  • is the way outsiders explored, particularly

  • outsiders who were specialists, and innovative specialists

  • explored sub-pieces.

  • And that unlocked the circular conundrum and the adaptation

  • conundrum.

  • That's the big insight of this experience.

  • The book spends a lot of time filling in the gaps about

  • why that happened and why.

  • It has a lot of consequence for thinking about, say,

  • for example, a company like this who supports

  • a lot of innovative specialists as a major platform,

  • and how would you think about taking activity to support?

  • And then start new platforms to support

  • new innovative specialists.

  • So in this instance, what we observed

  • was this interplay between all the specialists

  • who raised the value of the investment

  • by all of the others.

  • And the other big lesson, in comparison, why did you

  • have this done in this way?

  • Why did the network grow this way,

  • and why didn't it grow from a telephone company?

  • There were lots of opportunities for publicly

  • supported telephone companies to grow a data network.

  • And why didn't it happen that way?

  • And the answer is that innovative specialists

  • perceived things that otherwise would not

  • rise to the top of priorities inside of a large firm.

  • You get multiple points of view supported

  • in this kind of market structure that you wouldn't otherwise

  • get in a single firm.

  • And as a consequence, you get more variety

  • than you would otherwise get in a single firm.

  • But if you were going to read this book with the present

  • in mind, I would start by saying you

  • would expect to see these two conundrums arising repeatedly.

  • They still do.

  • For example, if you look at big data 3.0-- as I say,

  • it looks to me like we're in 3.0 of big data-- we've

  • been in big data for a long time as an industry.

  • But the present era of big data, you

  • would expect to see circular conundrum issues showing up,

  • which you do.

  • And you see major firms trying to take positions

  • as coordinators.

  • I think you're in that business.

  • So is Amazon.

  • So is Microsoft.

  • You see institutions that help coordinate large data as well.

  • Again, we tend to have a lot of open systems doing that.

  • You see government mandates, again,

  • trying to take positions to unlock circular conundrums,

  • particularly in the Health Care Act.

  • There was actually lots of subsidies in the Health Care

  • Act to get hospitals all to do computing

  • inside their organizations so that then they

  • would all use the same field so they could exchange data.

  • That's a very standard way to overcome a circular conundrum.

  • Then on adaptation, you would also expect to see that.

  • You see that again.

  • I mean, I could run through it again,

  • but you see that in the present environment.

  • My own forecast on say, for example, the big data changes

  • today, is that adaptation is actually much easier

  • than we saw 20 years ago, partially

  • because you don't really have to involve households very much.

  • Most of investments being done in the infrastructure

  • are behind the scenes, and it's being done by major businesses.

  • And so largely those investments are done for private reasons

  • and don't need to be coordinated very heavily

  • with a lot of other firms.

  • There's some standardisation issues, of course,

  • and some big government privacy issues that are difficult.

  • It's a challenging problem, but it's easier than the one

  • we just observed in this book.

  • Thanks.

  • [APPLAUSE]

  • I'm happy to have a conversation.

  • It's small enough in here.

  • AUDIENCE: Could you give a specific example

  • of a circular conundrum that you [INAUDIBLE]?

  • SHANE GREENSTEIN: Oh, certainly on the smartphone market.

  • I mean, yeah, though we're over that one at this point.

  • In smart phones 10 years ago, we were still-- think about it,

  • before the iPhone we were still facing

  • the same old circular conundrum.

  • Nokia and Microsoft had both done a lot of investments

  • to try to overcome that.

  • And then the iPhone ended up being the catalyst

  • to start things, and Android was close enough

  • behind, and with a governance structure that

  • was very friendly to programmers and app developers

  • that it also managed to develop a network.

  • That's what you have in mind?

  • AUDIENCE: Yeah, well, how about one

  • that hasn't been resolved yet?

  • SHANE GREENSTEIN: Oh, that hasn't been resolved.

  • Certainly internet of things has got that in it,

  • because of a bunch of the standards about security,

  • for example, and how things should work with each other

  • when they come across from different firms.

  • AUDIENCE: Do you see the emerging television standards,

  • now that everything is going on the internet, essentially?

  • There are already beginning to be interoperability

  • issues between smart TVs and Roku and so forth.

  • And in fact, I was just on the other side of the building,

  • and people were talking about the possibility of testing

  • applications on things that have new models out every season.

  • SHANE GREENSTEIN: Yeah, just in the streaming video side,

  • even in the consumer side, there's

  • still some serious issues.

  • You know, there's actually some public policy there also

  • in getting the coordination between the-- I

  • almost hesitate to get into the weeds on this-- on edge

  • providers, if you will, and broadband providers,

  • and what's appropriate behavior at handoff points and gateways

  • between network providers.

  • If you look, for example, at the issues that

  • arose when Netflix was not working too well in January

  • of 2014, to use a very simple example,

  • that was from not having an understanding

  • about how to coordinate data handoff between, at that point,

  • either a backbone provider who was carrying a lot of data

  • and passing it into a broadband network,

  • or from a CDN into a broadband network.

  • And there was a disagreement about the proper way

  • to do that, or what both parties wanted to do.

  • That's a pretty nasty circular conundrum effect,

  • if one keeps arising, especially if everything goes online,

  • as we're all forecasting.

  • That's another one.

  • Is that helpful?

  • AUDIENCE: Yeah.

  • Well, I mean, are there any broad trends

  • that you can use to predict how, say, internet of things--

  • SHANE GREENSTEIN: I mean, cars, which your firm is involved in,

  • is a pretty good one as well.

  • We can all see that one coming.

  • There's more than just-- I mean, the cars already work, right?

  • Yeah.

  • They already work.

  • So the prototypes-- we're in a situation

  • now where the prototypes all work.

  • We can all forecast there's going to be a scale

  • decline in cost pretty soon.

  • And there's an enormous amount of coordination

  • that needs to take place between road building, insurance

  • companies, legal standards for accidents, and liability.

  • AUDIENCE: But in this case, it doesn't

  • seem like firms are waiting to invest, right?

  • There's already lots of companies investing in that.

  • SHANE GREENSTEIN: Yes.

  • There is already a lot of investment.

  • AUDIENCE: Is it that there isn't a clear direction, so there's--

  • SHANE GREENSTEIN: Yeah.

  • So the danger at the moment in that area is we're

  • going to get Balkanized standards.

  • So we'll get two or three different ways of doing things.

  • In fact, it almost seems inevitable Europe will go one

  • way and the US will go another.

  • That just almost seems inevitable on this one.

  • Even worse is California goes one way and the rest

  • of the country goes another.

  • That seems possible also, particular with cars,

  • because, California has always gone its own way on, say,

  • for example pollution controls.

  • AUDIENCE: So in this case, so for cars,

  • government regulations are what's

  • going to ultimately determine--

  • SHANE GREENSTEIN: It's going to be a major determinant.

  • AUDIENCE: Is that always the case?

  • Like for Internet of Things, is there another way it go?

  • Can you predict how the net will be resolved?

  • SHANE GREENSTEIN: No, it's hard to predict.

  • I never like to predict.

  • I would be a little cautious.

  • In this example, 20 years ago, government regulation

  • had two roles, and so we should be careful.

  • Sometimes it's very interventionist

  • because competition policy intervenes

  • very directly when you have a monopoly provision.

  • That's still going to happen in this country.

  • There's a longstanding dislike for monopoly provision

  • in the United States.

  • That's not going to go away.

  • Monopoly provision is going to happen somewhere

  • in transportation because there always are, it always does.

  • And you can forecast there will be government intervention very

  • directly in the places where monopoly provision of transport

  • services allows somebody to jack up prices or dictate terms,

  • and government regulation will intervene.

  • Just know that, because that there's a long history of that

  • here.

  • Having said that, one of the interesting things

  • about watching the internet experience is,

  • government policy was not orchestrating.

  • It was often stepping back.

  • It was very deliberately stepping back and letting firms

  • invest as discretion dictated.

  • And you see a lot of that in the history here of particularly

  • federal forbearance is the word the lawyers use,

  • a deliberate stepping back from making decisions.

  • So it would enable private industry

  • to choose what it wanted to do without orchestrating

  • the whole thing.

  • And it was very selective intervention

  • in things like establishing the Internet Engineering Task

  • Force, or in privatizing the backbone.

  • But it was very selective.

  • I would say it was always wise.

  • I mean, the domain name system wasn't done particularly well,

  • for example.

  • So there's something equivalent's

  • got to happen in cars.

  • There's got to be a set of standards, for example,

  • on how information is going to be interchanged

  • between the various parties, particularly

  • between the people who watch roads and individual cars.

  • Some of the things-- I mean, you guys

  • would actually know better, I suspect.

  • But if you've watched some of the prototypes I've seen,

  • you get that you get real time communication

  • between the vehicle and some other public source

  • of information.

  • And then that requires something.

  • AUDIENCE: Your colleague Professor Christianson

  • argues [INAUDIBLE] and how companies basically

  • get stuck at [INAUDIBLE].

  • You were saying that specialists are

  • need to resolve that dilemma.

  • SHANE GREENSTEIN: Can help resolve that dilemma, yes.

  • AUDIENCE: How do you see companies or leading businesses

  • such as Google avoid that dilemma of having specialists

  • inside?

  • SHANE GREENSTEIN: I was ready for this question.

  • I brought a slide.

  • So can I do the history first?

  • If I had to take a history.

  • OK, I have an Al Gore slide, too, in case you're curious.

  • OK.

  • So if I was going to take-- I know people at Google

  • might resist being compared to Microsoft 20 years ago.

  • But work with it for a minute.

  • Microsoft was approximately 20 years old

  • when these events occurred.

  • Not saying-- Google's not exactly 20 years old,

  • but it's pretty close.

  • There was some very strong personalities

  • at the heart of that firm at the time.

  • I'm not saying that's particularly true here.

  • But there's a very large firm.

  • What happened to Microsoft in this situation,

  • the details are well known.

  • Gates had lots of personal authority.

  • And he had misunderstood the potential for the internet.

  • And there was a skunkworks inside

  • of the company that had done a lot of advanced work.

  • And then I put a picture of Ben Slivka

  • up here because he's actually the guy who wrote the memo that

  • grabbed Gates' attention.

  • And they grabbed his attention late.

  • So that that's a historical fact.

  • He came to understand what was about to happen later

  • than many other in industry.

  • If you look at that example and step back from it and say,

  • what's the lesson, which is the essence of your question,

  • I would sort of be both empathetic and critical

  • at the same time.

  • If you look at Microsoft at the time,

  • they were very good at what you would think of as a big push,

  • deploying products that took several thousand people,

  • organized over multiple years, towards a very big goal.

  • They were extraordinarily good at that.

  • And you know, specialists actually

  • can't do that very well typically.

  • So it was a valuable thing for them to do.

  • The best example we have at the time was Windows 95

  • actually fits this.

  • What were they very poor at doing?

  • And I would guess the same would be true here as well.

  • There are sort of two things they were not

  • very good at doing.

  • And it's just inherently true.

  • Every large firm is poor doing this.

  • They weren't very good at planning.

  • They were extraordinarily good at planning relative

  • to their rivals, but they still weren't

  • very good at seeing the future, because everybody's

  • poor at doing that.

  • And second, they resisted cannibalizing their own product

  • lines.

  • And lots of reasons why.

  • We could go into those reasons, but lots of reasons why.

  • And it led them in the direction that you're hinting,

  • to resist understanding businesses that

  • were inconsistent with their present business.

  • That was the actual thing that happened here.

  • If you look at the mistake Gates made at the time,

  • it was, he didn't want to cannibalize Windows 95.

  • And he understood its value in a very particular way

  • and resisted another understanding that

  • was inconsistent with that.

  • And the result of that was it slowed them

  • down a tremendous amount.

  • And even for a long time after Gates' change of direction,

  • he resisted.

  • He actually did resist investments

  • to take advantage of what the commercial internet would have

  • allowed his firm to do, because he just resisted cannibalizing

  • his own investments.

  • That, I think, is the big danger.

  • It's a big danger in a firm like this.

  • There's just natural reasons why existing firms hang

  • on to existing product markets, existing revenue

  • sources, and existing perceptions

  • about where the source of value comes from.

  • Yeah, that's the issue.

  • And then the hard part-- the hard part

  • is getting the timing right.

  • Gates was late.

  • That was a preventable error in his case.

  • I think, in practice, I actually want to be more forgiving.

  • It's actually very hard to get timing right in general.

  • But that's the lesson of this case.

  • You want the Al Gore slide?

  • OK.

  • Sure.

  • Everybody always asks.

  • Nobody's asked yet.

  • But I'm always prepared for this because everyone always asks.

  • What did Al Gore invent and when did he invent it?

  • The book-- actually, I felt an obligation

  • to figure out what actually happened here.

  • This is the actual quote that started it all.

  • This is a Wolf Blitzer interview in 1999.

  • You can read it as well as I can,

  • but it's "I will be offering my vision when my campaign begins,

  • and it will be comprehensive and sweeping.

  • And I hope that it will be compelling enough

  • to draw people toward it.

  • I feel that it will be, but it will emerge from my dialogue

  • with the American people.

  • I've traveled to every part of this country

  • during the last six years.

  • During my service in the United States Congress

  • I took the initiative in creating the internet.

  • I took the initiative in moving forward

  • a whole range of initiatives," et cetera, et cetera.

  • That's what did it.

  • So after that interview, the next day,

  • there was a bunch of opposition research, most famous

  • of which came from Trent Lott.

  • "If Al Gore invented the internet,

  • I invented the paper clip."

  • Dan Quayle was my favorite quote from here.

  • "If Al Gore invented the internet,

  • then I invented the spell checker."

  • And that's how the meme started.

  • And then this meme got started on late night television.

  • Top 10 things Al Gore invented.

  • And it just gained its own momentum.

  • And the ridicule is quite funny, because it's

  • obvious no one individual could have invented the internet,

  • nor could one policymaker orchestrate the entire thing.

  • That's sort of inherently ridiculous.

  • And that's why it was funny.

  • It was also made for good political campaign, opposition

  • campaign.

  • But that's its source.

  • And the interesting thing, actually,

  • watching this in retrospect-- try

  • to explain this to your kids, to someone who wasn't there.

  • How did this survive for so long as a meme?

  • And that's the part that's actually hard to explain.

  • And it was just very good politics.

  • And this politician lost control of the conversation.

  • That's where it comes from.

  • It's a great joke, though.

  • AUDIENCE: But he did push through legislation that--

  • SHANE GREENSTEIN: Yes.

  • So his actual legislative history,

  • if you want that-- his actual legislative history is

  • two things.

  • It's two pieces of legislation.

  • It's primarily, though, with funding the National Science

  • Foundation network, particularly the latter bill that

  • upgraded the backbone for the internet and funded

  • supercomputer centers, which were attached to it.

  • And then one of those supercomputer centers

  • was the source of Mosaic, the browser that

  • generated the prototype browser that

  • was the catalyst for the commercial browser.

  • And that backbone was the backbone that was privatized,

  • that generated the other movement

  • towards commercial internet.

  • So yeah, he deserves credit for that.

  • That's a real thing.

  • How's that?

  • Cool.

  • Well, thank you very much.

  • [APPLAUSE]

SHANE GREENSTEIN: Thank you for having me.

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Shane Greenstein:"互聯網如何成為商業"|谷歌講座 (Shane Greenstein: "How the Internet Became Commercial" | Talks at Google)

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    richardwang 發佈於 2021 年 01 月 14 日
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