Tim O’Reilly

Government as a Platform

During the past 15 Jahre, the World Wide Web has created remarkable new meth-
ods for harnessing the creativity of people in groups, and in the process has creat-
ed powerful business models that are reshaping our economy. As the Web has
undermined old media and software companies, it has demonstrated the enor-
mous power of a new approach, often referred to as Web 2.0. In a nutshell: Die
secret to the success of bellwethers like Google, Amazon, eBay, Craigslist,
Wikipedia, Facebook, and Twitter is that each of these sites, in its own way, hat
learned to harness the power of its users to add value to—no, more than that, Zu
co-create—its offerings.

Jetzt, a new generation has come of age with the Web, and it is committed to
using its lessons of creativity and collaboration to address challenges facing our
country and the world. In der Zwischenzeit, with the proliferation of issues and not enough
resources to address them all, many government leaders recognize the opportuni-
ties Web 2.0 technologies provide not just to help them get elected, but to help
them do a better job. By analogy, many are calling this movement Government 2.0.

What the heck does that mean?

Tim O’Reilly is the founder and CEO of O’Reilly Media, Inc., thought by many to be
the best computer book publisher in the world. In addition to Foo Camps (“Friends of
O’Reilly” Camps, which gave rise to the “un-conference” movement), O’Reilly Media
also hosts conferences on technology topics, including the Web 2.0 Summit, the Web
2.0 Expo, the O’Reilly Open Source Convention, the Gov 2.0 Summit, and the Gov 2.0
Expo. Tim’s blog, the O’Reilly Radar, “watches the alpha geeks” to determine emerg-
ing technology trends, and serves as a platform for advocacy about issues of impor-
tance to the technical community. Tim’s long-term vision for his company is to change
the world by spreading the knowledge of innovators. In addition to O’Reilly Media,
Tim is a founder of Safari Books Online, a pioneering subscription service for access-
ing books online, and O’Reilly AlphaTech Ventures, an early-stage venture firm.

This essay first appeared as chapter 1 in Daniel Lathrop, Laurel Ruma, Hrsg. (2010),
Open Government: Zusammenarbeit, Transparency, and Participation in Practice,”
O’Reilly Media. We have published it in Innovations, with permission from the
author, under Creative Commons Attribution-Noncommercial-No Derivative Works
3.0 United States license.

© 2010 O’Reilly Media, Inc.
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Tim O’Reilly

Much like its predecessor, Netz 2.0, “Government 2.0” is a chameleon, a white
rabbit term, that seems to be used by people to mean whatever they want it to
mean. Für einige, it is the use of social media by government agencies. For others,
it is government transparency, especially as aided by government-provided data
APIs. Still others think of it as the adoption of cloud computing, wikis, crowd-
sourcing, mobile applications, mashups, developer contests, or all of the other
epiphenomena of Web 2.0 as applied to the job of government.

All of these ideas seem important, but none of them seem to get to the heart

of the matter.

Netz 2.0 was not a new version of the World Wide Web; it was a renaissance
after the dark ages of the dotcom bust, a rediscovery of the power hidden in the
original design of the World Wide Web. Ähnlich, Government 2.0 is not a new
kind of government; it is government stripped down to its core, rediscovered and
reimagined as if for the first time.

And in that reimagining, this is the idea that becomes clear: government is, bei
bottom, a mechanism for collective action. We band together, make laws, pay taxes,
and build the institutions of government to manage problems that are too large for
us individually and whose solution is in our common interest.

Government 2.0, Dann, is the use of technology—especially the collaborative
technologies at the heart of Web 2.0—to better solve collective problems at a city,
state, National, and international level.

The hope is that Internet technologies will allow us to rebuild the kind of par-
ticipatory government envisioned by our nation’s founders, in which, as Thomas
Jefferson wrote in a letter to Joseph Cabell, “every man…feels that he is a partici-
pator in the government of affairs, not merely at an election one day in the year,
but every day.”1

As President Obama explained the idea during his campaign: “We must use all
available technologies and methods to open up the federal government, creating a
new level of transparency to change the way business is conducted in Washington,
and giving Americans the chance to participate in government deliberations and
decision making in ways that were not possible only a few years ago.”

Allowing citizens to see and share in the deliberations of government and cre-
ating a “new level of transparency” are remarkable and ambitious goals, and would
indeed “change the way business is conducted in Washington.” Yet these goals do
not go far enough.

LESSONS LEARNED FROM THE SUCCESS OF COMPUTER PLATFORMS

There is a new compact on the horizon: information produced by and on behalf of
citizens is the lifeblood of the economy and the nation; government has a respon-
sibility to treat that information as a national asset. Citizens are connected like
never before and have the skill sets and passion to solve problems affecting them
locally as well as nationally. Government information and services can be provid-
ed to citizens where and when they need them. Citizens are empowered to spark

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Government as a Platform

the innovation that will result in an improved approach to governance. In this
Modell, government is a convener and an enabler rather than the first mover of
civic action.

This is a radical departure from the existing model of government, welche
Donald Kettl so aptly named “vending machine government.” 2 We pay our taxes,
we expect services. And when we don’t get what we expect, our “participation” is
limited to protest—essentially, shaking the vending machine. Collective action has
been watered down to collective complaint. (Kettl used the vending machine anal-
ogy in a very different way, to distinguish between the routine operation of gov-
ernment and the solution of new and extraordinary problems, but I owe him cred-
it for the image nonetheless.)

What if, instead of a vending machine, we thought of government as the man-
ager of a marketplace? In The Cathedral & the Bazaar, Eric Raymond uses the
image of a bazaar to contrast the collaborative development model of open source
software with traditional software development, but the analogy is equally appli-
cable to government. 3 In the vending machine model, the full menu of available
services is determined beforehand. A small number of vendors have the ability to
get their products into the machine, and as a result, the choices are limited, und das
prices are high. A bazaar, by contrast, is a place where the community itself
exchanges goods and services.

But not all bazaars are created equal. Some are sorry affairs, with not much
more choice than the vending machine, while others are vibrant marketplaces in
which many merchants compete to provide the same goods and services, bringen
an abundance of choice as well as lower prices.

In the technology world, the equivalent of a thriving bazaar is a successful plat-
bilden. If you look at the history of the computer industry, the innovations that
define each era are frameworks that enabled a whole ecosystem of participation
from companies large and small. The personal computer was such a platform. Also
was the World Wide Web. This same platform dynamic is playing out right now in
the recent success of the Apple iPhone. Where other phones have had a limited
menu of applications developed by the phone vendor and a few carefully chosen
Partner, Apple built a framework that allowed virtually anyone to build applica-
tions for the phone, leading to an explosion of creativity, with more than 100,000
applications appearing for the phone in little more than 18 months, and more than
3,000 new ones now appearing every week. 4

This is the right way to frame the question of Government 2.0. How does gov-
ernment become an open platform that allows people inside and outside govern-
ment to innovate? How do you design a system in which all of the outcomes aren’t
specified beforehand, but instead evolve through interactions between government
and its citizens, as a service provider enabling its user community?

This chapter focuses primarily on the application of platform thinking to gov-
ernment technology projects. But it is worth noting that the idea of government as
a platform applies to every aspect of the government’s role in society. Zum Beispiel,
the Federal-Aid Highway Act of 1956, which committed the United States to build-

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Tim O’Reilly

ing an interstate highway system, was a triumph of platform thinking, a key invest-
ment in facilities that had a huge economic and social multiplier effect. Though
government builds the network of roads that tie our cities together, it does not
operate the factories, farms, and businesses that use that network: that opportuni-
ty is afforded to “we the people.” Government does set policies for the use of those
Straßen, regulating interstate commerce, levying gasoline taxes and fees on heavy
vehicles that damage the roads, setting and policing speed limits, specifying crite-
ria for the safety of bridges, tunnels, and even vehicles that travel on the roads, Und
performing many other responsibilities appropriate to a “platform provider.”

While it has become common to ridicule the 1990s description of the Internet
as the “information superhighway,” the analogy is actually quite apt. Like the
Internet, the road system is a “network of networks,” in which national, state, local,
and private roads all interconnect, for the most part without restrictive fees. Wir
have the same rules of the road everywhere in the country, yet anyone, down to a
local landowner adding a driveway to an unimproved lot, can connect to the
nation’s system of roads.

The launch of weather, communications, and positioning satellites is a similar
exercise of platform strategy. When you use a car navigation system to guide you
to your destination, you are using an application built on the government plat-
bilden, extended and enriched by massive private sector investment. When you
check the weather—on TV or on the Internet—you are using applications built
using the National Weather Service (or equivalent services in other countries) as a
platform. Until recently, the private sector had neither the resources nor the incen-
tives to create space-based infrastructure. Government as a platform provider cre-
ated capabilities that enrich the possibilities for subsequent private sector invest-
ment.

There are other areas where the appropriate role of the platform provider and
the marketplace of application providers is less clear. Health care is a contentious
Beispiel. Should the government be providing health care or leaving it to the pri-
vate sector? The answer is in the outcomes. If the private sector is doing a good job
of providing necessary services that lead to the overall increase in the vitality of the
country, government should stay out. But just as the interstate highway system
increased the vitality of our transportation infrastructure, it is certainly possible
that greater government involvement in health care could do the same. But if the
lesson is correctly learned, it should do so not by competing with the private sec-
tor to deliver health services, but by investing in infrastructure (and “rules of the
road”) that will lead to a more robust private sector ecosystem.

Gleichzeitig, platforms always require choices, and those choices must be
periodically revisited. Platforms lose their power when they fail to adapt. The U.S.
investment in the highway system helped to vitiate our railroads, shaping a socie-
ty of automobiles and suburbs. Heute, we need to rethink the culture of sprawl and
fossil fuel use that platform choice encouraged. A platform that once seemed so
generative of positive outcomes can become a dead weight over time.

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Government as a Platform

Police, fire services, garbage collection: these are fundamental platform servic-
es, just like analogous services in computer operating systems. And of course, Hier
we have an “antipattern” from technology platforms: the failure to provide securi-
ty, Zum Beispiel, as a fundamental system service, leaving it instead to the “private
sector” of application vendors, has imposed a huge downstream cost on the tech-
nology ecosystem.

The question of Government 2.0, Dann, is this: if government is a platform,

how can we use technology to make it into a better platform?

This question allows us to fruitfully extend the platform metaphor and ask:
what lessons can government take from the success of computer platforms, als es
tries to harness the power of technology to remake government?

LESSON 1: OPEN STANDARDS SPARK INNOVATION AND GROWTH

Time and again, the platforms that are the most generative of new economic activ-
ity are those that are the most open. The modern era in computing began in 1981
when IBM published the specifications for a personal computer that anyone could
build using off-the-shelf parts. Prior to the introduction of the PC, IBM had a
stranglehold on the computer market. It was a valuable but limited market, mit
very few vendors serving a small number of very big customers.

After the introduction of the PC, barriers to market entry were so low that
Michael Dell, a Texas college student, was able to start what became a multibillion
dollar company out of his dorm room. The market for personal computers explod-
Hrsg. IBM had estimated a total of 245,000 PCs would be sold over five years; as we
now know, the eventual market size was in the billions, as scrappy little companies
like Microsoft worked to put “a computer on every desk and in every home.” 5

Gleichzeitig, the standardization of the personal computer led to unex-
pected consequences: software became a higher-margin business than hardware;
industry power shifted from IBM to Microsoft.

In its early years, Microsoft triumphed by establishing the best platform for
independent software developers. Just as the standard architecture of the IBM PC
lowered the barriers to marketplace entry by hardware manufacturers, the stan-
dardized APIs of MS-DOS and, später, Microsoft Windows made it easy for devel-
opers to “add value” to the personal computer.

Over time, Microsoft began to abuse their market power as the platform
provider to give advantage to their own applications. At that point, the PC software
marketplace became less and less vibrant, with most of the profits accruing to a few
dominant companies. Infolge, many people mistakenly take the lesson from the
PC era that owning a platform is the secret of marketplace control and outsized
profits.

Tatsächlich, von 1995, the PC era had run out of gas. The PC became less and less
like a bazaar and more and more like a vending machine. We’d moved from the
open personal computer as the platform to the closed and tightly controlled

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Tim O’Reilly

Microsoft Windows as the platform. When one vendor controls the platform,
innovation suffers.

What reinvigorated the industry was a new open platform: the Internet, Und
more specifically, the World Wide Web. Both were radically decentralized—a set of
rules for programs to cooperate and communicate, with applications provided by
anyone who had a good idea and the skills to write one. Noch einmal, barriers to
marketplace entry were low, with multibillion dollar companies created out of col-
lege dorm rooms, and tens of thousands of companies competing to provide pre-
viously unimaginable new services. The bazaar was back.

We see the same dynamic playing out today in the cell phone market. Cell
phone providers have traditionally operated on the vending machine model. Apple
changed the rules of the game with the iPhone developer platform. Suddenly, any-
one could develop smartphone applications.

The smartphone platform story is perhaps the one most comforting to those
inside government. Unlike the IBM PC or the Internet, the Apple iPhone is not a
completely uncontrolled Wild West. Apple actively manages the platform to
encourage innovation and choice while enforcing clear rules. Some observers
believe that over time, the iPhone platform will not prove open enough, and will
be superseded by other, more open platforms. But for the moment, Apple appears
to be creating an effective balance between control and what Jonathan Zittrain
calls generativity. 6

There are two lessons for government in these stories. The first is the extraor-
dinary power of open standards to foster innovation. When the barriers to entry
to a market are low, entrepreneurs are free to invent the future. When barriers are
hoch, innovation moves elsewhere. The second is that vibrant platforms become
less generative over time, usually because the platform vendor has begun to com-
pete with its developer ecosystem.

Some readers may take the lesson to be that government plays an important
role in antitrust enforcement, keeping a level playing field. Facing the crises of the
day, from banking to health care, we see a story in which entrenched players have
grown large and have used their resulting power to remove choice from the mar-
ketplace, extracting outsized profits not by creating value but by cornering it.

There may be an “antitrust 2.0” alternative. Rather than simply limiting the size
or power of an entrenched player, can government insistence on openness and
interoperability be used to cause a “market reset,” through which innovation can
once again flourish? Antitrust actions against Microsoft were focused on existing
business models, yet the real competition for Microsoft came not from other busi-
nesses selling software, but from an entirely new class of advertising-based busi-
ness models that were invented in the initially noncommercial, wide-open spaces
of the World Wide Web.

One of the most important ways that government can promote competition is
not through after-the-fact antitrust enforcement but by encouraging more inno-
vation. And as has been argued here, the best way to do that is with open standards.
Also, Zum Beispiel, faced with the race by major players to dominate the emerging

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Government as a Platform

Figur 1. Government spending as percent of GDP since 1910.

Quelle: USGovernmentSpending.com

world of cloud computing, the government can forestall the risk of single-player
dominance by throwing its weight behind open standards and interoperability in
cloud computing. And in fact, this is just what we’re seeing. The recent General
Services Administration (GSA) Infrastructure as a Service (IaaS) solicitation
devoted 5 of its 25 questions to vendors to the subject of interoperability:7

5. Please address the following Interoperability and Portability questions:

5.1. Describe your recommendations regarding “cloud-to-cloud” commu-
nication and ensuring interoperability of cloud solutions.

5.2. Describe your experience in weaving together multiple different cloud
computing services offered by you, wenn überhaupt, or by other vendors.

5.3. As part of your service offering, describe the tools you support for
integrating with other vendors in terms of monitoring and managing mul-
tiple cloud computing services.

5.4. Please explain application portability; d.h., exit strategy for applications
running in your cloud, should it be necessary to vacate.

5.5. Describe how you prevent vendor lock in.

The recent U.S. Department of Defense guidance on the use of open source soft-
ware by the military is a similar move that uses open standards to enhance compe-
tition. 8 The government’s move to push for open patient records9 also recognizes
the power of open standards to promote innovation and bring down costs. And of

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Tim O’Reilly

Figur 2. Jack Dorsey’s original vision of Twitter.

course, the White House’s Data.gov initiative, a portal for open APIs to govern-
ment data, takes this idea to a new level.

In considering how open, generative systems eventually become closed over
Zeit, losing their innovative spark in the process, there is also a lesson for govern-
ment itself. Figur 1, “Government spending as percent of GDP since 1910” shows
the rising share of the U.S. gross domestic product consumed by all levels of gov-
ernment during the past 100 Jahre.

As a platform provider, when does government stop being generative, Und
when does it start to compete with the private sector? When do its decisions raise
barriers to marketplace entry rather than reduce them? What programs or func-
tions that were used to bootstrap a new market are now getting in the way? Dort
is no Justice Department that can bring an antitrust action against government;
there is no Schumpeterian “creative destruction” 10 to bring unneeded government
programs to an end. Government 2.0 will require deep thinking about how to end
programs that no longer work, and how to use the platform power of the govern-
ment not to extend government’s reach, aber stattdessen, how to use it to better enable
its citizenry and its economy.

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Government as a Platform

LESSON 2: BUILD A SIMPLE SYSTEM AND LET IT EVOLVE

In one of the early classics of software engineering, Systemantics, John Gall wrote:
“A complex system that works is invariably found to have evolved from a simple
system that worked. The inverse proposition also appears to be true. A complex
system designed from scratch never works and cannot be made to work. You have
to start over beginning with a working simple system.” 11

Wieder, the Internet is a case in point. In den 1980er Jahren, an international standards
committee got together to define the future of computer networking. The Open
Systems Interconnect (OSI) model was comprehensive and complete, and one of
the industry pundits of the day wrote, In 1986: 12

Over the long haul, most vendors are going to migrate from TCP/IP to
support Layer 4, the transport layer of the OSI model. For the short term,
Jedoch, TCP/IP provides organizations with enough functionality to
protect their existing equipment investment and over the long term,
TCP/IP promises to allow for easy migration to OSI.

Au contraire. It was the profoundly simple protocols of the Internet that grew rich-
er and more complex, while the OSI protocol stack became relegated to the status
of an academic reference model used to describe network architecture.

In der Zwischenzeit, over on the TCP/IP standardization side, there was this wonderful,
naive, glorious statement by Jon Postel in RFC 761: 13 “TCP implementation should
follow a general principle of robustness. Be conservative in what you do. Be liber-
al in what you accept from others.” It sounds like something out of the Bible, Die
Golden Rule as applied to computers. What a fabulous statement of philosophy!
“We’re not going to specify all of the details of how you interoperate; we’re just
going to say, ‘Please do it.’”

Twitter is another good example of a fundamentally simple system. Jack
Dorsey’s original design sketch fit on a few lines of paper (see Figure 2, “Jack
Dorsey’s original vision of Twitter”). Much has grown from that sketch. Es gibt
now thousands of Twitter applications, precisely because the core Twitter service
does so little. By thinking simple, Twitter allowed its users and an ecosystem of
application developers to evolve new features and functionality. This is the essence
of generativity.

Natürlich, in a government context when you say “build a simple system; let it
evolve,” that sounds like a real challenge. But let’s remember that TCP/IP was a
government-funded project. It can be done. The first step is getting a philosophy
of simplicity into your work, understanding that designing foundations that oth-
ers can build on is an important part of platform thinking. It’s about creating the
starting point, something that others can reuse and extend.

Designing simple systems is one of the great challenges of Government 2.0. Es
means the end of grand, feature-filled programs, and their replacement by mini-
mal services extensible by others.

This quest for simplicity is one of the drivers behind Federal CIO Vivek
Kundra’s emphasis on Data.gov, a collection of APIs to government data. Kundra

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Service-Oriented Architecture at Amazon

Amazon revolutionized the computer world in 2006 with the introduction of its
cloud computing platform: the Elastic Compute Cloud, or EC2; the Simple
Storage Service, or S3; and a series of other related services that make it possible
for developers to host their applications on the same infrastructure that Amazon
itself uses.

Amazon’s revolutionary business model included cheap, transparent, pay-
as-you-go pricing without contracts or commitments, making launching a web
application a completely self-service proposition. But what’s perhaps more
important was the architectural commitment Amazon had made over the previ-
ous five years to building a true service-oriented architecture.* As Amazon Chief
Technology Officer Werner Vogels described it in a 2008 Information Week inter-
view:**

Each of those pieces that make up the e-commerce platform are actu-
ally separate services. Whether it’s Sales Rank, or Listmania, oder
Recommendations, all of those are separate services. If you hit one of
Amazon’s pages, it goes out to between 250 Und 300 services to build
that page.

It’s not just an architectural model, it’s also organizational. Each serv-
ice has a team associated with it that takes the reliability of that service
and is responsible for the innovation of that service…. [W]e found
that a lot of those teams were spending their time on the same kind of
Dinge. In essence, they were all spending time on managing infrastruc-
tur, and that was a byproduct of the organization that we had chosen,
which was very decentralized.

So…we decided to go to a shared-services platform and that became
the infrastructure services platform that we now know in the outside
world as AWS [Amazon Web Services].

Amazon is a bellwether example of why Robinson et al. urge that “federal
websites themselves use the same open systems for accessing the underlying data
as they make available to the public at large.” Amazon’s ability to deliver low-cost
web services to the public started with its own total embrace of an internal web
services architecture, in which Amazon’s own applications are based on the same
services that they offer to the public.

* http://webservices.xml.com/pub/a/ws/2003/09/30/soa.html
**http://www.informationweek.com/news/global-
cio/interviews/showArticle.jhtml?articleID=212501404

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Government as a Platform

realizes that rather than having the government itself build out all of the websites
and applications that use that data, providing application programming interfaces
to the private sector will allow independent developers to come up with new uses
for government data.

The rationale for Data.gov was laid out convincingly by David G. Robinson et
al. in “Government Data and the Invisible Hand” (see Chapter 6 for an updated
take on this), and the emphasis below is mine: 14

In the current Presidential cycle, all three candidates have indicated that
they think the federal government could make better use of the
Internet…. But the situation to which these candidates are responding—
the wide gap between the exciting uses of Internet technology by private
parties, on the one hand, and the government’s lagging technical infra-
structure on the other—is not new. The federal government has shown
itself consistently unable to keep pace with the fast-evolving power of the
Internet.

In order for public data to benefit from the same innovation and
dynamism that characterize private parties’ use of the Internet, the feder-
al government must reimagine its role as an information provider. Eher
than struggling, as it currently does, to design sites that meet each end-
user need, it should focus on creating a simple, reliable and publicly acces-
sible infrastructure that “exposes” the underlying data. Private actors,
either nonprofit or commercial, are better suited to deliver government
information to citizens and can constantly create and reshape the tools
individuals use to find and leverage public data. The best way to ensure
that the government allows private parties to compete on equal terms in
the provision of government data is to require that federal websites them-
selves use the same open systems for accessing the underlying data as they
make available to the public at large.

Our approach follows the engineering principle of separating data from
interaction, which is commonly used in constructing websites.
Government must provide data, but we argue that websites that provide
interactive access for the public can best be built by private parties. Das
approach is especially important given recent advances in interaction,
which go far beyond merely offering data for viewing, to offer services
such as advanced search, automated content analysis, cross-indexing with
other data sources, and data visualization tools. These tools are promis-
ing but it is far from obvious how best to combine them to maximize the
public value of government data. Given this uncertainty, the best policy
is not to hope government will choose the one best way, but to rely on
private parties with their vibrant marketplace of engineering ideas to dis-
cover what works.

Data.gov reflects another key Gov 2.0 und Web 2.0 principle, namely that data is at

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Tim O’Reilly

the heart of Internet applications. But even here, the goal is not just to provide
greater access to government data, but to establish a simple framework that makes
it possible for the nation—the citizens, not just the government—to create and
share useful data

LESSON 3: DESIGN FOR PARTICIPATION

Closely related to the idea of simplicity is the idea of designing for participation.
Participatory systems are often remarkably simple—they have to be, or they just
don’t work. But when a system is designed from the ground up to consist of com-
ponents developed by independent developers (in a government context, read
Länder, federal agencies, Staaten, cities, private sector entities), magic happens.

Open source software projects like Linux and open systems like the Internet
work not because there’s a central board of approval making sure that all the pieces
fit together but because the original designers of the system laid down clear rules
for cooperation and interoperability. (Ja, there is some oversight: Linus Torvalds
and his codevelopers manage the development of the Linux kernel; the Apache
Software Foundation manages the development of Apache; the Internet
Engineering Task Force [IETF] and the Internet Architecture Board develop and
manage Internet standards; and the World Wide Web Consortium manages web
Standards. But there is little or no official coordination between any of these “local”
governance mechanisms. The coordination is all in the design of the system itself.)
In the case of Unix, the original design on which Linux was based, the creators
started out with a philosophy of small cooperating tools15 with standardized inputs
and outputs that could be assembled into pipelines. Rather than building complex
Lösungen, they provided building blocks, and defined how anyone could write
additional building blocks of their own simply by following the same set of rules.
This allowed Unix, and then Linux, to be an operating system literally created as
an assemblage of thousands of different projects. While the Linux kernel, devel-
oped by Linus Torvalds, is the best known part of the operating system and gave
its name to the entire system, it is a tiny part of the overall code.

The Internet took a similar approach.
Tim Berners-Lee’s first implementation of the World Wide Web is a great
example of the Internet approach at work. Berners-Lee was a developer at CERN,
the high energy physics lab in Switzerland, trying to figure out how to make col-
laboration easier between scientists. To do that, he simply wrote some code. Er
didn’t have to get permission from some central design body. All he needed was
one other site to install his server. And it grew from there. He built on top of exist-
ing platform components, the Internet Protocol, the Transmission Control
Protocol, the Domain Name System, which were already part of the TCP/IP stack.
What he defined in addition was HTTP, a protocol for web servers and clients to
exchange documents, and HTML, the data format of those documents. He wrote
a sample client and a sample server, both of which he put into the public domain.
The industry has been off to the races ever since.

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Government as a Platform

There were a number of key design breakthroughs in the World Wide Web’s

“architecture of participation”: 16
• The HTML syntax for formatting a web page was not embedded in a propri-

etary document format. Stattdessen, HTML documents are ordinary, human-read-
able text files. What’s more, every web browser includes a “View Source” menu
command, which allows users to study and understand the formatting of web
Seiten, and to copy innovative new features. Many early web pages weren’t writ-
ten from scratch, but were modifications of other people’s pages.

• Anyone could link to any other page on the Web, without the permission or
knowledge of the destination page’s owner. This idea was the reversal of one
taken for granted in previous hypertext systems, that links must always be two-
way—an agreement between the parties, so to speak. If the document on the
other end of a link goes away, an error (the famous “404” seen by any web
surfer) appears, but no further action is taken. This tolerance of failure is a
good example of Jon Postel’s Robustness Principle at work.

Another way to frame the idea that anyone could link to any other web page
without permission is to say that the Web was open “by default.” That is, Wann
developers design software, they make certain choices on behalf of their users
about the way that software will work unless the user intervenes to change it. Für
Beispiel, in the design of the World Wide Web, it was possible to make web pages
that were private and accessible only after login, but unless proactive steps were
taken to hide it, any web page was visible to anyone else on the Internet.

In many ways, the choice of “open by default” is the key to the breakaway suc-
cess of many of the Internet’s most successful sites. Zum Beispiel, early Internet
photo-sharing sites asked their users to identify people with whom they’d like to
share their photos. Flickr made “public” the default value for all photos, and soon
became the gold standard for online photo sharing. Wikipedia allowed anyone to
create and edit entries in their online encyclopedia, miraculously succeeding where
more carefully curated online encyclopedias had failed. YouTube provided mecha-
nisms whereby anyone could embed their videos on any web page, without com-
ing to the central YouTube portal. Skype doesn’t ask users for permission to share
their bandwidth with other users, but the system is designed that way. Twitter took
off because it allows anyone to follow status updates from anyone else (von
default—you have to take an extra step to make your updates private), in stark
contrast to previous social networks that required approval.

Cass Sunstein, now head of President Obama’s Office of Information and
Regulatory Affairs, is no stranger to the importance of default choices in public
Politik. In his book, Nudge, coauthored with economist Richard Thaler, er argumentiert
that “choice architecture” can help nudge people to make better decisions. 17 Der
most publicized policy proposal in the book was to make 401K participation “opt
out” rather than “opt in” (d.h., participation by default), but the book is full of many
other examples. As Sunstein and Thaler wrote:

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A choice architect has the responsibility for organizing the context in
which people make decisions…. If you design the ballot voters use to
choose candidates, you are a choice architect. If you are a doctor and
must describe the alternative treatments available to a patient, you are a
choice architect. If you design the form that new employees fill out to
enroll in the company health plan, you are a choice architect. If you are a
parent, describing possible educational options to your son or daughter,
you are a choice architect.

And of course, if you are designing a government program, you are a choice archi-
tect. The ideas of Thaler and Sunstein have great relevance to areas such as agricul-
tural policy (why are we subsidizing corn syrup when we face an obesity epidem-
ic?); job creation (how do we encourage more entrepreneurs, 18 including immi-
grants?); Gesundheitspflege (why does Medicare provide reimbursement for treatments
that don’t work?); and tax policy (where this concept is of course well understood,
and the traditional bone of contention between America’s political parties).
Venture capitalist John Doerr’s suggestion on immigration policy19 that we “staple
a Green Card to the diploma of anyone that graduates with a degree in the physi-
cal sciences or engineering” is another example of how policy defaults could have
an impact on innovation. Pigovian taxes20 are another application of this principle
to government. 21

In the context of government as a platform, the key question is what architec-
tures will lead to the most generative outcome. The goal is to design programs and
supporting infrastructure that enable “we the people” to do most of the work.

A ROBUSTNESS PRINCIPLE FOR GOVERNMENT

President Obama’s memorandum calling for transparent, participatory, collabora-
tive government is also just a statement of philosophy. 22 But it’s a statement of phi-
losophy that’s fundamentally actionable in the same way that the TCP robustness
principle was, or the design rules that are the heart of Unix. And even though none
of these things is a formal specification, it is a set of design principles that guide
the design of the platform we are collectively trying to build.

It’s important to think deeply about what the three design principles of trans-

parency, participation, and collaboration mean in the context of technology.

Zum Beispiel, the word “transparency” can lead us astray as we think about the
opportunity for Government 2.0. Ja, it’s a good thing when government data is
available so that journalists and watchdog groups like the Sunlight Foundation can
disclose cost overruns in government projects or highlight the influence of lobby-
ists. But that’s just the beginning. The magic of open data is that the same open-
ness that enables transparency also enables innovation, as developers build appli-
cations that reuse government data in unexpected ways. Glücklicherweise, Vivek Kundra
and others in the administration understand this distinction, and are providing
data for both purposes.

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Government as a Platform

Do It Ourselves: An Example from Hawaii

One of the most dramatic contemporary examples is a story reported by CNN,
“Island DIY: Kauai residents don’t wait for state to repair road”:* “Their liveli-
hood was being threatened, and they were tired of waiting for government help,
so business owners and residents on Hawaii’s Kauai island pulled together and
completed a $4 million repair job to a state park—for free.” Especially striking in the story are the cost and time savings: “It would not have been open this summer, and it probably wouldn’t be open next summer,” said Bruce Pleas, a local surfer who helped organize the vol- unteers. “They said it would probably take two years. And with the way they are cutting funds, we felt like they’d never get the money to fix it.” And if the repairs weren’t made, some business owners faced the possibility of having to shut down…. So Slack [owner of a kayak tour business in the park], other business own- ers and residents made the decision not to sit on their hands and wait for state money that many expected would never come. Stattdessen, they pulled together machinery and manpower and hit the ground running March 23. And after only eight days, all of the repairs were done, Pleas said. It was a shockingly quick fix to a problem that may have taken much longer if they wait- ed for state money to funnel in…. “We can wait around for the state or federal government to make this move, or we can go out and do our part,” Slack said. “Just like everyone’s sitting around waiting for a stimulus check, we were waiting for this but decided we couldn’t wait anymore.” Now is the time for a renewal of our commitment to make our own institu- tionen, our own communities, and our own difference. There’s a kind of passivi- ty even to most activism: collective action has come to mean collective com- plaint. Or at most, a collective effort to raise money. What the rebuilding of the washed out road in Polihale State Park teaches us is that we can do more than that. We can rediscover the spirit of public service, and apply the DIY spirit on a civic scale. Scott Heiferman, the founder of Meetup.com, suggests going beyond the term DIY (Do It Yourself) to embrace a new spirit of DIO: Do It Ourselves! * http://www.cnn.com/2009/US/04/09/hawaii.volunteers.repair/index.html Likewise, we can be misled by the notion of participation to think that it’s lim- ited to having government decision-makers “get input” from citizens. This would be like thinking that enabling comments on a website is the beginning and end of social media! It’s a trap for outsiders to think that Government 2.0 is a way to use new technology to amplify the voices of citizens to influence those in power, and by insiders as a way to harness and channel those voices to advance their causes. Participation means true engagement with citizens in the business of govern- ment, and actual collaboration with citizens in the design of government pro- Innovationen / Volumen 6, number 1 27 Von http heruntergeladen://direct.mit.edu/itgg/article-pdf/6/1/13/1626142/inov_a_00056.pdf by guest on 08 September 2023 Tim O’Reilly Everyone Has Something to Offer The reflex exerted by government to gather new information, whether in pursuit of spreading around money for housing or planning its next steps in Afghanistan, is to convene an advisory committee of experts. A whole set of laws and regulations, such as the Federal Advisory Committee Act (FACA), controls this process. Such panels are typically drawn from a limited group of academics and industry experts. A list of these advisors would no doubt show a familiar pattern of high-ranking universities. Recent popular research on crowdsourcing and the wisdom of crowds sug- gests a totally different approach. Asking everybody for input generates better results than just asking the experts. Certainly, a single recognized expert will tend to offer better facts, Vorhersagen, or advice than a random individual. But put a few dozen random individuals together—on the right kind of task—and the facts, Vorhersagen, or advice that shake out are better than what the experts alone produce. The reasons behind the success of crowdsourcing are still being investigated, but the key seems to be this: in a mix of right and wrong answers, the wrong ones tend to cancel each other out, leaving the right ones. This is the secret behind the famous appeals to the audience in the game show Who Wants to Be a Millionaire, as well as the success of prediction markets such as the University of Iowa’s Electronic Market.* Wikipedia, which invariably makes a central appearance in every reference to crowdsourcing, plays the different opinions of the crowd against each other in more explicit ways. On relatively uncontroversial articles, contributors are expected to discuss their differences and reach consensus. This process is aided by a rarely cited technical trait of web pages: because they present no artificial space limitations, there can always be room for another point of view. On con- troversial topics, Wikipedia has over the years developed more formal mecha- nisms, but the impetus for change still wells up from the grassroots. It’s also worth mentioning, in regard to crowdsourcing, the use of low-paid or volunteer labor to carry out simple tasks such as identifying the subjects of photographs. These are called Mechanical Turk projects, in reference to a crowd- sourcing technology platform provided by Amazon.com, which is itself named after an eighteenth-century hoax** in which a person pretended to be an intel- Gramm. Zum Beispiel, the Open Government Brainstorming conducted by the White House is an attempt to truly engage citizens in the making of policy, not just to hear their opinions after the fact. 23 Open government APIs enable a different kind of participation. When anyone can write a citizen-facing application using government data, software developers have an opportunity to create new interfaces to government. 28 Innovationen / Data Democracy Downloaded from http://direct.mit.edu/itgg/article-pdf/6/1/13/1626142/inov_a_00056.pdf by guest on 08 September 2023 Government as a Platform ligent machine; in the modern incarnation, thousands of people are serving as functions invoked by a computer application. Crowdsourcing has already slipped into government procedures in low-key ways. Governments already use input from self-appointed members of the pub- lic on all kinds of things, ranging from reports of potholes to anonymous tips that put criminals behind bars. One of the key skills required of both technologists and government officials is how best to aggregate public opinion or data produced by public actions to reveal new information or patterns. Zum Beispiel, cities learn a lot about neigh- borhoods by aggregating crime reports from residents. They could understand their needs for broadband network access much more accurately if they took resident reports into account and didn’t depend just on what the broadband vendors told them (because geographic anomalies often cause dead zones in areas that the vendors claim to serve). Allgemein, people can provide input on several levels: Observations such as reports of potholes and crimes Feedback on government proposals New ideas generated through brainstorming sessions Full-fledged applications that operate on publicly available data Some of those applications may operate on existing government data, but they can also be designed to collect new data from ordinary people, in a virtu- ous circle by which private sector applications (like SeeClickFix) increase the intelligence and responsiveness of government. Governments are more likely to use some form of filtering than to rely on public consensus, as Wikipedia does. The combination of free debate among the public and some adult supervision from a government official makes a powerful combination, already seen in the open government brainstorming session men- tioned in Lesson 3. Endlich, crowds can produce data without even realizing it—implicit data that smart programmers can collect and use to uncover whole worlds of infor- mation. Tatsächlich, smart programmers in the private sector have been doing that for years. Lesson 5 covers this trend. —Andy Oram * http://www.biz.uiowa.edu/iem/index.cfm ** http://en.wikipedia.org/wiki/Amazon_Mechanical_Turk Perhaps most interesting are applications and APIs that allow citizens to actu- ally replace functions of government, in a self-service analogue to Craigslist. Zum Beispiel, FixMyStreet, a project developed by UK nonprofit mySociety, made it possible for citizens to report potholes, broken streetlights, graffiti, and other problems that would otherwise have had to wait on an overworked government inspector. This concept has now been taken up widely by forward-thinking cities as well as entrepreneurial companies like SeeClickFix, and there is even a stan- Innovationen / Volumen 6, number 1 29 Von http heruntergeladen://direct.mit.edu/itgg/article-pdf/6/1/13/1626142/inov_a_00056.pdf by guest on 08 September 2023 Tim O’Reilly dard—Open311—for creating APIs to city services of this kind, so that third-party developers can create applications that will work not just for one city, but for every city. Taking the idea of citizen self-service even further, you can imagine govern- ment using a platform like Meetup to support citizens in self-organizing to take on major projects that the government would otherwise leave undone. Heute, there are thousands of civic-minded meetups around issues like beach, road, and water- way cleanups. How many more might there be if local governments themselves embraced the idea of harnessing and supporting citizen concerns as expressed by self-organized meetups? Citizen self-organization is a powerful concept. It’s worth remembering that early in our nation’s history, many functions now handled by government were self-organized by citizens: militias, fire brigades, lending libraries, not to mention roads, harbors and bridges. And even today, volunteer fire departments play a major role in protecting many of our communities. Traditional communities still perform barn raisings. Those of us who spend our time on the Internet celebrate Wikipedia, but most of us have forgotten how to do crowdsourcing in the physical world. LESSON 4: LEARN FROM YOUR “HACKERS” The secret of generative systems is that the most creative ideas for how a new plat- form can be used don’t necessarily come from the creators of the platform. It was not IBM but Dan Bricklin and Bob Frankston (VisiCalc), Mitch Kapor (Lotus 1-2- 3), and Bill Gates who developed the “killer applications” that made the IBM per- sonal computer such a success. It was Tim Berners-Lee, not Vint Cerf and Bob Kahn (the designers of the Internet’s TCP/IP protocol), who developed the Internet’s own first killer application, the World Wide Web. And it was Larry Page and Sergey Brin, not Tim Berners-Lee, who figured out how to turn the World Wide Web into a tool that revolutionized business. Such stories suggest how technology advances, as each new generation stands on the shoulders of preceding giants. Fundamental technology breakthroughs are often not exploited by their creators, but by a second generation of entrepreneurs who put it to work. But advances don’t just come from entrepreneurs playing by the rules of new platforms. Sometimes they come from those who break the rules. MIT professor Eric von Hippel has written extensively about this phenomenon, how “lead users” 24 of a product push it to its limits and beyond, showing vendors where their prod- uct wants to go, in much the way that rushing water carves its own path through the earth. There’s no better contemporary example than Google Maps, introduced in 2005, nearly 10 years after MapQuest, the first Internet site providing maps and directions. Yet today, Google Maps is the dominant mapping platform by most measures. How did this happen? 30 Innovationen / Data Democracy Downloaded from http://direct.mit.edu/itgg/article-pdf/6/1/13/1626142/inov_a_00056.pdf by guest on 08 September 2023 Government as a Platform When Google Maps was introduced, it featured a cool new AJAX (Asynchronous JavaScript and XML) interface that made it easy to dynamically drag and zoom the map. But there was a hidden feature as well, soon discovered by independent developers. Because JavaScript is interpreted code, it was possible to extract the underlying map coordinate data. A programmer named Paul Rademacher introduced the first Google Maps mashup, HousingMaps.com, taking data from another Internet site, Craigslist.org, and creating an application that put Craigslist apartment and home listings onto a Google Map. What did Google do? Far from shutting down Rademacher’s site and branding him a pirate, Google hired him, and soon put out an API that made it easier for anyone to do what he did. Competitors, who had long had mapping APIs but locked them up behind tightly controlled corporate developer programs, failed to seize the opportunity. Before long there were thousands of Google Maps mashups, and mapping had become an integral part of every web developer’s toolkit. Heute, according to the site ProgrammableWeb.com, which tracks mashups and reuse of web APIs, Google Maps accounts for nearly 90% of all mapping mashups, versus only a few percent each for MapQuest, Yahoo!, and Microsoft, even though these companies had a huge head start in web mapping. There are potent lessons here for governments opening up access to their data via APIs. Developers may use those APIs in unexpected ways. This is a good thing. If you see signs of uses that you didn’t consider, respond quickly, adapting the APIs to those new uses rather than trying to block them. In this regard, consider an instructive counterexample to Google Maps from the government sector. The New York Metropolitan Transit Authority recently attempted to stop the distribution of an iPhone app called StationStops, which provides schedule information for Metro-North trains. After a legal battle, the MTA relented. 25 Other cities, meanwhile, realized that having independent devel- opers build applications that provide information to citizens is a benefit both to citizens and to overworked government agencies, not “copyright infringement and intellectual property theft,” as the MTA had originally maintained. The whole point of government as a platform is to encourage the private sec- tor to build applications that government didn’t consider or doesn’t have the resources to create. Open data is a powerful way to enable the private sector to do just that. DATA IS THE “INTEL INSIDE” Open data is important not just because it is a key enabler of outside innovation. It’s also important to place in the context of current Internet business models. To explain, we require a brief excursion. One of the central platform lessons of the PC era is summed up in a principle that Harvard Business School Professor Clayton Christensen called “the law of conservation of attractive profits”: 26 Innovationen / Volumen 6, number 1 31 Von http heruntergeladen://direct.mit.edu/itgg/article-pdf/6/1/13/1626142/inov_a_00056.pdf by guest on 08 September 2023 Tim O’Reilly When attractive profits disappear at one stage in the value chain because a product becomes modular and commoditized, the opportunity to earn attractive profits with proprietary products will usually emerge at an adjacent stage. As the IBM PC—built from commodity off-the-shelf parts—became domi- nant, hardware margins declined, over time becoming razor thin. But according to Christensen’s law, something else became valuable, namely software, and Microsoft was soon earning the outsized profits that once were claimed by IBM. But even in an ecosystem of standard off-the-shelf parts, it is sometimes possible to corner a market, and that’s just what Intel did when it broke with IBM’s policy that every component had to be available from at least two suppliers, and refused to license its 80386 design to other chip manufacturers. That was the origin of the other half of the famous “Wintel” duopoly of Microsoft and Intel. If you can become the sole source of an essential commodity that is key to an otherwise commoditized prod- uct, you too can aspire to a logo like the ubiquitous “Intel Inside.” Reflecting on the role of open source software and open protocols and stan- dards in commoditizing the software of the Internet, I concluded in my 2003 paper “The Open Source Paradigm Shift” 27 that something similar would happen on the Internet. Exactly what that was didn’t become clear to me till 2005, when I wrote “What Is Web 2.0?” 28 If there’s one lesson that is central to the success of Web 2.0, it’s that data and the algorithms that produce value from it—not the software APIs and applications that were the key to the PC era—are the key to marketplace advantage in today’s Internet. Virtually all of the greatest Internet success stories, from eBay, Craigslist, and Amazon through Google, Facebook, and Twitter, are data-driven companies. Insbesondere, they are companies whose databases have a special characteristic: they get better the more people use them, making it difficult for competitors to enter the market. Once eBay or Craigslist had a critical mass of buyers and sellers, it became far more difficult for competitors to enter the market. Once Google established a virtuous circle of network effects among its AdWords advertisers, it was hard for others to achieve similar results. The Internet business ecosystem can thus be seen as a competition to establish monopolies over various classes of data. It is indeed data that is the “Intel Inside” of the Internet. What does this have to do with Government 2.0? If data is indeed the coin of the realm of Internet business models, it stands to reason that companies will find advantage in taking data created at public expense, and working to take control of that data for private gain. Consider the story of Routesy, an application providing iPhone users with bus arrival data in the San Francisco Bay Area. Like StationStops in New York, it was taken down from the iPhone App Store after a legal complaint. While Muni (the San Francisco transit authority) was supportive of Routesy and believed that its data was public, the contract that Muni had signed with technology provider NextBus allowed NextBus to claim copyright in the data. 29 If you want to have the kind of responsiveness that Google showed in supporting HousingMaps.com and 32 Innovationen / Data Democracy Downloaded from http://direct.mit.edu/itgg/article-pdf/6/1/13/1626142/inov_a_00056.pdf by guest on 08 September 2023 Government as a Platform launching the Google Maps mashup ecosystem, you have to make sure that public data remains public! Glücklicherweise, like MTA/StationStops, with a win for the public sector. The San Francisco Municipal Transit Authority has now released an XML API to the NextBus data. 30 the NextBus/Routesy dispute was resolved, LESSON 5: DATA MINING ALLOWS YOU TO HARNESS IMPLICIT PARTICIPATION When thinking about user participation and the co-creation of value, it’s easy to focus on technology platforms that explicitly feature the creations of their users, like Wikipedia, YouTube, Twitter, Facebook, and blogs. Yet in many ways, the breakthroughs in Web 2.0 have often come from exploring a far wider range of possibilities for collaboration: • Open source technology platforms such as the TCP/IP protocol suite and utili- ties created as part of Berkeley Unix, as well as Linux, Apache, and MySQL, and open source programming languages such as Perl, Python, PHP, and Ruby, all built and maintained by collaborative communities, provided the fundamental building blocks of the Internet as we know it today. • The World Wide Web itself has an architecture of participation. Anyone can put up a website and can link to any other website without permission. Blogging platforms made it even easier for any individual to create a site. Later platforms like Facebook and Twitter are also enablers of this kind of explicit participation. • First-generation web giants like Yahoo! got their start by building catalogs of the content assembled by the participatory multitudes of the Net, catalogs that later grew into search engines. eBay aggregated millions of buyers and sellers into a global garage sale. Craigslist replaced newspaper classified advertising by turning it all into a self-service business, right down to the policing of inappro- priate content, having users flag postings that they find offensive. Even Amazon.com, nominally an online retailer, gained competitive advantage by harnessing customers to provide reviews and ratings, as well as using their pur- chase patterns to make automated recommendations. • Google’s search engine dominance began with two brilliant insights into user participation. Erste, the PageRank algorithm that Larry Page and Sergey Brin created while still at Stanford was based on the realization that every link on the World Wide Web was a kind of vote on the value of the site being pointed to by that link. Das ist, every time any of us makes a link to another site on the Web, we’re contributing to Google. Zweite, Google realized that it could pro- vide better advertising results not by selling advertisements to the highest bid- der, but by measuring and predicting user click-through rates on ads. A $10 Anzeige
that is twice as likely to be clicked on is worth more than a $15 Anzeige. Google
could only deliver these results by understanding that every click on a Google
search result is a kind of user contribution. Since then, Google has gone on to

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Tim O’Reilly

mine user participation in many other aspects of its core business as well as in
new businesses, including speech recognition, location-based services, auto-
mated translation, and much more. Google is a master at extracting value from
implicit participation. It makes use of data that its users provide simply in
going about their lives on the Internet to provide them with results that quite
literally could not exist without them.

Just as Google has become the bellwether company of the Internet era, it is
actually systems for harnessing implicit participation that offer some of the great-
est opportunities for Government 2.0.

There are great examples to be found in health care. As costs soar, we discover
that costs and outcomes aren’t correlated. Atul Gawande’s New Yorker article31 on
this disconnect—outlining how McAllen, Texas, the city with the highest health
care costs in the U.S., also had the worst health outcomes—led to what Health and
Human Services CTO Todd Park referred to in a conversation with me as a “holy
cow moment.” Todd is now working on what he calls a “holy cow machine,” a set
of services that will allow every city to understand how its health care costs and
outcomes compare to those of other cities.

We have all the data we need—generated by the interactions of our citizens
with our health care system—to understand how to better align costs and out-
comes. Taking this idea to its full potential, we need to get beyond transparency
Und, as Google did with AdWords, start building data-driven feedback loops right
into the system. Google’s tools for estimating the effectiveness of keyword adver-
tising are available to advertisers, but that’s wonky, back-office stuff. The real magic
is that Google uses all its data expertise to directly benefit its users by automatical-
ly providing better search results and more relevant advertisements. The most
amazing thing about Google is how dynamically the prices for its advertising are
set. Every single Google search has its own automated ad auction. The price is set
dynamically, matching supply and demand, seven or eight billion times a day. Nur
financial markets operate at this kind of speed and scale.

A Gov 2.0 analogue would not just be a “holy cow machine” for transparency;
it might, Zum Beispiel, be a new, dynamic pricing system for Medicare. Currently,
an outside advisory board makes recommendations to Congress on appropriate
Medicare reimbursement rates. As David Leonhardt noted in the New York Times,
“Congress generally ignores them, in deference to the various industry groups that
oppose any cuts to their payments.” 32 Leonhardt’s solution: an independent body,
akin to the Federal Reserve, empowered to set reimbursement rates in the same
way the Fed sets interest rates.

But shouldn’t such a body go even further than periodic resets? Technologie
would allow us actually to manage reimbursements in much the same way as
Google dynamically adjusts its algorithms to produce optimal search results and
optimal ad placements. Google takes into account hundreds of factors; so too
could a Medicare rate-setting algorithm. To take two examples from Leonhardt’s
Artikel:

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Government as a Platform

Each year, um 100,000 people die from preventable infections they
contract in a hospital. Wann 108 hospitals in Michigan instituted a sim-
ple process to prevent some of these infections, it nearly eliminated them.
If Medicare reduced payments for the treatment of such infections, Es
would give hospitals a huge financial incentive to prevent them….

There are a handful of possible treatments for early-stage prostate cancer,
and the fastest-growing are the most expensive. But no one knows which
ones work best.

By measuring outcomes and linking reimbursements to those outcomes—rather
than the current “fee for service” model, which encourages unnecessary proce-
dures—Medicare could pave the way to a real revolution in health care.

Because of the political difficulty of such an intervention, it’s unlikely that
Medicare would be allowed to unilaterally introduce such an algorithmic payment
System. Infolge, I do suspect that this kind of innovation will come first from
the private sector, which will trounce its competition in the same way that Google
trounced its competitors in the search advertising market. As a platform provider,
obwohl, it’s possible to see how government investment in the data infrastructure
to measure and report on outcomes could jump-start and encourage private sec-
tor investment.

Real-time linkage of health costs and outcomes data will lead to wholesale
changes in medical practice when an innovative health care provider uses them to
improve its effectiveness and lower its costs. Such a breakthrough would sooner or
later be copied by less effective providers. So rather than attempting to enforce bet-
ter practices through detailed regulations, a Government 2.0 approach would use
open government data to enable innovative private sector participants to improve
their products and services. And to the extent that the government itself is a health
care provider (as with the Veterans Administration) or medical insurer (as with
Medicare), it can best move the ball forward by demonstrating in its own opera-
tions that it has been able to harness technology to get the job done better and
more cost-effectively.

LESSON 6: LOWER THE BARRIERS TO EXPERIMENTATION

In a memorable moment during the Apollo 13 moon mission, when mechanical
failures required that the mission be aborted and the astronauts rescued using only
materials on board the craft, mission controller Gene Kranz famously said, “Failure
is not an option.” In that case, he was right. But far too often, government pro-
grams are designed as though there is only one right answer, and with the assump-
tion that the specification developed by a project team must by definition be cor-
rect.

In Wirklichkeit, for most projects, failure is an option. Tatsächlich, technology companies

embrace failure, Experimentieren, and rapid iteration.

This has been true long before the latest wave of technology companies. In

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Tim O’Reilly

describing his quest for a working electric light bulb, Thomas Edison said, “I did-
n’t fail 10,000 mal. I succeeded 10,000 times in figuring out something that did
not work.”

You can conceive of the technology marketplace as a series of competitive
experiments. But even within a single company, one of the advantages of web-
based business models is the ease of experimentation. Companies routinely run
A/B tests of new features on subsets of their users. They add and subtract features
in real time in a process of constant improvement that I’ve sometimes called the
“perpetual beta.”

More recently, thinkers such as Steve Blank and Eric Ries have described an
idea that Ries refers to as “the lean startup,” in which he describes exploring the
market via a series of “minimal viable products,” each of which tells you more
about what the market really wants. 33

This is at great variance with typical government thinking, welche, by ignoring
the possibility of failure, paradoxically creates the conditions that encourage it.
Government 2.0 requires a new approach to the design of programs, not as fin-
ished products, perfected in a congressional bill, executive order, or procurement
specification, but as ongoing experiments.

Quite frankly, this is likely the greatest challenge in Government 2.0, not only
because of the nature of the government procurement process, but also because
government programs are often dictated by legislation, or by agency regulations
that are outside the scope of the agency actually making the decisions. What’s
mehr, while the commercial marketplace benefits from Schumpeterian “creative
destruction,” government programs are rarely scrapped or sunsetted.

This is all the more reason why government programs must be designed from
the outset not as a fixed set of specifications, but as open-ended platforms that
allow for extensibility and revision by the marketplace. Platform thinking is an
antidote to the complete specifications that currently dominate the government
approach not only to IT but to programs of all kinds.

A cultural change is also required. Empowering employees to “fail forward
fast” accepts and acknowledges that even when an experiment fails, you will still
learn something. Software and web culture not only embraces this mindset, Aber
revels in it—you never know which idea will be the million-dollar idea. Once the
cost of that experimentation is reduced, you can quickly scrap a product or feature
that no one uses and accept that it just wasn’t the thing that needed to be built after
alle.

Endlich, it is essential for best practices—and even working code—to be shared
between agencies of the federal government, between states, and between munici-
palities. After all, as Justice Louis Brandeis wrote in 1932, “It is one of the happy
incidents of the federal system that a single courageous state may, if its citizens
wählen, serve as a laboratory; and try novel social and economic experiments with-
out risk to the rest of the country.” 34

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Government as a Platform

How Platform Thinking Changes the
Big Government/Small Government Debate

It should be obvious by now that platform thinking provides a real alternative to
the endless argument between liberals and conservatives that has so dominated
UNS. political discourse in recent decades. The idea that we have to choose
between government providing services to citizens and leaving everything to the
private sector is a false dichotomy. Tim Berners-Lee didn’t develop hundreds of
millions of websites; Google didn’t develop thousands of Google Maps mashups;
Apple developed only a few of the tens of thousands of applications for the
iPhone.

Being a platform provider means government stripped down to the essen-
tials. A platform provider builds essential infrastructure, creates core applica-
tions that demonstrate the power of the platform and inspire outside developers
to push the platform even further, and enforces “rules of the road” that ensure
that applications work well together.

LESSON 7: LEAD BY EXAMPLE

When Microsoft introduced Microsoft Windows, it didn’t just introduce the plat-
bilden; it introduced two applications, Microsoft Word and Microsoft Excel, Das
showed off the ease of use that came with graphical user interfaces. When Apple
introduced the iPhone, it didn’t even introduce the platform until its second year.
Erste, it built a device with remarkable new features and a suite of applications that
showed off their power.

Despite everything I’ve said about the importance of a platform provider not
competing with its developer ecosystem, it’s also a mistake to think that you can
build a platform in the abstract. A great platform provider does things that are
ahead of the curve and that take time for the market to catch up to. It’s essential to
prime the pump by showing what can be done.

This is why, Zum Beispiel, Apps.DC.gov, the “App Store” for the city of
Washington, D.C., provides a better Gov 2.0 platform model than the federal
equivalent Data.gov (siehe Abbildung 3, “Apps.DC.gov home page”). Although Apps.gov
provides a huge service in opening up and promoting APIs to all the data resources
of the federal government, it’s hard to know what’s important, because there are no
compelling “applications” that show how that data can be put to use. Im Gegensatz,
Apps.DC.gov features a real app store, with applications written by the city of
Washington, D.C.’s own technology team (or funded by them) demonstrating how
to use key features. D.C. then took the further step of highlighting, at a top level,
third-party apps created by independent developers. This is a model for every gov-
ernment app store to follow.

It is true that the sheer size and scope of the federal data sets, as well as the
remoteness of many of them from the everyday lives of citizens, makes for a big-
ger challenge. But that’s precisely why the federal Gov 2.0 initiative needs to do

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Tim O’Reilly

Figur 3. Apps.DC.gov home page

deep thinking about what federal data resources and APIs will make the most dif-
ference to citizens, and invest strategically in applications that will show what can
getan werden.

But the idea of leading by example is far bigger than just Data.gov. Noch einmal,

consider health care.

If the current model of “health care reform” were an operating system, it would
be Windows Vista, touted as a major revisioning of the system, but in the end, a set
of patches that preserve what went before without bringing anything radically new
to the table.

If the government wants buy-in for government-run health care, we need the
equivalent of an iPhone for the system, something that re-envisions the market so
thoroughly that every existing player needs to copy it. I’ve suggested that an oppor-
tunity exists to reinvent Medicare so that it is more efficient than any private insur-
ance company, and to make the VA better than any private hospital system. Aber
being realistic, technology teaches us that it’s always harder to refactor an existing
system or application than it is to start fresh.

That’s why the “public option” proposed in some current health care bills is
such an opportunity. Can we create a new health insurance program that uses the
lessons of technology—open standards, simplicity in design, customer self-service,
measurement of outcomes, and real-time response to what is learned, not to men-
tion access via new consumer devices—to improve service and reduce costs so rad-
ically that the entire market follows?

This is the true measure of Gov 2.0: does it make incremental changes to the
existing system, or does it constitute a revolution? Considering the examples of
Microsoft, Google, Amazon, Apple, and other giants of the technology world, es ist
clear that they succeeded by changing all the rules, not by playing within the exist-
ing system. The personal computer, the World Wide Web, and the iPhone have

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Government as a Platform

each managed to simultaneously bring down costs while increasing consumer
choice—each by orders of magnitude.

They did this by demonstrating how a radically new approach to existing solu-
tions and business models was, quite simply, orders of magnitude better than what
went before.

If government is a platform, and Gov 2.0 is the next release, let’s make it one

that shakes up—and reshapes—the world.

PRACTICAL STEPS FOR GOVERNMENT AGENCIES

1. Issue your own open government directive. San Francisco Mayor Gavin Newsom
has done just that. You might consider his Open Data Executive Directive as a
Modell. 35

2. As Robinson et al. propose, create “a simple, reliable and publicly accessible
infrastructure that ‘exposes’ the underlying data” from your city, county, state, oder
Agentur. Before you can create a site like Data.gov, you must first adopt a data-driv-
In, service-oriented architecture for all your applications. The “Eight Open
Government Data Principles” document outlines the key requirements for open
government data. 36

3. “Build your own websites and applications using the same open systems for
accessing the underlying data as they make available to the public at large”
(Robinson et al. wieder). 37

4. Share those open APIs with the public, using Data.gov for federal APIs and
creating state and local equivalents. Zum Beispiel, cities such as San Francisco
(DataSF.org) and Washington, D.C. (Data.DC.gov and Apps.DC.gov) include not
only data catalogs but also repositories of apps that use that data, created by both
city developers and the private sector.

5. Share your work with other cities, counties, Staaten, or agencies. This might
mean providing your work as open source software, working with other govern-
mental bodies to standardize web services for common functions, building a com-
mon cloud computing platform, or simply sharing best practices. Code for
America is a new organization designed to help cities do just that.

6. Don’t reinvent the wheel: support existing open standards and use open
source software whenever possible. (Open311 is a great example of an open stan-
dard being adopted by many cities.) Figure out who has problems similar to yours,
and see if they’ve done some work that you can build on.

7. Create a list of software applications that can be reused by your government

employees without procurement.

8. Create an “app store” that features applications created by the private sector

as well as those created by your own government unit (see Apps.DC.gov).

9. Create permissive social media guidelines that allow government employees

to engage the public without having to get pre-approval from superiors.

10. Sponsor meetups, code camps, and other activity sessions to actually put

citizens to work on civic issues.

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Tim O’Reilly

1. The Founders’ Constitution, Kapitel 4, Document 34.
2. The Next Government of the United States: Why Our Institutions Fail Us and How to Fix Them,

Donald Kettl, W. W. Norton & Unternehmen, 2008.

3. The Cathedral & the Bazaar, Eric Raymond, O’Reilly, 1999.
4. http://radar.oreilly.com/2009/07/itunes-app-store-incubation-period-increases.html
5. http://www.microsoft.com/about/companyinformation/ourbusinesses/profile.mspx
6. The Future of the Internet-And How to Stop It, Jonathan Zittrain, Yale University Press, 2008.
7. https://www.fbo.gov/index?tab=core&s=opportunity&mode=form&id=
d208ac8b8687dd9c6921d2633603aedb&tabmode=list&cck=1&au=&ck=
8. http://radar.oreilly.com/2009/10/defense-department-releases-op.html
9. http://healthit.hhs.gov/blog/faca/
10. http://en.wikipedia.org/wiki/Creative_destruction
11. Systemantics: How Systems Work and Especially How They Fail, John Gall, Quadrangle, 1977.
12. “TCP/IP: Stairway to OSI,” Robert A. Moskowitz, Computer Decisions, April 22, 1986.
13. DOD Standard: Transmission Control Protocol report.
14. “Government Data and the Invisible Hand,” David G. Robinson, Harlan Yu, William Zeller, Und

Edward W. Felten, Yale Journal of Law & Technologie, Bd. 11, 2009.

15. Unix Programming Environment, Brian W. Kernighan and Rob Pike, Prentice Hall, 1984.
16. http://www.oreillynet.com/pub/a/oreilly/tim/articles/architecture_of_participation.html
17. Nudge: Improving Decisions About Health, Wealth, and Happiness, Richard H. Thaler and Cass R.

Sunstein, Penguin, 2009.

18. http://www.feld.com/wp/archives/2009/09/the-founders-visa-movement.html
19. http://blog.actonline.org/2008/11/doerr-staple-a-green-card-to-diplomas.html
20. http://en.wikipedia.org/wiki/Pigovian_tax
21. For an excellent summary of Thaler and Sunstein’s ideas on government policy, see Nudge-ocra-

cy: Barack Obama’s new theory of the state.

22. http://www.whitehouse.gov/the_press_office/TransparencyandOpenGovernment/
23. http://www.whitehouse.gov/blog/wrap-up-of-the-open-government-brainstormingparticipa-

tion/

24. http://en.wikipedia.org/wiki/Lead_user
25. “M.T.A. Is Easing Its Strict, Sometimes Combative, Approach to Outside Web Developers,” New

York Times, September 27, 2009.

26. The Innovator’s Solution: Creating and Sustaining Successful Growth, Clayton M. Christensen and

Michael E. Raynor, Harvard Business Press, 2003.
27. http://tim.oreilly.com/articles/paradigmshift_0504.html
28. http://oreilly.com/web2/archive/what-is-web-20.html
29. “Does A Private Company Own Your Muni Arrival Times?”, SF Appeal, Juni 25, 2009.
30. http://www.sfmta.com/cms/asite/nextmunidata.htm
31. “The Cost Conundrum,” Atul Gawande, The New Yorker, Juni 1, 2009.
32. “Falling Far Short of Reform,” David Leonhardt, The New York Times, November 10, 2009.
33. http://www.startuplessonslearned.com/2009/10/inc-magazine-on-minimum-viable-

product.html

34. http://www.whitehouse.gov/blog/2009/11/19/open-government-laboratories-democracy
35. http://www.sfmayor.org/wp-content/uploads/2009/10/ED-09-06-Open-Data.pdf
36. http://resource.org/8_principles.html
37. “Government Data and the Invisible Hand,” David G. Robinson, Harlan Yu, William Zeller, Und

Edward W. Felten, Yale Journal of Law & Technologie, Bd. 11, 2009

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